Enhanced simulator software for image validation and interpretation for multimodal localization super-resolution fluorescence microscopy

NASA Astrophysics Data System (ADS)

Erdélyi, Miklós; Sinkó, József; Gajdos, Tamás.; Novák, Tibor

2017-02-01

Optical super-resolution techniques such as single molecule localization have become one of the most dynamically developed areas in optical microscopy. These techniques routinely provide images of fixed cells or tissues with sub-diffraction spatial resolution, and can even be applied for live cell imaging under appropriate circumstances. Localization techniques are based on the precise fitting of the point spread functions (PSF) to the measured images of stochastically excited, identical fluorescent molecules. These techniques require controlling the rate between the on, off and the bleached states, keeping the number of active fluorescent molecules at an optimum value, so their diffraction limited images can be detected separately both spatially and temporally. Because of the numerous (and sometimes unknown) parameters, the imaging system can only be handled stochastically. For example, the rotation of the dye molecules obscures the polarization dependent PSF shape, and only an averaged distribution - typically estimated by a Gaussian function - is observed. TestSTORM software was developed to generate image stacks for traditional localization microscopes, where localization meant the precise determination of the spatial position of the molecules. However, additional optical properties (polarization, spectra, etc.) of the emitted photons can be used for further monitoring the chemical and physical properties (viscosity, pH, etc.) of the local environment. The image stack generating program was upgraded by several new features, such as: multicolour, polarization dependent PSF, built-in 3D visualization, structured background. These features make the program an ideal tool for optimizing the imaging and sample preparation conditions.

A user's guide to localization-based super-resolution fluorescence imaging.

PubMed

Dempsey, Graham T

2013-01-01

Advances in far-field fluorescence microscopy over the past decade have led to the development of super-resolution imaging techniques that provide more than an order of magnitude improvement in spatial resolution compared to conventional light microscopy. One such approach, called Stochastic Optical Reconstruction Microscopy (STORM) uses the sequential, nanometer-scale localization of individual fluorophores to reconstruct a high-resolution image of a structure of interest. This is an attractive method for biological investigation at the nanoscale due to its relative simplicity, both conceptually and practically in the laboratory. Like most research tools, however, the devil is in the details. The aim of this chapter is to serve as a guide for applying STORM to the study of biological samples. This chapter will discuss considerations for choosing a photoswitchable fluorescent probe, preparing a sample, selecting hardware for data acquisition, and collecting and analyzing data for image reconstruction. Copyright © 2013 Elsevier Inc. All rights reserved.

Characterization of the Distance Relationship Between Localized Serotonin Receptors and Glia Cells on Fluorescence Microscopy Images of Brain Tissue.

PubMed

Jacak, Jaroslaw; Schaller, Susanne; Borgmann, Daniela; Winkler, Stephan M

2015-08-01

We here present two new methods for the characterization of fluorescent localization microscopy images obtained from immunostained brain tissue sections. Direct stochastic optical reconstruction microscopy images of 5-HT1A serotonin receptors and glial fibrillary acidic proteins in healthy cryopreserved brain tissues are analyzed. In detail, we here present two image processing methods for characterizing differences in receptor distribution on glial cells and their distribution on neural cells: One variant relies on skeleton extraction and adaptive thresholding, the other on k-means based discrete layer segmentation. Experimental results show that both methods can be applied for distinguishing classes of images with respect to serotonin receptor distribution. Quantification of nanoscopic changes in relative protein expression on particular cell types can be used to analyze degeneration in tissues caused by diseases or medical treatment.

Superresolution microscopy for microbiology

PubMed Central

Coltharp, Carla; Xiao, Jie

2014-01-01

Summary This review provides a practical introduction to superresolution microscopy from the perspective of microbiological research. Because of the small sizes of bacterial cells, superresolution methods are particularly powerful and suitable for revealing details of cellular structures that are not resolvable under conventional fluorescence light microscopy. Here we describe the methodological concepts behind three major categories of super-resolution light microscopy: photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) and stimulated emission-depletion (STED) microscopy. We then present recent applications of each of these techniques to microbial systems, which have revealed novel conformations of cellular structures and described new properties of in vivo protein function and interactions. Finally, we discuss the unique issues related to implementing each of these superresolution techniques with bacterial specimens and suggest avenues for future development. The goal of this review is to provide the necessary technical background for interested microbiologists to choose the appropriate super-resolution method for their biological systems, and to introduce the practical considerations required for designing and analysing superresolution imaging experiments. PMID:22947061

Review of advanced imaging techniques

PubMed Central

Chen, Yu; Liang, Chia-Pin; Liu, Yang; Fischer, Andrew H.; Parwani, Anil V.; Pantanowitz, Liron

2012-01-01

Pathology informatics encompasses digital imaging and related applications. Several specialized microscopy techniques have emerged which permit the acquisition of digital images (“optical biopsies”) at high resolution. Coupled with fiber-optic and micro-optic components, some of these imaging techniques (e.g., optical coherence tomography) are now integrated with a wide range of imaging devices such as endoscopes, laparoscopes, catheters, and needles that enable imaging inside the body. These advanced imaging modalities have exciting diagnostic potential and introduce new opportunities in pathology. Therefore, it is important that pathology informaticists understand these advanced imaging techniques and the impact they have on pathology. This paper reviews several recently developed microscopic techniques, including diffraction-limited methods (e.g., confocal microscopy, 2-photon microscopy, 4Pi microscopy, and spatially modulated illumination microscopy) and subdiffraction techniques (e.g., photoactivated localization microscopy, stochastic optical reconstruction microscopy, and stimulated emission depletion microscopy). This article serves as a primer for pathology informaticists, highlighting the fundamentals and applications of advanced optical imaging techniques. PMID:22754737

A Bayesian cluster analysis method for single-molecule localization microscopy data.

PubMed

Griffié, Juliette; Shannon, Michael; Bromley, Claire L; Boelen, Lies; Burn, Garth L; Williamson, David J; Heard, Nicholas A; Cope, Andrew P; Owen, Dylan M; Rubin-Delanchy, Patrick

2016-12-01

Cell function is regulated by the spatiotemporal organization of the signaling machinery, and a key facet of this is molecular clustering. Here, we present a protocol for the analysis of clustering in data generated by 2D single-molecule localization microscopy (SMLM)-for example, photoactivated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). Three features of such data can cause standard cluster analysis approaches to be ineffective: (i) the data take the form of a list of points rather than a pixel array; (ii) there is a non-negligible unclustered background density of points that must be accounted for; and (iii) each localization has an associated uncertainty in regard to its position. These issues are overcome using a Bayesian, model-based approach. Many possible cluster configurations are proposed and scored against a generative model, which assumes Gaussian clusters overlaid on a completely spatially random (CSR) background, before every point is scrambled by its localization precision. We present the process of generating simulated and experimental data that are suitable to our algorithm, the analysis itself, and the extraction and interpretation of key cluster descriptors such as the number of clusters, cluster radii and the number of localizations per cluster. Variations in these descriptors can be interpreted as arising from changes in the organization of the cellular nanoarchitecture. The protocol requires no specific programming ability, and the processing time for one data set, typically containing 30 regions of interest, is ∼18 h; user input takes ∼1 h.

Facile method to stain the bacterial cell surface for super-resolution fluorescence microscopy†

PubMed Central

Gunsolus, Ian L.; Hu, Dehong; Mihai, Cosmin; Lohse, Samuel E.; Lee, Chang-soo; Torelli, Marco D.; Hamers, Robert J.; Murhpy, Catherine J.; Orr, Galya

2015-01-01

A method to fluorescently stain the surfaces of both Gram-negative and Gram-positive bacterial cells compatible with super-resolution fluorescence microscopy is presented. This method utilizes a commercially-available fluorescent probe to label primary amines at the surface of the cell. We demonstrate eficient staining of two bacterial strains, the Gram-negative Shewanella oneidensis MR-1 and the Gram-positive Bacillus subtilis 168. Using structured illumination microscopy and stochastic optical reconstruction microscopy, which require high quantum yield or specialized dyes, we show that this staining method may be used to resolve the bacterial cell surface with sub-diffraction-limited resolution. We further use this method to identify localization patterns of nanomaterials, specifically cadmium selenide quantum dots, following interaction with bacterial cells. PMID:24816810

Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy

PubMed Central

Kim, Doory; Deerinck, Thomas J.; Sigal, Yaron M.; Babcock, Hazen P.; Ellisman, Mark H.; Zhuang, Xiaowei

2015-01-01

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets. PMID:25874453

Common fluorescent proteins for single-molecule localization microscopy

NASA Astrophysics Data System (ADS)

Klementieva, Natalia V.; Bozhanova, Nina G.; Mishina, Natalie M.; Zagaynova, Elena V.; Lukyanov, Konstantin A.; Mishin, Alexander S.

2015-07-01

Super-resolution techniques for breaking the diffraction barrier are spread out over multiple studies nowadays. Single-molecule localization microscopy such as PALM, STORM, GSDIM, etc allow to get super-resolved images of cell ultrastructure by precise localization of individual fluorescent molecules via their temporal isolation. However, these methods are supposed the use of fluorescent dyes and proteins with special characteristics (photoactivation/photoconversion). At the same time, there is a need for retaining high photostability of fluorophores during long-term acquisition. Here, we first showed the potential of common red fluorescent protein for single-molecule localization microscopy based on spontaneous intrinsic blinking. Also, we assessed the effect of different imaging media on photobleaching of these fluorescent proteins. Monomeric orange and red fluorescent proteins were examined for stochastic switching from a dark state to a bright fluorescent state. We studied fusions with cytoskeletal proteins in NIH/3T3 and HeLa cells. Imaging was performed on the Nikon N-STORM system equipped with EMCCD camera. To define the optimal imaging conditions we tested several types of cell culture media and buffers. As a result, high-resolution images of cytoskeleton structure were obtained. Essentially, low-intensity light was sufficient to initiate the switching of tested red fluorescent protein reducing phototoxicity and provide long-term live-cell imaging.

Single particle maximum likelihood reconstruction from superresolution microscopy images

PubMed Central

Verdier, Timothée; Gunzenhauser, Julia; Manley, Suliana; Castelnovo, Martin

2017-01-01

Point localization superresolution microscopy enables fluorescently tagged molecules to be imaged beyond the optical diffraction limit, reaching single molecule localization precisions down to a few nanometers. For small objects whose sizes are few times this precision, localization uncertainty prevents the straightforward extraction of a structural model from the reconstructed images. We demonstrate in the present work that this limitation can be overcome at the single particle level, requiring no particle averaging, by using a maximum likelihood reconstruction (MLR) method perfectly suited to the stochastic nature of such superresolution imaging. We validate this method by extracting structural information from both simulated and experimental PALM data of immature virus-like particles of the Human Immunodeficiency Virus (HIV-1). MLR allows us to measure the radii of individual viruses with precision of a few nanometers and confirms the incomplete closure of the viral protein lattice. The quantitative results of our analysis are consistent with previous cryoelectron microscopy characterizations. Our study establishes the framework for a method that can be broadly applied to PALM data to determine the structural parameters for an existing structural model, and is particularly well suited to heterogeneous features due to its single particle implementation. PMID:28253349

Super-Resolution Scanning Laser Microscopy Based on Virtually Structured Detection

PubMed Central

Zhi, Yanan; Wang, Benquan; Yao, Xincheng

2016-01-01

Light microscopy plays a key role in biological studies and medical diagnosis. The spatial resolution of conventional optical microscopes is limited to approximately half the wavelength of the illumination light as a result of the diffraction limit. Several approaches—including confocal microscopy, stimulated emission depletion microscopy, stochastic optical reconstruction microscopy, photoactivated localization microscopy, and structured illumination microscopy—have been established to achieve super-resolution imaging. However, none of these methods is suitable for the super-resolution ophthalmoscopy of retinal structures because of laser safety issues and inevitable eye movements. We recently experimentally validated virtually structured detection (VSD) as an alternative strategy to extend the diffraction limit. Without the complexity of structured illumination, VSD provides an easy, low-cost, and phase artifact–free strategy to achieve super-resolution in scanning laser microscopy. In this article we summarize the basic principles of the VSD method, review our demonstrated single-point and line-scan super-resolution systems, and discuss both technical challenges and the potential of VSD-based instrumentation for super-resolution ophthalmoscopy of the retina. PMID:27480461

Quantitative Super-Resolution Microscopy of Nanopipette-Deposited Fluorescent Patterns.

PubMed

Hennig, Simon; van de Linde, Sebastian; Bergmann, Stephan; Huser, Thomas; Sauer, Markus

2015-08-25

We describe a method for the deposition of minute amounts of fluorophore-labeled oligonucleotides with high local precision in conductive and transparent solid layers of poly(vinyl alcohol) (PVA) doped with glycerin and cysteamine (PVA-G-C layers). Deposition of negatively charged fluorescent molecules was accomplished with a setup based on a scanning ion conductance microscope (SICM) using nanopipettes with tip diameters of ∼100 nm by using the ion flux flowing between two electrodes through the nanopipette. To investigate the precision of the local deposition process, we performed in situ super-resolution microscopy by direct stochastic optical reconstruction microscopy (dSTORM). Exploiting the single-molecule sensitivity and reliability of dSTORM, we determine the number of fluorescent molecules deposited in single spots. The correlation of applied charge and number of deposited molecules enables the quantification of delivered molecules by measuring the charge during the delivery process. We demonstrate the reproducible deposition of 3-168 fluorescent molecules in single spots and the creation of fluorescent structures. The fluorescent structures are highly stable and can be reused several times.

Can single molecule localization microscopy be used to map closely spaced RGD nanodomains?

PubMed Central

Nicovich, Philip R.; Soeriyadi, Alexander; Nieves, Daniel J.; Gooding, J. Justin; Gaus, Katharina

2017-01-01

Cells sense and respond to nanoscale variations in the distribution of ligands to adhesion receptors. This makes single molecule localization microscopy (SMLM) an attractive tool to map the distribution of ligands on nanopatterned surfaces. We explore the use of SMLM spatial cluster analysis to detect nanodomains of the cell adhesion-stimulating tripeptide arginine-glycine-aspartic acid (RGD). These domains were formed by the phase separation of block copolymers with controllable spacing on the scale of tens of nanometers. We first determined the topology of the block copolymer with atomic force microscopy (AFM) and then imaged the localization of individual RGD peptides with direct stochastic optical reconstruction microscopy (dSTORM). To compare the data, we analyzed the dSTORM data with DBSCAN (density-based spatial clustering application with noise). The ligand distribution and polymer topology are not necessary identical since peptides may attach to the polymer outside the nanodomains and/or coupling and detection of peptides within the nanodomains is incomplete. We therefore performed simulations to explore the extent to which nanodomains could be mapped with dSTORM. We found that successful detection of nanodomains by dSTORM was influenced by the inter-domain spacing and the localization precision of individual fluorophores, and less by non-specific absorption of ligands to the substratum. For example, under our imaging conditions, DBSCAN identification of nanodomains spaced further than 50 nm apart was largely independent of background localisations, while nanodomains spaced closer than 50 nm required a localization precision of ~11 nm to correctly estimate the modal nearest neighbor distance (NDD) between nanodomains. We therefore conclude that SMLM is a promising technique to directly map the distribution and nanoscale organization of ligands and would benefit from an improved localization precision. PMID:28723958

Nanoscopy for nanoscience: how super-resolution microscopy extends imaging for nanotechnology.

PubMed

Johnson, Sam A

2015-01-01

Imaging methods have presented scientists with powerful means of investigation for centuries. The ability to resolve structures using light microscopes is though limited to around 200 nm. Fluorescence-based super-resolution light microscopy techniques of several principles and methods have emerged in recent years and offer great potential to extend the capabilities of microscopy. This resolution improvement is especially promising for nanoscience where the imaging of nanoscale structures is inherently restricted by the resolution limit of standard forms of light microscopy. Resolution can be improved by several distinct approaches including structured illumination microscopy, stimulated emission depletion, and single-molecule positioning methods such as photoactivated localization microscopy and stochastic optical reconstruction microscopy and several derivative variations of each of these. These methods involve substantial differences in the resolutions achievable in the different axes, speed of acquisition, compatibility with different labels, ease of use, hardware complexity, and compatibility with live biological samples. The field of super-resolution imaging and its application to nanotechnology is relatively new and still rapidly developing. An overview of how these methods may be used with nanomaterials is presented with some examples of pioneering uses of these approaches. © 2014 Wiley Periodicals, Inc.

Sequential Super-Resolution Imaging of Bacterial Regulatory Proteins: The Nucleoid and the Cell Membrane in Single, Fixed E. coli Cells.

PubMed

Spahn, Christoph; Glaesmann, Mathilda; Gao, Yunfeng; Foo, Yong Hwee; Lampe, Marko; Kenney, Linda J; Heilemann, Mike

2017-01-01

Despite their small size and the lack of compartmentalization, bacteria exhibit a striking degree of cellular organization, both in time and space. During the last decade, a group of new microscopy techniques emerged, termed super-resolution microscopy or nanoscopy, which facilitate visualizing the organization of proteins in bacteria at the nanoscale. Single-molecule localization microscopy (SMLM) is especially well suited to reveal a wide range of new information regarding protein organization, interaction, and dynamics in single bacterial cells. Recent developments in click chemistry facilitate the visualization of bacterial chromatin with a resolution of ~20 nm, providing valuable information about the ultrastructure of bacterial nucleoids, especially at short generation times. In this chapter, we describe a simple-to-realize protocol that allows determining precise structural information of bacterial nucleoids in fixed cells, using direct stochastic optical reconstruction microscopy (dSTORM). In combination with quantitative photoactivated localization microscopy (PALM), the spatial relationship of proteins with the bacterial chromosome can be studied. The position of a protein of interest with respect to the nucleoids and the cell cylinder can be visualized by super-resolving the membrane using point accumulation for imaging in nanoscale topography (PAINT). The combination of the different SMLM techniques in a sequential workflow maximizes the information that can be extracted from single cells, while maintaining optimal imaging conditions for each technique.

Sequential Superresolution Imaging of Multiple Targets Using a Single Fluorophore

PubMed Central

Lidke, Diane S.; Lidke, Keith A.

2015-01-01

Fluorescence superresolution (SR) microscopy, or fluorescence nanoscopy, provides nanometer scale detail of cellular structures and allows for imaging of biological processes at the molecular level. Specific SR imaging methods, such as localization-based imaging, rely on stochastic transitions between on (fluorescent) and off (dark) states of fluorophores. Imaging multiple cellular structures using multi-color imaging is complicated and limited by the differing properties of various organic dyes including their fluorescent state duty cycle, photons per switching event, number of fluorescent cycles before irreversible photobleaching, and overall sensitivity to buffer conditions. In addition, multiple color imaging requires consideration of multiple optical paths or chromatic aberration that can lead to differential aberrations that are important at the nanometer scale. Here, we report a method for sequential labeling and imaging that allows for SR imaging of multiple targets using a single fluorophore with negligible cross-talk between images. Using brightfield image correlation to register and overlay multiple image acquisitions with ~10 nm overlay precision in the x-y imaging plane, we have exploited the optimal properties of AlexaFluor647 for dSTORM to image four distinct cellular proteins. We also visualize the changes in co-localization of the epidermal growth factor (EGF) receptor and clathrin upon EGF addition that are consistent with clathrin-mediated endocytosis. These results are the first to demonstrate sequential SR (s-SR) imaging using direct stochastic reconstruction microscopy (dSTORM), and this method for sequential imaging can be applied to any superresolution technique. PMID:25860558

Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome.

PubMed

Markert, Sebastian Matthias; Britz, Sebastian; Proppert, Sven; Lang, Marietta; Witvliet, Daniel; Mulcahy, Ben; Sauer, Markus; Zhen, Mei; Bessereau, Jean-Louis; Stigloher, Christian

2016-10-01

Correlating molecular labeling at the ultrastructural level with high confidence remains challenging. Array tomography (AT) allows for a combination of fluorescence and electron microscopy (EM) to visualize subcellular protein localization on serial EM sections. Here, we describe an application for AT that combines near-native tissue preservation via high-pressure freezing and freeze substitution with super-resolution light microscopy and high-resolution scanning electron microscopy (SEM) analysis on the same section. We established protocols that combine SEM with structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). We devised a method for easy, precise, and unbiased correlation of EM images and super-resolution imaging data using endogenous cellular landmarks and freely available image processing software. We demonstrate that these methods allow us to identify and label gap junctions in Caenorhabditis elegans with precision and confidence, and imaging of even smaller structures is feasible. With the emergence of connectomics, these methods will allow us to fill in the gap-acquiring the correlated ultrastructural and molecular identity of electrical synapses.

Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements

PubMed Central

Coltharp, Carla; Kessler, Rene P.; Xiao, Jie

2012-01-01

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (tThresh and dThresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems. PMID:23251611

Quantitative Aspects of Single Molecule Microscopy

PubMed Central

Ober, Raimund J.; Tahmasbi, Amir; Ram, Sripad; Lin, Zhiping; Ward, E. Sally

2015-01-01

Single molecule microscopy is a relatively new optical microscopy technique that allows the detection of individual molecules such as proteins in a cellular context. This technique has generated significant interest among biologists, biophysicists and biochemists, as it holds the promise to provide novel insights into subcellular processes and structures that otherwise cannot be gained through traditional experimental approaches. Single molecule experiments place stringent demands on experimental and algorithmic tools due to the low signal levels and the presence of significant extraneous noise sources. Consequently, this has necessitated the use of advanced statistical signal and image processing techniques for the design and analysis of single molecule experiments. In this tutorial paper, we provide an overview of single molecule microscopy from early works to current applications and challenges. Specific emphasis will be on the quantitative aspects of this imaging modality, in particular single molecule localization and resolvability, which will be discussed from an information theoretic perspective. We review the stochastic framework for image formation, different types of estimation techniques and expressions for the Fisher information matrix. We also discuss several open problems in the field that demand highly non-trivial signal processing algorithms. PMID:26167102

Clustered localization of STAT3 during the cell cycle detected by super-resolution fluorescence microscopy

NASA Astrophysics Data System (ADS)

Gao, Jing; Chen, Junling; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Tong, Ti; Wang, Hongda

2017-06-01

Signal transducer and activator of transcription 3 (STAT3) plays a key role in various cellular processes such as cell proliferation, differentiation, apoptosis and immune responses. In particular, STAT3 has emerged as a potential molecular target for cancer therapy. The functional role and standard activation mechanism of STAT3 have been well studied, however, the spatial distribution of STAT3 during the cell cycle is poorly known. Therefore, it is indispensable to study STAT3 spatial arrangement and nuclear-cytoplasimic localization at the different phase of cell cycle in cancer cells. By direct stochastic optical reconstruction microscopy imaging, we find that STAT3 forms various number and size of clusters at the different cell-cycle stage, which could not be clearly observed by conventional fluorescent microscopy. STAT3 clusters get more and larger gradually from G1 to G2 phase, during which time transcription and other related activities goes on consistently. The results suggest that there is an intimate relationship between the clustered characteristic of STAT3 and the cell-cycle behavior. Meanwhile, clustering would facilitate STAT3 rapid response to activating signals due to short distances between molecules. Our data might open a new door to develop an antitumor drug for inhibiting STAT3 signaling pathway by destroying its clusters.

Measuring true localization accuracy in super resolution microscopy with DNA-origami nanostructures

NASA Astrophysics Data System (ADS)

Reuss, Matthias; Fördős, Ferenc; Blom, Hans; Öktem, Ozan; Högberg, Björn; Brismar, Hjalmar

2017-02-01

A common method to assess the performance of (super resolution) microscopes is to use the localization precision of emitters as an estimate for the achieved resolution. Naturally, this is widely used in super resolution methods based on single molecule stochastic switching. This concept suffers from the fact that it is hard to calibrate measures against a real sample (a phantom), because true absolute positions of emitters are almost always unknown. For this reason, resolution estimates are potentially biased in an image since one is blind to true position accuracy, i.e. deviation in position measurement from true positions. We have solved this issue by imaging nanorods fabricated with DNA-origami. The nanorods used are designed to have emitters attached at each end in a well-defined and highly conserved distance. These structures are widely used to gauge localization precision. Here, we additionally determined the true achievable localization accuracy and compared this figure of merit to localization precision values for two common super resolution microscope methods STED and STORM.

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Wilkins, David C.; Roth, Dan

2010-01-01

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs.

Stochastic effects in EUV lithography: random, local CD variability, and printing failures

NASA Astrophysics Data System (ADS)

De Bisschop, Peter

2017-10-01

Stochastic effects in lithography are usually quantified through local CD variability metrics, such as line-width roughness or local CD uniformity (LCDU), and these quantities have been measured and studied intensively, both in EUV and optical lithography. Next to the CD-variability, stochastic effects can also give rise to local, random printing failures, such as missing contacts or microbridges in spaces. When these occur, there often is no (reliable) CD to be measured locally, and then such failures cannot be quantified with the usual CD-measuring techniques. We have developed algorithms to detect such stochastic printing failures in regular line/space (L/S) or contact- or dot-arrays from SEM images, leading to a stochastic failure metric that we call NOK (not OK), which we consider a complementary metric to the CD-variability metrics. This paper will show how both types of metrics can be used to experimentally quantify dependencies of stochastic effects to, e.g., CD, pitch, resist, exposure dose, etc. As it is also important to be able to predict upfront (in the OPC verification stage of a production-mask tape-out) whether certain structures in the layout are likely to have a high sensitivity to stochastic effects, we look into the feasibility of constructing simple predictors, for both stochastic CD-variability and printing failure, that can be calibrated for the process and exposure conditions used and integrated into the standard OPC verification flow. Finally, we briefly discuss the options to reduce stochastic variability and failure, considering the entire patterning ecosystem.

Hybrid-coded 3D structured illumination imaging with Bayesian estimation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Chen, Hsi-Hsun; Luo, Yuan; Singh, Vijay R.

2016-03-01

Light induced fluorescent microscopy has long been developed to observe and understand the object at microscale, such as cellular sample. However, the transfer function of lense-based imaging system limits the resolution so that the fine and detailed structure of sample cannot be identified clearly. The techniques of resolution enhancement are fascinated to break the limit of resolution for objective given. In the past decades, the resolution enhancement imaging has been investigated through variety of strategies, including photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), stimulated emission depletion (STED), and structure illuminated microscopy (SIM). In those methods, only SIM can intrinsically improve the resolution limit for a system without taking the structure properties of object into account. In this paper, we develop a SIM associated with Bayesian estimation, furthermore, with optical sectioning capability rendered from HiLo processing, resulting the high resolution through 3D volume. This 3D SIM can provide the optical sectioning and resolution enhancement performance, and be robust to noise owing to the Data driven Bayesian estimation reconstruction proposed. For validating the 3D SIM, we show our simulation result of algorithm, and the experimental result demonstrating the 3D resolution enhancement.

Planar Diffractive Lenses: Fundamentals, Functionalities, and Applications.

PubMed

Huang, Kun; Qin, Fei; Liu, Hong; Ye, Huapeng; Qiu, Cheng-Wei; Hong, Minghui; Luk'yanchuk, Boris; Teng, Jinghua

2018-06-01

Traditional objective lenses in modern microscopy, based on the refraction of light, are restricted by the Rayleigh diffraction limit. The existing methods to overcome this limit can be categorized into near-field (e.g., scanning near-field optical microscopy, superlens, microsphere lens) and far-field (e.g., stimulated emission depletion microscopy, photoactivated localization microscopy, stochastic optical reconstruction microscopy) approaches. However, they either operate in the challenging near-field mode or there is the need to label samples in biology. Recently, through manipulation of the diffraction of light with binary masks or gradient metasurfaces, some miniaturized and planar lenses have been reported with intriguing functionalities such as ultrahigh numerical aperture, large depth of focus, and subdiffraction-limit focusing in far-field, which provides a viable solution for the label-free superresolution imaging. Here, the recent advances in planar diffractive lenses (PDLs) are reviewed from a united theoretical account on diffraction-based focusing optics, and the underlying physics of nanofocusing via constructive or destructive interference is revealed. Various approaches of realizing PDLs are introduced in terms of their unique performances and interpreted by using optical aberration theory. Furthermore, a detailed tutorial about applying these planar lenses in nanoimaging is provided, followed by an outlook regarding future development toward practical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

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

Chen, Yi; Jakeman, John; Gittelson, Claude

2015-01-08

In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less

Restoration of STORM images from sparse subset of localizations (Conference Presentation)

NASA Astrophysics Data System (ADS)

Moiseev, Alexander A.; Gelikonov, Grigory V.; Gelikonov, Valentine M.

2016-02-01

To construct a Stochastic Optical Reconstruction Microscopy (STORM) image one should collect sufficient number of localized fluorophores to satisfy Nyquist criterion. This requirement limits time resolution of the method. In this work we propose a probabalistic approach to construct STORM images from a subset of localized fluorophores 3-4 times sparser than required from Nyquist criterion. Using a set of STORM images constructed from number of localizations sufficient for Nyquist criterion we derive a model which allows us to predict the probability for every location to be occupied by a fluorophore at the end of hypothetical acquisition, having as an input parameters distribution of already localized fluorophores in the proximity of this location. We show that probability map obtained from number of fluorophores 3-4 times less than required by Nyquist criterion may be used as superresolution image itself. Thus we are able to construct STORM image from a subset of localized fluorophores 3-4 times sparser than required from Nyquist criterion, proportionaly decreasing STORM data acquisition time. This method may be used complementary with other approaches desined for increasing STORM time resolution.

Stochastic goal-oriented error estimation with memory

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

Active and inactive β1 integrins segregate into distinct nanoclusters in focal adhesions.

PubMed

Spiess, Matthias; Hernandez-Varas, Pablo; Oddone, Anna; Olofsson, Helene; Blom, Hans; Waithe, Dominic; Lock, John G; Lakadamyali, Melike; Strömblad, Staffan

2018-06-04

Integrins are the core constituents of cell-matrix adhesion complexes such as focal adhesions (FAs) and play key roles in physiology and disease. Integrins fluctuate between active and inactive conformations, yet whether the activity state influences the spatial organization of integrins within FAs has remained unclear. In this study, we address this question and also ask whether integrin activity may be regulated either independently for each integrin molecule or through locally coordinated mechanisms. We used two distinct superresolution microscopy techniques, stochastic optical reconstruction microscopy (STORM) and stimulated emission depletion microscopy (STED), to visualize active versus inactive β1 integrins. We first reveal a spatial hierarchy of integrin organization with integrin molecules arranged in nanoclusters, which align to form linear substructures that in turn build FAs. Remarkably, within FAs, active and inactive β1 integrins segregate into distinct nanoclusters, with active integrin nanoclusters being more organized. This unexpected segregation indicates synchronization of integrin activities within nanoclusters, implying the existence of a coordinate mechanism of integrin activity regulation. © 2018 Spiess et al.

Dynamic placement of plasmonic hotspots for super-resolution surface-enhanced Raman scattering.

PubMed

Ertsgaard, Christopher T; McKoskey, Rachel M; Rich, Isabel S; Lindquist, Nathan C

2014-10-28

In this paper, we demonstrate dynamic placement of locally enhanced plasmonic fields using holographic laser illumination of a silver nanohole array. To visualize these focused "hotspots", the silver surface was coated with various biological samples for surface-enhanced Raman spectroscopy (SERS) imaging. Due to the large field enhancements, blinking behavior of the SERS hotspots was observed and processed using a stochastic optical reconstruction microscopy algorithm enabling super-resolution localization of the hotspots to within 10 nm. These hotspots were then shifted across the surface in subwavelength (<100 nm for a wavelength of 660 nm) steps using holographic illumination from a spatial light modulator. This created a dynamic imaging and sensing surface, whereas static illumination would only have produced stationary hotspots. Using this technique, we also show that such subwavelength shifting and localization of plasmonic hotspots has potential for imaging applications. Interestingly, illuminating the surface with randomly shifting SERS hotspots was sufficient to completely fill in a wide field of view for super-resolution chemical imaging.

Imaging and reconstruction of cell cortex structures near the cell surface

NASA Astrophysics Data System (ADS)

Jin, Luhong; Zhou, Xiaoxu; Xiu, Peng; Luo, Wei; Huang, Yujia; Yu, Feng; Kuang, Cuifang; Sun, Yonghong; Liu, Xu; Xu, Yingke

2017-11-01

Total internal reflection fluorescence microscopy (TIRFM) provides high optical sectioning capability and superb signal-to-noise ratio for imaging of cell cortex structures. The development of multi-angle (MA)-TIRFM permits high axial resolution imaging and reconstruction of cellular structures near the cell surface. Cytoskeleton is composed of a network of filaments, which are important for maintenance of cell function. The high-resolution imaging and quantitative analysis of filament organization would contribute to our understanding of cytoskeleton regulation in cell. Here, we used a custom-developed MA-TIRFM setup, together with stochastic photobleaching and single molecule localization method, to enhance the lateral resolution of TIRFM imaging to about 100 nm. In addition, we proposed novel methods to perform filament segmentation and 3D reconstruction from MA-TIRFM images. Furthermore, we applied these methods to study the 3D localization of cortical actin and microtubule structures in U373 cancer cells. Our results showed that cortical actins localize ∼ 27 nm closer to the plasma membrane when compared with microtubules. We found that treatment of cells with chemotherapy drugs nocodazole and cytochalasin B disassembles cytoskeletal network and induces the reorganization of filaments towards the cell periphery. In summary, this study provides feasible approaches for 3D imaging and analyzing cell surface distribution of cytoskeletal network. Our established microscopy platform and image analysis toolkits would facilitate the study of cytoskeletal network in cells.

Stress induced magnetic-domain evolution in magnetoelectric composites

NASA Astrophysics Data System (ADS)

Trivedi, Harsh; Shvartsman, Vladimir V.; Lupascu, Doru C.; Medeiros, Marco S. A.; Pullar, Robert C.

2018-06-01

Local observation of the stress mediated magnetoelectric (ME) effect in composites has gained a great deal of interest over the last decades. However, there is an apparent lack of rigorous methods for a quantitative characterization of the ME effect at the local scale, especially in polycrystalline microstructures. In the present work, we address this issue by locally probing the surface magnetic state of barium titante–hexagonal barium ferrite (BaTiO3–BaFe12O19) ceramic composites using magnetic force microscopy (MFM). The effect of the piezoelectrically induced local stress on the magnetostrictive component (BaFe12O19, BaM) was observed in the form of the evolution of the magnetic domains. The local piezoelectric stress was induced by applying a voltage to the neighboring BaTiO3 grains, using a conductive atomic force microscopy tip. The resulting stochastic evolution of magnetic domains was studied in the context of the induced magnetoelastic anisotropy. In order to overcome the ambiguity in the domain changes observed by MFM, certain generalizations about the observed MFM contrast are put forward, followed by application of an algorithm for extracting the average micromagnetic changes. An average change in domain wall thickness of 50 nm was extracted, giving a lower limit on the corresponding induced magnetoelastic anisotropy energy. Furthermore, we demonstrate that this induced magnetomechanical energy is approximately equal to the K1 magnetocrystalline anisotropy constant of BaM, and compare it with a modeled value of applied elastic energy density. The comparison allowed us to judge the quality of the interfaces in the composite system, by roughly gauging the energy conversion ratio.

Techniques for super-resolution microscopy using NV-diamond

NASA Astrophysics Data System (ADS)

Trifonov, Alexei; Glenn, David; Bar-Gill, Nir; Le Sage, David; Walsworth, Ronald

2011-05-01

We discuss the development and application of techniques for super-resolution microscopy using NV centers in diamond: stimulated emission depletion (STED), metastable ground state depletion (GSD), and stochastic optical reconstruction microscopy (STORM). NV centers do not bleach under optical excitation, are not biotoxic, and have long-lived electronic spin coherence and spin-state-dependent fluorescence. Thus NV-diamond has great potential as a fluorescent biomarker and as a magnetic biosensor.

Super-resolution microscopy reveals structural diversity in molecular exchange among peptide amphiphile nanofibres

DOE PAGES

da Silva, Ricardo M. P.; van der Zwaag, Daan; Albertazzi, Lorenzo; ...

2016-05-19

The dynamic behaviour of supramolecular systems is an important dimension of their potential functions. Here, we report on the use of stochastic optical reconstruction microscopy to study the molecular exchange of peptide amphiphile nanofibres, supramolecular systems known to have important biomedical functions. Solutions of nanofibres labelled with different dyes (Cy3 and Cy5) were mixed, and the distribution of dyes inserting into initially single-colour nanofibres was quantified using correlative image analysis. Our observations are consistent with an exchange mechanism involving monomers or small clusters of molecules inserting randomly into a fibre. Different exchange rates are observed within the same fibre, suggestingmore » that local cohesive structures exist on the basis of beta-sheet discontinuous domains. The results reported here show that peptide amphiphile supramolecular systems can be dynamic and that their intermolecular interactions affect exchange patterns. Lastly, this information can be used to generate useful aggregate morphologies for improved biomedical function.« less

Suppression of large edge-localized modes in high-confinement DIII-D plasmas with a stochastic magnetic boundary.

PubMed

Evans, T E; Moyer, R A; Thomas, P R; Watkins, J G; Osborne, T H; Boedo, J A; Doyle, E J; Fenstermacher, M E; Finken, K H; Groebner, R J; Groth, M; Harris, J H; La Haye, R J; Lasnier, C J; Masuzaki, S; Ohyabu, N; Pretty, D G; Rhodes, T L; Reimerdes, H; Rudakov, D L; Schaffer, M J; Wang, G; Zeng, L

2004-06-11

A stochastic magnetic boundary, produced by an applied edge resonant magnetic perturbation, is used to suppress most large edge-localized modes (ELMs) in high confinement (H-mode) plasmas. The resulting H mode displays rapid, small oscillations with a bursty character modulated by a coherent 130 Hz envelope. The H mode transport barrier and core confinement are unaffected by the stochastic boundary, despite a threefold drop in the toroidal rotation. These results demonstrate that stochastic boundaries are compatible with H modes and may be attractive for ELM control in next-step fusion tokamaks.

Stochastic Representations of Seismic Anisotropy: Verification of Effective Media Models and Application to the Continental Crust

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2017-12-01

The seismic anisotropy of the continental crust is dominated by two mechanisms: the local (intrinsic) anisotropy of crustal rocks caused by the lattice-preferred orientation of their constituent minerals, and the geometric (extrinsic) anisotropy caused by the alignment and layering of elastic heterogeneities by sedimentation and deformation. To assess the relative importance of these mechanisms, we have applied Jordan's (GJI, 2015) self-consistent, second-order theory to compute the effective elastic parameters of stochastic media with hexagonal local anisotropy and small-scale 3D heterogeneities that have transversely isotropic (TI) statistics. The theory pertains to stochastic TI media in which the eighth-order covariance tensor of the elastic moduli can be separated into a one-point variance tensor that describes the local anisotropy in terms of a anisotropy orientation ratio (ξ from 0 to ∞), and a two-point correlation function that describes the geometric anisotropy in terms of a heterogeneity aspect ratio (η from 0 to ∞). If there is no local anisotropy, then, in the limiting case of a horizontal stochastic laminate (η→∞), the effective-medium equations reduce to the second-order equations derived by Backus (1962) for a stochastically layered medium. This generalization of the Backus equations to 3D stochastic media, as well as the introduction of local, stochastically rotated anisotropy, provides a powerful theory for interpreting the anisotropic signatures of sedimentation and deformation in continental environments; in particular, the parameterizations that we propose are suitable for tomographic inversions. We have verified this theory through a series high-resolution numerical experiments using both isotropic and anisotropic wave-propagation codes.

The 2015 super-resolution microscopy roadmap

NASA Astrophysics Data System (ADS)

Hell, Stefan W.; Sahl, Steffen J.; Bates, Mark; Zhuang, Xiaowei; Heintzmann, Rainer; Booth, Martin J.; Bewersdorf, Joerg; Shtengel, Gleb; Hess, Harald; Tinnefeld, Philip; Honigmann, Alf; Jakobs, Stefan; Testa, Ilaria; Cognet, Laurent; Lounis, Brahim; Ewers, Helge; Davis, Simon J.; Eggeling, Christian; Klenerman, David; Willig, Katrin I.; Vicidomini, Giuseppe; Castello, Marco; Diaspro, Alberto; Cordes, Thorben

2015-11-01

Far-field optical microscopy using focused light is an important tool in a number of scientific disciplines including chemical, (bio)physical and biomedical research, particularly with respect to the study of living cells and organisms. Unfortunately, the applicability of the optical microscope is limited, since the diffraction of light imposes limitations on the spatial resolution of the image. Consequently the details of, for example, cellular protein distributions, can be visualized only to a certain extent. Fortunately, recent years have witnessed the development of ‘super-resolution’ far-field optical microscopy (nanoscopy) techniques such as stimulated emission depletion (STED), ground state depletion (GSD), reversible saturated optical (fluorescence) transitions (RESOLFT), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) or saturated structured illumination microscopy (SSIM), all in one way or another addressing the problem of the limited spatial resolution of far-field optical microscopy. While SIM achieves a two-fold improvement in spatial resolution compared to conventional optical microscopy, STED, RESOLFT, PALM/STORM, or SSIM have all gone beyond, pushing the limits of optical image resolution to the nanometer scale. Consequently, all super-resolution techniques open new avenues of biomedical research. Because the field is so young, the potential capabilities of different super-resolution microscopy approaches have yet to be fully explored, and uncertainties remain when considering the best choice of methodology. Thus, even for experts, the road to the future is sometimes shrouded in mist. The super-resolution optical microscopy roadmap of Journal of Physics D: Applied Physics addresses this need for clarity. It provides guidance to the outstanding questions through a collection of short review articles from experts in the field, giving a thorough discussion on the concepts underlying super-resolution optical microscopy, the potential of different approaches, the importance of label optimization (such as reversible photoswitchable proteins) and applications in which these methods will have a significant impact. Mark Bates, Christian Eggeling

Aptamer-recognized carbohydrates on the cell membrane revealed by super-resolution microscopy.

PubMed

Jing, Yingying; Cai, Mingjun; Xu, Haijiao; Zhou, Lulu; Yan, Qiuyan; Gao, Jing; Wang, Hongda

2018-04-26

Carbohydrates are one of the most important components on the cell membrane, which participate in various physiological activities, and their aberrant expression is a consequence of pathological changes. In previous studies, carbohydrate analysis basically relied on lectins. However, discrimination between lectins still exists due to their multivalent character. Furthermore, the structures obtained by carbohydrate-lectin crosslinking confuse our direct observation to some extent. Fortunately, the emergence of aptamers, which are smaller and more flexible, has provided us an unprecedented choice. Herein, an aptamer recognition method with high precise localization was developed for imaging membrane-bound N-acetylgalactosamine (GalNAc). By using direct stochastic optical reconstruction microscopy (dSTORM), we compared this aptamer recognition method with the lectin recognition method for visualizing the detailed structure of GalNAc at the nanometer scale. The results indicated that GalNAc forms irregular clusters on the cell membrane with a resolution of 23 ± 7 nm by aptamer recognition. Additionally, when treated with N-acetylgalactosidase, the aptamer-recognized GalNAc shows a more significant decrease in cluster size and localization density, thus verifying better specificity of aptamers than lectins. Collectively, our study suggests that aptamers can act as perfect substitutes for lectins in carbohydrate labeling, which will be of great potential value in the field of super-resolution fluorescence imaging.

Using dSTORM to probe the molecular architecture of filopodia

NASA Astrophysics Data System (ADS)

Ahmed, Sohail; Chou, Amy; Sem, K. P.; Thankiah, Sudaharan; Wright, Graham; Lim, John; Hariharan, Srivats

2014-03-01

IRSp53 is a Cdc42 effector and a member of the Inverse-Bin-Amphiphysins-Rvs (I-BAR) domain family which can induce negative membrane curvature. IRSp53 generates filopodia by coupling membrane protrusion (I-BAR domain) with actin dynamics through its SH3 domain binding partners. Dynamin 1 (Dyn1), a large GTPase associated with endocytosis, is a novel interacting partner of IRSp53 that localises to filopodia. Using rapid time-lapse TIRF microscopy we have shown that Dyn1 localized to a subcellular region just behind Mena at the leading edge, or in filopodial tip complexes when co-expressed with IRSp53. Dyn1-GFP was strongly localized in the filopodial shaft during the early phase of elongation, after which it moved rearward, suggestive of a role in early filopodia assembly. Mena and Eps8, accumulate at the tip complex in sequence and are involved in filopodial extension and retraction, respectively (Chou at al, 2014 submitted). Here we describe the use of dSTORM to investigate the molecular architecture of filopodia and in particular the size of the F-actin bundle in these structures. The data suggest that direct Stochastic Optical Reconstruction Microscopy (dSTORM) in combination with other techniques will allow the molecular architecture of

Single-spin stochastic optical reconstruction microscopy

PubMed Central

Pfender, Matthias; Aslam, Nabeel; Waldherr, Gerald; Neumann, Philipp; Wrachtrup, Jörg

2014-01-01

We experimentally demonstrate precision addressing of single-quantum emitters by combined optical microscopy and spin resonance techniques. To this end, we use nitrogen vacancy (NV) color centers in diamond confined within a few ten nanometers as individually resolvable quantum systems. By developing a stochastic optical reconstruction microscopy (STORM) technique for NV centers, we are able to simultaneously perform sub–diffraction-limit imaging and optically detected spin resonance (ODMR) measurements on NV spins. This allows the assignment of spin resonance spectra to individual NV center locations with nanometer-scale resolution and thus further improves spatial discrimination. For example, we resolved formerly indistinguishable emitters by their spectra. Furthermore, ODMR spectra contain metrology information allowing for sub–diffraction-limit sensing of, for instance, magnetic or electric fields with inherently parallel data acquisition. As an example, we have detected nuclear spins with nanometer-scale precision. Finally, we give prospects of how this technique can evolve into a fully parallel quantum sensor for nanometer resolution imaging of delocalized quantum correlations. PMID:25267655

Partitioning of the Golgi Apparatus during Mitosis in Living HeLa Cells

PubMed Central

Shima, David T.; Haldar, Kasturi; Pepperkok, Rainer; Watson, Rose; Warren, Graham

1997-01-01

The Golgi apparatus of HeLa cells was fluorescently tagged with a green fluorescent protein (GFP), localized by attachment to the NH2-terminal retention signal of N-acetylglucosaminyltransferase I (NAGT I). The location was confirmed by immunogold and immunofluorescence microscopy using a variety of Golgi markers. The behavior of the fluorescent Golgi marker was observed in fixed and living mitotic cells using confocal microscopy. By metaphase, cells contained a constant number of Golgi fragments dispersed throughout the cytoplasm. Conventional and cryoimmunoelectron microscopy showed that the NAGT I–GFP chimera (NAGFP)-positive fragments were tubulo-vesicular mitotic Golgi clusters. Mitotic conversion of Golgi stacks into mitotic clusters had surprisingly little effect on the polarity of Golgi membrane markers at the level of fluorescence microscopy. In living cells, there was little self-directed movement of the clusters in the period from metaphase to early telophase. In late telophase, the Golgi ribbon began to be reformed by a dynamic process of congregation and tubulation of the newly inherited Golgi fragments. The accuracy of partitioning the NAGFP-tagged Golgi was found to exceed that expected for a stochastic partitioning process. The results provide direct evidence for mitotic clusters as the unit of partitioning and suggest that precise regulation of the number, position, and compartmentation of mitotic membranes is a critical feature for the ordered inheritance of the Golgi apparatus. PMID:9182657

Correlative super-resolution fluorescence microscopy combined with optical coherence microscopy

NASA Astrophysics Data System (ADS)

Kim, Sungho; Kim, Gyeong Tae; Jang, Soohyun; Shim, Sang-Hee; Bae, Sung Chul

2015-03-01

Recent development of super-resolution fluorescence imaging technique such as stochastic optical reconstruction microscopy (STORM) and photoactived localization microscope (PALM) has brought us beyond the diffraction limits. It allows numerous opportunities in biology because vast amount of formerly obscured molecular structures, due to lack of spatial resolution, now can be directly observed. A drawback of fluorescence imaging, however, is that it lacks complete structural information. For this reason, we have developed a super-resolution multimodal imaging system based on STORM and full-field optical coherence microscopy (FF-OCM). FF-OCM is a type of interferometry systems based on a broadband light source and a bulk Michelson interferometer, which provides label-free and non-invasive visualization of biological samples. The integration between the two systems is simple because both systems use a wide-field illumination scheme and a conventional microscope. This combined imaging system gives us both functional information at a molecular level (~20nm) and structural information at the sub-cellular level (~1μm). For thick samples such as tissue slices, while FF-OCM is readily capable of imaging the 3D architecture, STORM suffer from aberrations and high background fluorescence that substantially degrade the resolution. In order to correct the aberrations in thick tissues, we employed an adaptive optics system in the detection path of the STORM microscope. We used our multimodal system to obtain images on brain tissue samples with structural and functional information.

Multidimensional stochastic approximation using locally contractive functions

NASA Technical Reports Server (NTRS)

Lawton, W. M.

1975-01-01

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

Dynamical Imaging using Spatial Nonlinearity

DTIC Science & Technology

2014-01-29

643. [5] R. Heintzmann, C. Cremer , Lateral modulated excitation microscopy: Improvement of resolution by using a diffraction grating, Proceedings...by stochastic optical reconstruction microscopy (STORM), Nat Methods, 3 ( 2006 ) 793-795. [14] E. Betzig, G.H. Patterson, R. Sougrat, O.W. Lindwasser...Science, 313 ( 2006 ) 1642-1645. [15] W. Lukosz, M. Marchand, Optischen Abbildung Unter Überschreitung der Beugungsbedingten Auflösungsgrenze, Optica

Asymmetric and Stochastic Behavior in Magnetic Vortices Studied by Soft X-ray Microscopy

NASA Astrophysics Data System (ADS)

Im, Mi-Young

Asymmetry and stochasticity in spin processes are not only long-standing fundamental issues but also highly relevant to technological applications of nanomagnetic structures to memory and storage nanodevices. Those nontrivial phenomena have been studied by direct imaging of spin structures in magnetic vortices utilizing magnetic transmission soft x-ray microscopy (BL6.1.2 at ALS). Magnetic vortices have attracted enormous scientific interests due to their fascinating spin structures consisting of circularity rotating clockwise (c = + 1) or counter-clockwise (c = -1) and polarity pointing either up (p = + 1) or down (p = -1). We observed a symmetry breaking in the formation process of vortex structures in circular permalloy (Ni80Fe20) disks. The generation rates of two different vortex groups with the signature of cp = + 1 and cp =-1 are completely asymmetric. The asymmetric nature was interpreted to be triggered by ``intrinsic'' Dzyaloshinskii-Moriya interaction (DMI) arising from the spin-orbit coupling due to the lack of inversion symmetry near the disk surface and ``extrinsic'' factors such as roughness and defects. We also investigated the stochastic behavior of vortex creation in the arrays of asymmetric disks. The stochasticity was found to be very sensitive to the geometry of disk arrays, particularly interdisk distance. The experimentally observed phenomenon couldn't be explained by thermal fluctuation effect, which has been considered as a main reason for the stochastic behavior in spin processes. We demonstrated for the first time that the ultrafast dynamics at the early stage of vortex creation, which has a character of classical chaos significantly affects the stochastic nature observed at the steady state in asymmetric disks. This work provided the new perspective of dynamics as a critical factor contributing to the stochasticity in spin processes and also the possibility for the control of the intrinsic stochastic nature by optimizing the design of asymmetric disk arrays. This work was supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by Leading Foreign Research Institute Recruitment Program through the NRF.

Gyrotactic swimmer dispersion in pipe flow: testing the theory

NASA Astrophysics Data System (ADS)

Croze, Ottavio A.; Bearon, Rachel N.; Bees, Martin A.

2017-04-01

Suspensions of microswimmers are a rich source of fascinating new fluid mechanics. Recently we predicted the active pipe flow dispersion of gyrotactic microalgae, whose orientation is biased by gravity and flow shear. Analytical theory predicts that these active swimmers disperse in a markedly distinct manner from passive tracers (Taylor dispersion). Dispersing swimmers display nonzero drift and effective diffusivity that is non-monotonic with P$\\'e$clet number. Such predictions agree with numerical simulations, but hitherto have not been tested experimentally. Here, to facilitate comparison, we obtain new solutions of the axial dispersion theory accounting both for swimmer negative buoyancy and a local nonlinear response of swimmers to shear, provided by two alternative microscopic stochastic descriptions. We obtain new predictions for suspensions of the model swimming alga $\\it Dunaliella\\,salina$, whose motility and buoyant mass we parametrise using tracking video microscopy. We then present a new experimental method to measure gyrotactic dispersion using fluorescently stained $\\it D. salina$ and provide a preliminary comparison with predictions of a nonzero drift above the mean flow for each microscopic stochastic description. Finally, we propose further experiments for a full experimental characterisation of gyrotactic dispersion measures and discuss implications of our results for algal dispersion in industrial photobioreactors.

Stochastically gated local and occupation times of a Brownian particle

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.

2017-01-01

We generalize the Feynman-Kac formula to analyze the local and occupation times of a Brownian particle moving in a stochastically gated one-dimensional domain. (i) The gated local time is defined as the amount of time spent by the particle in the neighborhood of a point in space where there is some target that only receives resources from (or detects) the particle when the gate is open; the target does not interfere with the motion of the Brownian particle. (ii) The gated occupation time is defined as the amount of time spent by the particle in the positive half of the real line, given that it can only cross the origin when a gate placed at the origin is open; in the closed state the particle is reflected. In both scenarios, the gate randomly switches between the open and closed states according to a two-state Markov process. We derive a stochastic, backward Fokker-Planck equation (FPE) for the moment-generating function of the two types of gated Brownian functional, given a particular realization of the stochastic gate, and analyze the resulting stochastic FPE using a moments method recently developed for diffusion processes in randomly switching environments. In particular, we obtain dynamical equations for the moment-generating function, averaged with respect to realizations of the stochastic gate.

Revealing the cellular localization of STAT1 during the cell cycle by super-resolution imaging

PubMed Central

Gao, Jing; Wang, Feng; Liu, Yanhou; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Wang, Hongda

2015-01-01

Signal transducers and activators of transcription (STATs) can transduce cytokine signals and regulate gene expression. The cellular localization and nuclear trafficking of STAT1, a representative of the STAT family with multiple transcriptional functions, is tightly related with transcription process, which usually happens in the interphase of the cell cycle. However, these priority questions regarding STAT1 distribution and localization at the different cell-cycle stages remain unclear. By using direct stochastic optical reconstruction microscopy (dSTORM), we found that the nuclear expression level of STAT1 increased gradually as the cell cycle carried out, especially after EGF stimulation. Furthermore, STAT1 formed clusters in the whole cell during the cell cycle, with the size and the number of clusters also increasing significantly from G1 to G2 phase, suggesting that transcription and other cell-cycle related activities can promote STAT1 to form more and larger clusters for fast response to signals. Our work reveals that the cellular localization and clustering distribution of STAT1 are associated with the cell cycle, and further provides an insight into the mechanism of cell-cycle regulated STAT1 signal transduction. PMID:25762114

Stochasticity in the signalling network of a model microbe

NASA Astrophysics Data System (ADS)

Bischofs, Ilka; Foley, Jonathan; Battenberg, Eric; Fontaine-Bodin, Lisa; Price, Gavin; Wolf, Denise; Arkin, Adam

2007-03-01

The soil dwelling bacterium Bacillus subtilis is an excellent model organism for studying stochastic stress response induction in an isoclonal population. Subjected to the same stressor cells undergo different cell fates, including sporulation, competence, degradative enzyme synthesis and motility. For example, under conditions of nutrient deprivation and high cell density only a portion of the cell population forms an endospore. Here we use a combined experimental and theoretical approach to study stochastic sporulation induction in Bacillus subtilis. Using several fluorescent reporter strains we apply time lapse fluorescent microscopy in combination with quantitative image analysis to study cell fate progression on a single cell basis and elucidate key noise generators in the underlying cellular network.

New ways of looking at very small holes - using optical nanoscopy to visualize liver sinusoidal endothelial cell fenestrations

NASA Astrophysics Data System (ADS)

Øie, Cristina I.; Mönkemöller, Viola; Hübner, Wolfgang; Schüttpelz, Mark; Mao, Hong; Ahluwalia, Balpreet S.; Huser, Thomas R.; McCourt, Peter

2018-02-01

Super-resolution fluorescence microscopy, also known as nanoscopy, has provided us with a glimpse of future impacts on cell biology. Far-field optical nanoscopy allows, for the first time, the study of sub-cellular nanoscale biological structures in living cells, which in the past was limited to electron microscopy (EM) (in fixed/dehydrated) cells or tissues. Nanoscopy has particular utility in the study of "fenestrations" - phospholipid transmembrane nanopores of 50-150 nm in diameter through liver sinusoidal endothelial cells (LSECs) that facilitate the passage of plasma, but (usually) not blood cells, to and from the surrounding hepatocytes. Previously, these fenestrations were only discernible with EM, but now they can be visualized in fixed and living cells using structured illumination microscopy (SIM) and in fixed cells using single molecule localization microscopy (SMLM) techniques such as direct stochastic optical reconstruction microscopy. Importantly, both methods use wet samples, avoiding dehydration artifacts. The use of nanoscopy can be extended to the in vitro study of fenestration dynamics, to address questions such as the following: are they actually dynamic structures, and how do they respond to endogenous and exogenous agents? A logical further extension of these methodologies to liver research (including the liver endothelium) will be their application to liver tissue sections from animal models with different pathological manifestations and ultimately to patient biopsies. This review will cover the current state of the art of the use of nanoscopy in the study of liver endothelium and the liver in general. Potential future applications in cell biology and the clinical implications will be discussed.

Conserving the linear momentum in stochastic dynamics: Dissipative particle dynamics as a general strategy to achieve local thermostatization in molecular dynamics simulations.

PubMed

Passler, Peter P; Hofer, Thomas S

2017-02-15

Stochastic dynamics is a widely employed strategy to achieve local thermostatization in molecular dynamics simulation studies; however, it suffers from an inherent violation of momentum conservation. Although this short-coming has little impact on structural and short-time dynamic properties, it can be shown that dynamics in the long-time limit such as diffusion is strongly dependent on the respective thermostat setting. Application of the methodically similar dissipative particle dynamics (DPD) provides a simple, effective strategy to ensure the advantages of local, stochastic thermostatization while at the same time the linear momentum of the system remains conserved. In this work, the key parameters to employ the DPD thermostats in the framework of periodic boundary conditions are investigated, in particular the dependence of the system properties on the size of the DPD-region as well as the treatment of forces near the cutoff. Structural and dynamical data for light and heavy water as well as a Lennard-Jones fluid have been compared to simulations executed via stochastic dynamics as well as via use of the widely employed Nose-Hoover chain and Berendsen thermostats. It is demonstrated that a small size of the DPD region is sufficient to achieve local thermalization, while at the same time artifacts in the self-diffusion characteristic for stochastic dynamics are eliminated. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting

PubMed Central

Veatch, Sarah L.; Machta, Benjamin B.; Shelby, Sarah A.; Chiang, Ethan N.; Holowka, David A.; Baird, Barbara A.

2012-01-01

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins. PMID:22384026

Stochastic Swift-Hohenberg Equation with Degenerate Linear Multiplicative Noise

NASA Astrophysics Data System (ADS)

Hernández, Marco; Ong, Kiah Wah

2018-03-01

We study the dynamic transition of the Swift-Hohenberg equation (SHE) when linear multiplicative noise acting on a finite set of modes of the dominant linear flow is introduced. Existence of a stochastic flow and a local stochastic invariant manifold for this stochastic form of SHE are both addressed in this work. We show that the approximate reduced system corresponding to the invariant manifold undergoes a stochastic pitchfork bifurcation, and obtain numerical evidence suggesting that this picture is a good approximation for the full system as well.

Gryphon: A Hybrid Agent-Based Modeling and Simulation Platform for Infectious Diseases

NASA Astrophysics Data System (ADS)

Yu, Bin; Wang, Jijun; McGowan, Michael; Vaidyanathan, Ganesh; Younger, Kristofer

In this paper we present Gryphon, a hybrid agent-based stochastic modeling and simulation platform developed for characterizing the geographic spread of infectious diseases and the effects of interventions. We study both local and non-local transmission dynamics of stochastic simulations based on the published parameters and data for SARS. The results suggest that the expected numbers of infections and the timeline of control strategies predicted by our stochastic model are in reasonably good agreement with previous studies. These preliminary results indicate that Gryphon is able to characterize other future infectious diseases and identify endangered regions in advance.

Rich stochastic dynamics of co-doped Er:Yb fluorescence upconversion nanoparticles in the presence of thermal, non-conservative, harmonic and optical forces

NASA Astrophysics Data System (ADS)

Nome, Rene A.; Sorbello, Cecilia; Jobbágy, Matías; Barja, Beatriz C.; Sanches, Vitor; Cruz, Joyce S.; Aguiar, Vinicius F.

2017-03-01

The stochastic dynamics of individual co-doped Er:Yb upconversion nanoparticles (UCNP) were investigated from experiments and simulations. The UCNP were characterized by high-resolution scanning electron microscopy, dynamic light scattering, and zeta potential measurements. Single UCNP measurements were performed by fluorescence upconversion micro-spectroscopy and optical trapping. The mean-square displacement (MSD) from single UCNP exhibited a time-dependent diffusion coefficient which was compared with Brownian dynamics simulations of a viscoelastic model of harmonically bound spheres. Experimental time-dependent two-dimensional trajectories of individual UCNP revealed correlated two-dimensional nanoparticle motion. The measurements were compared with stochastic trajectories calculated in the presence of a non-conservative rotational force field. Overall, the complex interplay of UCNP adhesion, thermal fluctuations and optical forces led to a rich stochastic behavior of these nanoparticles.

Effective stochastic generator with site-dependent interactions

NASA Astrophysics Data System (ADS)

Khamehchi, Masoumeh; Jafarpour, Farhad H.

2017-11-01

It is known that the stochastic generators of effective processes associated with the unconditioned dynamics of rare events might consist of non-local interactions; however, it can be shown that there are special cases for which these generators can include local interactions. In this paper, we investigate this possibility by considering systems of classical particles moving on a one-dimensional lattice with open boundaries. The particles might have hard-core interactions similar to the particles in an exclusion process, or there can be many arbitrary particles at a single site in a zero-range process. Assuming that the interactions in the original process are local and site-independent, we will show that under certain constraints on the microscopic reaction rules, the stochastic generator of an unconditioned process can be local but site-dependent. As two examples, the asymmetric zero-temperature Glauber model and the A-model with diffusion are presented and studied under the above-mentioned constraints.

A stochastic model for eye movements during fixation on a stationary target.

NASA Technical Reports Server (NTRS)

Vasudevan, R.; Phatak, A. V.; Smith, J. D.

1971-01-01

A stochastic model describing small eye movements occurring during steady fixation on a stationary target is presented. Based on eye movement data for steady gaze, the model has a hierarchical structure; the principal level represents the random motion of the image point within a local area of fixation, while the higher level mimics the jump processes involved in transitions from one local area to another. Target image motion within a local area is described by a Langevin-like stochastic differential equation taking into consideration the microsaccadic jumps pictured as being due to point processes and the high frequency muscle tremor, represented as a white noise. The transform of the probability density function for local area motion is obtained, leading to explicit expressions for their means and moments. Evaluation of these moments based on the model is comparable with experimental results.

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com

Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less

Superresolution microscopy reveals the three-dimensional organization of meiotic chromosome axes in intact Caenorhabditis elegans tissue

PubMed Central

Köhler, Simone; Wojcik, Michal; Dernburg, Abby F.

2017-01-01

When cells enter meiosis, their chromosomes reorganize as linear arrays of chromatin loops anchored to a central axis. Meiotic chromosome axes form a platform for the assembly of the synaptonemal complex (SC) and play central roles in other meiotic processes, including homologous pairing, recombination, and chromosome segregation. However, little is known about the 3D organization of components within the axes, which include cohesin complexes and additional meiosis-specific proteins. Here, we investigate the molecular organization of meiotic chromosome axes in Caenorhabditis elegans through STORM (stochastic optical reconstruction microscopy) and PALM (photo-activated localization microscopy) superresolution imaging of intact germ-line tissue. By tagging one axis protein (HIM-3) with a photoconvertible fluorescent protein, we established a spatial reference for other components, which were localized using antibodies against epitope tags inserted by CRISPR/Cas9 genome editing. Using 3D averaging, we determined the position of all known components within synapsed chromosome axes to high spatial precision in three dimensions. We find that meiosis-specific HORMA domain proteins span a gap between cohesin complexes and the central region of the SC, consistent with their essential roles in SC assembly. Our data further suggest that the two different meiotic cohesin complexes are distinctly arranged within the axes: Although cohesin complexes containing the kleisin REC-8 protrude above and below the plane defined by the SC, complexes containing COH-3 or -4 kleisins form a central core, which may physically separate sister chromatids. This organization may help to explain the role of the chromosome axes in promoting interhomolog repair of meiotic double-strand breaks by inhibiting intersister repair. PMID:28559338

Multi-Algorithm Particle Simulations with Spatiocyte.

PubMed

Arjunan, Satya N V; Takahashi, Koichi

2017-01-01

As quantitative biologists get more measurements of spatially regulated systems such as cell division and polarization, simulation of reaction and diffusion of proteins using the data is becoming increasingly relevant to uncover the mechanisms underlying the systems. Spatiocyte is a lattice-based stochastic particle simulator for biochemical reaction and diffusion processes. Simulations can be performed at single molecule and compartment spatial scales simultaneously. Molecules can diffuse and react in 1D (filament), 2D (membrane), and 3D (cytosol) compartments. The implications of crowded regions in the cell can be investigated because each diffusing molecule has spatial dimensions. Spatiocyte adopts multi-algorithm and multi-timescale frameworks to simulate models that simultaneously employ deterministic, stochastic, and particle reaction-diffusion algorithms. Comparison of light microscopy images to simulation snapshots is supported by Spatiocyte microscopy visualization and molecule tagging features. Spatiocyte is open-source software and is freely available at http://spatiocyte.org .

The scaling of population persistence with carrying capacity does not asymptote in populations of a fish experiencing extreme climate variability.

PubMed

White, Richard S A; Wintle, Brendan A; McHugh, Peter A; Booker, Douglas J; McIntosh, Angus R

2017-06-14

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. © 2017 The Author(s).

Stochastic simulation of biological reactions, and its applications for studying actin polymerization.

PubMed

Ichikawa, Kazuhisa; Suzuki, Takashi; Murata, Noboru

2010-11-30

Molecular events in biological cells occur in local subregions, where the molecules tend to be small in number. The cytoskeleton, which is important for both the structural changes of cells and their functions, is also a countable entity because of its long fibrous shape. To simulate the local environment using a computer, stochastic simulations should be run. We herein report a new method of stochastic simulation based on random walk and reaction by the collision of all molecules. The microscopic reaction rate P(r) is calculated from the macroscopic rate constant k. The formula involves only local parameters embedded for each molecule. The results of the stochastic simulations of simple second-order, polymerization, Michaelis-Menten-type and other reactions agreed quite well with those of deterministic simulations when the number of molecules was sufficiently large. An analysis of the theory indicated a relationship between variance and the number of molecules in the system, and results of multiple stochastic simulation runs confirmed this relationship. We simulated Ca²(+) dynamics in a cell by inward flow from a point on the cell surface and the polymerization of G-actin forming F-actin. Our results showed that this theory and method can be used to simulate spatially inhomogeneous events.

2–stage stochastic Runge–Kutta for stochastic delay differential equations

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

Rosli, Norhayati; Jusoh Awang, Rahimah; Bahar, Arifah

2015-05-15

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

Environmental Noise Could Promote Stochastic Local Stability of Behavioral Diversity Evolution

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2018-05-01

In this Letter, we investigate stochastic stability in a two-phenotype evolutionary game model for an infinite, well-mixed population undergoing discrete, nonoverlapping generations. We assume that the fitness of a phenotype is an exponential function of its expected payoff following random pairwise interactions whose outcomes randomly fluctuate with time. We show that the stochastic local stability of a constant interior equilibrium can be promoted by the random environmental noise even if the system may display a complicated nonlinear dynamics. This result provides a new perspective for a better understanding of how environmental fluctuations may contribute to the evolution of behavioral diversity.

In-situ atomic force microscopy observation revealing gel-like plasticity on a metallic glass surface

NASA Astrophysics Data System (ADS)

Lu, Y. M.; Zeng, J. F.; Huang, J. C.; Kuan, S. Y.; Nieh, T. G.; Wang, W. H.; Pan, M. X.; Liu, C. T.; Yang, Y.

2017-03-01

It has been decade-long and enduring efforts to decipher the structural mechanism of plasticity in metallic glasses; however, it still remains a challenge to directly reveal the structural change, if any, that precedes; and dominant plastics flow in them. Here, by using the dynamic atomic force microscope as an "imaging" as well as a "forcing" tool, we unfold a real-time sequence of structural evolution occurring on the surface of an Au-Si thin film metallic glass. In sharp contrast to the common notion that plasticity comes along with mechanical softening in bulk metallic glasses, our experimental results directly reveal three types of nano-sized surface regions, which undergo plasticity but exhibit different characters of structural evolution following the local plasticity events, including stochastic structural rearrangement, unusual local relaxation and rejuvenation. As such, yielding on the metallic-glass surface manifests as a dynamic equilibrium between local relaxation and rejuvenation as opposed to shear instability in bulk metallic-glasses. Our finding demonstrates that plasticity on the metallic glass surface of Au-Si metallic glass bears much resemblance to that of the colloidal gels, of which nonlinear rheology rather than shear instability governs the constitutive behavior of plasticity.

Spatially heterogeneous stochasticity and the adaptive diversification of dormancy.

PubMed

Rajon, E; Venner, S; Menu, F

2009-10-01

Diversified bet-hedging, a strategy that leads several individuals with the same genotype to express distinct phenotypes in a given generation, is now well established as a common evolutionary response to environmental stochasticity. Life-history traits defined as diversified bet-hedging (e.g. germination or diapause strategies) display marked differences between populations in spatial proximity. In order to find out whether such differences can be explained by local adaptations to spatially heterogeneous environmental stochasticity, we explored the evolution of bet-hedging dormancy strategies in a metapopulation using a two-patch model with patch differences in stochastic juvenile survival. We found that spatial differences in the level of environmental stochasticity, restricted dispersal, increased fragmentation and intermediate survival during dormancy all favour the adaptive diversification of bet-hedging dormancy strategies. Density dependency also plays a major role in the diversification of dormancy strategies because: (i) it may interact locally with environmental stochasticity and amplify its effects; however, (ii) it can also generate chaotic population dynamics that may impede diversification. Our work proposes new hypotheses to explain the spatial patterns of bet-hedging strategies that we hope will encourage new empirical studies of this topic.

Systemic localization of seven major types of carbohydrates on cell membranes by dSTORM imaging.

PubMed

Chen, Junling; Gao, Jing; Zhang, Min; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Tian, Zhiyuan; Wang, Hongda

2016-07-25

Carbohydrates on the cell surface control intercellular interactions and play a vital role in various physiological processes. However, their systemic distribution patterns are poorly understood. Through the direct stochastic optical reconstruction microscopy (dSTORM) strategy, we systematically revealed that several types of representative carbohydrates are found in clustered states. Interestingly, the results from dual-color dSTORM imaging indicate that these carbohydrate clusters are prone to connect with one another and eventually form conjoined platforms where different functional glycoproteins aggregate (e.g., epidermal growth factor receptor, (EGFR) and band 3 protein). A thorough understanding of the ensemble distribution of carbohydrates on the cell surface paves the way for elucidating the structure-function relationship of cell membranes and the critical roles of carbohydrates in various physiological and pathological cell processes.

Systemic localization of seven major types of carbohydrates on cell membranes by dSTORM imaging

PubMed Central

Chen, Junling; Gao, Jing; Zhang, Min; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Tian, Zhiyuan; Wang, Hongda

2016-01-01

Carbohydrates on the cell surface control intercellular interactions and play a vital role in various physiological processes. However, their systemic distribution patterns are poorly understood. Through the direct stochastic optical reconstruction microscopy (dSTORM) strategy, we systematically revealed that several types of representative carbohydrates are found in clustered states. Interestingly, the results from dual-color dSTORM imaging indicate that these carbohydrate clusters are prone to connect with one another and eventually form conjoined platforms where different functional glycoproteins aggregate (e.g., epidermal growth factor receptor, (EGFR) and band 3 protein). A thorough understanding of the ensemble distribution of carbohydrates on the cell surface paves the way for elucidating the structure-function relationship of cell membranes and the critical roles of carbohydrates in various physiological and pathological cell processes. PMID:27453176

Functional imaging for regenerative medicine.

PubMed

Leahy, Martin; Thompson, Kerry; Zafar, Haroon; Alexandrov, Sergey; Foley, Mark; O'Flatharta, Cathal; Dockery, Peter

2016-04-19

In vivo imaging is a platform technology with the power to put function in its natural structural context. With the drive to translate stem cell therapies into pre-clinical and clinical trials, early selection of the right imaging techniques is paramount to success. There are many instances in regenerative medicine where the biological, biochemical, and biomechanical mechanisms behind the proposed function of stem cell therapies can be elucidated by appropriate imaging. Imaging techniques can be divided according to whether labels are used and as to whether the imaging can be done in vivo. In vivo human imaging places additional restrictions on the imaging tools that can be used. Microscopies and nanoscopies, especially those requiring fluorescent markers, have made an extraordinary impact on discovery at the molecular and cellular level, but due to their very limited ability to focus in the scattering tissues encountered for in vivo applications they are largely confined to superficial imaging applications in research laboratories. Nanoscopy, which has tremendous benefits in resolution, is limited to the near-field (e.g. near-field scanning optical microscope (NSNOM)) or to very high light intensity (e.g. stimulated emission depletion (STED)) or to slow stochastic events (photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM)). In all cases, nanoscopy is limited to very superficial applications. Imaging depth may be increased using multiphoton or coherence gating tricks. Scattering dominates the limitation on imaging depth in most tissues and this can be mitigated by the application of optical clearing techniques that can impose mild (e.g. topical application of glycerol) or severe (e.g. CLARITY) changes to the tissue to be imaged. Progression of therapies through to clinical trials requires some thought as to the imaging and sensing modalities that should be used. Smoother progression is facilitated by the use of comparable imaging modalities throughout the discovery and trial phases, giving label-free techniques an advantage wherever they can be used, although this is seldom considered in the early stages. In this paper, we will explore the techniques that have found success in aiding discovery in stem cell therapies and try to predict the likely technologies best suited to translation and future directions.

A Stochastic Water Balance Framework for Lowland Watersheds

NASA Astrophysics Data System (ADS)

Thompson, Sally; MacVean, Lissa; Sivapalan, Murugesu

2017-11-01

The water balance dynamics in lowland watersheds are influenced not only by local hydroclimatic controls on energy and water availability, but also by imports of water from the upstream watershed. These imports result in a stochastic extent of inundation in lowland watersheds that is determined by the local flood regime, watershed topography, and the rate of loss processes such as drainage and evaporation. Thus, lowland watershed water balances depend on two stochastic processes—rainfall and local inundation dynamics. Lowlands are high productivity environments that are disproportionately associated with urbanization, high productivity agriculture, biodiversity, and flood risk. Consequently, they are being rapidly altered by human development—generally with clear economic and social motivation—but also with significant trade-offs in ecosystem services provision, directly related to changes in the components and variability of the lowland water balance. We present a stochastic framework to assess the lowland water balance and its sensitivity to two common human interventions—replacement of native vegetation with alternative land uses, and construction of local flood protection levees. By providing analytical solutions for the mean and PDF of the water balance components, the proposed framework provides a mechanism to connect human interventions to hydrologic outcomes, and, in conjunction with ecosystem service production estimates, to evaluate trade-offs associated with lowland watershed development.

Microsphere-aided optical microscopy and its applications for super-resolution imaging

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Pramanik, Manojit

2017-12-01

The spatial resolution of a standard optical microscope (SOM) is limited by diffraction. In visible spectrum, SOM can provide ∼ 200 nm resolution. To break the diffraction limit several approaches were developed including scanning near field microscopy, metamaterial super-lenses, nanoscale solid immersion lenses, super-oscillatory lenses, confocal fluorescence microscopy, techniques that exploit non-linear response of fluorophores like stimulated emission depletion microscopy, stochastic optical reconstruction microscopy, etc. Recently, photonic nanojet generated by a dielectric microsphere was used to break the diffraction limit. The microsphere-approach is simple, cost-effective and can be implemented under a standard microscope, hence it has gained enormous attention for super-resolution imaging. In this article, we briefly review the microsphere approach and its applications for super-resolution imaging in various optical imaging modalities.

A passive physical model for DnaK chaperoning

NASA Astrophysics Data System (ADS)

Uhl, Lionel; Dumont, Audrey; Dukan, Sam

2018-03-01

Almost all living organisms use protein chaperones with a view to preventing proteins from misfolding or aggregation either spontaneously or during cellular stress. This work uses a reaction-diffusion stochastic model to describe the dynamic localization of the Hsp70 chaperone DnaK in Escherichia coli cells during transient proteotoxic collapse characterized by the accumulation of insoluble proteins. In the model, misfolded (‘abnormal’) proteins are produced during alcoholic stress and have the propensity to aggregate with a polymerization-like kinetics. When aggregates diffuse more slowly they grow larger. According to Michaelis-Menten-type kinetics, DnaK has the propensity to bind with misfolded proteins or aggregates in order to catalyse refolding. To match experimental fluorescence microscopy data showing clusters of DnaK-GFP localized in multiple foci, the model includes spatial zones with local reduced diffusion rates to generate spontaneous assemblies of DnaK called ‘foci’. Numerical simulations of our model succeed in reproducing the kinetics of DnaK localization experimentally observed. DnaK starts from foci, moves to large aggregates during acute stress, resolves those aggregates during recovery and finally returns to its initial punctate localization pattern. Finally, we compare real biological events with hypothetical repartitions of the protein aggregates or DnaK. We then notice that DnaK action is more efficient on protein aggregates than on protein homogeneously distributed.

Electrostatic force microscopy as a broadly applicable method for characterizing pyroelectric materials.

PubMed

Martin-Olmos, Cristina; Stieg, Adam Z; Gimzewski, James K

2012-06-15

A general method based on the combination of electrostatic force microscopy with thermal cycling of the substrate holder is presented for direct, nanoscale characterization of the pyroelectric effect in a range of materials and sample configurations using commercial atomic force microscope systems. To provide an example of its broad applicability, the technique was applied to the examination of natural tourmaline gemstones. The method was validated using thermal cycles similar to those experienced in ambient conditions, where the induced pyroelectric response produced localized electrostatic surface charges whose magnitude demonstrated a correlation with the iron content and heat dissipation of each gemstone variety. In addition, the surface charge was shown to persist even at thermal equilibrium. This behavior is attributed to constant, stochastic cooling of the gemstone surface through turbulent contact with the surrounding air and indicates a potential utility for energy harvesting in applications including environmental sensors and personal electronics. In contrast to previously reported methods, ours has a capacity to carry out such precise nanoscale measurements with little or no restriction on the sample of interest, and represents a powerful new tool for the characterization of pyroelectric materials and devices.

Electrostatic force microscopy as a broadly applicable method for characterizing pyroelectric materials

NASA Astrophysics Data System (ADS)

Martin-Olmos, Cristina; Stieg, Adam Z.; Gimzewski, James K.

2012-06-01

A general method based on the combination of electrostatic force microscopy with thermal cycling of the substrate holder is presented for direct, nanoscale characterization of the pyroelectric effect in a range of materials and sample configurations using commercial atomic force microscope systems. To provide an example of its broad applicability, the technique was applied to the examination of natural tourmaline gemstones. The method was validated using thermal cycles similar to those experienced in ambient conditions, where the induced pyroelectric response produced localized electrostatic surface charges whose magnitude demonstrated a correlation with the iron content and heat dissipation of each gemstone variety. In addition, the surface charge was shown to persist even at thermal equilibrium. This behavior is attributed to constant, stochastic cooling of the gemstone surface through turbulent contact with the surrounding air and indicates a potential utility for energy harvesting in applications including environmental sensors and personal electronics. In contrast to previously reported methods, ours has a capacity to carry out such precise nanoscale measurements with little or no restriction on the sample of interest, and represents a powerful new tool for the characterization of pyroelectric materials and devices.

Super resolution imaging of HER2 gene amplification

NASA Astrophysics Data System (ADS)

Okada, Masaya; Kubo, Takuya; Masumoto, Kanako; Iwanaga, Shigeki

2016-02-01

HER2 positive breast cancer is currently examined by counting HER2 genes using fluorescence in situ hybridization (FISH)-stained breast carcinoma samples. In this research, two-dimensional super resolution fluorescence microscopy based on stochastic optical reconstruction microscopy (STORM), with a spatial resolution of approximately 20 nm in the lateral direction, was used to more precisely distinguish and count HER2 genes in a FISH-stained tissue section. Furthermore, by introducing double-helix point spread function (DH-PSF), an optical phase modulation technique, to super resolution microscopy, three-dimensional images were obtained of HER2 in a breast carcinoma sample approximately 4 μm thick.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Visible/near-infrared subdiffraction imaging reveals the stochastic nature of DNA walkers.

PubMed

Pan, Jing; Cha, Tae-Gon; Li, Feiran; Chen, Haorong; Bragg, Nina A; Choi, Jong Hyun

2017-01-01

DNA walkers are designed with the structural specificity and functional diversity of oligonucleotides to actively convert chemical energy into mechanical translocation. Compared to natural protein motors, DNA walkers' small translocation distance (mostly <100 nm) and slow reaction rate (<0.1 nm s -1 ) make single-molecule characterization of their kinetics elusive. An important indication of single-walker kinetics is the rate-limiting reactions that a particular walker design bears. We introduce an integrated super-resolved fluorescence microscopy approach that is capable of long-term imaging to investigate the stochastic behavior of DNA walkers. Subdiffraction tracking and imaging in the visible and second near-infrared spectra resolve walker structure and reaction rates. The distributions of walker kinetics are analyzed using a stochastic model to reveal reaction randomness and the rate-limiting biochemical reaction steps.

Visible/near-infrared subdiffraction imaging reveals the stochastic nature of DNA walkers

PubMed Central

Pan, Jing; Cha, Tae-Gon; Li, Feiran; Chen, Haorong; Bragg, Nina A.; Choi, Jong Hyun

2017-01-01

DNA walkers are designed with the structural specificity and functional diversity of oligonucleotides to actively convert chemical energy into mechanical translocation. Compared to natural protein motors, DNA walkers’ small translocation distance (mostly <100 nm) and slow reaction rate (<0.1 nm s−1) make single-molecule characterization of their kinetics elusive. An important indication of single-walker kinetics is the rate-limiting reactions that a particular walker design bears. We introduce an integrated super-resolved fluorescence microscopy approach that is capable of long-term imaging to investigate the stochastic behavior of DNA walkers. Subdiffraction tracking and imaging in the visible and second near-infrared spectra resolve walker structure and reaction rates. The distributions of walker kinetics are analyzed using a stochastic model to reveal reaction randomness and the rate-limiting biochemical reaction steps. PMID:28116353

Probing the stochastic, motor-driven properties of the cytoplasm using force spectrum microscopy

PubMed Central

Guo, Ming; Ehrlicher, Allen J.; Jensen, Mikkel H.; Renz, Malte; Moore, Jeffrey R.; Goldman, Robert D.; Lippincott-Schwartz, Jennifer; Mackintosh, Frederick C.; Weitz, David A.

2014-01-01

SUMMARY Molecular motors in cells typically produce highly directed motion; however, the aggregate, incoherent effect of all active processes also creates randomly fluctuating forces, which drive diffusive-like, non-thermal motion. Here we introduce force-spectrum-microscopy (FSM) to directly quantify random forces within the cytoplasm of cells and thereby probe stochastic motor activity. This technique combines measurements of the random motion of probe particles with independent micromechanical measurements of the cytoplasm to quantify the spectrum of force fluctuations. Using FSM, we show that force fluctuations substantially enhance intracellular movement of small and large components. The fluctuations are three times larger in malignant cells than in their benign counterparts. We further demonstrate that vimentin acts globally to anchor organelles against randomly fluctuating forces in the cytoplasm, with no effect on their magnitude. Thus, FSM has broad applications for understanding the cytoplasm and its intracellular processes in relation to cell physiology in healthy and diseased states. PMID:25126787

Single molecule characterization of DNA binding and strand displacement reactions on lithographic DNA origami microarrays.

PubMed

Scheible, Max B; Pardatscher, Günther; Kuzyk, Anton; Simmel, Friedrich C

2014-03-12

The combination of molecular self-assembly based on the DNA origami technique with lithographic patterning enables the creation of hierarchically ordered nanosystems, in which single molecules are positioned at precise locations on multiple length scales. Based on a hybrid assembly protocol utilizing DNA self-assembly and electron-beam lithography on transparent glass substrates, we here demonstrate a DNA origami microarray, which is compatible with the requirements of single molecule fluorescence and super-resolution microscopy. The spatial arrangement allows for a simple and reliable identification of single molecule events and facilitates automated read-out and data analysis. As a specific application, we utilize the microarray to characterize the performance of DNA strand displacement reactions localized on the DNA origami structures. We find considerable variability within the array, which results both from structural variations and stochastic reaction dynamics prevalent at the single molecule level.

Super-Resolution Optical Fluctuation Bio-Imaging with Dual-Color Carbon Nanodots.

PubMed

Chizhik, Anna M; Stein, Simon; Dekaliuk, Mariia O; Battle, Christopher; Li, Weixing; Huss, Anja; Platen, Mitja; Schaap, Iwan A T; Gregor, Ingo; Demchenko, Alexander P; Schmidt, Christoph F; Enderlein, Jörg; Chizhik, Alexey I

2016-01-13

Success in super-resolution imaging relies on a proper choice of fluorescent probes. Here, we suggest novel easily produced and biocompatible nanoparticles-carbon nanodots-for super-resolution optical fluctuation bioimaging (SOFI). The particles revealed an intrinsic dual-color fluorescence, which corresponds to two subpopulations of particles of different electric charges. The neutral nanoparticles localize to cellular nuclei suggesting their potential use as an inexpensive, easily produced nucleus-specific label. The single particle study revealed that the carbon nanodots possess a unique hybrid combination of fluorescence properties exhibiting characteristics of both dye molecules and semiconductor nanocrystals. The results suggest that charge trapping and redistribution on the surface of the particles triggers their transitions between emissive and dark states. These findings open up new possibilities for the utilization of carbon nanodots in the various super-resolution microscopy methods based on stochastic optical switching.

A state space based approach to localizing single molecules from multi-emitter images.

PubMed

Vahid, Milad R; Chao, Jerry; Ward, E Sally; Ober, Raimund J

2017-01-28

Single molecule super-resolution microscopy is a powerful tool that enables imaging at sub-diffraction-limit resolution. In this technique, subsets of stochastically photoactivated fluorophores are imaged over a sequence of frames and accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Available localization methods typically first determine the regions of the image that contain emitting fluorophores through a process referred to as detection. Then, the locations of the fluorophores are estimated accurately in an estimation step. We propose a novel localization method which combines the detection and estimation steps. The method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix, and determines the locations of intensity peaks in the image as the pole locations of the resulting system. The locations of the most significant peaks correspond to the locations of single molecules in the original image. Although the accuracy of the location estimates is reasonably good, we demonstrate that, by using the estimates as the initial conditions for a maximum likelihood estimator, refined estimates can be obtained that have a standard deviation close to the Cramér-Rao lower bound-based limit of accuracy. We validate our method using both simulated and experimental multi-emitter images.

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

PubMed Central

Hosny, Neveen A.; Song, Mingying; Connelly, John T.; Ameer-Beg, Simon; Knight, Martin M.; Wheeler, Ann P.

2013-01-01

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging. PMID:24130668

Finite metapopulation models with density-dependent migration and stochastic local dynamics

PubMed Central

Saether, B.-E.; Engen, S.; Lande, R.

1999-01-01

The effects of small density-dependent migration on the dynamics of a metapopulation are studied in a model with stochastic local dynamics. We use a diffusion approximation to study how changes in the migration rate and habitat occupancy affect the rates of local colonization and extinction. If the emigration rate increases or if the immigration rate decreases with local population size, a positive expected rate of change in habitat occupancy is found for a greater range of habitat occupancies than when the migration is density-independent. In contrast, the reverse patterns of density dependence in respective emigration and immigration reduce the range of habitat occupancies where the metapopulation will be viable. This occurs because density-dependent migration strongly influences both the establishment and rescue effects in the local dynamics of metapopulations.

Facile method to stain the bacterial cell surface for super-resolution fluorescence microscopy

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

Gunsolus, Ian L.; Hu, Dehong; Mihai, Cosmin

A method to fluorescently stain the surfaces of both Gram-negative and Gram-positive bacterial cells compatible with super-resolution fluorescence microscopy is presented. This method utilizes a commercially-available fluorescent probe to label primary amines at the surface of the cell. We demonstrate efficient staining of two bacterial strains, the Gram-negative Shewanella oneidensis MR-1 and the Gram-positive Bacillus subtilis 168. Using structured illumination microscopy and stochastic optical reconstruction microscopy, which require high quantum yield or specialized dyes, we show that this staining method may be used to resolve the bacterial cell surface with sub-diffraction-limited resolution. We further use this method to identify localizationmore » patterns of nanomaterials, specifically cadmium selenide quantum dots, following interaction with bacterial cells.« less

Evolution with Stochastic Fitness and Stochastic Migration

PubMed Central

Rice, Sean H.; Papadopoulos, Anthony

2009-01-01

Background Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration. Methodology/Principal Findings We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter. Conclusions/Significance As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory. PMID:19816580

What Shapes the Phylogenetic Structure of Anuran Communities in a Seasonal Environment? The Influence of Determinism at Regional Scale to Stochasticity or Antagonistic Forces at Local Scale

PubMed Central

Ferreira, Vanda Lúcia; Strüssmann, Christine; Tomas, Walfrido Moraes

2015-01-01

Ecological communities are structured by both deterministic and stochastic processes. We investigated phylogenetic patterns at regional and local scales to understand the influences of seasonal processes in shaping the structure of anuran communities in the southern Pantanal wetland, Brazil. We assessed the phylogenetic structure at different scales, using the Net Relatedness Index (NRI), the Nearest Taxon Index (NTI), and phylobetadiversity indexes, as well as a permutation test, to evaluate the effect of seasonality. The anuran community was represented by a non-random set of species with a high degree of phylogenetic relatedness at the regional scale. However, at the local scale the phylogenetic structure of the community was weakly related with the seasonality of the system, indicating that oriented stochastic processes (e.g. colonization, extinction and ecological drift) and/or antagonist forces drive the structure of such communities in the southern Pantanal. PMID:26102202

What Shapes the Phylogenetic Structure of Anuran Communities in a Seasonal Environment? The Influence of Determinism at Regional Scale to Stochasticity or Antagonistic Forces at Local Scale.

PubMed

Martins, Clarissa de Araújo; Roque, Fabio de Oliveira; Santos, Bráulio A; Ferreira, Vanda Lúcia; Strüssmann, Christine; Tomas, Walfrido Moraes

2015-01-01

Ecological communities are structured by both deterministic and stochastic processes. We investigated phylogenetic patterns at regional and local scales to understand the influences of seasonal processes in shaping the structure of anuran communities in the southern Pantanal wetland, Brazil. We assessed the phylogenetic structure at different scales, using the Net Relatedness Index (NRI), the Nearest Taxon Index (NTI), and phylobetadiversity indexes, as well as a permutation test, to evaluate the effect of seasonality. The anuran community was represented by a non-random set of species with a high degree of phylogenetic relatedness at the regional scale. However, at the local scale the phylogenetic structure of the community was weakly related with the seasonality of the system, indicating that oriented stochastic processes (e.g. colonization, extinction and ecological drift) and/or antagonist forces drive the structure of such communities in the southern Pantanal.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy

PubMed Central

Valades Cruz, Cesar Augusto; Shaban, Haitham Ahmed; Kress, Alla; Bertaux, Nicolas; Monneret, Serge; Mavrakis, Manos; Savatier, Julien; Brasselet, Sophie

2016-01-01

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells. PMID:26831082

Stochastic locality and master-field simulations of very large lattices

NASA Astrophysics Data System (ADS)

Lüscher, Martin

2018-03-01

In lattice QCD and other field theories with a mass gap, the field variables in distant regions of a physically large lattice are only weakly correlated. Accurate stochastic estimates of the expectation values of local observables may therefore be obtained from a single representative field. Such master-field simulations potentially allow very large lattices to be simulated, but require various conceptual and technical issues to be addressed. In this talk, an introduction to the subject is provided and some encouraging results of master-field simulations of the SU(3) gauge theory are reported.

Geographic variation in density-dependent dynamics impacts the synchronizing effect of dispersal and regional stochasticity

Treesearch

Andrew M. Liebhold; Derek M. Johnson; Ottar N. Bj& #248rnstad

2006-01-01

Explanations for the ubiquitous presence of spatially synchronous population dynamics have assumed that density-dependent processes governing the dynamics of local populations are identical among disjunct populations, and low levels of dispersal or small amounts of regionalized stochasticity ("Moran effect") can act to synchronize populations. In this study...

On Local Homogeneity and Stochastically Ordered Mixed Rasch Models

ERIC Educational Resources Information Center

Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg

2006-01-01

Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…

Nanostructure of DNA repair foci revealed by superresolution microscopy.

PubMed

Sisario, Dmitri; Memmel, Simon; Doose, Sören; Neubauer, Julia; Zimmermann, Heiko; Flentje, Michael; Djuzenova, Cholpon S; Sauer, Markus; Sukhorukov, Vladimir L

2018-06-12

Induction of DNA double-strand breaks (DSBs) by ionizing radiation leads to formation of micrometer-sized DNA-repair foci, whose organization on the nanometer-scale remains unknown because of the diffraction limit (∼200 nm) of conventional microscopy. Here, we applied diffraction-unlimited, direct stochastic optical-reconstruction microscopy ( dSTORM) with a lateral resolution of ∼20 nm to analyze the focal nanostructure of the DSB marker histone γH2AX and the DNA-repair protein kinase (DNA-PK) in irradiated glioblastoma multiforme cells. Although standard confocal microscopy revealed substantial colocalization of immunostained γH2AX and DNA-PK, in our dSTORM images, the 2 proteins showed very little (if any) colocalization despite their close spatial proximity. We also found that γH2AX foci consisted of distinct circular subunits ("nanofoci") with a diameter of ∼45 nm, whereas DNA-PK displayed a diffuse, intrafocal distribution. We conclude that γH2AX nanofoci represent the elementary, structural units of DSB repair foci, that is, individual γH2AX-containing nucleosomes. dSTORM-based γH2AX nanofoci counting and distance measurements between nanofoci provided quantitative information on the total amount of chromatin involved in DSB repair as well as on the number and longitudinal distribution of γH2AX-containing nucleosomes in a chromatin fiber. We thus estimate that a single focus involves between ∼0.6 and ∼1.1 Mbp of chromatin, depending on radiation treatment. Because of their ability to unravel the nanostructure of DSB-repair foci, dSTORM and related single-molecule localization nanoscopy methods will likely emerge as powerful tools in biology and medicine to elucidate the effects of DNA damaging agents in cells.-Sisario, D., Memmel, S., Doose, S., Neubauer, J., Zimmermann, H., Flentje, M., Djuzenova, C. S., Sauer, M., Sukhorukov, V. L. Nanostructure of DNA repair foci revealed by superresolution microscopy.

Stochastic resonance on a modular neuronal network of small-world subnetworks with a subthreshold pacemaker

NASA Astrophysics Data System (ADS)

Yu, Haitao; Wang, Jiang; Liu, Chen; Deng, Bin; Wei, Xile

2011-12-01

We study the phenomenon of stochastic resonance on a modular neuronal network consisting of several small-world subnetworks with a subthreshold periodic pacemaker. Numerical results show that the correlation between the pacemaker frequency and the dynamical response of the network is resonantly dependent on the intensity of additive spatiotemporal noise. This effect of pacemaker-driven stochastic resonance of the system depends extensively on the local and the global network structure, such as the intra- and inter-coupling strengths, rewiring probability of individual small-world subnetwork, the number of links between different subnetworks, and the number of subnetworks. All these parameters play a key role in determining the ability of the network to enhance the noise-induced outreach of the localized subthreshold pacemaker, and only they bounded to a rather sharp interval of values warrant the emergence of the pronounced stochastic resonance phenomenon. Considering the rather important role of pacemakers in real-life, the presented results could have important implications for many biological processes that rely on an effective pacemaker for their proper functioning.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2006-11-01

A stochastic output error (OE) vibration-based methodology for damage detection and assessment (localization and quantification) in structures under earthquake excitation is introduced. The methodology is intended for assessing the state of a structure following potential damage occurrence by exploiting vibration signal measurements produced by low-level earthquake excitations. It is based upon (a) stochastic OE model identification, (b) statistical hypothesis testing procedures for damage detection, and (c) a geometric method (GM) for damage assessment. The methodology's advantages include the effective use of the non-stationary and limited duration earthquake excitation, the handling of stochastic uncertainties, the tackling of the damage localization and quantification subproblems, the use of "small" size, simple and partial (in both the spatial and frequency bandwidth senses) identified OE-type models, and the use of a minimal number of measured vibration signals. Its feasibility and effectiveness are assessed via Monte Carlo experiments employing a simple simulation model of a 6 storey building. It is demonstrated that damage levels of 5% and 20% reduction in a storey's stiffness characteristics may be properly detected and assessed using noise-corrupted vibration signals.

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

PubMed Central

Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

2018-01-01

Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

PubMed

Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

2018-06-01

The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2016-06-01

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

Angular reconstitution-based 3D reconstructions of nanomolecular structures from superresolution light-microscopy images

PubMed Central

Salas, Desirée; Le Gall, Antoine; Fiche, Jean-Bernard; Valeri, Alessandro; Ke, Yonggang; Bron, Patrick; Bellot, Gaetan

2017-01-01

Superresolution light microscopy allows the imaging of labeled supramolecular assemblies at a resolution surpassing the classical diffraction limit. A serious limitation of the superresolution approach is sample heterogeneity and the stochastic character of the labeling procedure. To increase the reproducibility and the resolution of the superresolution results, we apply multivariate statistical analysis methods and 3D reconstruction approaches originally developed for cryogenic electron microscopy of single particles. These methods allow for the reference-free 3D reconstruction of nanomolecular structures from two-dimensional superresolution projection images. Since these 2D projection images all show the structure in high-resolution directions of the optical microscope, the resulting 3D reconstructions have the best possible isotropic resolution in all directions. PMID:28811371

Consistent nonlinear deterministic and stochastic evolution equations for deep to shallow water wave shoaling

NASA Astrophysics Data System (ADS)

Vrecica, Teodor; Toledo, Yaron

2015-04-01

One-dimensional deterministic and stochastic evolution equations are derived for the dispersive nonlinear waves while taking dissipation of energy into account. The deterministic nonlinear evolution equations are formulated using operational calculus by following the approach of Bredmose et al. (2005). Their formulation is extended to include the linear and nonlinear effects of wave dissipation due to friction and breaking. The resulting equation set describes the linear evolution of the velocity potential for each wave harmonic coupled by quadratic nonlinear terms. These terms describe the nonlinear interactions between triads of waves, which represent the leading-order nonlinear effects in the near-shore region. The equations are translated to the amplitudes of the surface elevation by using the approach of Agnon and Sheremet (1997) with the correction of Eldeberky and Madsen (1999). The only current possibility for calculating the surface gravity wave field over large domains is by using stochastic wave evolution models. Hence, the above deterministic model is formulated as a stochastic one using the method of Agnon and Sheremet (1997) with two types of stochastic closure relations (Benney and Saffman's, 1966, and Hollway's, 1980). These formulations cannot be applied to the common wave forecasting models without further manipulation, as they include a non-local wave shoaling coefficients (i.e., ones that require integration along the wave rays). Therefore, a localization method was applied (see Stiassnie and Drimer, 2006, and Toledo and Agnon, 2012). This process essentially extracts the local terms that constitute the mean nonlinear energy transfer while discarding the remaining oscillatory terms, which transfer energy back and forth. One of the main findings of this work is the understanding that the approximated non-local coefficients behave in two essentially different manners. In intermediate water depths these coefficients indeed consist of rapidly oscillating terms, but as the water depth becomes shallow they change to an exponential growth (or decay) behavior. Hence, the formerly used localization technique cannot be justified for the shallow water region. A new formulation is devised for the localization in shallow water, it approximates the nonlinear non-local shoaling coefficient in shallow water and matches it to the one fitting to the intermediate water region. This allows the model behavior to be consistent from deep water to intermediate depths and up to the shallow water regime. Various simulations of the model were performed for the cases of intermediate, and shallow water, overall the model was found to give good results in both shallow and intermediate water depths. The essential difference between the shallow and intermediate nonlinear shoaling physics is explained via the dominating class III Bragg resonances phenomenon. By inspecting the resonance conditions and the nature of the dispersion relation, it is shown that unlike in the intermediate water regime, in shallow water depths the formation of resonant interactions is possible without taking into account bottom components. References Agnon, Y. & Sheremet, A. 1997 Stochastic nonlinear shoaling of directional spectra. J. Fluid Mech. 345, 79-99. Benney, D. J. & Saffman, P. G. 1966 Nonlinear interactions of random waves. Proc. R. Soc. Lond. A 289, 301-321. Bredmose, H., Agnon, Y., Madsen, P.A. & Schaffer, H.A. 2005 Wave transformation models with exact second-order transfer. European J. of Mech. - B/Fluids 24 (6), 659-682. Eldeberky, Y. & Madsen, P. A. 1999 Deterministic and stochastic evolution equations for fully dispersive and weakly nonlinear waves. Coastal Engineering 38, 1-24. Kaihatu, J. M. & Kirby, J. T. 1995 Nonlinear transformation of waves in infinite water depth. Phys. Fluids 8, 175-188. Holloway, G. 1980 Oceanic internal waves are not weak waves. J. Phys. Oceanogr. 10, 906-914. Stiassnie, M. & Drimer, N. 2006 Prediction of long forcing waves for harbor agitation studies. J. of waterways, port, coastal and ocean engineering 132(3), 166-171. Toledo, Y. & Agnon, Y. 2012 Stochastic evolution equations with localized nonlinear shoaling coefficients. European J. of Mech. - B/Fluids 34, 13-18.

Characterization and reconstruction of 3D stochastic microstructures via supervised learning.

PubMed

Bostanabad, R; Chen, W; Apley, D W

2016-12-01

The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing-structure-property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user-defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

An improved stochastic fractal search algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Sun, Chuan; Wang, Bin; Wang, Xiaojun

2018-05-03

Protein structure prediction (PSP) is a significant area for biological information research, disease treatment, and drug development and so on. In this paper, three-dimensional structures of proteins are predicted based on the known amino acid sequences, and the structure prediction problem is transformed into a typical NP problem by an AB off-lattice model. This work applies a novel improved Stochastic Fractal Search algorithm (ISFS) to solve the problem. The Stochastic Fractal Search algorithm (SFS) is an effective evolutionary algorithm that performs well in exploring the search space but falls into local minimums sometimes. In order to avoid the weakness, Lvy flight and internal feedback information are introduced in ISFS. In the experimental process, simulations are conducted by ISFS algorithm on Fibonacci sequences and real peptide sequences. Experimental results prove that the ISFS performs more efficiently and robust in terms of finding the global minimum and avoiding getting stuck in local minimums.

Empirical method to measure stochasticity and multifractality in nonlinear time series

NASA Astrophysics Data System (ADS)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

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

Halsted, Michelle; Wilmoth, Jared L.; Briggs, Paige A.

Microbial communities are incredibly complex systems that dramatically and ubiquitously influence our lives. They help to shape our climate and environment, impact agriculture, drive business, and have a tremendous bearing on healthcare and physical security. Spatial confinement, as well as local variations in physical and chemical properties, affects development and interactions within microbial communities that occupy critical niches in the environment. Recent work has demonstrated the use of silicon based microwell arrays, combined with parylene lift-off techniques, to perform both deterministic and stochastic assembly of microbial communities en masse, enabling the high-throughput screening of microbial communities for their response tomore » growth in confined environments under different conditions. The implementation of a transparent microwell array platform can expand and improve the imaging modalities that can be used to characterize these assembled communities. In this paper, the fabrication and characterization of a next generation transparent microwell array is described. The transparent arrays, comprised of SU-8 patterned on a glass coverslip, retain the ability to use parylene lift-off by integrating a low temperature atomic layer deposition of silicon dioxide into the fabrication process. This silicon dioxide layer prevents adhesion of the parylene material to the patterned SU-8, facilitating dry lift-off, and maintaining the ability to easily assemble microbial communities within the microwells. These transparent microwell arrays can screen numerous community compositions using continuous, high resolution, imaging. Finally, the utility of the design was successfully demonstrated through the stochastic seeding and imaging of green fluorescent protein expressing Escherichia coli using both fluorescence and brightfield microscopies.« less

Stochastic Local Search for Core Membership Checking in Hedonic Games

NASA Astrophysics Data System (ADS)

Keinänen, Helena

Hedonic games have emerged as an important tool in economics and show promise as a useful formalism to model multi-agent coalition formation in AI as well as group formation in social networks. We consider a coNP-complete problem of core membership checking in hedonic coalition formation games. No previous algorithms to tackle the problem have been presented. In this work, we overcome this by developing two stochastic local search algorithms for core membership checking in hedonic games. We demonstrate the usefulness of the algorithms by showing experimentally that they find solutions efficiently, particularly for large agent societies.

Repurposing a photosynthetic antenna protein as a super-resolution microscopy label.

PubMed

Barnett, Samuel F H; Hitchcock, Andrew; Mandal, Amit K; Vasilev, Cvetelin; Yuen, Jonathan M; Morby, James; Brindley, Amanda A; Niedzwiedzki, Dariusz M; Bryant, Donald A; Cadby, Ashley J; Holten, Dewey; Hunter, C Neil

2017-12-01

Techniques such as Stochastic Optical Reconstruction Microscopy (STORM) and Structured Illumination Microscopy (SIM) have increased the achievable resolution of optical imaging, but few fluorescent proteins are suitable for super-resolution microscopy, particularly in the far-red and near-infrared emission range. Here we demonstrate the applicability of CpcA, a subunit of the photosynthetic antenna complex in cyanobacteria, for STORM and SIM imaging. The periodicity and width of fabricated nanoarrays of CpcA, with a covalently attached phycoerythrobilin (PEB) or phycocyanobilin (PCB) chromophore, matched the lines in reconstructed STORM images. SIM and STORM reconstructions of Escherichia coli cells harbouring CpcA-labelled cytochrome bd 1 ubiquinol oxidase in the cytoplasmic membrane show that CpcA-PEB and CpcA-PCB are suitable for super-resolution imaging in vivo. The stability, ease of production, small size and brightness of CpcA-PEB and CpcA-PCB demonstrate the potential of this largely unexplored protein family as novel probes for super-resolution microscopy.

Super-resolution Microscopical Localization of Dopamine Receptors 1 and 2 in Rat Hippocampal Synaptosomes.

PubMed

Miklosi, Andras G; Del Favero, Giorgia; Bulat, Tanja; Höger, Harald; Shigemoto, Ryuichi; Marko, Doris; Lubec, Gert

2018-06-01

Although dopamine receptors D1 and D2 play key roles in hippocampal function, their synaptic localization within the hippocampus has not been fully elucidated. In order to understand precise functions of pre- or postsynaptic dopamine receptors (DRs), the development of protocols to differentiate pre- and postsynaptic DRs is essential. So far, most studies on determination and quantification of DRs did not discriminate between subsynaptic localization. Therefore, the aim of the study was to generate a robust workflow for the localization of DRs. This work provides the basis for future work on hippocampal DRs, in light that DRs may have different functions at pre- or postsynaptic sites. Synaptosomes from rat hippocampi isolated by a sucrose gradient protocol were prepared for super-resolution direct stochastic optical reconstruction microscopy (dSTORM) using Bassoon as a presynaptic zone and Homer1 as postsynaptic density marker. Direct labeling of primary validated antibodies against dopamine receptors D1 (D1R) and D2 (D2R) with Alexa Fluor 594 enabled unequivocal assignment of D1R and D2R to both, pre- and postsynaptic sites. D1R immunoreactivity clusters were observed within the presynaptic active zone as well as at perisynaptic sites at the edge of the presynaptic active zone. The results may be useful for the interpretation of previous studies and the design of future work on DRs in the hippocampus. Moreover, the reduction of the complexity of brain tissue by the use of synaptosomal preparations and dSTORM technology may represent a useful tool for synaptic localization of brain proteins.

Evolutionary stability concepts in a stochastic environment

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2017-09-01

Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

Structural analysis of herpes simplex virus by optical super-resolution imaging

NASA Astrophysics Data System (ADS)

Laine, Romain F.; Albecka, Anna; van de Linde, Sebastian; Rees, Eric J.; Crump, Colin M.; Kaminski, Clemens F.

2015-01-01

Herpes simplex virus type-1 (HSV-1) is one of the most widespread pathogens among humans. Although the structure of HSV-1 has been extensively investigated, the precise organization of tegument and envelope proteins remains elusive. Here we use super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM) in combination with a model-based analysis of single-molecule localization data, to determine the position of protein layers within virus particles. We resolve different protein layers within individual HSV-1 particles using multi-colour dSTORM imaging and discriminate envelope-anchored glycoproteins from tegument proteins, both in purified virions and in virions present in infected cells. Precise characterization of HSV-1 structure was achieved by particle averaging of purified viruses and model-based analysis of the radial distribution of the tegument proteins VP16, VP1/2 and pUL37, and envelope protein gD. From this data, we propose a model of the protein organization inside the tegument.

High abundance of BDNF within glutamatergic presynapses of cultured hippocampal neurons

PubMed Central

Andreska, Thomas; Aufmkolk, Sarah; Sauer, Markus; Blum, Robert

2014-01-01

In the mammalian brain, the neurotrophin brain-derived neurotrophic factor (BDNF) has emerged as a key factor for synaptic refinement, plasticity and learning. Although BDNF-induced signaling cascades are well known, the spatial aspects of the synaptic BDNF localization remained unclear. Recent data provide strong evidence for an exclusive presynaptic location and anterograde secretion of endogenous BDNF at synapses of the hippocampal circuit. In contrast, various studies using BDNF overexpression in cultured hippocampal neurons support the idea that postsynaptic elements and other dendritic structures are the preferential sites of BDNF localization and release. In this study we used rigorously tested anti-BDNF antibodies and achieved a dense labeling of endogenous BDNF close to synapses. Confocal microscopy showed natural BDNF close to many, but not all glutamatergic synapses, while neither GABAergic synapses nor postsynaptic structures carried a typical synaptic BDNF label. To visualize the BDNF distribution within the fine structure of synapses, we implemented super resolution fluorescence imaging by direct stochastic optical reconstruction microscopy (dSTORM). Two-color dSTORM images of neurites were acquired with a spatial resolution of ~20 nm. At this resolution, the synaptic scaffold proteins Bassoon and Homer exhibit hallmarks of mature synapses and form juxtaposed bars, separated by a synaptic cleft. BDNF imaging signals form granule-like clusters with a mean size of ~60 nm and are preferentially found within the fine structure of the glutamatergic presynapse. Individual glutamatergic presynapses carried up to 90% of the synaptic BDNF immunoreactivity, and only a minor fraction of BDNF molecules was found close to the postsynaptic bars. Our data proof that hippocampal neurons are able to enrich and store high amounts of BDNF in small granules within the mature glutamatergic presynapse, at a principle site of synaptic plasticity. PMID:24782711

Roles of dispersal, stochasticity, and nonlinear dynamics in the spatial structuring of seasonal natural enemy-victim populations

Treesearch

Patrick C. Tobin; Ottar N. Bjornstad

2005-01-01

Natural enemy-victim systems may exhibit a range of dynamic space-time patterns. We used a theoretical framework to study spatiotemporal structuring in a transient natural enemy-victim system subject to differential rates of dispersal, stochastic forcing, and nonlinear dynamics. Highly mobile natural enemies that attacked less mobile victims were locally spatially...

Role of demographic stochasticity in a speciation model with sexual reproduction

NASA Astrophysics Data System (ADS)

Lafuerza, Luis F.; McKane, Alan J.

2016-03-01

Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM).

PubMed

Wang, Yilin; Kanchanawong, Pakorn

2016-12-01

Fluorescence microscopy enables direct visualization of specific biomolecules within cells. However, for conventional fluorescence microscopy, the spatial resolution is restricted by diffraction to ~ 200 nm within the image plane and > 500 nm along the optical axis. As a result, fluorescence microscopy has long been severely limited in the observation of ultrastructural features within cells. The recent development of super resolution microscopy methods has overcome this limitation. In particular, the advent of photoswitchable fluorophores enables localization-based super resolution microscopy, which provides resolving power approaching the molecular-length scale. Here, we describe the application of a three-dimensional super resolution microscopy method based on single-molecule localization microscopy and multiphase interferometry, called interferometric PhotoActivated Localization Microscopy (iPALM). This method provides nearly isotropic resolution on the order of 20 nm in all three dimensions. Protocols for visualizing the filamentous actin cytoskeleton, including specimen preparation and operation of the iPALM instrument, are described here. These protocols are also readily adaptable and instructive for the study of other ultrastructural features in cells.

Superresolution microscopy reveals spatial separation of UCP4 and F0F1-ATP synthase in neuronal mitochondria

PubMed Central

Klotzsch, Enrico; Smorodchenko, Alina; Löfler, Lukas; Moldzio, Rudolf; Parkinson, Elena; Schütz, Gerhard J.; Pohl, Elena E.

2015-01-01

Because different proteins compete for the proton gradient across the inner mitochondrial membrane, an efficient mechanism is required for allocation of associated chemical potential to the distinct demands, such as ATP production, thermogenesis, regulation of reactive oxygen species (ROS), etc. Here, we used the superresolution technique dSTORM (direct stochastic optical reconstruction microscopy) to visualize several mitochondrial proteins in primary mouse neurons and test the hypothesis that uncoupling protein 4 (UCP4) and F0F1-ATP synthase are spatially separated to eliminate competition for the proton motive force. We found that UCP4, F0F1-ATP synthase, and the mitochondrial marker voltage-dependent anion channel (VDAC) have various expression levels in different mitochondria, supporting the hypothesis of mitochondrial heterogeneity. Our experimental results further revealed that UCP4 is preferentially localized in close vicinity to VDAC, presumably at the inner boundary membrane, whereas F0F1-ATP synthase is more centrally located at the cristae membrane. The data suggest that UCP4 cannot compete for protons because of its spatial separation from both the proton pumps and the ATP synthase. Thus, mitochondrial morphology precludes UCP4 from acting as an uncoupler of oxidative phosphorylation but is consistent with the view that UCP4 may dissipate the excessive proton gradient, which is usually associated with ROS production. PMID:25535394

Managerial performance and cost efficiency of Japanese local public hospitals: a latent class stochastic frontier model.

PubMed

Besstremyannaya, Galina

2011-09-01

The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management. Copyright © 2011 John Wiley & Sons, Ltd.

Classification of Four-Qubit States by Means of a Stochastic Local Operation and the Classical Communication Invariant

NASA Astrophysics Data System (ADS)

Zha, Xin-Wei; Ma, Gang-Long

2011-02-01

It is a recent observation that entanglement classification for qubits is closely related to stochastic local operations and classical communication (SLOCC) invariants. Verstraete et al.[Phys. Rev. A 65 (2002) 052112] showed that for pure states of four qubits there are nine different degenerate SLOCC entanglement classes. Li et al.[Phys. Rev. A 76 (2007) 052311] showed that there are at feast 28 distinct true SLOCC entanglement classes for four qubits by means of the SLOCC invariant and semi-invariant. We give 16 different entanglement classes for four qubits by means of basic SLOCC invariants.

Local-scale Partitioning of Functional and Phylogenetic Beta Diversity in a Tropical Tree Assemblage.

PubMed

Yang, Jie; Swenson, Nathan G; Zhang, Guocheng; Ci, Xiuqin; Cao, Min; Sha, Liqing; Li, Jie; Ferry Slik, J W; Lin, Luxiang

2015-08-03

The relative degree to which stochastic and deterministic processes underpin community assembly is a central problem in ecology. Quantifying local-scale phylogenetic and functional beta diversity may shed new light on this problem. We used species distribution, soil, trait and phylogenetic data to quantify whether environmental distance, geographic distance or their combination are the strongest predictors of phylogenetic and functional beta diversity on local scales in a 20-ha tropical seasonal rainforest dynamics plot in southwest China. The patterns of phylogenetic and functional beta diversity were generally consistent. The phylogenetic and functional dissimilarity between subplots (10 × 10 m, 20 × 20 m, 50 × 50 m and 100 × 100 m) was often higher than that expected by chance. The turnover of lineages and species function within habitats was generally slower than that across habitats. Partitioning the variation in phylogenetic and functional beta diversity showed that environmental distance was generally a better predictor of beta diversity than geographic distance thereby lending relatively more support for deterministic environmental filtering over stochastic processes. Overall, our results highlight that deterministic processes play a stronger role than stochastic processes in structuring community composition in this diverse assemblage of tropical trees.

Transient ensemble dynamics in time-independent galactic potentials

NASA Astrophysics Data System (ADS)

Mahon, M. Elaine; Abernathy, Robert A.; Bradley, Brendan O.; Kandrup, Henry E.

1995-07-01

This paper summarizes a numerical investigation of the short-time, possibly transient, behaviour of ensembles of stochastic orbits evolving in fixed non-integrable potentials, with the aim of deriving insights into the structure and evolution of galaxies. The simulations involved three different two-dimensional potentials, quite different in appearance. However, despite these differences, ensembles in all three potentials exhibit similar behaviour. This suggests that the conclusions inferred from the simulations are robust, relying only on basic topological properties, e.g., the existence of KAM tori and cantori. Generic ensembles of initial conditions, corresponding to stochastic orbits, exhibit a rapid coarse-grained approach towards a near-invariant distribution on a time-scale <>t_H, although various irregularities associated with external and/or internal irregularities can drastically accelerate this process. A principal tool in the analysis is the notion of a local Liapounov exponent, which provides a statistical characterization of the overall instability of stochastic orbits over finite time intervals. In particular, there is a precise sense in which confined stochastic orbits are less unstable, with smaller local Liapounov exponents, than are unconfined stochastic orbits.

A stochastic model for the probability of malaria extinction by mass drug administration.

PubMed

Pemberton-Ross, Peter; Chitnis, Nakul; Pothin, Emilie; Smith, Thomas A

2017-09-18

Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. The results indicate that mass drug administration (Firstly, R c must be sustained at R c  < 1.2 to avoid the rapid re-establishment of infections in the population. Secondly, the MDA must produce effective cure rates of >95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

A stochastic approach for quantifying immigrant integration: the Spanish test case

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Contucci, Pierluigi; Sandell, Richard; Vernia, Cecilia

2014-10-01

We apply stochastic process theory to the analysis of immigrant integration. Using a unique and detailed data set from Spain, we study the relationship between local immigrant density and two social and two economic immigration quantifiers for the period 1999-2010. As opposed to the classic time-series approach, by letting immigrant density play the role of ‘time’ and the quantifier the role of ‘space,’ it becomes possible to analyse the behavior of the quantifiers by means of continuous time random walks. Two classes of results are then obtained. First, we show that social integration quantifiers evolve following diffusion law, while the evolution of economic quantifiers exhibits ballistic dynamics. Second, we make predictions of best- and worst-case scenarios taking into account large local fluctuations. Our stochastic process approach to integration lends itself to interesting forecasting scenarios which, in the hands of policy makers, have the potential to improve political responses to integration problems. For instance, estimating the standard first-passage time and maximum-span walk reveals local differences in integration performance for different immigration scenarios. Thus, by recognizing the importance of local fluctuations around national means, this research constitutes an important tool to assess the impact of immigration phenomena on municipal budgets and to set up solid multi-ethnic plans at the municipal level as immigration pressures build.

Estimation and prediction under local volatility jump-diffusion model

NASA Astrophysics Data System (ADS)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

Super-resolution microscopy reveals protein spatial reorganization in early innate immune responses.

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

Carson, Bryan D.; Aaron, Jesse S.; Timlin, Jerilyn Ann

2010-10-01

Over the past decade optical approaches were introduced that effectively break the diffraction barrier. Of particular note were introductions of Stimulated Emission/Depletion (STED) microscopy, Photo-Activated Localization Microscopy (PALM), and the closely related Stochastic Optical Reconstruction Microscopy (STORM). STORM represents an attractive method for researchers, as it does not require highly specialized optical setups, can be implemented using commercially available dyes, and is more easily amenable to multicolor imaging. We implemented a simultaneous dual-color, direct-STORM imaging system through the use of an objective-based TIRF microscope and filter-based image splitter. This system allows for excitation and detection of two fluorophors simultaneously, viamore » projection of each fluorophor's signal onto separate regions of a detector. We imaged the sub-resolution organization of the TLR4 receptor, a key mediator of innate immune response, after challenge with lipopolysaccharide (LPS), a bacteria-specific antigen. While distinct forms of LPS have evolved among various bacteria, only some LPS variations (such as that derived from E. coli) typically result in significant cellular immune response. Others (such as from the plague bacteria Y. pestis) do not, despite affinity to TLR4. We will show that challenge with LPS antigens produces a statistically significant increase in TLR4 receptor clusters on the cell membrane, presumably due to recruitment of receptors to lipid rafts. These changes, however, are only detectable below the diffraction limit and are not evident using conventional imaging methods. Furthermore, we will compare the spatiotemporal behavior of TLR4 receptors in response to different LPS chemotypes in order to elucidate possible routes by which pathogens such as Y. pestis are able to circumvent the innate immune system. Finally, we will exploit the dual-color STORM capabilities to simultaneously image LPS and TLR4 receptors in the cellular membrane at resolutions at or below 40nm.« less

Disentangling Mechanisms That Mediate the Balance Between Stochastic and Deterministic Processes in Microbial Succession

DOE PAGES

Dini-Andreote, Francisco; Stegen, James C.; van Elsas, Jan D.; ...

2015-03-17

Despite growing recognition that deterministic and stochastic factors simultaneously influence bacterial communities, little is known about mechanisms shifting their relative importance. To better understand underlying mechanisms, we developed a conceptual model linking ecosystem development during primary succession to shifts in the stochastic/deterministic balance. To evaluate the conceptual model we coupled spatiotemporal data on soil bacterial communities with environmental conditions spanning 105 years of salt marsh development. At the local scale there was a progression from stochasticity to determinism due to Na accumulation with increasing ecosystem age, supporting a main element of the conceptual model. At the regional-scale, soil organic mattermore » (SOM) governed the relative influence of stochasticity and the type of deterministic ecological selection, suggesting scale-dependency in how deterministic ecological selection is imposed. Analysis of a new ecological simulation model supported these conceptual inferences. Looking forward, we propose an extended conceptual model that integrates primary and secondary succession in microbial systems.« less

Diffusive transport in the presence of stochastically gated absorption

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.; Karamched, Bhargav R.; Lawley, Sean D.; Levien, Ethan

2017-08-01

We analyze a population of Brownian particles moving in a spatially uniform environment with stochastically gated absorption. The state of the environment at time t is represented by a discrete stochastic variable k (t )∈{0 ,1 } such that the rate of absorption is γ [1 -k (t )] , with γ a positive constant. The variable k (t ) evolves according to a two-state Markov chain. We focus on how stochastic gating affects the attenuation of particle absorption with distance from a localized source in a one-dimensional domain. In the static case (no gating), the steady-state attenuation is given by an exponential with length constant √{D /γ }, where D is the diffusivity. We show that gating leads to slower, nonexponential attenuation. We also explore statistical correlations between particles due to the fact that they all diffuse in the same switching environment. Such correlations can be determined in terms of moments of the solution to a corresponding stochastic Fokker-Planck equation.

The influence of Stochastic perturbation of Geotechnical media On Electromagnetic tomography

NASA Astrophysics Data System (ADS)

Song, Lei; Yang, Weihao; Huangsonglei, Jiahui; Li, HaiPeng

2015-04-01

Electromagnetic tomography (CT) are commonly utilized in Civil engineering to detect the structure defects or geological anomalies. CT are generally recognized as a high precision geophysical method and the accuracy of CT are expected to be several centimeters and even to be several millimeters. Then, high frequency antenna with short wavelength are utilized commonly in Civil Engineering. As to the geotechnical media, stochastic perturbation of the EM parameters are inevitably exist in geological scales, in structure scales and in local scales, et al. In those cases, the geometric dimensionings of the target body, the EM wavelength and the accuracy expected might be of the same order. When the high frequency EM wave propagated in the stochastic geotechnical media, the GPR signal would be reflected not only from the target bodies but also from the stochastic perturbation of the background media. To detect the karst caves in dissolution fracture rock, one need to assess the influence of the stochastic distributed dissolution holes and fractures; to detect the void in a concrete structure, one should master the influence of the stochastic distributed stones, et al. In this paper, on the base of stochastic media discrete realizations, the authors try to evaluate quantificationally the influence of the stochastic perturbation of Geotechnical media by Radon/Iradon Transfer through full-combined Monte Carlo numerical simulation. It is found the stochastic noise is related with transfer angle, perturbing strength, angle interval, autocorrelation length, et al. And the quantitative formula of the accuracy of the electromagnetic tomography is also established, which could help on the precision estimation of GPR tomography in stochastic perturbation Geotechnical media. Key words: Stochastic Geotechnical Media; Electromagnetic Tomography; Radon/Iradon Transfer.

Evolution of probability densities in stochastic coupled map lattices

NASA Astrophysics Data System (ADS)

Losson, Jérôme; Mackey, Michael C.

1995-08-01

This paper describes the statistical properties of coupled map lattices subjected to the influence of stochastic perturbations. The stochastic analog of the Perron-Frobenius operator is derived for various types of noise. When the local dynamics satisfy rather mild conditions, this equation is shown to possess either stable, steady state solutions (i.e., a stable invariant density) or density limit cycles. Convergence of the phase space densities to these limit cycle solutions explains the nonstationary behavior of statistical quantifiers at equilibrium. Numerical experiments performed on various lattices of tent, logistic, and shift maps with diffusivelike interelement couplings are examined in light of these theoretical results.

Morphogenesis of nanostructures in glancing angle deposition of metal thin film coatings

NASA Astrophysics Data System (ADS)

Brown, Timothy James

Atomic vapors condensed onto solid surfaces form a remarkable category of condensed matter materials, the so-called thin films, with a myriad of compositions, morphological structures, and properties. The dynamic process of atomic condensation exhibits self-assembled pattern formation, producing morphologies with atomic-scale three- dimensional structures of seemingly limitless variety. This study attempts to shed new light on the dynamical growth processes of thin film deposition by analyzing in detail a previously unreported specific distinct emergent structure, a crystalline triangular-shaped spike that grows within copper and silver thin films. I explored the deposition parameters that lead to the growth of these unique structures, referred to as "nanospikes", fabricating approximately 55 thin films and used scanning electron microscopy and x-ray diffraction analysis. The variation of parameters include: vapor incidence angle, film thickness, substrate temperature, deposition rate, deposition material, substrate, and source-to-substrate distance. Microscopy analysis reveals that the silver and copper films deposited at glancing vapor incidence angles, 80 degrees and greater, have a high degree of branching interconnectivity between adjacent inclined nanorods. Diffraction analysis reveals that the vapor incidence angle influences the sub-populations of crystallites in the films, producing two different [110] crystal texture orientations. I hypothesize that the growth of nanospikes from nanorods is initiated by the stochastic arrival of vapor atoms and photons emitted from the deposition source at small diameter nanorods, and then driven by localized heating from vapor condensation and photon absorption. Restricted heat flow due to nanoscale thermal conduction maintains an elevated local temperature at the nanorod, enhancing adatom diffusion and enabling fast epitaxial crystal growth, leading to the formation and growth of nanospikes. Electron microscopy and x-ray diffraction analysis, and comparisons to related scientific literature, support this hypothesis. I also designed a highly modular ultrahigh vacuum deposition chamber, capable of concurrently mounting several different pieces of deposition equipment, that allows for a high degree of control of the growth dynamics of deposited thin films. I used the newly designed chamber to fabricate tailor-made nanostructured tantalum films for use in ultracapacitors, for the Cabot Corporation.

Revisiting the cape cod bacteria injection experiment using a stochastic modeling approach

USGS Publications Warehouse

Maxwell, R.M.; Welty, C.; Harvey, R.W.

2007-01-01

Bromide and resting-cell bacteria tracer tests conducted in a sandy aquifer at the U.S. Geological Survey Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach. Bacteria transport was coupled to colloid filtration theory through functional dependence of local-scale colloid transport parameters upon hydraulic conductivity and seepage velocity in a stochastic advection - dispersion/attachment - detachment model. Geostatistical information on the hydraulic conductivity (K) field that was unavailable at the time of the original test was utilized as input. Using geostatistical parameters, a groundwater flow and particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data. An optimization routine was employed over 100 realizations to adjust the mean and variance ofthe natural-logarithm of hydraulic conductivity (InK) field to achieve best fit of a simulated, average bromide breakthrough curve. A stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of mean bacteria breakthrough were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech (Environ. Sci. Technol. 2004, 38, 529-536) correlation equation for estimating single collector efficiency were compared to those using the older Rajagopalan and Tien (AIChE J. 1976, 22, 523-533) model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions. Simulations using a distribution of bacterial cell diameters available from original field notes yielded a slight improvement in the model and data agreement compared to simulations using an average bacterial diameter. The stochastic approach based on estimates of local-scale parameters for the bacteria-transport process reasonably captured the mean bacteria transport behavior and calculated an envelope of uncertainty that bracketed the observations in most simulation cases. ?? 2007 American Chemical Society.

Stochastic mechanics of reciprocal diffusions

NASA Astrophysics Data System (ADS)

Levy, Bernard C.; Krener, Arthur J.

1996-02-01

The dynamics and kinematics of reciprocal diffusions were examined in a previous paper [J. Math. Phys. 34, 1846 (1993)], where it was shown that reciprocal diffusions admit a chain of conservation laws, which close after the first two laws for two disjoint subclasses of reciprocal diffusions, the Markov and quantum diffusions. For the case of quantum diffusions, the conservation laws are equivalent to Schrödinger's equation. The Markov diffusions were employed by Schrödinger [Sitzungsber. Preuss. Akad. Wiss. Phys. Math Kl. 144 (1931); Ann. Inst. H. Poincaré 2, 269 (1932)], Nelson [Dynamical Theories of Brownian Motion (Princeton University, Princeton, NJ, 1967); Quantum Fluctuations (Princeton University, Princeton, NJ, 1985)], and other researchers to develop stochastic formulations of quantum mechanics, called stochastic mechanics. We propose here an alternative version of stochastic mechanics based on quantum diffusions. A procedure is presented for constructing the quantum diffusion associated to a given wave function. It is shown that quantum diffusions satisfy the uncertainty principle, and have a locality property, whereby given two dynamically uncoupled but statistically correlated particles, the marginal statistics of each particle depend only on the local fields to which the particle is subjected. However, like Wigner's joint probability distribution for the position and momentum of a particle, the finite joint probability densities of quantum diffusions may take negative values.

Discrete-State Stochastic Models of Calcium-Regulated Calcium Influx and Subspace Dynamics Are Not Well-Approximated by ODEs That Neglect Concentration Fluctuations

PubMed Central

Weinberg, Seth H.; Smith, Gregory D.

2012-01-01

Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597

Development of transparent microwell arrays for optical monitoring and dissection of microbial communities

DOE PAGES

Halsted, Michelle; Wilmoth, Jared L.; Briggs, Paige A.; ...

2016-09-29

Microbial communities are incredibly complex systems that dramatically and ubiquitously influence our lives. They help to shape our climate and environment, impact agriculture, drive business, and have a tremendous bearing on healthcare and physical security. Spatial confinement, as well as local variations in physical and chemical properties, affects development and interactions within microbial communities that occupy critical niches in the environment. Recent work has demonstrated the use of silicon based microwell arrays, combined with parylene lift-off techniques, to perform both deterministic and stochastic assembly of microbial communities en masse, enabling the high-throughput screening of microbial communities for their response tomore » growth in confined environments under different conditions. The implementation of a transparent microwell array platform can expand and improve the imaging modalities that can be used to characterize these assembled communities. In this paper, the fabrication and characterization of a next generation transparent microwell array is described. The transparent arrays, comprised of SU-8 patterned on a glass coverslip, retain the ability to use parylene lift-off by integrating a low temperature atomic layer deposition of silicon dioxide into the fabrication process. This silicon dioxide layer prevents adhesion of the parylene material to the patterned SU-8, facilitating dry lift-off, and maintaining the ability to easily assemble microbial communities within the microwells. These transparent microwell arrays can screen numerous community compositions using continuous, high resolution, imaging. Finally, the utility of the design was successfully demonstrated through the stochastic seeding and imaging of green fluorescent protein expressing Escherichia coli using both fluorescence and brightfield microscopies.« less

Mapping the architecture of the HIV-lTat circuit: A decision-making circuit that lacks bistability and exploits stochastic noise

PubMed Central

Razooky, Brandon S.; Weinberger, Leor S.

2014-01-01

Upon infection of a CD4+ T cell, HIV-l appears to ‘choose’ between two alternate fates: active replication or a long-lived dormant statetermed proviral latency. A transcriptional positive-feedback loop generated by the HIV-l Tat protein appears sufficient to mediate this decision. Here, we describea coupled wet-lab and computational approach that uses mathematical modeling and live-cell time-lapse microscopy to map the architecture of the HIV-l Tat transcriptional regulatorycircuit and generate predictive models of HIV-l latency. This approach provided the first characterization of a ‘decision-making’ circuit that lacks bistability andinstead exploits stochastic fluctuations in cellular molecules (i.e. noise) to generate a decision between an on or off transcriptional state. PMID:21167940

Stochastic first passage time accelerated with CUDA

NASA Astrophysics Data System (ADS)

Pierro, Vincenzo; Troiano, Luigi; Mejuto, Elena; Filatrella, Giovanni

2018-05-01

The numerical integration of stochastic trajectories to estimate the time to pass a threshold is an interesting physical quantity, for instance in Josephson junctions and atomic force microscopy, where the full trajectory is not accessible. We propose an algorithm suitable for efficient implementation on graphical processing unit in CUDA environment. The proposed approach for well balanced loads achieves almost perfect scaling with the number of available threads and processors, and allows an acceleration of about 400× with a GPU GTX980 respect to standard multicore CPU. This method allows with off the shell GPU to challenge problems that are otherwise prohibitive, as thermal activation in slowly tilted potentials. In particular, we demonstrate that it is possible to simulate the switching currents distributions of Josephson junctions in the timescale of actual experiments.

Think globally, act locally: the role of local demographics and vaccination coverage in the dynamic response of measles infection to control.

PubMed

Ferrari, M J; Grenfell, B T; Strebel, P M

2013-08-05

The global reduction of the burden of morbidity and mortality owing to measles has been a major triumph of public health. However, the continued persistence of measles infection probably not only reflects local variation in progress towards vaccination target goals, but may also reflect local variation in dynamic processes of transmission, susceptible replenishment through births and stochastic local extinction. Dynamic models predict that vaccination should increase the mean age of infection and increase inter-annual variability in incidence. Through a comparative approach, we assess national-level patterns in the mean age of infection and measles persistence. We find that while the classic predictions do hold in general, the impact of vaccination on the age distribution of cases and stochastic fadeout are mediated by local birth rate. Thus, broad-scale vaccine coverage goals are unlikely to have the same impact on the interruption of measles transmission in all demographic settings. Indeed, these results suggest that the achievement of further measles reduction or elimination goals is likely to require programmatic and vaccine coverage goals that are tailored to local demographic conditions.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE PAGES

Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...

2017-09-21

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

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

Desai, Ajit; Khalil, Mohammad; Pettit, Chris

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Observation of energetic electron confinement in a largely stochastic reversed-field pinch plasma

NASA Astrophysics Data System (ADS)

Clayton, D. J.; Chapman, B. E.; O'Connell, R.; Almagri, A. F.; Burke, D. R.; Forest, C. B.; Goetz, J. A.; Kaufman, M. C.; Bonomo, F.; Franz, P.; Gobbin, M.; Piovesan, P.

2010-01-01

Runaway electrons with energies >100 keV are observed with the appearance of an m =1 magnetic island in the core of otherwise stochastic Madison Symmetric Torus [Dexter et al., Fusion Technol. 19, 131 (1991)] reversed-field-pinch plasmas. The island is associated with the innermost resonant tearing mode, which is usually the largest in the m =1 spectrum. The island appears over a range of mode spectra, from those with a weakly dominant mode to those, referred to as quasi single helicity, with a strongly dominant mode. In a stochastic field, the rate of electron loss increases with electron parallel velocity. Hence, high-energy electrons imply a region of reduced stochasticity. The global energy confinement time is about the same as in plasmas without high-energy electrons or an island in the core. Hence, the region of reduced stochasticity must be localized. Within a numerical reconstruction of the magnetic field topology, high-energy electrons are substantially better confined inside the island, relative to the external region. Therefore, it is deduced that the island provides a region of reduced stochasticity and that the high-energy electrons are generated and well confined within this region.

A stochastic two-scale model for pressure-driven flow between rough surfaces

PubMed Central

Larsson, Roland; Lundström, Staffan; Wall, Peter; Almqvist, Andreas

2016-01-01

Seal surface topography typically consists of global-scale geometric features as well as local-scale roughness details and homogenization-based approaches are, therefore, readily applied. These provide for resolving the global scale (large domain) with a relatively coarse mesh, while resolving the local scale (small domain) in high detail. As the total flow decreases, however, the flow pattern becomes tortuous and this requires a larger local-scale domain to obtain a converged solution. Therefore, a classical homogenization-based approach might not be feasible for simulation of very small flows. In order to study small flows, a model allowing feasibly-sized local domains, for really small flow rates, is developed. Realization was made possible by coupling the two scales with a stochastic element. Results from numerical experiments, show that the present model is in better agreement with the direct deterministic one than the conventional homogenization type of model, both quantitatively in terms of flow rate and qualitatively in reflecting the flow pattern. PMID:27436975

Unidirectional random growth with resetting

NASA Astrophysics Data System (ADS)

Biró, T. S.; Néda, Z.

2018-06-01

We review stochastic processes without detailed balance condition and derive their H-theorem. We obtain stationary distributions and investigate their stability in terms of generalized entropic distances beyond the Kullback-Leibler formula. A simple stochastic model with local growth rates and direct resetting to the ground state is investigated and applied to various networks, scientific citations and Facebook popularity, hadronic yields in high energy particle reactions, income and wealth distributions, biodiversity and settlement size distributions.

Stochastic description of quantum Brownian dynamics

NASA Astrophysics Data System (ADS)

Yan, Yun-An; Shao, Jiushu

2016-08-01

Classical Brownian motion has well been investigated since the pioneering work of Einstein, which inspired mathematicians to lay the theoretical foundation of stochastic processes. A stochastic formulation for quantum dynamics of dissipative systems described by the system-plus-bath model has been developed and found many applications in chemical dynamics, spectroscopy, quantum transport, and other fields. This article provides a tutorial review of the stochastic formulation for quantum dissipative dynamics. The key idea is to decouple the interaction between the system and the bath by virtue of the Hubbard-Stratonovich transformation or Itô calculus so that the system and the bath are not directly entangled during evolution, rather they are correlated due to the complex white noises introduced. The influence of the bath on the system is thereby defined by an induced stochastic field, which leads to the stochastic Liouville equation for the system. The exact reduced density matrix can be calculated as the stochastic average in the presence of bath-induced fields. In general, the plain implementation of the stochastic formulation is only useful for short-time dynamics, but not efficient for long-time dynamics as the statistical errors go very fast. For linear and other specific systems, the stochastic Liouville equation is a good starting point to derive the master equation. For general systems with decomposable bath-induced processes, the hierarchical approach in the form of a set of deterministic equations of motion is derived based on the stochastic formulation and provides an effective means for simulating the dissipative dynamics. A combination of the stochastic simulation and the hierarchical approach is suggested to solve the zero-temperature dynamics of the spin-boson model. This scheme correctly describes the coherent-incoherent transition (Toulouse limit) at moderate dissipation and predicts a rate dynamics in the overdamped regime. Challenging problems such as the dynamical description of quantum phase transition (local- ization) and the numerical stability of the trace-conserving, nonlinear stochastic Liouville equation are outlined.

Investigation of podosome ring protein arrangement using localization microscopy images.

PubMed

Staszowska, Adela D; Fox-Roberts, Patrick; Foxall, Elizabeth; Jones, Gareth E; Cox, Susan

2017-02-15

Podosomes are adhesive structures formed on the plasma membrane abutting the extracellular matrix of macrophages, osteoclasts, and dendritic cells. They consist of an f-actin core and a ring structure composed of integrins and integrin-associated proteins. The podosome ring plays a major role in adhesion to the underlying extracellular matrix, but its detailed structure is poorly understood. Recently, it has become possible to study the nano-scale structure of podosome rings using localization microscopy. Unlike traditional microscopy images, localization microscopy images are reconstructed using discrete points, meaning that standard image analysis methods cannot be applied. Here, we present a pipeline for podosome identification, protein position calculation, and creating a podosome ring model for use with localization microscopy data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A stochastic spatiotemporal model of a response-regulator network in the Caulobacter crescentus cell cycle

NASA Astrophysics Data System (ADS)

Li, Fei; Subramanian, Kartik; Chen, Minghan; Tyson, John J.; Cao, Yang

2016-06-01

The asymmetric cell division cycle in Caulobacter crescentus is controlled by an elaborate molecular mechanism governing the production, activation and spatial localization of a host of interacting proteins. In previous work, we proposed a deterministic mathematical model for the spatiotemporal dynamics of six major regulatory proteins. In this paper, we study a stochastic version of the model, which takes into account molecular fluctuations of these regulatory proteins in space and time during early stages of the cell cycle of wild-type Caulobacter cells. We test the stochastic model with regard to experimental observations of increased variability of cycle time in cells depleted of the divJ gene product. The deterministic model predicts that overexpression of the divK gene blocks cell cycle progression in the stalked stage; however, stochastic simulations suggest that a small fraction of the mutants cells do complete the cell cycle normally.

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters: Theory and application to microfilaments

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

Li, Tong; Gu, YuanTong, E-mail: yuantong.gu@qut.edu.au

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grainedmore » level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.« less

Stochastic approach and fluctuation theorem for charge transport in diodes

NASA Astrophysics Data System (ADS)

Gu, Jiayin; Gaspard, Pierre

2018-05-01

A stochastic approach for charge transport in diodes is developed in consistency with the laws of electricity, thermodynamics, and microreversibility. In this approach, the electron and hole densities are ruled by diffusion-reaction stochastic partial differential equations and the electric field generated by the charges is determined with the Poisson equation. These equations are discretized in space for the numerical simulations of the mean density profiles, the mean electric potential, and the current-voltage characteristics. Moreover, the full counting statistics of the carrier current and the measured total current including the contribution of the displacement current are investigated. On the basis of local detailed balance, the fluctuation theorem is shown to hold for both currents.

Design Of Combined Stochastic Feedforward/Feedback Control

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1989-01-01

Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

Quantum dot immunocytochemical localization of somatostatin in somatostatinoma by Widefield Epifluorescence, super-resolution light, and immunoelectron microscopy.

PubMed

Killingsworth, Murray C; Lai, Ken; Wu, Xiaojuan; Yong, Jim L C; Lee, C Soon

2012-11-01

Quantum dot nanocrystal probes (QDs) have been used for detection of somatostatin hormone in secretory granules of somatostatinoma tumor cells by immunofluorescence light microscopy, super-resolution light microscopy, and immunoelectron microscopy. Immunostaining for all modalities was done using sections taken from an epoxy resin-embedded tissue specimen and a similar labeling protocol. This approach allowed assessment of labeling at light microscopy level before examination at super-resolution and electron microscopy level and was a significant aid in interpretation. Etching of ultrathin sections with saturated sodium metaperiodate was a critical step presumably able to retrieve some tissue antigenicity masked by processing in epoxy resin. Immunofluorescence microscopy of QD-immunolabeled sections showed somatostatin hormone localization in cytoplasmic granules. Some variable staining of tumor gland-like structures appeared related to granule maturity and dispersal of granule contents within the tumor cell cytoplasm. Super-resolution light microscopy demonstrated localization of somatostatin within individual secretory granules to be heterogeneous, and this staining pattern was confirmed by immunoelectron microscopy.

Quantum Dot Immunocytochemical Localization of Somatostatin in Somatostatinoma by Widefield Epifluorescence, Super-resolution Light, and Immunoelectron Microscopy

PubMed Central

Lai, Ken; Wu, Xiaojuan; Yong, Jim L. C.; Lee, C. Soon

2012-01-01

Quantum dot nanocrystal probes (QDs) have been used for detection of somatostatin hormone in secretory granules of somatostatinoma tumor cells by immunofluorescence light microscopy, super-resolution light microscopy, and immunoelectron microscopy. Immunostaining for all modalities was done using sections taken from an epoxy resin-embedded tissue specimen and a similar labeling protocol. This approach allowed assessment of labeling at light microscopy level before examination at super-resolution and electron microscopy level and was a significant aid in interpretation. Etching of ultrathin sections with saturated sodium metaperiodate was a critical step presumably able to retrieve some tissue antigenicity masked by processing in epoxy resin. Immunofluorescence microscopy of QD-immunolabeled sections showed somatostatin hormone localization in cytoplasmic granules. Some variable staining of tumor gland-like structures appeared related to granule maturity and dispersal of granule contents within the tumor cell cytoplasm. Super-resolution light microscopy demonstrated localization of somatostatin within individual secretory granules to be heterogeneous, and this staining pattern was confirmed by immunoelectron microscopy. PMID:22899862

Super-resolution atomic force photoactivated microscopy of biological samples (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Kim, Hyemin; Shin, Seungjun; Doh, Junsang; Kim, Chulhong

2017-03-01

Optical microscopy (OM) and photoacoustic microscopy (PAM) have previously been used to image the optical absorption of intercellular features of biological cells. However, the optical diffraction limit ( 200 nm) makes it difficult for these modalities to image nanoscale inner cell structures and the distribution of internal cell components. Although super-resolution fluorescence microscopy, such as stimulated emission depletion microscopy (STED) and stochastic optical reconstruction microscopy (STORM), has successfully performed nanoscale biological imaging, these modalities require the use of exogenous fluorescence agents, which are unfavorable for biological samples. Our newly developed atomic force photoactivated microscopy (AFPM) can provide optical absorption images with nanoscale lateral resolution without any exogenous contrast agents. AFPM combines conventional atomic force microscopy (AFM) and an optical excitation system, and simultaneously provides multiple contrasts, such as the topography and magnitude of optical absorption. AFPM can detect the intrinsic optical absorption of samples with 8 nm lateral resolution, easily overcoming the diffraction limit. Using the label-free AFPM system, we have successfully imaged the optical absorption properties of a single melanoma cell (B16F10) and a rosette leaf epidermal cell of Arabidopsis (ecotype Columbia (Col-0)) with nanoscale lateral resolution. The remarkable images show the melanosome distribution of a melanoma cell and the biological structures of a plant cell. AFPM provides superior imaging of optical absorption with a nanoscale lateral resolution, and it promises to become widely used in biological and chemical research.

Peculiar orientational disorder in 4-bromo-4'-nitrobiphenyl (BNBP) and 4-bromo-4'-cyanobiphenyl (BCNBP) leading to bipolar crystals.

PubMed

Burgener, Matthias; Aboulfadl, Hanane; Labat, Gaël Charles; Bonin, Michel; Sommer, Martin; Sankolli, Ravish; Wübbenhorst, Michael; Hulliger, Jürg

2016-05-01

180° orientational disorder of molecular building blocks can lead to a peculiar spatial distribution of polar properties in molecular crystals. Here we present two examples [4-bromo-4'-nitrobiphenyl (BNBP) and 4-bromo-4'-cyanobiphenyl (BCNBP)] which develop into a bipolar final growth state. This means orientational disorder taking place at the crystal/nutrient interface produces domains of opposite average polarity for as-grown crystals. The spatial inhomogeneous distribution of polarity was investigated by scanning pyroelectric microscopy (SPEM), phase-sensitive second harmonic microscopy (PS-SHM) and selected volume X-ray diffraction (SVXD). As a result, the acceptor groups (NO2 or CN) are predominantly present at crystal surfaces. However, the stochastic process of polarity formation can be influenced by adding a symmetrical biphenyl to a growing system. For this case, Monte Carlo simulations predict an inverted net polarity compared with the growth of pure BNBP and BCNBP. SPEM results clearly demonstrate that 4,4'-dibromobiphenyl (DBBP) can invert the polarity for both crystals. Phenomena reported in this paper belong to the most striking processes seen for molecular crystals, demonstrated by a stochastic process giving rise to symmetry breaking. We encounter here further examples supporting the general thesis that monodomain polar molecular crystals for fundamental reasons cannot exist.

A combined stochastic feedforward and feedback control design methodology with application to autoland design

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

Analysis of stochastic model for non-linear volcanic dynamics

NASA Astrophysics Data System (ADS)

Alexandrov, D.; Bashkirtseva, I.; Ryashko, L.

2014-12-01

Motivated by important geophysical applications we consider a dynamic model of the magma-plug system previously derived by Iverson et al. (2006) under the influence of stochastic forcing. Due to strong nonlinearity of the friction force for solid plug along its margins, the initial deterministic system exhibits impulsive oscillations. Two types of dynamic behavior of the system under the influence of the parametric stochastic forcing have been found: random trajectories are scattered on both sides of the deterministic cycle or grouped on its internal side only. It is shown that dispersions are highly inhomogeneous along cycles in the presence of noises. The effects of noise-induced shifts, pressure stabilization and localization of random trajectories have been revealed with increasing the noise intensity. The plug velocity, pressure and displacement are highly dependent of noise intensity as well. These new stochastic phenomena are related with the nonlinear peculiarities of the deterministic phase portrait. It is demonstrated that the repetitive stick-slip motions of the magma-plug system in the case of stochastic forcing can be connected with drumbeat earthquakes.

Three-dimensional stochastic modeling of radiation belts in adiabatic invariant coordinates

NASA Astrophysics Data System (ADS)

Zheng, Liheng; Chan, Anthony A.; Albert, Jay M.; Elkington, Scot R.; Koller, Josef; Horne, Richard B.; Glauert, Sarah A.; Meredith, Nigel P.

2014-09-01

A 3-D model for solving the radiation belt diffusion equation in adiabatic invariant coordinates has been developed and tested. The model, named Radbelt Electron Model, obtains a probabilistic solution by solving a set of Itô stochastic differential equations that are mathematically equivalent to the diffusion equation. This method is capable of solving diffusion equations with a full 3-D diffusion tensor, including the radial-local cross diffusion components. The correct form of the boundary condition at equatorial pitch angle α0=90° is also derived. The model is applied to a simulation of the October 2002 storm event. At α0 near 90°, our results are quantitatively consistent with GPS observations of phase space density (PSD) increases, suggesting dominance of radial diffusion; at smaller α0, the observed PSD increases are overestimated by the model, possibly due to the α0-independent radial diffusion coefficients, or to insufficient electron loss in the model, or both. Statistical analysis of the stochastic processes provides further insights into the diffusion processes, showing distinctive electron source distributions with and without local acceleration.

Circular analysis in complex stochastic systems

PubMed Central

Valleriani, Angelo

2015-01-01

Ruling out observations can lead to wrong models. This danger occurs unwillingly when one selects observations, experiments, simulations or time-series based on their outcome. In stochastic processes, conditioning on the future outcome biases all local transition probabilities and makes them consistent with the selected outcome. This circular self-consistency leads to models that are inconsistent with physical reality. It is also the reason why models built solely on macroscopic observations are prone to this fallacy. PMID:26656656

Characterizing Spatial Organization of Cell Surface Receptors in Human Breast Cancer with STORM

NASA Astrophysics Data System (ADS)

Lyall, Evan; Chapman, Matthew R.; Sohn, Lydia L.

2012-02-01

Regulation and control of complex biological functions are dependent upon spatial organization of biological structures at many different length scales. For instance Eph receptors and their ephrin ligands bind when opposing cells come into contact during development, resulting in spatial organizational changes on the nanometer scale that lead to changes on the macro scale, in a process known as organ morphogenesis. One technique able to probe this important spatial organization at both the nanometer and micrometer length scales, including at cell-cell junctions, is stochastic optical reconstruction microscopy (STORM). STORM is a technique that localizes individual fluorophores based on the centroids of their point spread functions and then reconstructs a composite image to produce super resolved structure. We have applied STORM to study spatial organization of the cell surface of human breast cancer cells, specifically the organization of tyrosine kinase receptors and chemokine receptors. A better characterization of spatial organization of breast cancer cell surface proteins is necessary to fully understand the tumorigenisis pathways in the most common malignancy in United States women.

Bowl Inversion and Electronic Switching of Buckybowls on Gold.

PubMed

Fujii, Shintaro; Ziatdinov, Maxim; Higashibayashi, Shuhei; Sakurai, Hidehiro; Kiguchi, Manabu

2016-09-21

Bowl-shaped π-conjugated compounds, or buckybowls, are a novel class of sp(2)-hybridized nanocarbon materials. In contrast to tubular carbon nanotubes and ball-shaped fullerenes, the buckybowls feature structural flexibility. Bowl-to-bowl structural inversion is one of the unique properties of the buckybowls in solutions. Bowl inversion on a surface modifies the metal-molecule interactions through bistable switching between bowl-up and bowl-down states on the surface, which makes surface-adsorbed buckybowls a relevant model system for elucidation of the mechano-electronic properties of nanocarbon materials. Here, we report a combination of scanning tunneling microscopy (STM) measurements and ab initio atomistic simulations to identify the adlayer structure of the sumanene buckybowl on Au(111) and reveal its unique bowl inversion behavior. We demonstrate that the bowl inversion can be induced by approaching the STM tip toward the molecule. By tuning the local metal-molecule interaction using the STM tip, the sumanene buckybowl exhibits structural bistability with a switching rate that is two orders of magnitude faster than that of the stochastic inversion process.

Reconstruction From Multiple Particles for 3D Isotropic Resolution in Fluorescence Microscopy.

PubMed

Fortun, Denis; Guichard, Paul; Hamel, Virginie; Sorzano, Carlos Oscar S; Banterle, Niccolo; Gonczy, Pierre; Unser, Michael

2018-05-01

The imaging of proteins within macromolecular complexes has been limited by the low axial resolution of optical microscopes. To overcome this problem, we propose a novel computational reconstruction method that yields isotropic resolution in fluorescence imaging. The guiding principle is to reconstruct a single volume from the observations of multiple rotated particles. Our new operational framework detects particles, estimates their orientation, and reconstructs the final volume. The main challenge comes from the absence of initial template and a priori knowledge about the orientations. We formulate the estimation as a blind inverse problem, and propose a block-coordinate stochastic approach to solve the associated non-convex optimization problem. The reconstruction is performed jointly in multiple channels. We demonstrate that our method is able to reconstruct volumes with 3D isotropic resolution on simulated data. We also perform isotropic reconstructions from real experimental data of doubly labeled purified human centrioles. Our approach revealed the precise localization of the centriolar protein Cep63 around the centriole microtubule barrel. Overall, our method offers new perspectives for applications in biology that require the isotropic mapping of proteins within macromolecular assemblies.

The WD40 Protein BamB Mediates Coupling of BAM Complexes into Assembly Precincts in the Bacterial Outer Membrane.

PubMed

Gunasinghe, Sachith D; Shiota, Takuya; Stubenrauch, Christopher J; Schulze, Keith E; Webb, Chaille T; Fulcher, Alex J; Dunstan, Rhys A; Hay, Iain D; Naderer, Thomas; Whelan, Donna R; Bell, Toby D M; Elgass, Kirstin D; Strugnell, Richard A; Lithgow, Trevor

2018-05-29

The β-barrel assembly machinery (BAM) complex is essential for localization of surface proteins on bacterial cells, but the mechanism by which it functions is unclear. We developed a direct stochastic optical reconstruction microscopy (dSTORM) methodology to view the BAM complex in situ. Single-cell analysis showed that discrete membrane precincts housing several BAM complexes are distributed across the E. coli surface, with a nearest neighbor distance of ∼200 nm. The auxiliary lipoprotein subunit BamB was crucial for this spatial distribution, and in situ crosslinking shows that BamB makes intimate contacts with BamA and BamB in neighboring BAM complexes within the precinct. The BAM complex precincts swell when outer membrane protein synthesis is maximal, visual proof that the precincts are active in protein assembly. This nanoscale interrogation of the BAM complex in situ suggests a model whereby bacterial outer membranes contain highly organized assembly precincts to drive integral protein assembly. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Granger-causality maps of diffusion processes.

PubMed

Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A

2016-02-01

Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.

Confocal Microscopy of Jammed Matter: From Elasticity to Granular Thermodynamics

NASA Astrophysics Data System (ADS)

Jorjadze, Ivane

Packings of particles are ubiquitous in nature and are of interest not only to the scientific community but also to the food, pharmaceutical, and oil industries. In this thesis we use confocal microscopy to investigate packing geometry and stress transmission in 3D jammed particulate systems. By introducing weak depletion attraction we probe the accessible phase-space and demonstrate that a microscopic approach to jammed matter gives validity to statistical mechanics framework, which is intriguing because our particles are not thermally activated. We show that the fluctuations of the local packing parameters can be successfully captured by the recently proposed 'granocentric' model, which generates packing statistics according to simple stochastic processes. This model enables us to calculate packing entropy and granular temperature, the so-called 'compactivity', therefore, providing a basis for a statistical mechanics of granular matter. At a jamming transition point at which there are formed just enough number of contacts to guarantee the mechanical stability, theoretical arguments suggest a singularity which gives rise to the surprising scaling behavior of the elastic moduli and the microstructure, as observed in numerical simulations. Since the contact network in 3D is typically hidden from view, experimental test of the scaling law between the coordination number and the applied pressure is lacking in the literature. Our data show corrections to the linear scaling of the pressure with density which takes into account the creation of contacts. Numerical studies of vibrational spectra, in turn, reveal sudden features such as excess of low frequency modes, dependence of mode localization and structure on the pressure. Chapter four describes the first calculation of vibrational density of states from the experimental 3D data and is in qualitative agreement with the analogous computer simulations. We study the configurational role of the pressure and demonstrate that low frequency modes become progressively localized as the packing density is increased. Another application of our oil-in-water emulsions serves to mimic cell adhesion in biological tissues. By analyzing the microstructure in 3D we find that a threshold compression force is necessary to overcome electrostatic repulsion and surface elasticity and establish protein-mediated adhesion.

Mathematical issues in eternal inflation

NASA Astrophysics Data System (ADS)

Singh Kohli, Ikjyot; Haslam, Michael C.

2015-04-01

In this paper, we consider the problem of the existence and uniqueness of solutions to the Einstein field equations for a spatially flat Friedmann-Lemaître-Robertson-Walker universe in the context of stochastic eternal inflation, where the stochastic mechanism is modelled by adding a stochastic forcing term representing Gaussian white noise to the Klein-Gordon equation. We show that under these considerations, the Klein-Gordon equation actually becomes a stochastic differential equation. Therefore, the existence and uniqueness of solutions to Einstein’s equations depend on whether the coefficients of this stochastic differential equation obey Lipschitz continuity conditions. We show that for any choice of V(φ ), the Einstein field equations are not globally well-posed, hence, any solution found to these equations is not guaranteed to be unique. Instead, the coefficients are at best locally Lipschitz continuous in the physical state space of the dynamical variables, which only exist up to a finite explosion time. We further perform Feller’s explosion test for an arbitrary power-law inflaton potential and prove that all solutions to the Einstein field equations explode in a finite time with probability one. This implies that the mechanism of stochastic inflation thus considered cannot be described to be eternal, since the very concept of eternal inflation implies that the process continues indefinitely. We therefore argue that stochastic inflation based on a stochastic forcing term would not produce an infinite number of universes in some multiverse ensemble. In general, since the Einstein field equations in both situations are not well-posed, we further conclude that the existence of a multiverse via the stochastic eternal inflation mechanism considered in this paper is still very much an open question that will require much deeper investigation.

Spatially and temporally resolved exciton dynamics and transport in single nanostructures and assemblies

NASA Astrophysics Data System (ADS)

Huang, Libai

2015-03-01

The frontier in solar energy conversion now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. To address this new frontier, I will discuss our recent efforts on elucidating multi-scale energy transfer, migration, and dissipation processes with simultaneous femtosecond temporal resolution and nanometer spatial resolution. We have developed ultrafast microscopy that combines ultrafast spectroscopy with optical microscopy to map exciton dynamics and transport with simultaneous ultrafast time resolution and diffraction-limited spatial resolution. We have employed pump-probe transient absorption microscopy to elucidate morphology and structure dependent exciton dynamics and transport in single nanostructures and molecular assemblies. More specifically, (1) We have applied transient absorption microscopy (TAM) to probe environmental and structure dependent exciton relaxation pathways in sing-walled carbon nanotubes (SWNTs) by mapping dynamics in individual pristine SWNTs with known structures. (2) We have systematically measured and modeled the optical properties of the Frenkel excitons in self-assembled porphyrin tubular aggregates that represent an analog to natural photosynthetic antennae. Using a combination of ultrafast optical microscopy and stochastic exciton modeling, we address exciton transport and relaxation pathways, especially those related to disorder.

Strategic Positioning and Biased Activity of the Mitochondrial Calcium Uniporter in Cardiac Muscle*

PubMed Central

De La Fuente, Sergio; Fernandez-Sanz, Celia; Vail, Caitlin; Agra, Elorm J.; Holmstrom, Kira; Sun, Junhui; Mishra, Jyotsna; Williams, Dewight; Finkel, Toren; Murphy, Elizabeth; Joseph, Suresh K.; Sheu, Shey-Shing; Csordás, György

2016-01-01

Control of myocardial energetics by Ca2+ signal propagation to the mitochondrial matrix includes local Ca2+ delivery from sarcoplasmic reticulum (SR) ryanodine receptors (RyR2) to the inner mitochondrial membrane (IMM) Ca2+ uniporter (mtCU). mtCU activity in cardiac mitochondria is relatively low, whereas the IMM surface is large, due to extensive cristae folding. Hence, stochastically distributed mtCU may not suffice to support local Ca2+ transfer. We hypothesized that mtCU concentrated at mitochondria-SR associations would promote the effective Ca2+ transfer. mtCU distribution was determined by tracking MCU and EMRE, the proteins essential for channel formation. Both proteins were enriched in the IMM-outer mitochondrial membrane (OMM) contact point submitochondrial fraction and, as super-resolution microscopy revealed, located more to the mitochondrial periphery (inner boundary membrane) than inside the cristae, indicating high accessibility to cytosol-derived Ca2+ inputs. Furthermore, MCU immunofluorescence distribution was biased toward the mitochondria-SR interface (RyR2), and this bias was promoted by Ca2+ signaling activity in intact cardiomyocytes. The SR fraction of heart homogenate contains mitochondria with extensive SR associations, and these mitochondria are highly enriched in EMRE. Size exclusion chromatography suggested for EMRE- and MCU-containing complexes a wide size range and also revealed MCU-containing complexes devoid of EMRE (thus disabled) in the mitochondrial but not the SR fraction. Functional measurements suggested more effective mtCU-mediated Ca2+ uptake activity by the mitochondria of the SR than of the mitochondrial fraction. Thus, mtCU “hot spots” can be formed at the cardiac muscle mitochondria-SR associations via localization and assembly bias, serving local Ca2+ signaling and the excitation-energetics coupling. PMID:27637331

Stochastic modeling of neurobiological time series: Power, coherence, Granger causality, and separation of evoked responses from ongoing activity

NASA Astrophysics Data System (ADS)

Chen, Yonghong; Bressler, Steven L.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Mingzhou

2006-06-01

In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.

Dynamical crossover in a stochastic model of cell fate decision

NASA Astrophysics Data System (ADS)

Yamaguchi, Hiroki; Kawaguchi, Kyogo; Sagawa, Takahiro

2017-07-01

We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e., proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multicellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.

Will systems biology offer new holistic paradigms to life sciences?

PubMed Central

Conti, Filippo; Valerio, Maria Cristina; Zbilut, Joseph P.

2008-01-01

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms. PMID:19003440

An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.

PubMed

Koh, Wonryull; Blackwell, Kim T

2011-04-21

Stochastic simulation of reaction-diffusion systems enables the investigation of stochastic events arising from the small numbers and heterogeneous distribution of molecular species in biological cells. Stochastic variations in intracellular microdomains and in diffusional gradients play a significant part in the spatiotemporal activity and behavior of cells. Although an exact stochastic simulation that simulates every individual reaction and diffusion event gives a most accurate trajectory of the system's state over time, it can be too slow for many practical applications. We present an accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems designed to improve the speed of simulation by reducing the number of time-steps required to complete a simulation run. This method is unique in that it employs two strategies that have not been incorporated in existing spatial stochastic simulation algorithms. First, diffusive transfers between neighboring subvolumes are based on concentration gradients. This treatment necessitates sampling of only the net or observed diffusion events from higher to lower concentration gradients rather than sampling all diffusion events regardless of local concentration gradients. Second, we extend the non-negative Poisson tau-leaping method that was originally developed for speeding up nonspatial or homogeneous stochastic simulation algorithms. This method calculates each leap time in a unified step for both reaction and diffusion processes while satisfying the leap condition that the propensities do not change appreciably during the leap and ensuring that leaping does not cause molecular populations to become negative. Numerical results are presented that illustrate the improvement in simulation speed achieved by incorporating these two new strategies.

Inference of Stochastic Nonlinear Oscillators with Applications to Physiological Problems

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.

2004-01-01

A new method of inferencing of coupled stochastic nonlinear oscillators is described. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is robust in a broad range of dynamical models. We illustrate the main ideas of the technique by inferencing a model of five globally and locally coupled noisy oscillators. Specific modifications of the technique for inferencing hidden degrees of freedom of coupled nonlinear oscillators is discussed in the context of physiological applications.

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue

PubMed Central

Spühler, Isabelle A.; Conley, Gaurasundar M.; Scheffold, Frank; Sprecher, Simon G.

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation. PMID:27303270

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue.

PubMed

Spühler, Isabelle A; Conley, Gaurasundar M; Scheffold, Frank; Sprecher, Simon G

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation.

Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock.

PubMed

Gerke, Kirill M; Karsanina, Marina V; Mallants, Dirk

2015-11-02

Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution. Merging multiscale images of shale rock is pivotal to quantify more reliably petrophysical properties needed for production optimization and environmental impacts minimization. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Practical applications are not limited to petroleum engineering or more broadly geosciences, but will also find their way in material sciences, climatology, and remote sensing.

Universal Stochastic Multiscale Image Fusion: An Example Application for Shale Rock

PubMed Central

Gerke, Kirill M.; Karsanina, Marina V.; Mallants, Dirk

2015-01-01

Spatial data captured with sensors of different resolution would provide a maximum degree of information if the data were to be merged into a single image representing all scales. We develop a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images of shale rock representing macro, micro and nanoscale spatial information on mineral, organic matter and porosity distribution. Merging multiscale images of shale rock is pivotal to quantify more reliably petrophysical properties needed for production optimization and environmental impacts minimization. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Practical applications are not limited to petroleum engineering or more broadly geosciences, but will also find their way in material sciences, climatology, and remote sensing. PMID:26522938

Raman Microscopy: A Noninvasive Method to Visualize the Localizations of Biomolecules in the Cornea.

PubMed

Kaji, Yuichi; Akiyama, Toshihiro; Segawa, Hiroki; Oshika, Tetsuro; Kano, Hideaki

2017-11-01

In vivo and in situ visualization of biomolecules without pretreatment will be important for diagnosis and treatment of ocular disorders in the future. Recently, multiphoton microscopy, based on the nonlinear interactions between molecules and photons, has been applied to reveal the localizations of various molecules in tissues. We aimed to use multimodal multiphoton microscopy to visualize the localizations of specific biomolecules in rat corneas. Multiphoton images of the corneas were obtained from nonlinear signals of coherent anti-Stokes Raman scattering, third-order sum frequency generation, and second-harmonic generation. The localizations of the adhesion complex-containing basement membrane and Bowman layer were clearly visible in the third-order sum frequency generation images. The fine structure of type I collagen was observed in the corneal stroma in the second-harmonic generation images. The localizations of lipids, proteins, and nucleic acids (DNA/RNA) was obtained in the coherent anti-Stokes Raman scattering images. Imaging technologies have progressed significantly and been applied in medical fields. Optical coherence tomography and confocal microscopy are widely used but do not provide information on the molecular structure of the cornea. By contrast, multiphoton microscopy provides information on the molecular structure of living tissues. Using this technique, we successfully visualized the localizations of various biomolecules including lipids, proteins, and nucleic acids in the cornea. We speculate that multiphoton microscopy will provide essential information on the physiological and pathological conditions of the cornea, as well as molecular localizations in tissues without pretreatment.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

BOOK REVIEW: Statistical Mechanics of Turbulent Flows

NASA Astrophysics Data System (ADS)

Cambon, C.

2004-10-01

This is a handbook for a computational approach to reacting flows, including background material on statistical mechanics. In this sense, the title is somewhat misleading with respect to other books dedicated to the statistical theory of turbulence (e.g. Monin and Yaglom). In the present book, emphasis is placed on modelling (engineering closures) for computational fluid dynamics. The probabilistic (pdf) approach is applied to the local scalar field, motivated first by the nonlinearity of chemical source terms which appear in the transport equations of reacting species. The probabilistic and stochastic approaches are also used for the velocity field and particle position; nevertheless they are essentially limited to Lagrangian models for a local vector, with only single-point statistics, as for the scalar. Accordingly, conventional techniques, such as single-point closures for RANS (Reynolds-averaged Navier-Stokes) and subgrid-scale models for LES (large-eddy simulations), are described and in some cases reformulated using underlying Langevin models and filtered pdfs. Even if the theoretical approach to turbulence is not discussed in general, the essentials of probabilistic and stochastic-processes methods are described, with a useful reminder concerning statistics at the molecular level. The book comprises 7 chapters. Chapter 1 briefly states the goals and contents, with a very clear synoptic scheme on page 2. Chapter 2 presents definitions and examples of pdfs and related statistical moments. Chapter 3 deals with stochastic processes, pdf transport equations, from Kramer-Moyal to Fokker-Planck (for Markov processes), and moments equations. Stochastic differential equations are introduced and their relationship to pdfs described. This chapter ends with a discussion of stochastic modelling. The equations of fluid mechanics and thermodynamics are addressed in chapter 4. Classical conservation equations (mass, velocity, internal energy) are derived from their counterparts at the molecular level. In addition, equations are given for multicomponent reacting systems. The chapter ends with miscellaneous topics, including DNS, (idea of) the energy cascade, and RANS. Chapter 5 is devoted to stochastic models for the large scales of turbulence. Langevin-type models for velocity (and particle position) are presented, and their various consequences for second-order single-point corelations (Reynolds stress components, Kolmogorov constant) are discussed. These models are then presented for the scalar. The chapter ends with compressible high-speed flows and various models, ranging from k-epsilon to hybrid RANS-pdf. Stochastic models for small-scale turbulence are addressed in chapter 6. These models are based on the concept of a filter density function (FDF) for the scalar, and a more conventional SGS (sub-grid-scale model) for the velocity in LES. The final chapter, chapter 7, is entitled `The unification of turbulence models' and aims at reconciling large-scale and small-scale modelling. This book offers a timely survey of techniques in modern computational fluid mechanics for turbulent flows with reacting scalars. It should be of interest to engineers, while the discussion of the underlying tools, namely pdfs, stochastic and statistical equations should also be attractive to applied mathematicians and physicists. The book's emphasis on local pdfs and stochastic Langevin models gives a consistent structure to the book and allows the author to cover almost the whole spectrum of practical modelling in turbulent CFD. On the other hand, one might regret that non-local issues are not mentioned explicitly, or even briefly. These problems range from the presence of pressure-strain correlations in the Reynolds stress transport equations to the presence of two-point pdfs in the single-point pdf equation derived from the Navier--Stokes equations. (One may recall that, even without scalar transport, a general closure problem for turbulence statistics results from both non-linearity and non-locality of Navier-Stokes equations, the latter coming from, e.g., the nonlocal relationship of velocity and pressure in the quasi-incompressible case. These two aspects are often intricately linked. It is well known that non-linearity alone is not responsible for the `problem', as evidenced by 1D turbulence without pressure (`Burgulence' from the Burgers equation) and probably 3D (cosmological gas). A local description in terms of pdf for the velocity can resolve the `non-linear' problem, which instead yields an infinite hierarchy of equations in terms of moments. On the other hand, non-locality yields a hierarchy of unclosed equations, with the single-point pdf equation for velocity derived from NS incompressible equations involving a two-point pdf, and so on. The general relationship was given by Lundgren (1967, Phys. Fluids 10 (5), 969-975), with the equation for pdf at n points involving the pdf at n+1 points. The nonlocal problem appears in various statistical models which are not discussed in the book. The simplest example is full RST or ASM models, in which the closure of pressure-strain correlations is pivotal (their counterpart ought to be identified and discussed in equations (5-21) and the following ones). The book does not address more sophisticated non-local approaches, such as two-point (or spectral) non-linear closure theories and models, `rapid distortion theory' for linear regimes, not to mention scaling and intermittency based on two-point structure functions, etc. The book sometimes mixes theoretical modelling and pure empirical relationships, the empirical character coming from the lack of a nonlocal (two-point) approach.) In short, the book is orientated more towards applications than towards turbulence theory; it is written clearly and concisely and should be useful to a large community, interested either in the underlying stochastic formalism or in CFD applications.

Model selection for integrated pest management with stochasticity.

PubMed

Akman, Olcay; Comar, Timothy D; Hrozencik, Daniel

2018-04-07

In Song and Xiang (2006), an integrated pest management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an integrated pest management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Irregular synchronous activity in stochastically-coupled networks of integrate-and-fire neurons.

PubMed

Lin, J K; Pawelzik, K; Ernst, U; Sejnowski, T J

1998-08-01

We investigate the spatial and temporal aspects of firing patterns in a network of integrate-and-fire neurons arranged in a one-dimensional ring topology. The coupling is stochastic and shaped like a Mexican hat with local excitation and lateral inhibition. With perfect precision in the couplings, the attractors of activity in the network occur at every position in the ring. Inhomogeneities in the coupling break the translational invariance of localized attractors and lead to synchronization within highly active as well as weakly active clusters. The interspike interval variability is high, consistent with recent observations of spike time distributions in visual cortex. The robustness of our results is demonstrated with more realistic simulations on a network of McGregor neurons which model conductance changes and after-hyperpolarization potassium currents.

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

PubMed Central

Refahi, Yassin; Brunoud, Géraldine; Farcot, Etienne; Jean-Marie, Alain; Pulkkinen, Minna; Vernoux, Teva; Godin, Christophe

2016-01-01

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems. DOI: http://dx.doi.org/10.7554/eLife.14093.001 PMID:27380805

Super-resolution binding activated localization microscopy through reversible change of DNA conformation.

PubMed

Szczurek, Aleksander; Birk, Udo; Knecht, Hans; Dobrucki, Jurek; Mai, Sabine; Cremer, Christoph

2018-01-01

Methods of super-resolving light microscopy (SRM) have found an exponentially growing range of applications in cell biology, including nuclear structure analyses. Recent developments have proven that Single Molecule Localization Microscopy (SMLM), a type of SRM, is particularly useful for enhanced spatial analysis of the cell nucleus due to its highest resolving capability combined with very specific fluorescent labeling. In this commentary we offer a brief review of the latest methodological development in the field of SMLM of chromatin designated DNA Structure Fluctuation Assisted Binding Activated Localization Microscopy (abbreviated as fBALM) as well as its potential future applications in biology and medicine.

Super-resolution binding activated localization microscopy through reversible change of DNA conformation

PubMed Central

Knecht, Hans; Dobrucki, Jurek; Mai, Sabine

2018-01-01

ABSTRACT Methods of super-resolving light microscopy (SRM) have found an exponentially growing range of applications in cell biology, including nuclear structure analyses. Recent developments have proven that Single Molecule Localization Microscopy (SMLM), a type of SRM, is particularly useful for enhanced spatial analysis of the cell nucleus due to its highest resolving capability combined with very specific fluorescent labeling. In this commentary we offer a brief review of the latest methodological development in the field of SMLM of chromatin designated DNA Structure Fluctuation Assisted Binding Activated Localization Microscopy (abbreviated as fBALM) as well as its potential future applications in biology and medicine. PMID:29297245

Stochastic seismic inversion based on an improved local gradual deformation method

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Zhu, Peimin

2017-12-01

A new stochastic seismic inversion method based on the local gradual deformation method is proposed, which can incorporate seismic data, well data, geology and their spatial correlations into the inversion process. Geological information, such as sedimentary facies and structures, could provide significant a priori information to constrain an inversion and arrive at reasonable solutions. The local a priori conditional cumulative distributions at each node of model to be inverted are first established by indicator cokriging, which integrates well data as hard data and geological information as soft data. Probability field simulation is used to simulate different realizations consistent with the spatial correlations and local conditional cumulative distributions. The corresponding probability field is generated by the fast Fourier transform moving average method. Then, optimization is performed to match the seismic data via an improved local gradual deformation method. Two improved strategies are proposed to be suitable for seismic inversion. The first strategy is that we select and update local areas of bad fitting between synthetic seismic data and real seismic data. The second one is that we divide each seismic trace into several parts and obtain the optimal parameters for each part individually. The applications to a synthetic example and a real case study demonstrate that our approach can effectively find fine-scale acoustic impedance models and provide uncertainty estimations.

Analysis of degree of nonlinearity and stochastic nature of HRV signal during meditation using delay vector variance method.

PubMed

Reddy, L Ram Gopal; Kuntamalla, Srinivas

2011-01-01

Heart rate variability analysis is fast gaining acceptance as a potential non-invasive means of autonomic nervous system assessment in research as well as clinical domains. In this study, a new nonlinear analysis method is used to detect the degree of nonlinearity and stochastic nature of heart rate variability signals during two forms of meditation (Chi and Kundalini). The data obtained from an online and widely used public database (i.e., MIT/BIH physionet database), is used in this study. The method used is the delay vector variance (DVV) method, which is a unified method for detecting the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. From the results it is clear that there is a significant change in the nonlinearity and stochastic nature of the signal before and during the meditation (p value > 0.01). During Chi meditation there is a increase in stochastic nature and decrease in nonlinear nature of the signal. There is a significant decrease in the degree of nonlinearity and stochastic nature during Kundalini meditation.

Drosophila parthenogenesis: A tool to decipher centrosomal vs acentrosomal spindle assembly pathways

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

Riparbelli, Maria Giovanna; Callaini, Giuliano

2008-04-15

Development of unfertilized eggs in the parthenogenetic strain K23-O-im of Drosophila mercatorum requires the stochastic interactions of self-assembled centrosomes with the female chromatin. In a portion of the unfertilized eggs that do not assemble centrosomes, microtubules organize a bipolar anastral mitotic spindle around the chromatin like the one formed during the first female meiosis, suggesting that similar pathways may be operative. In the cytoplasm of eggs in which centrosomes do form, monastral and biastral spindles are found. Analysis by laser scanning confocal microscopy suggests that these spindles are derived from the stochastic interaction of astral microtubules directly with kinetochore regionsmore » or indirectly with kinetochore microtubules. Our findings are consistent with the idea that mitotic spindle assembly requires both acentrosomal and centrosomal pathways, strengthening the hypothesis that astral microtubules can dictate the organization of the spindle by capturing kinetochore microtubules.« less

Nano-fEM: protein localization using photo-activated localization microscopy and electron microscopy.

PubMed

Watanabe, Shigeki; Richards, Jackson; Hollopeter, Gunther; Hobson, Robert J; Davis, Wayne M; Jorgensen, Erik M

2012-12-03

Mapping the distribution of proteins is essential for understanding the function of proteins in a cell. Fluorescence microscopy is extensively used for protein localization, but subcellular context is often absent in fluorescence images. Immuno-electron microscopy, on the other hand, can localize proteins, but the technique is limited by a lack of compatible antibodies, poor preservation of morphology and because most antigens are not exposed to the specimen surface. Correlative approaches can acquire the fluorescence image from a whole cell first, either from immuno-fluorescence or genetically tagged proteins. The sample is then fixed and embedded for electron microscopy, and the images are correlated (1-3). However, the low-resolution fluorescence image and the lack of fiducial markers preclude the precise localization of proteins. Alternatively, fluorescence imaging can be done after preserving the specimen in plastic. In this approach, the block is sectioned, and fluorescence images and electron micrographs of the same section are correlated (4-7). However, the diffraction limit of light in the correlated image obscures the locations of individual molecules, and the fluorescence often extends beyond the boundary of the cell. Nano-resolution fluorescence electron microscopy (nano-fEM) is designed to localize proteins at nano-scale by imaging the same sections using photo-activated localization microscopy (PALM) and electron microscopy. PALM overcomes the diffraction limit by imaging individual fluorescent proteins and subsequently mapping the centroid of each fluorescent spot (8-10). We outline the nano-fEM technique in five steps. First, the sample is fixed and embedded using conditions that preserve the fluorescence of tagged proteins. Second, the resin blocks are sectioned into ultrathin segments (70-80 nm) that are mounted on a cover glass. Third, fluorescence is imaged in these sections using the Zeiss PALM microscope. Fourth, electron dense structures are imaged in these same sections using a scanning electron microscope. Fifth, the fluorescence and electron micrographs are aligned using gold particles as fiducial markers. In summary, the subcellular localization of fluorescently tagged proteins can be determined at nanometer resolution in approximately one week.

Establishing a beachhead: A stochastic population model with an Allee effect applied to species invasion

USGS Publications Warehouse

Ackleh, A.S.; Allen, L.J.S.; Carter, J.

2007-01-01

We formulated a spatially explicit stochastic population model with an Allee effect in order to explore how invasive species may become established. In our model, we varied the degree of migration between local populations and used an Allee effect with variable birth and death rates. Because of the stochastic component, population sizes below the Allee effect threshold may still have a positive probability for successful invasion. The larger the network of populations, the greater the probability of an invasion occurring when initial population sizes are close to or above the Allee threshold. Furthermore, if migration rates are low, one or more than one patch may be successfully invaded, while if migration rates are high all patches are invaded. ?? 2007 Elsevier Inc. All rights reserved.

Design Tool Using a New Optimization Method Based on a Stochastic Process

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Yamaguchi, Katsuhito; Ishikawa, Yoshio

Conventional optimization methods are based on a deterministic approach since their purpose is to find out an exact solution. However, such methods have initial condition dependence and the risk of falling into local solution. In this paper, we propose a new optimization method based on the concept of path integrals used in quantum mechanics. The method obtains a solution as an expected value (stochastic average) using a stochastic process. The advantages of this method are that it is not affected by initial conditions and does not require techniques based on experiences. We applied the new optimization method to a hang glider design. In this problem, both the hang glider design and its flight trajectory were optimized. The numerical calculation results prove that performance of the method is sufficient for practical use.

Optimal Control via Self-Generated Stochasticity

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.

A study approach on ferroelectric domains in BaTiO{sub 3}

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

Rocha, L.S.R.; Cavalcanti, C.S.

Atomic Force Acoustic Microscopy (AFAM) and Piezoresponse Force Microscopy (PFM) were used to study local elastic and electromechanical response in BaTiO{sub 3} ceramics. A commercial multi-mode Scanning Probe Microscopy (SPM) and AFAM mode to image contact stiffness were employed to accomplish the aforementioned purposes. Stiffness parameters along with Young's moduli and piezo coefficients were quantitatively determined. PFM studies were based on electrostatic and electromechanical response from localized tip-surface contact. Comparison was made regarding the Young's moduli obtained by AFAM and PFM. In addition, phase and amplitude images were analyzed based on poling behavior, obtained via the application of − 10more » V to + 10 V local voltage. - Highlights: •Nanoscale behavior of piezo domains in BaTiO{sub 3} ferroelectric materials •Use of Atomic Force Acoustic Microscopy (AFAM) and Piezo Force Microscopy (PFM) •Local elastic and electromechanical response in BaTiO{sub 3} ceramics •The young's moduli obtained from AFAM and PFM.« less

Neighborhood diversity of large trees shows independent species patterns in a mixed dipterocarp forest in Sri Lanka.

PubMed

Punchi-Manage, Ruwan; Wiegand, Thorsten; Wiegand, Kerstin; Getzin, Stephan; Huth, Andreas; Gunatilleke, C V Savitri; Gunatilleke, I A U Nimal

2015-07-01

Interactions among neighboring individuals influence plant performance and should create spatial patterns in local community structure. In order to assess the role of large trees in generating spatial patterns in local species richness, we used the individual species-area relationship (ISAR) to evaluate the species richness of trees of different size classes (and dead trees) in circular neighborhoods with varying radius around large trees of different focal species. To reveal signals of species interactions, we compared the ISAR function of the individuals of focal species with that of randomly selected nearby locations. We expected that large trees should strongly affect the community structure of smaller trees in their neighborhood, but that these effects should fade away with increasing size class. Unexpectedly, we found that only few focal species showed signals of species interactions with trees of the different size classes and that this was less likely for less abundant focal species. However, the few and relatively weak departures from independence were consistent with expectations of the effect of competition for space and the dispersal syndrome on spatial patterns. A noisy signal of competition for space found for large trees built up gradually with increasing life stage; it was not yet present for large saplings but detectable for intermediates. Additionally, focal species with animal-dispersed seeds showed higher species richness in their neighborhood than those with gravity- and gyration-dispersed seeds. Our analysis across the entire ontogeny from recruits to large trees supports the hypothesis that stochastic effects dilute deterministic species interactions in highly diverse communities. Stochastic dilution is a consequence of the stochastic geometry of biodiversity in species-rich communities where the identities of the nearest neighbors of a given plant are largely unpredictable. While the outcome of local species interactions is governed for each plant by deterministic fitness and niche differences, the large variability of competitors causes also a large variability in the outcomes of interactions and does not allow for strong directed responses at the species level. Collectively, our results highlight the critical effect of the stochastic geometry of biodiversity in structuring local spatial patterns of tropical forest diversity.

A non-stochastic iterative computational method to model light propagation in turbid media

NASA Astrophysics Data System (ADS)

McIntyre, Thomas J.; Zemp, Roger J.

2015-03-01

Monte Carlo models are widely used to model light transport in turbid media, however their results implicitly contain stochastic variations. These fluctuations are not ideal, especially for inverse problems where Jacobian matrix errors can lead to large uncertainties upon matrix inversion. Yet Monte Carlo approaches are more computationally favorable than solving the full Radiative Transport Equation. Here, a non-stochastic computational method of estimating fluence distributions in turbid media is proposed, which is called the Non-Stochastic Propagation by Iterative Radiance Evaluation method (NSPIRE). Rather than using stochastic means to determine a random walk for each photon packet, the propagation of light from any element to all other elements in a grid is modelled simultaneously. For locally homogeneous anisotropic turbid media, the matrices used to represent scattering and projection are shown to be block Toeplitz, which leads to computational simplifications via convolution operators. To evaluate the accuracy of the algorithm, 2D simulations were done and compared against Monte Carlo models for the cases of an isotropic point source and a pencil beam incident on a semi-infinite turbid medium. The model was shown to have a mean percent error less than 2%. The algorithm represents a new paradigm in radiative transport modelling and may offer a non-stochastic alternative to modeling light transport in anisotropic scattering media for applications where the diffusion approximation is insufficient.

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines.

PubMed

Neftci, Emre O; Pedroni, Bruno U; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

2016-01-01

Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware.

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

PubMed Central

Neftci, Emre O.; Pedroni, Bruno U.; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

2016-01-01

Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware. PMID:27445650

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation

PubMed Central

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms. PMID:29670508

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation.

PubMed

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO 2 ) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms.

Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.

PubMed

Marrero-Ponce, Yovani; Martínez-Albelo, Eugenio R; Casañola-Martín, Gerardo M; Castillo-Garit, Juan A; Echevería-Díaz, Yunaimy; Zaldivar, Vicente Romero; Tygat, Jan; Borges, José E Rodriguez; García-Domenech, Ramón; Torrens, Francisco; Pérez-Giménez, Facundo

2010-11-01

Novel bond-level molecular descriptors are proposed, based on linear maps similar to the ones defined in algebra theory. The kth edge-adjacency matrix (E(k)) denotes the matrix of bond linear indices (non-stochastic) with regard to canonical basis set. The kth stochastic edge-adjacency matrix, ES(k), is here proposed as a new molecular representation easily calculated from E(k). Then, the kth stochastic bond linear indices are calculated using ES(k) as operators of linear transformations. In both cases, the bond-type formalism is developed. The kth non-stochastic and stochastic total linear indices are calculated by adding the kth non-stochastic and stochastic bond linear indices, respectively, of all bonds in molecule. First, the new bond-based molecular descriptors (MDs) are tested for suitability, for the QSPRs, by analyzing regressions of novel indices for selected physicochemical properties of octane isomers (first round). General performance of the new descriptors in this QSPR studies is evaluated with regard to the well-known sets of 2D/3D MDs. From the analysis, we can conclude that the non-stochastic and stochastic bond-based linear indices have an overall good modeling capability proving their usefulness in QSPR studies. Later, the novel bond-level MDs are also used for the description and prediction of the boiling point of 28 alkyl-alcohols (second round), and to the modeling of the specific rate constant (log k), partition coefficient (log P), as well as the antibacterial activity of 34 derivatives of 2-furylethylenes (third round). The comparison with other approaches (edge- and vertices-based connectivity indices, total and local spectral moments, and quantum chemical descriptors as well as E-state/biomolecular encounter parameters) exposes a good behavior of our method in this QSPR studies. Finally, the approach described in this study appears to be a very promising structural invariant, useful not only for QSPR studies but also for similarity/diversity analysis and drug discovery protocols.

Analysis of gene expression levels in individual bacterial cells without image segmentation.

PubMed

Kwak, In Hae; Son, Minjun; Hagen, Stephen J

2012-05-11

Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly. Copyright © 2012 Elsevier Inc. All rights reserved.

Stochastic nonlinear electrical characteristics of graphene

NASA Astrophysics Data System (ADS)

Jun Shin, Young; Gopinadhan, Kalon; Narayanapillai, Kulothungasagaran; Kalitsov, Alan; Bhatia, Charanjit S.; Yang, Hyunsoo

2013-01-01

A stochastic nonlinear electrical characteristic of graphene is reported. Abrupt current changes are observed from voltage sweeps between the source and drain with an on/off ratio up to 103. It is found that graphene channel experiences the topological change. Active radicals in an uneven graphene channel cause local changes of electrostatic potential. Simulation results based on the self-trapped electron and hole mechanism account well for the experimental data. Our findings illustrate an important issue of reliable electron transports and help for the understanding of transport properties in graphene devices.

Nonisothermal fluctuating hydrodynamics and Brownian motion

NASA Astrophysics Data System (ADS)

Falasco, G.; Kroy, K.

2016-03-01

The classical theory of Brownian dynamics follows from coarse graining the underlying linearized fluctuating hydrodynamics of the solvent. We extend this procedure to globally nonisothermal conditions, requiring only a local thermal equilibration of the solvent. Starting from the conservation laws, we establish the stochastic equations of motion for the fluid momentum fluctuations in the presence of a suspended Brownian particle. These are then contracted to the nonisothermal generalized Langevin description of the suspended particle alone, for which the coupling to stochastic temperature fluctuations is found to be negligible under typical experimental conditions.

Psychological effect on single-species population models in a polluted environment.

PubMed

Wei, Fengying; Chen, Lihong

2017-08-01

We formulate and investigate the psychological effect of single-species population models in a polluted environment in this paper. For the deterministic single-species population model, the conditions that guarantee the local extinction and persistence in the mean are derived firstly. We then show that, around the pollution-free equilibrium, the stochastic single-species population is weakly persistent in the mean, and is stochastically permanent under some conditions. As a consequence, some numerical simulations demonstrate the efficiency of the main results. Copyright © 2017 Elsevier Inc. All rights reserved.

The divine clockwork: Bohr's correspondence principle and Nelson's stochastic mechanics for the atomic elliptic state

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

Durran, Richard; Neate, Andrew; Truman, Aubrey

2008-03-15

We consider the Bohr correspondence limit of the Schroedinger wave function for an atomic elliptic state. We analyze this limit in the context of Nelson's stochastic mechanics, exposing an underlying deterministic dynamical system in which trajectories converge to Keplerian motion on an ellipse. This solves the long standing problem of obtaining Kepler's laws of planetary motion in a quantum mechanical setting. In this quantum mechanical setting, local mild instabilities occur in the Keplerian orbit for eccentricities greater than (1/{radical}(2)) which do not occur classically.

Site correction of stochastic simulation in southwestern Taiwan

NASA Astrophysics Data System (ADS)

Lun Huang, Cong; Wen, Kuo Liang; Huang, Jyun Yan

2014-05-01

Peak ground acceleration (PGA) of a disastrous earthquake, is concerned both in civil engineering and seismology study. Presently, the ground motion prediction equation is widely used for PGA estimation study by engineers. However, the local site effect is another important factor participates in strong motion prediction. For example, in 1985 the Mexico City, 400km far from the epicenter, suffered massive damage due to the seismic wave amplification from the local alluvial layers. (Anderson et al., 1986) In past studies, the use of stochastic method had been done and showed well performance on the simulation of ground-motion at rock site (Beresnev and Atkinson, 1998a ; Roumelioti and Beresnev, 2003). In this study, the site correction was conducted by the empirical transfer function compared with the rock site response from stochastic point-source (Boore, 2005) and finite-fault (Boore, 2009) methods. The error between the simulated and observed Fourier spectrum and PGA are calculated. Further we compared the estimated PGA to the result calculated from ground motion prediction equation. The earthquake data used in this study is recorded by Taiwan Strong Motion Instrumentation Program (TSMIP) from 1991 to 2012; the study area is located at south-western Taiwan. The empirical transfer function was generated by calculating the spectrum ratio between alluvial site and rock site (Borcheret, 1970). Due to the lack of reference rock site station in this area, the rock site ground motion was generated through stochastic point-source model instead. Several target events were then chosen for stochastic point-source simulating to the halfspace. Then, the empirical transfer function for each station was multiplied to the simulated halfspace response. Finally, we focused on two target events: the 1999 Chi-Chi earthquake (Mw=7.6) and the 2010 Jiashian earthquake (Mw=6.4). Considering the large event may contain with complex rupture mechanism, the asperity and delay time for each sub-fault is to be concerned. Both the stochastic point-source and the finite-fault model were used to check the result of our correction.

Stochastic differential equations as a tool to regularize the parameter estimation problem for continuous time dynamical systems given discrete time measurements.

PubMed

Leander, Jacob; Lundh, Torbjörn; Jirstrand, Mats

2014-05-01

In this paper we consider the problem of estimating parameters in ordinary differential equations given discrete time experimental data. The impact of going from an ordinary to a stochastic differential equation setting is investigated as a tool to overcome the problem of local minima in the objective function. Using two different models, it is demonstrated that by allowing noise in the underlying model itself, the objective functions to be minimized in the parameter estimation procedures are regularized in the sense that the number of local minima is reduced and better convergence is achieved. The advantage of using stochastic differential equations is that the actual states in the model are predicted from data and this will allow the prediction to stay close to data even when the parameters in the model is incorrect. The extended Kalman filter is used as a state estimator and sensitivity equations are provided to give an accurate calculation of the gradient of the objective function. The method is illustrated using in silico data from the FitzHugh-Nagumo model for excitable media and the Lotka-Volterra predator-prey system. The proposed method performs well on the models considered, and is able to regularize the objective function in both models. This leads to parameter estimation problems with fewer local minima which can be solved by efficient gradient-based methods. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

3D aquifer characterization using stochastic streamline calibration

NASA Astrophysics Data System (ADS)

Jang, Minchul

2007-03-01

In this study, a new inverse approach, stochastic streamline calibration is proposed. Using both a streamline concept and a stochastic technique, stochastic streamline calibration optimizes an identified field to fit in given observation data in a exceptionally fast and stable fashion. In the stochastic streamline calibration, streamlines are adopted as basic elements not only for describing fluid flow but also for identifying the permeability distribution. Based on the streamline-based inversion by Agarwal et al. [Agarwal B, Blunt MJ. Streamline-based method with full-physics forward simulation for history matching performance data of a North sea field. SPE J 2003;8(2):171-80], Wang and Kovscek [Wang Y, Kovscek AR. Streamline approach for history matching production data. SPE J 2000;5(4):353-62], permeability is modified rather along streamlines than at the individual gridblocks. Permeabilities in the gridblocks which a streamline passes are adjusted by being multiplied by some factor such that we can match flow and transport properties of the streamline. This enables the inverse process to achieve fast convergence. In addition, equipped with a stochastic module, the proposed technique supportively calibrates the identified field in a stochastic manner, while incorporating spatial information into the field. This prevents the inverse process from being stuck in local minima and helps search for a globally optimized solution. Simulation results indicate that stochastic streamline calibration identifies an unknown permeability exceptionally quickly. More notably, the identified permeability distribution reflected realistic geological features, which had not been achieved in the original work by Agarwal et al. with the limitations of the large modifications along streamlines for matching production data only. The constructed model by stochastic streamline calibration forecasted transport of plume which was similar to that of a reference model. By this, we can expect the proposed approach to be applied to the construction of an aquifer model and forecasting of the aquifer performances of interest.

A manifold independent approach to understanding transport in stochastic dynamical systems

NASA Astrophysics Data System (ADS)

Bollt, Erik M.; Billings, Lora; Schwartz, Ira B.

2002-12-01

We develop a new collection of tools aimed at studying stochastically perturbed dynamical systems. Specifically, in the setting of bi-stability, that is a two-attractor system, it has previously been numerically observed that a small noise volume is sufficient to destroy would be zero-noise case barriers in the phase space (pseudo-barriers), thus creating a pre-heteroclinic tangency chaos-like behavior. The stochastic dynamical system has a corresponding Frobenius-Perron operator with a stochastic kernel, which describes how densities of initial conditions move under the noisy map. Thus in studying the action of the Frobenius-Perron operator, we learn about the transport of the map; we have employed a Galerkin-Ulam-like method to project the Frobenius-Perron operator onto a discrete basis set of characteristic functions to highlight this action localized in specified regions of the phase space. Graph theoretic methods allow us to re-order the resulting finite dimensional Markov operator approximation so as to highlight the regions of the original phase space which are particularly active pseudo-barriers of the stochastic dynamics. Our toolbox allows us to find: (1) regions of high activity of transport, (2) flux across pseudo-barriers, and also (3) expected time of escape from pseudo-basins. Some of these quantities are also possible via the manifold dependent stochastic Melnikov method, but Melnikov only applies to a very special class of models for which the unperturbed homoclinic orbit is available. Our methods are unique in that they can essentially be considered as a “black-box” of tools which can be applied to a wide range of stochastic dynamical systems in the absence of a priori knowledge of manifold structures. We use here a model of childhood diseases to showcase our methods. Our tools will allow us to make specific observations of: (1) loss of reducibility between basins with increasing noise, (2) identification in the phase space of active regions of stochastic transport, (3) stochastic flux which essentially completes the heteroclinic tangle.

Localizing Proteins in Fixed Giardia lamblia and Live Cultured Mammalian Cells by Confocal Fluorescence Microscopy.

PubMed

Nyindodo-Ogari, Lilian; Schwartzbach, Steven D; Skalli, Omar; Estraño, Carlos E

2016-01-01

Confocal fluorescence microscopy and electron microscopy (EM) are complementary methods for studying the intracellular localization of proteins. Confocal fluorescence microscopy provides a rapid and technically simple method to identify the organelle in which a protein localizes but only EM can identify the suborganellular compartment in which that protein is present. Confocal fluorescence microscopy, however, can provide information not obtainable by EM but required to understand the dynamics and interactions of specific proteins. In addition, confocal fluorescence microscopy of cells transfected with a construct encoding a protein of interest fused to a fluorescent protein tag allows live cell studies of the subcellular localization of that protein and the monitoring in real time of its trafficking. Immunostaining methods for confocal fluorescence microscopy are also faster and less involved than those for EM allowing rapid optimization of the antibody dilution needed and a determination of whether protein antigenicity is maintained under fixation conditions used for EM immunogold labeling. This chapter details a method to determine by confocal fluorescence microscopy the intracellular localization of a protein by transfecting the organism of interest, in this case Giardia lamblia, with the cDNA encoding the protein of interest and then processing these organisms for double label immunofluorescence staining after chemical fixation. Also presented is a method to identify the organelle targeting information in the presequence of a precursor protein, in this case the presequence of the precursor to the Euglena light harvesting chlorophyll a/b binding protein of photosystem II precursor (pLHCPII), using live cell imaging of mammalian COS7 cells transiently transfected with a plasmid encoding a pLHCPII presequence fluorescent protein fusion and stained with organelle-specific fluorescent dyes.

The Tool for Designing Engineering Systems Using a New Optimization Method Based on a Stochastic Process

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Yamaguchi, Katsuhito; Ishikawa, Yoshio

The conventional optimization methods were based on a deterministic approach, since their purpose is to find out an exact solution. However, these methods have initial condition dependence and risk of falling into local solution. In this paper, we propose a new optimization method based on a concept of path integral method used in quantum mechanics. The method obtains a solutions as an expected value (stochastic average) using a stochastic process. The advantages of this method are not to be affected by initial conditions and not to need techniques based on experiences. We applied the new optimization method to a design of the hang glider. In this problem, not only the hang glider design but also its flight trajectory were optimized. The numerical calculation results showed that the method has a sufficient performance.

(Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

NASA Astrophysics Data System (ADS)

Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

2018-02-01

The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

Emerging optical nanoscopy techniques

PubMed Central

Montgomery, Paul C; Leong-Hoi, Audrey

2015-01-01

To face the challenges of modern health care, new imaging techniques with subcellular resolution or detection over wide fields are required. Far field optical nanoscopy presents many new solutions, providing high resolution or detection at high speed. We present a new classification scheme to help appreciate the growing number of optical nanoscopy techniques. We underline an important distinction between superresolution techniques that provide improved resolving power and nanodetection techniques for characterizing unresolved nanostructures. Some of the emerging techniques within these two categories are highlighted with applications in biophysics and medicine. Recent techniques employing wider angle imaging by digital holography and scattering lens microscopy allow superresolution to be achieved for subcellular and even in vivo, imaging without labeling. Nanodetection techniques are divided into four subcategories using contrast, phase, deconvolution, and nanomarkers. Contrast enhancement is illustrated by means of a polarized light-based technique and with strobed phase-contrast microscopy to reveal nanostructures. Very high sensitivity phase measurement using interference microscopy is shown to provide nanometric surface roughness measurement or to reveal internal nanometric structures. Finally, the use of nanomarkers is illustrated with stochastic fluorescence microscopy for mapping intracellular structures. We also present some of the future perspectives of optical nanoscopy. PMID:26491270

Stochastic charging of dust grains in planetary rings: Diffusion rates and their effects on Lorentz resonances

NASA Technical Reports Server (NTRS)

Schaffer, L.; Burns, J. A.

1995-01-01

Dust grains in planetary rings acquire stochastically fluctuating electric charges as they orbit through any corotating magnetospheric plasma. Here we investigate the nature of this stochastic charging and calculate its effect on the Lorentz resonance (LR). First we model grain charging as a Markov process, where the transition probabilities are identified as the ensemble-averaged charging fluxes due to plasma pickup and photoemission. We determine the distribution function P(t;N), giving the probability that a grain has N excess charges at time t. The autocorrelation function tau(sub q) for the strochastic charge process can be approximated by a Fokker-Planck treatment of the evolution equations for P(t; N). We calculate the mean square response to the stochastic fluctuations in the Lorentz force. We find that transport in phase space is very small compared to the resonant increase in amplitudes due to the mean charge, over the timescale that the oscillator is resonantly pumped up. Therefore the stochastic charge variations cannot break the resonant interaction; locally, the Lorentz resonance is a robust mechanism for the shaping of etheral dust ring systems. Slightly stronger bounds on plasma parameters are required when we consider the longer transit times between Lorentz resonances.

Tissue and cellular localization of tannins in Tunisian dates (Phoenix dactylifera L.) by light and transmission electron microscopy.

PubMed

Hammouda, Hédi; Alvarado, Camille; Bouchet, Brigitte; Kalthoum-Chérif, Jamila; Trabelsi-Ayadi, Malika; Guyot, Sylvain

2014-07-16

A histological approach including light microscopy and transmission electron microscopy (TEM) was used to provide accurate information on the localization of condensed tannins in the edible tissues and in the stone of date fruits (Phoenix dactylifera L.). Light microscopy was carried out on fresh tissues after staining by 4-dimethylaminocinnamaldehyde (DMACA) for a specific detection of condensed tannins. Thus, whether under light microscopy or transmission electron microscopy (TEM), results showed that tannins are not located in the epidermis but more deeply in the mesocarp in the vacuole of very large cells. Regarding the stones, tannins are found in a specific cell layer located at 50 μm from the sclereid cells of the testa.

Inferring diffusion in single live cells at the single-molecule level

PubMed Central

Robson, Alex; Burrage, Kevin; Leake, Mark C.

2013-01-01

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffusing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell membrane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the molecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to discriminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells. PMID:23267182

Magnetoelectric force microscopy based on magnetic force microscopy with modulated electric field.

PubMed

Geng, Yanan; Wu, Weida

2014-05-01

We present the realization of a mesoscopic imaging technique, namely, the Magnetoelectric Force Microscopy (MeFM), for visualization of local magnetoelectric effect. The basic principle of MeFM is the lock-in detection of local magnetoelectric response, i.e., the electric field-induced magnetization, using magnetic force microscopy. We demonstrate MeFM capability by visualizing magnetoelectric domains on single crystals of multiferroic hexagonal manganites. Results of several control experiments exclude artifacts or extrinsic origins of the MeFM signal. The parameters are tuned to optimize the signal to noise ratio.

Spatial scaling patterns and functional redundancies in a changing boreal lake landscape

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Uden, Daniel R.; Johnson, Richard K.

2015-01-01

Global transformations extend beyond local habitats; therefore, larger-scale approaches are needed to assess community-level responses and resilience to unfolding environmental changes. Using longterm data (1996–2011), we evaluated spatial patterns and functional redundancies in the littoral invertebrate communities of 85 Swedish lakes, with the objective of assessing their potential resilience to environmental change at regional scales (that is, spatial resilience). Multivariate spatial modeling was used to differentiate groups of invertebrate species exhibiting spatial patterns in composition and abundance (that is, deterministic species) from those lacking spatial patterns (that is, stochastic species). We then determined the functional feeding attributes of the deterministic and stochastic invertebrate species, to infer resilience. Between one and three distinct spatial patterns in invertebrate composition and abundance were identified in approximately one-third of the species; the remainder were stochastic. We observed substantial differences in metrics between deterministic and stochastic species. Functional richness and diversity decreased over time in the deterministic group, suggesting a loss of resilience in regional invertebrate communities. However, taxon richness and redundancy increased monotonically in the stochastic group, indicating the capacity of regional invertebrate communities to adapt to change. Our results suggest that a refined picture of spatial resilience emerges if patterns of both the deterministic and stochastic species are accounted for. Spatially extensive monitoring may help increase our mechanistic understanding of community-level responses and resilience to regional environmental change, insights that are critical for developing management and conservation agendas in this current period of rapid environmental transformation.

Neutral evolution in a biological population as diffusion in phenotype space: reproduction with local mutation but without selection.

PubMed

Lawson, Daniel John; Jensen, Henrik Jeldtoft

2007-03-02

The process of "evolutionary diffusion," i.e., reproduction with local mutation but without selection in a biological population, resembles standard diffusion in many ways. However, evolutionary diffusion allows the formation of localized peaks that undergo drift, even in the infinite population limit. We relate a microscopic evolution model to a stochastic model which we solve fully. This allows us to understand the large population limit, relates evolution to diffusion, and shows that independent local mutations act as a diffusion of interacting particles taking larger steps.

Local conductance: A means to extract polarization and depolarizing fields near domain walls in ferroelectrics

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

Douglas, A. M.; Kumar, A.; Gregg, J. M.

Conducting atomic force microscopy images of bulk semiconducting BaTiO{sub 3} surfaces show clear stripe domain contrast. High local conductance correlates with strong out-of-plane polarization (mapped independently using piezoresponse force microscopy), and current-voltage characteristics are consistent with dipole-induced alterations in Schottky barriers at the metallic tip-ferroelectric interface. Indeed, analyzing current-voltage data in terms of established Schottky barrier models allows relative variations in the surface polarization, and hence the local domain structure, to be determined. Fitting also reveals the signature of surface-related depolarizing fields concentrated near domain walls. Domain information obtained from mapping local conductance appears to be more surface-sensitive than thatmore » from piezoresponse force microscopy. In the right materials systems, local current mapping could therefore represent a useful complementary technique for evaluating polarization and local electric fields with nanoscale resolution.« less

Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values

NASA Astrophysics Data System (ADS)

López Ríos, Pablo; Monserrat, Bartomeu; Needs, Richard J.

2018-02-01

The thermal lines method for the evaluation of vibrational expectation values of electronic observables [B. Monserrat, Phys. Rev. B 93, 014302 (2016), 10.1103/PhysRevB.93.014302] was recently proposed as a physically motivated approximation offering balance between the accuracy of direct Monte Carlo integration and the low computational cost of using local quadratic approximations. In this paper we reformulate thermal lines as a stochastic implementation of quadrature-grid integration, analyze the analytical form of its bias, and extend the method to multiple-point quadrature grids applicable to any factorizable harmonic or anharmonic nuclear wave function. The bias incurred by thermal lines is found to depend on the local form of the expectation value, and we demonstrate that the use of finer quadrature grids along selected modes can eliminate this bias, while still offering an ˜30 % lower computational cost than direct Monte Carlo integration in our tests.

Role of weakest links and system-size scaling in multiscale modeling of stochastic plasticity

NASA Astrophysics Data System (ADS)

Ispánovity, Péter Dusán; Tüzes, Dániel; Szabó, Péter; Zaiser, Michael; Groma, István

2017-02-01

Plastic deformation of crystalline and amorphous matter often involves intermittent local strain burst events. To understand the physical background of the phenomenon a minimal stochastic mesoscopic model was introduced, where details of the microstructure evolution are statistically represented in terms of a fluctuating local yield threshold. In the present paper we propose a method for determining the corresponding yield stress distribution for the case of crystal plasticity from lower scale discrete dislocation dynamics simulations which we combine with weakest link arguments. The success of scale linking is demonstrated by comparing stress-strain curves obtained from the resulting mesoscopic and the underlying discrete dislocation models in the microplastic regime. As shown by various scaling relations they are statistically equivalent and behave identically in the thermodynamic limit. The proposed technique is expected to be applicable to different microstructures and also to amorphous materials.

Stochastic process of pragmatic information for 2D spiral wave turbulence in globally and locally coupled Alief-Panfilov oscillators

NASA Astrophysics Data System (ADS)

Kuwahara, Jun; Miyata, Hajime; Konno, Hidetoshi

2017-09-01

Recently, complex dynamics of globally coupled oscillators have been attracting many researcher's attentions. In spite of their numerous studies, their features of nonlinear oscillator systems with global and local couplings in two-dimension (2D) are not understood fully. The paper focuses on 2D states of coherent, clustered and chaotic oscillation especially under the effect of negative global coupling (NGC) in 2D Alief-Panfilov model. It is found that the tuning NGC can cause various new coupling-parameter dependency on the features of oscillations. Then quantitative characterization of various states of oscillations (so called spiral wave turbulence) is examined by using the pragmatic information (PI) which have been utilized in analyzing multimode laser, solar activity and neuronal systems. It is demonstrated that the dynamics of the PI for various oscillations can be characterized successfully by the Hyper-Gamma stochastic process.

Stochastic Set-Based Particle Swarm Optimization Based on Local Exploration for Solving the Carpool Service Problem.

PubMed

Chou, Sheng-Kai; Jiau, Ming-Kai; Huang, Shih-Chia

2016-08-01

The growing ubiquity of vehicles has led to increased concerns about environmental issues. These concerns can be mitigated by implementing an effective carpool service. In an intelligent carpool system, an automated service process assists carpool participants in determining routes and matches. It is a discrete optimization problem that involves a system-wide condition as well as participants' expectations. In this paper, we solve the carpool service problem (CSP) to provide satisfactory ride matches. To this end, we developed a particle swarm carpool algorithm based on stochastic set-based particle swarm optimization (PSO). Our method introduces stochastic coding to augment traditional particles, and uses three terminologies to represent a particle: 1) particle position; 2) particle view; and 3) particle velocity. In this way, the set-based PSO (S-PSO) can be realized by local exploration. In the simulation and experiments, two kind of discrete PSOs-S-PSO and binary PSO (BPSO)-and a genetic algorithm (GA) are compared and examined using tested benchmarks that simulate a real-world metropolis. We observed that the S-PSO outperformed the BPSO and the GA thoroughly. Moreover, our method yielded the best result in a statistical test and successfully obtained numerical results for meeting the optimization objectives of the CSP.

Renormalizing a viscous fluid model for large scale structure formation

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

Führer, Florian; Rigopoulos, Gerasimos, E-mail: fuhrer@thphys.uni-heidelberg.de, E-mail: gerasimos.rigopoulos@ncl.ac.uk

2016-02-01

Using the Stochastic Adhesion Model (SAM) as a simple toy model for cosmic structure formation, we study renormalization and the removal of the cutoff dependence from loop integrals in perturbative calculations. SAM shares the same symmetry with the full system of continuity+Euler equations and includes a viscosity term and a stochastic noise term, similar to the effective theories recently put forward to model CDM clustering. We show in this context that if the viscosity and noise terms are treated as perturbative corrections to the standard eulerian perturbation theory, they are necessarily non-local in time. To ensure Galilean Invariance higher ordermore » vertices related to the viscosity and the noise must then be added and we explicitly show at one-loop that these terms act as counter terms for vertex diagrams. The Ward Identities ensure that the non-local-in-time theory can be renormalized consistently. Another possibility is to include the viscosity in the linear propagator, resulting in exponential damping at high wavenumber. The resulting local-in-time theory is then renormalizable to one loop, requiring less free parameters for its renormalization.« less

Sources and Sinks: A Stochastic Model of Evolution in Heterogeneous Environments

NASA Astrophysics Data System (ADS)

Hermsen, Rutger; Hwa, Terence

2010-12-01

We study evolution driven by spatial heterogeneity in a stochastic model of source-sink ecologies. A sink is a habitat where mortality exceeds reproduction so that a local population persists only due to immigration from a source. Immigrants can, however, adapt to conditions in the sink by mutation. To characterize the adaptation rate, we derive expressions for the first arrival time of adapted mutants. The joint effects of migration, mutation, birth, and death result in two distinct parameter regimes. These results may pertain to the rapid evolution of drug-resistant pathogens and insects.

Local Improvement Results for Anderson Acceleration with Inaccurate Function Evaluations

DOE PAGES

Toth, Alex; Ellis, J. Austin; Evans, Tom; ...

2017-10-26

Here, we analyze the convergence of Anderson acceleration when the fixed point map is corrupted with errors. We also consider uniformly bounded errors and stochastic errors with infinite tails. We prove local improvement results which describe the performance of the iteration up to the point where the accuracy of the function evaluation causes the iteration to stagnate. We illustrate the results with examples from neutronics.

Local Improvement Results for Anderson Acceleration with Inaccurate Function Evaluations

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

Toth, Alex; Ellis, J. Austin; Evans, Tom

Here, we analyze the convergence of Anderson acceleration when the fixed point map is corrupted with errors. We also consider uniformly bounded errors and stochastic errors with infinite tails. We prove local improvement results which describe the performance of the iteration up to the point where the accuracy of the function evaluation causes the iteration to stagnate. We illustrate the results with examples from neutronics.

Assessing local population vulnerability to wind energy development with branching process models: an application to wind energy development

USGS Publications Warehouse

Erickson, Richard A.; Eager, Eric A.; Stanton, Jessica C.; Beston, Julie A.; Diffendorfer, James E.; Thogmartin, Wayne E.

2015-01-01

Quantifying the impact of anthropogenic development on local populations is important for conservation biology and wildlife management. However, these local populations are often subject to demographic stochasticity because of their small population size. Traditional modeling efforts such as population projection matrices do not consider this source of variation whereas individual-based models, which include demographic stochasticity, are computationally intense and lack analytical tractability. One compromise between approaches is branching process models because they accommodate demographic stochasticity and are easily calculated. These models are known within some sub-fields of probability and mathematical ecology but are not often applied in conservation biology and applied ecology. We applied branching process models to quantitatively compare and prioritize species locally vulnerable to the development of wind energy facilities. Specifically, we examined species vulnerability using branching process models for four representative species: A cave bat (a long-lived, low fecundity species), a tree bat (short-lived, moderate fecundity species), a grassland songbird (a short-lived, high fecundity species), and an eagle (a long-lived, slow maturation species). Wind turbine-induced mortality has been observed for all of these species types, raising conservation concerns. We simulated different mortality rates from wind farms while calculating local extinction probabilities. The longer-lived species types (e.g., cave bats and eagles) had much more pronounced transitions from low extinction risk to high extinction risk than short-lived species types (e.g., tree bats and grassland songbirds). High-offspring-producing species types had a much greater variability in baseline risk of extinction than the lower-offspring-producing species types. Long-lived species types may appear stable until a critical level of incidental mortality occurs. After this threshold, the risk of extirpation for a local population may rapidly increase with only minimal increases in wind mortality. Conservation biologists and wildlife managers may need to consider this mortality pattern when issuing take permits and developing monitoring protocols for wind facilities. We also describe how our branching process models may be generalized across a wider range of species for a larger assessment project and then describe how our methods may be applied to other stressors in addition to wind.

Membrane Fusion Involved in Neurotransmission: Glimpse from Electron Microscope and Molecular Simulation

PubMed Central

Yang, Zhiwei; Gou, Lu; Chen, Shuyu; Li, Na; Zhang, Shengli; Zhang, Lei

2017-01-01

Membrane fusion is one of the most fundamental physiological processes in eukaryotes for triggering the fusion of lipid and content, as well as the neurotransmission. However, the architecture features of neurotransmitter release machinery and interdependent mechanism of synaptic membrane fusion have not been extensively studied. This review article expounds the neuronal membrane fusion processes, discusses the fundamental steps in all fusion reactions (membrane aggregation, membrane association, lipid rearrangement and lipid and content mixing) and the probable mechanism coupling to the delivery of neurotransmitters. Subsequently, this work summarizes the research on the fusion process in synaptic transmission, using electron microscopy (EM) and molecular simulation approaches. Finally, we propose the future outlook for more exciting applications of membrane fusion involved in synaptic transmission, with the aid of stochastic optical reconstruction microscopy (STORM), cryo-EM (cryo-EM), and molecular simulations. PMID:28638320

Empirical correction for earth sensor horizon radiance variation

NASA Technical Reports Server (NTRS)

Hashmall, Joseph A.; Sedlak, Joseph; Andrews, Daniel; Luquette, Richard

1998-01-01

A major limitation on the use of infrared horizon sensors for attitude determination is the variability of the height of the infrared Earth horizon. This variation includes a climatological component and a stochastic component of approximately equal importance. The climatological component shows regular variation with season and latitude. Models based on historical measurements have been used to compensate for these systematic changes. The stochastic component is analogous to tropospheric weather. It can cause extreme, localized changes that for a period of days, overwhelm the climatological variation. An algorithm has been developed to compensate partially for the climatological variation of horizon height and at least to mitigate the stochastic variation. This method uses attitude and horizon sensor data from spacecraft to update a horizon height history as a function of latitude. For spacecraft that depend on horizon sensors for their attitudes (such as the Total Ozone Mapping Spectrometer-Earth Probe-TOMS-EP) a batch least squares attitude determination system is used. It is assumed that minimizing the average sensor residual throughout a full orbit of data results in attitudes that are nearly independent of local horizon height variations. The method depends on the additional assumption that the mean horizon height over all latitudes is approximately independent of season. Using these assumptions, the method yields the latitude dependent portion of local horizon height variations. This paper describes the algorithm used to generate an empirical horizon height. Ideally, an international horizon height database could be established that would rapidly merge data from various spacecraft to provide timely corrections that could be used by all.

Bubonic plague: a metapopulation model of a zoonosis.

PubMed Central

Keeling, M J; Gilligan, C A

2000-01-01

Bubonic plague (Yersinia pestis) is generally thought of as a historical disease; however, it is still responsible for around 1000-3000 deaths each year worldwide. This paper expands the analysis of a model for bubonic plague that encompasses the disease dynamics in rat, flea and human populations. Some key variables of the deterministic model, including the force of infection to humans, are shown to be robust to changes in the basic parameters, although variation in the flea searching efficiency, and the movement rates of rats and fleas will be considered throughout the paper. The stochastic behaviour of the corresponding metapopulation model is discussed, with attention focused on the dynamics of rats and the force of infection at the local spatial scale. Short-lived local epidemics in rats govern the invasion of the disease and produce an irregular pattern of human cases similar to those observed. However, the endemic behaviour in a few rat subpopulations allows the disease to persist for many years. This spatial stochastic model is also used to identify the criteria for the spread to human populations in terms of the rat density. Finally, the full stochastic model is reduced to the form of a probabilistic cellular automaton, which allows the analysis of a large number of replicated epidemics in large populations. This simplified model enables us to analyse the spatial properties of rat epidemics and the effects of movement rates, and also to test whether the emergent metapopulation behaviour is a property of the local dynamics rather than the precise details of the model. PMID:11413636

Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification.

PubMed

Chebouba, Lokmane; Boughaci, Dalila; Guziolowski, Carito

2018-06-04

The use of data issued from high throughput technologies in drug target problems is widely widespread during the last decades. This study proposes a meta-heuristic framework using stochastic local search (SLS) combined with random forest (RF) where the aim is to specify the most important genes and proteins leading to the best classification of Acute Myeloid Leukemia (AML) patients. First we use a stochastic local search meta-heuristic as a feature selection technique to select the most significant proteins to be used in the classification task step. Then we apply RF to classify new patients into their corresponding classes. The evaluation technique is to run the RF classifier on the training data to get a model. Then, we apply this model on the test data to find the appropriate class. We use as metrics the balanced accuracy (BAC) and the area under the receiver operating characteristic curve (AUROC) to measure the performance of our model. The proposed method is evaluated on the dataset issued from DREAM 9 challenge. The comparison is done with a pure random forest (without feature selection), and with the two best ranked results of the DREAM 9 challenge. We used three types of data: only clinical data, only proteomics data, and finally clinical and proteomics data combined. The numerical results show that the highest scores are obtained when using clinical data alone, and the lowest is obtained when using proteomics data alone. Further, our method succeeds in finding promising results compared to the methods presented in the DREAM challenge.

Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging

NASA Astrophysics Data System (ADS)

Errico, Claudia; Pierre, Juliette; Pezet, Sophie; Desailly, Yann; Lenkei, Zsolt; Couture, Olivier; Tanter, Mickael

2015-11-01

Non-invasive imaging deep into organs at microscopic scales remains an open quest in biomedical imaging. Although optical microscopy is still limited to surface imaging owing to optical wave diffusion and fast decorrelation in tissue, revolutionary approaches such as fluorescence photo-activated localization microscopy led to a striking increase in resolution by more than an order of magnitude in the last decade. In contrast with optics, ultrasonic waves propagate deep into organs without losing their coherence and are much less affected by in vivo decorrelation processes. However, their resolution is impeded by the fundamental limits of diffraction, which impose a long-standing trade-off between resolution and penetration. This limits clinical and preclinical ultrasound imaging to a sub-millimetre scale. Here we demonstrate in vivo that ultrasound imaging at ultrafast frame rates (more than 500 frames per second) provides an analogue to optical localization microscopy by capturing the transient signal decorrelation of contrast agents—inert gas microbubbles. Ultrafast ultrasound localization microscopy allowed both non-invasive sub-wavelength structural imaging and haemodynamic quantification of rodent cerebral microvessels (less than ten micrometres in diameter) more than ten millimetres below the tissue surface, leading to transcranial whole-brain imaging within short acquisition times (tens of seconds). After intravenous injection, single echoes from individual microbubbles were detected through ultrafast imaging. Their localization, not limited by diffraction, was accumulated over 75,000 images, yielding 1,000,000 events per coronal plane and statistically independent pixels of ten micrometres in size. Precise temporal tracking of microbubble positions allowed us to extract accurately in-plane velocities of the blood flow with a large dynamic range (from one millimetre per second to several centimetres per second). These results pave the way for deep non-invasive microscopy in animals and humans using ultrasound. We anticipate that ultrafast ultrasound localization microscopy may become an invaluable tool for the fundamental understanding and diagnostics of various disease processes that modify the microvascular blood flow, such as cancer, stroke and arteriosclerosis.

Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging.

PubMed

Errico, Claudia; Pierre, Juliette; Pezet, Sophie; Desailly, Yann; Lenkei, Zsolt; Couture, Olivier; Tanter, Mickael

2015-11-26

Non-invasive imaging deep into organs at microscopic scales remains an open quest in biomedical imaging. Although optical microscopy is still limited to surface imaging owing to optical wave diffusion and fast decorrelation in tissue, revolutionary approaches such as fluorescence photo-activated localization microscopy led to a striking increase in resolution by more than an order of magnitude in the last decade. In contrast with optics, ultrasonic waves propagate deep into organs without losing their coherence and are much less affected by in vivo decorrelation processes. However, their resolution is impeded by the fundamental limits of diffraction, which impose a long-standing trade-off between resolution and penetration. This limits clinical and preclinical ultrasound imaging to a sub-millimetre scale. Here we demonstrate in vivo that ultrasound imaging at ultrafast frame rates (more than 500 frames per second) provides an analogue to optical localization microscopy by capturing the transient signal decorrelation of contrast agents--inert gas microbubbles. Ultrafast ultrasound localization microscopy allowed both non-invasive sub-wavelength structural imaging and haemodynamic quantification of rodent cerebral microvessels (less than ten micrometres in diameter) more than ten millimetres below the tissue surface, leading to transcranial whole-brain imaging within short acquisition times (tens of seconds). After intravenous injection, single echoes from individual microbubbles were detected through ultrafast imaging. Their localization, not limited by diffraction, was accumulated over 75,000 images, yielding 1,000,000 events per coronal plane and statistically independent pixels of ten micrometres in size. Precise temporal tracking of microbubble positions allowed us to extract accurately in-plane velocities of the blood flow with a large dynamic range (from one millimetre per second to several centimetres per second). These results pave the way for deep non-invasive microscopy in animals and humans using ultrasound. We anticipate that ultrafast ultrasound localization microscopy may become an invaluable tool for the fundamental understanding and diagnostics of various disease processes that modify the microvascular blood flow, such as cancer, stroke and arteriosclerosis.

Spontaneous Polarization in Bio-organic Materials Studied by Scanning Pyroelectric Microscopy (SPEM) and Second Harmonic Generation Microscopy (SHGM)

NASA Astrophysics Data System (ADS)

Putzeys, T.; Wübbenhorst, M.; van der Veen, M. A.

2015-06-01

Bio-organic materials such as bones, teeth, and tendon generally show nonlinear optical (Masters and So in Handbook of Biomedical Nonlinear Optical Microscopy, 2008), pyro- and piezoelectric (Fukada and Yasuda in J Phys Soc Jpn 12:1158, 1957) properties, implying a permanent polarization, the presence of which can be rationalized by describing the growth of the sample and the creation of a polar axis according to Markov's theory of stochastic processes (Hulliger in Biophys J 84:3501, 2003; Batagiannis et al. in Curr Opin Solid State Mater Sci 17:107, 2010). Two proven, versatile techniques for probing spontaneous polarization distributions in solids are scanning pyroelectric microscopy (SPEM) and second harmonic generation microscopy (SHGM). The combination of pyroelectric scanning with SHG-microscopy in a single experimental setup leading to complementary pyroelectric and nonlinear optical data is demonstrated, providing us with a more complete image of the polarization in organic materials. Crystals consisting of a known polar and hyperpolarizable material, CNS (4-chloro-4-nitrostilbene) are used as a reference sample, to verify the functionality of the setup, with both SPEM and SHGM images revealing the same polarization domain information. In contrast, feline and human nails exhibit a pyroelectric response, but a second harmonic response is absent for both keratin containing materials, implying that there may be symmetry-allowed SHG, but with very inefficient second harmonophores. This new approach to polarity detection provides additional information on the polar and hyperpolar nature in a variety of (bio) materials.

Noise-induced escape in an excitable system

NASA Astrophysics Data System (ADS)

Khovanov, I. A.; Polovinkin, A. V.; Luchinsky, D. G.; McClintock, P. V. E.

2013-03-01

We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neuronal model, for different classes of excitability. We discuss, first, the threshold structure of the FHN model as an example of a system without a saddle state. We then develop a nonlinear (nonlocal) stability approach based on the theory of large fluctuations, including a finite-noise correction, to describe noise-induced escape in the excitable regime. We show that the threshold structure is revealed via patterns of most probable (optimal) fluctuational paths. The approach allows us to estimate the escape rate and the exit location distribution. We compare the responses of a monostable resonator and monostable integrator to stochastic input signals and to a mixture of periodic and stochastic stimuli. Unlike the commonly used local analysis of the stable state, our nonlocal approach based on optimal paths yields results that are in good agreement with direct numerical simulations of the Langevin equation.

Large-deviation properties of Brownian motion with dry friction.

PubMed

Chen, Yaming; Just, Wolfram

2014-10-01

We investigate piecewise-linear stochastic models with regard to the probability distribution of functionals of the stochastic processes, a question that occurs frequently in large deviation theory. The functionals that we are looking into in detail are related to the time a stochastic process spends at a phase space point or in a phase space region, as well as to the motion with inertia. For a Langevin equation with discontinuous drift, we extend the so-called backward Fokker-Planck technique for non-negative support functionals to arbitrary support functionals, to derive explicit expressions for the moments of the functional. Explicit solutions for the moments and for the distribution of the so-called local time, the occupation time, and the displacement are derived for the Brownian motion with dry friction, including quantitative measures to characterize deviation from Gaussian behavior in the asymptotic long time limit.

Activity-dependent stochastic resonance in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Volman, Vladislav

2009-03-01

An important source of noise for neuronal networks is that of the stochastic nature of synaptic transmission. In particular, there can occur spontaneous asynchronous release of neurotransmitter at a rate that is strongly dependent on the presynaptic Ca2+ concentration and hence strongly dependent on the rate of spike induced Ca2+. Here it is shown that this noise can lead to a new form of stochastic resonance for local circuits consisting of roughly 100 neurons - a ``microcolumn''- coupled via noisy plastic synapses. Furthermore, due to the plastic coupling and activity-dependent noise component, the detection of weak stimuli will also depend on the structure of the latter. In addition, the circuit can exhibit short-term memory, by which we mean that spiking will continue to occur for a transient period following removal of the stimulus. These results can be directly tested in experiments on cultured networks.

Resilient filtering for time-varying stochastic coupling networks under the event-triggering scheduling

NASA Astrophysics Data System (ADS)

Wang, Fan; Liang, Jinling; Dobaie, Abdullah M.

2018-07-01

The resilient filtering problem is considered for a class of time-varying networks with stochastic coupling strengths. An event-triggered strategy is adopted to save the network resources by scheduling the signal transmission from the sensors to the filters based on certain prescribed rules. Moreover, the filter parameters to be designed are subject to gain perturbations. The primary aim of the addressed problem is to determine a resilient filter that ensures an acceptable filtering performance for the considered network with event-triggering scheduling. To handle such an issue, an upper bound on the estimation error variance is established for each node according to the stochastic analysis. Subsequently, the resilient filter is designed by locally minimizing the derived upper bound at each iteration. Moreover, rigorous analysis shows the monotonicity of the minimal upper bound regarding the triggering threshold. Finally, a simulation example is presented to show effectiveness of the established filter scheme.

Stochastic sensitivity measure for mistuned high-performance turbines

NASA Technical Reports Server (NTRS)

Murthy, Durbha V.; Pierre, Christophe

1992-01-01

A stochastic measure of sensitivity is developed in order to predict the effects of small random blade mistuning on the dynamic aeroelastic response of turbomachinery blade assemblies. This sensitivity measure is based solely on the nominal system design (i.e., on tuned system information), which makes it extremely easy and inexpensive to calculate. The measure has the potential to become a valuable design tool that will enable designers to evaluate mistuning effects at a preliminary design stage and thus assess the need for a full mistuned rotor analysis. The predictive capability of the sensitivity measure is illustrated by examining the effects of mistuning on the aeroelastic modes of the first stage of the oxidizer turbopump in the Space Shuttle Main Engine. Results from a full analysis mistuned systems confirm that the simple stochastic sensitivity measure predicts consistently the drastic changes due to misturning and the localization of aeroelastic vibration to a few blades.

Stochastic fire-diffuse-fire model with realistic cluster dynamics.

PubMed

Calabrese, Ana; Fraiman, Daniel; Zysman, Daniel; Ponce Dawson, Silvina

2010-09-01

Living organisms use waves that propagate through excitable media to transport information. Ca2+ waves are a paradigmatic example of this type of processes. A large hierarchy of Ca2+ signals that range from localized release events to global waves has been observed in Xenopus laevis oocytes. In these cells, Ca2+ release occurs trough inositol 1,4,5-trisphosphate receptors (IP3Rs) which are organized in clusters of channels located on the membrane of the endoplasmic reticulum. In this article we construct a stochastic model for a cluster of IP3R 's that replicates the experimental observations reported in [D. Fraiman, Biophys. J. 90, 3897 (2006)]. We then couple this phenomenological cluster model with a reaction-diffusion equation, so as to have a discrete stochastic model for calcium dynamics. The model we propose describes the transition regimes between isolated release and steadily propagating waves as the IP3 concentration is increased.

Nanoscale Membrane Curvature detected by Polarized Localization Microscopy

NASA Astrophysics Data System (ADS)

Kelly, Christopher; Maarouf, Abir; Woodward, Xinxin

Nanoscale membrane curvature is a necessary component of countless cellular processes. Here we present Polarized Localization Microscopy (PLM), a super-resolution optical imaging technique that enables the detection of nanoscale membrane curvature with order-of-magnitude improvements over comparable optical techniques. PLM combines the advantages of polarized total internal reflection fluorescence microscopy and fluorescence localization microscopy to reveal single-fluorophore locations and orientations without reducing localization precision by point spread function manipulation. PLM resolved nanoscale membrane curvature of a supported lipid bilayer draped over polystyrene nanoparticles on a glass coverslip, thus creating a model membrane with coexisting flat and curved regions and membrane radii of curvature as small as 20 nm. Further, PLM provides single-molecule trajectories and the aggregation of curvature-inducing proteins with super-resolution to reveal the correlated effects of membrane curvature, dynamics, and molecular sorting. For example, cholera toxin subunit B has been observed to induce nanoscale membrane budding and concentrate at the bud neck. PLM reveals a previously hidden and critical information of membrane topology.

Formation of gold nanorods by a stochastic "popcorn" mechanism.

PubMed

Edgar, Jonathan A; McDonagh, Andrew M; Cortie, Michael B

2012-02-28

Gold nanorods have significant technological potential and are of broad interest to the nanotechnology community. The discovery of the seeded, wet-chemical synthetic process to produce them may be regarded as a landmark in the control of metal nanoparticle shape. However, the mechanism by which the initial spherical gold seeds acquire anisotropy is a critical, yet poorly understood, factor. Here we examine the very early stages of rod growth using a combination of techniques including cryogenic transmission electron microscopy, optical spectroscopy, and computational modeling. Reconciliation of the available experimental observations can only be achieved by invoking a stochastic, "popcorn"-like mechanism of growth, in which individual seeds lie quiescent for some time before suddenly and rapidly growing into rods. This is quite different from the steady, concurrent growth of nanorods that has been previously generally assumed. Furthermore we propose that the shape is controlled by the ratio of surface energy of rod sides to rod ends, with values of this quantity in the range of 0.3-0.8 indicated for typical growth solutions.

Super-resolution and super-localization microscopy: A novel tool for imaging chemical and biological processes

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

Dong, Bin

2015-01-01

Optical microscopy imaging of single molecules and single particles is an essential method for studying fundamental biological and chemical processes at the molecular and nanometer scale. The best spatial resolution (~ λ/2) achievable in traditional optical microscopy is governed by the diffraction of light. However, single molecule-based super-localization and super-resolution microscopy imaging techniques have emerged in the past decade. Individual molecules can be localized with nanometer scale accuracy and precision for studying of biological and chemical processes.This work uncovered the heterogeneous properties of the pore structures. In this dissertation, the coupling of molecular transport and catalytic reaction at the singlemore » molecule and single particle level in multilayer mesoporous nanocatalysts was elucidated. Most previous studies dealt with these two important phenomena separately. A fluorogenic oxidation reaction of non-fluorescent amplex red to highly fluorescent resorufin was tested. The diffusion behavior of single resorufin molecules in aligned nanopores was studied using total internal reflection fluorescence microscopy (TIRFM).« less

Identifying Nanoscale Structure-Function Relationships Using Multimodal Atomic Force Microscopy, Dimensionality Reduction, and Regression Techniques.

PubMed

Kong, Jessica; Giridharagopal, Rajiv; Harrison, Jeffrey S; Ginger, David S

2018-05-31

Correlating nanoscale chemical specificity with operational physics is a long-standing goal of functional scanning probe microscopy (SPM). We employ a data analytic approach combining multiple microscopy modes, using compositional information in infrared vibrational excitation maps acquired via photoinduced force microscopy (PiFM) with electrical information from conductive atomic force microscopy. We study a model polymer blend comprising insulating poly(methyl methacrylate) (PMMA) and semiconducting poly(3-hexylthiophene) (P3HT). We show that PiFM spectra are different from FTIR spectra, but can still be used to identify local composition. We use principal component analysis to extract statistically significant principal components and principal component regression to predict local current and identify local polymer composition. In doing so, we observe evidence of semiconducting P3HT within PMMA aggregates. These methods are generalizable to correlated SPM data and provide a meaningful technique for extracting complex compositional information that are impossible to measure from any one technique.

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

NASA Astrophysics Data System (ADS)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

Allee effects and the spatial dynamics of a locally endangered butterfly, the high brown fritillary (Argynnis adippe).

PubMed

Bonsall, Michael B; Dooley, Claire A; Kasparson, Anna; Brereton, Tom; Roy, David B; Thomas, Jeremy A

2014-01-01

Conservation of endangered species necessitates a full appreciation of the ecological processes affecting the regulation, limitation, and persistence of populations. These processes are influenced by birth, death, and dispersal events, and characterizing them requires careful accounting of both the deterministic and stochastic processes operating at both local and regional population levels. We combined ecological theory and observations on Allee effects by linking mathematical analysis and the spatial and temporal population dynamics patterns of a highly endangered butterfly, the high brown fritillary, Argynnis adippe. Our theoretical analysis showed that the role of density-dependent feedbacks in the presence of local immigration can influence the strength of Allee effects. Linking this theory to the analysis of the population data revealed strong evidence for both negative density dependence and Allee effects at the landscape or regional scale. These regional dynamics are predicted to be highly influenced by immigration. Using a Bayesian state-space approach, we characterized the local-scale births, deaths, and dispersal effects together with measurement and process uncertainty in the metapopulation. Some form of an Allee effect influenced almost three-quarters of these local populations. Our joint analysis of the deterministic and stochastic dynamics suggests that a conservation priority for this species would be to increase resource availability in currently occupied and, more importantly, in unoccupied sites.

Monosynaptic convergence of chorda tympani and glossopharyngeal afferents onto ascending relay neurons in the nucleus of the solitary tract: A high-resolution confocal and correlative electron microscopy approach

PubMed Central

Corson, James A.; Erisir, Alev

2014-01-01

While physiological studies suggested convergence of chorda tympani and glossopharyngeal afferent axons onto single neurons of the rostral nucleus of the solitary tract (rNTS), anatomical evidence has been elusive. The current study uses high-magnification confocal microscopy to identify putative synaptic contacts from afferent fibers of the two nerves onto individual projection neurons. Imaged tissue is re-visualized with electron microscopy, confirming that overlapping fluorescent signals in confocal z-stacks accurately identify appositions between labeled terminal and dendrite pairs. Monte Carlo modeling reveals that the probability of overlapping fluorophores is stochastically unrelated to the density of afferent label suggesting that convergent innervation in the rNTS is selective rather than opportunistic. Putative synaptic contacts from each nerve are often compartmentalized onto dendrite segments of convergently innervated neurons. These results have important implications for orosensory processing in the rNTS, and the techniques presented here have applications in investigations of neural microcircuitry with an emphasis on innervation patterning. PMID:23640852

Exploring the interactome: microfluidic isolation of proteins and interacting partners for quantitative analysis by electron microscopy.

PubMed

Giss, Dominic; Kemmerling, Simon; Dandey, Venkata; Stahlberg, Henning; Braun, Thomas

2014-05-20

Multimolecular protein complexes are important for many cellular processes. However, the stochastic nature of the cellular interactome makes the experimental detection of complex protein assemblies difficult and quantitative analysis at the single molecule level essential. Here, we present a fast and simple microfluidic method for (i) the quantitative isolation of endogenous levels of untagged protein complexes from minute volumes of cell lysates under close to physiological conditions and (ii) the labeling of specific components constituting these complexes. The method presented uses specific antibodies that are conjugated via a photocleavable linker to magnetic beads that are trapped in microcapillaries to immobilize the target proteins. Proteins are released by photocleavage, eluted, and subsequently analyzed by quantitative transmission electron microscopy at the single molecule level. Additionally, before photocleavage, immunogold can be employed to label proteins that interact with the primary target protein. Thus, the presented method provides a new way to study the interactome and, in combination with single molecule transmission electron microscopy, to structurally characterize the large, dynamic, heterogeneous multimolecular protein complexes formed.

The radial electric field as a measure for field penetration of resonant magnetic perturbations

DOE PAGES

Mordijck, Saskia; Moyer, Richard A.; Ferraro, Nathaniel M.; ...

2014-06-18

In this study, we introduce a new indirect method for identifying the radial extent of the stochastic layer due to applying resonant magnetic perturbations (RMPs) in H-mode plasmas by measuring the spin-up of the plasma near the separatrix. This spin-up is a predicted consequence of enhanced loss of electrons due to magnetic stochastization. We find that in DIII-D H-mode plasmas with n = 3 RMPs applied for edge localized mode (ELM) suppression, the stochastic layer is limited to the outer 5% region in normalized magnetic flux, Ψ N. This is in contrast to vacuum modeling predictions where this layer canmore » penetrate up to 20% in Ψ N. Theoretical predictions of a stochastic red radial electric field, E r component exceed the experimental measurements by about a factor 3 close to the separatrix, suggesting that the outer region of the plasma is weakly stochastic. Linear response calculations with M3D-C1, a resistive two-fluid model, show that in this outer 5% region, plasma response often reduces the resonant magnetic field components by 67% or more in comparison with vacuum calculations. These results for DIII-D are in reasonable agreement with results from the MAST tokamak, where the magnetic field perturbation from vacuum field calculations needed to be reduced by 75% for agreement with experimental measurements of the x-point lobe structures.« less

Localization and spectral isolation of special nuclear material using stochastic image reconstruction

NASA Astrophysics Data System (ADS)

Hamel, M. C.; Polack, J. K.; Poitrasson-Rivière, A.; Clarke, S. D.; Pozzi, S. A.

2017-01-01

In this work we present a technique for isolating the gamma-ray and neutron energy spectra from multiple radioactive sources localized in an image. Image reconstruction algorithms for radiation scatter cameras typically focus on improving image quality. However, with scatter cameras being developed for non-proliferation applications, there is a need for not only source localization but also source identification. This work outlines a modified stochastic origin ensembles algorithm that provides localized spectra for all pixels in the image. We demonstrated the technique by performing three experiments with a dual-particle imager that measured various gamma-ray and neutron sources simultaneously. We showed that we could isolate the peaks from 22Na and 137Cs and that the energy resolution is maintained in the isolated spectra. To evaluate the spectral isolation of neutrons, a 252Cf source and a PuBe source were measured simultaneously and the reconstruction showed that the isolated PuBe spectrum had a higher average energy and a greater fraction of neutrons at higher energies than the 252Cf. Finally, spectrum isolation was used for an experiment with weapons grade plutonium, 252Cf, and AmBe. The resulting neutron and gamma-ray spectra showed the expected characteristics that could then be used to identify the sources.

Neutral Evolution in a Biological Population as Diffusion in Phenotype Space: Reproduction with Local Mutation but without Selection

NASA Astrophysics Data System (ADS)

Lawson, Daniel John; Jensen, Henrik Jeldtoft

2007-03-01

The process of “evolutionary diffusion,” i.e., reproduction with local mutation but without selection in a biological population, resembles standard diffusion in many ways. However, evolutionary diffusion allows the formation of localized peaks that undergo drift, even in the infinite population limit. We relate a microscopic evolution model to a stochastic model which we solve fully. This allows us to understand the large population limit, relates evolution to diffusion, and shows that independent local mutations act as a diffusion of interacting particles taking larger steps.

Studying localized corrosion using liquid cell transmission electron microscopy

DOE PAGES

Chee, See Wee; Pratt, Sarah H.; Hattar, Khalid; ...

2014-11-07

Using liquid cell transmission electron microscopy (LCTEM), localized corrosion of Cu and Al thin films immersed in aqueous NaCl solutions was studied. We demonstrate that potentiostatic control can be used to initiate pitting and that local compositional changes, due to focused ion beam implantation of Au + ions, can modify the corrosion susceptibility of Al films. Likewise, a discussion on strategies to control the onset of pitting is also presented.

Biological oscillations: Fluorescence monitoring by confocal microscopy

NASA Astrophysics Data System (ADS)

Chattoraj, Shyamtanu; Bhattacharyya, Kankan

2016-09-01

Fluctuations play a vital role in biological systems. Single molecule spectroscopy has recently revealed many new kinds of fluctuations in biological molecules. In this account, we focus on structural fluctuations of an antigen-antibody complex, conformational dynamics of a DNA quadruplex, effects of taxol on dynamics of microtubules, intermittent red-ox oscillations at different organelles in a live cell (mitochondria, lipid droplets, endoplasmic reticulum and cell membrane) and stochastic resonance in gene silencing. We show that there are major differences in these dynamics between a cancer cell and the corresponding non-cancer cell.

Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm.

PubMed

Agarwal, Krishna; Macháň, Radek; Prasad, Dilip K

2018-03-21

Localization microscopy and multiple signal classification algorithm use temporal stack of image frames of sparse emissions from fluorophores to provide super-resolution images. Localization microscopy localizes emissions in each image independently and later collates the localizations in all the frames, giving same weight to each frame irrespective of its signal-to-noise ratio. This results in a bias towards frames with low signal-to-noise ratio and causes cluttered background in the super-resolved image. User-defined heuristic computational filters are employed to remove a set of localizations in an attempt to overcome this bias. Multiple signal classification performs eigen-decomposition of the entire stack, irrespective of the relative signal-to-noise ratios of the frames, and uses a threshold to classify eigenimages into signal and null subspaces. This results in under-representation of frames with low signal-to-noise ratio in the signal space and over-representation in the null space. Thus, multiple signal classification algorithms is biased against frames with low signal-to-noise ratio resulting into suppression of the corresponding fluorophores. This paper presents techniques to automatically debias localization microscopy and multiple signal classification algorithm of these biases without compromising their resolution and without employing heuristics, user-defined criteria. The effect of debiasing is demonstrated through five datasets of invitro and fixed cell samples.

Perturbation expansions of stochastic wavefunctions for open quantum systems

NASA Astrophysics Data System (ADS)

Ke, Yaling; Zhao, Yi

2017-11-01

Based on the stochastic unravelling of the reduced density operator in the Feynman path integral formalism for an open quantum system in touch with harmonic environments, a new non-Markovian stochastic Schrödinger equation (NMSSE) has been established that allows for the systematic perturbation expansion in the system-bath coupling to arbitrary order. This NMSSE can be transformed in a facile manner into the other two NMSSEs, i.e., non-Markovian quantum state diffusion and time-dependent wavepacket diffusion method. Benchmarked by numerically exact results, we have conducted a comparative study of the proposed method in its lowest order approximation, with perturbative quantum master equations in the symmetric spin-boson model and the realistic Fenna-Matthews-Olson complex. It is found that our method outperforms the second-order time-convolutionless quantum master equation in the whole parameter regime and even far better than the fourth-order in the slow bath and high temperature cases. Besides, the method is applicable on an equal footing for any kind of spectral density function and is expected to be a powerful tool to explore the quantum dynamics of large-scale systems, benefiting from the wavefunction framework and the time-local appearance within a single stochastic trajectory.

Tangent map intermittency as an approximate analysis of intermittency in a high dimensional fully stochastic dynamical system: The Tangled Nature model.

PubMed

Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto

2016-12-01

It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low-dimensional one appears to be illuminating.

On an aggregation in birth-and-death stochastic dynamics

NASA Astrophysics Data System (ADS)

Finkelshtein, Dmitri; Kondratiev, Yuri; Kutoviy, Oleksandr; Zhizhina, Elena

2014-06-01

We consider birth-and-death stochastic dynamics of particle systems with attractive interaction. The heuristic generator of the dynamics has a constant birth rate and density-dependent decreasing death rate. The corresponding statistical dynamics is constructed. Using the Vlasov-type scaling we derive the limiting mesoscopic evolution and prove that this evolution propagates chaos. We study a nonlinear non-local kinetic equation for the first correlation function (density of population). The existence of uniformly bounded solutions as well as solutions growing inside of a bounded domain and expanding in the space are shown. These solutions describe two regimes in the mesoscopic system: regulation and aggregation.

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

NASA Technical Reports Server (NTRS)

Englander, Arnold C.; Englander, Jacob A.

2017-01-01

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Application of Effective Medium Theory to the Three-Dimensional Heterogeneity of Mantle Anisotropy

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2015-12-01

A self-consistent theory for the effective elastic parameters of stochastic media with small-scale 3D heterogeneities has been developed using a 2nd-order Born approximation to the scattered wavefield (T. H. Jordan, GJI, in press). Here we apply the theory to assess how small-scale variations in the local anisotropy of the upper mantle affect seismic wave propagation. We formulate a anisotropic model in which the local elastic properties are specified by a constant stiffness tensor with hexagonal symmetry of arbitrary orientation. This orientation is guided by a Gaussian random vector field with transversely isotropic (TI) statistics. If the outer scale of the statistical variability is small compared to a wavelength, then the effective seismic velocities are TI and depend on two parameters, a horizontal-to-vertical orientation ratio ξ and a horizontal-to-vertical aspect ratio, η. If ξ = 1, the symmetry axis is isotropically distributed; if ξ < 1, it is vertical biased (bipolar distribution), and if ξ > 1, it is horizontally biased (girdle distribution). If η = 1, the heterogeneity is geometrically isotropic; as η à∞, the medium becomes a horizontal stochastic laminate; as η à0, the medium becomes a vertical stochastic bundle. Using stiffness tensors constrained by laboratory measurements of mantle xenoliths, we explore the dependence of the effective P and S velocities on ξ and η. The effective velocities are strongly controlled by the orientation ratio ξ; e.g., if the hexagonal symmetry axis of the local anisotropy is the fast direction of propagation, then vPH > vPV and vSH > vSV for ξ > 1. A more surprising result is the 2nd-order insensitivity of the velocities to the heterogeneity aspect ratio η. Consequently, the geometrical anisotropy of upper-mantle heterogeneity significantly enhances seismic-wave anisotropy only through local variations in the Voigt-averaged velocities, which depend primarily on rock composition and not deformation history.

Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay

NASA Technical Reports Server (NTRS)

Botai, O. J.; Combrinck, L.; Sivakumar, V.; Schuh, H.; Bohm, J.

2010-01-01

Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

The properties of borderlines in discontinuous conservative systems

NASA Astrophysics Data System (ADS)

Wang, X.-M.; Fang, Z.-J.

2006-02-01

The properties of the set of borderline images in discontinuous conservative systems are commonly investigated. The invertible system in which a stochastic web was found in 1999 is re-discussed here. The result shows that the set of images of the borderline actually forms the same stochastic web. The web has two typical local fine structures. Firstly, in some parts of the web the borderline crosses the manifold of hyperbolic points so that the chaotic diffusion is damped greatly; secondly, in other parts of phase space many holes and elliptic islands appear in the stochastic layer. This local structure shows infinite self-similarity. The noninvertible system in which the so-called chaotic quasi-attractor was found in [X.-M. Wang et al., Eur. Phys. J. D 19, 119 (2002)] is also studied here. The numerical investigation shows that such a chaotic quasi-attractor is confined by the preceding lower order images of the borderline. The mechanism of this confinement is revealed: a forbidden zone exists that any orbit can not visit, which is the sub-phase space of one side of the first image of the borderline. Each order of the images of the forbidden zone can be qualitatively divided into two sub-phase regions: one is the so-called escaping region that provides the orbit with an escaping channel, the other is the so-called dissipative region where the contraction of phase space occurs.

Pandemic Diseases and the Aviation Network SARS, a case study

NASA Astrophysics Data System (ADS)

Hufnagel, Lars; Brockmann, Dirk; Geisel, Theo

2005-03-01

We investigate the mechanisms of the worldwide spread of infectious diseases in a modern world in which humans travel on all scales. We introduce a probabilistic model which accounts for the worldwide spread of infectious diseases on the global aviation network. The analysis indicates that a forecast of the geographical spread of an epidemic is indeed possible, provided that local dynamical parameters of the disease such as the basic reproduction number are known. The model consists of local stochastic infection dynamics and stochastic transport of individuals on the worldwide aviation network which takes into account over 95% of the entire the national and international civil aviation traffic. Our simulations of the SARS outbreak are in surprisingly good agreement with published case reports. Despite the fact that the system is stochastic with a high number of degrees of freedom the outcome of a single simulation exhibits only a small magnitude of variability. We show that this is due to the strong heterogeneity of the network ranging from a few two over 25,000 passengers between nodes of the network. Thus, we propose that our model can be employed to predict the worldwide spread of future pandemic diseases and to identify endangered regions in advance. Based on the connectivity of the aviation network we evaluate the performance of different control strategies and show that a quick and focused reaction is essential to inhibit the global spread of infectious diseases.

Time-lapse microscopy and image processing for stem cell research: modeling cell migration

NASA Astrophysics Data System (ADS)

Gustavsson, Tomas; Althoff, Karin; Degerman, Johan; Olsson, Torsten; Thoreson, Ann-Catrin; Thorlin, Thorleif; Eriksson, Peter

2003-05-01

This paper presents hardware and software procedures for automated cell tracking and migration modeling. A time-lapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.

Vascular bursts enhance permeability of tumour blood vessels and improve nanoparticle delivery

NASA Astrophysics Data System (ADS)

Matsumoto, Yu; Nichols, Joseph W.; Toh, Kazuko; Nomoto, Takahiro; Cabral, Horacio; Miura, Yutaka; Christie, R. James; Yamada, Naoki; Ogura, Tadayoshi; Kano, Mitsunobu R.; Matsumura, Yasuhiro; Nishiyama, Nobuhiro; Yamasoba, Tatsuya; Bae, You Han; Kataoka, Kazunori

2016-06-01

Enhanced permeability in tumours is thought to result from malformed vascular walls with leaky cell-to-cell junctions. This assertion is backed by studies using electron microscopy and polymer casts that show incomplete pericyte coverage of tumour vessels and the presence of intercellular gaps. However, this gives the impression that tumour permeability is static amid a chaotic tumour environment. Using intravital confocal laser scanning microscopy we show that the permeability of tumour blood vessels includes a dynamic phenomenon characterized by vascular bursts followed by brief vigorous outward flow of fluid (named ‘eruptions’) into the tumour interstitial space. We propose that ‘dynamic vents’ form transient openings and closings at these leaky blood vessels. These stochastic eruptions may explain the enhanced extravasation of nanoparticles from the tumour blood vessels, and offer insights into the underlying distribution patterns of an administered drug.

Quantitative super-resolution imaging of Bruchpilot distinguishes active zone states

NASA Astrophysics Data System (ADS)

Ehmann, Nadine; van de Linde, Sebastian; Alon, Amit; Ljaschenko, Dmitrij; Keung, Xi Zhen; Holm, Thorge; Rings, Annika; Diantonio, Aaron; Hallermann, Stefan; Ashery, Uri; Heckmann, Manfred; Sauer, Markus; Kittel, Robert J.

2014-08-01

The precise molecular architecture of synaptic active zones (AZs) gives rise to different structural and functional AZ states that fundamentally shape chemical neurotransmission. However, elucidating the nanoscopic protein arrangement at AZs is impeded by the diffraction-limited resolution of conventional light microscopy. Here we introduce new approaches to quantify endogenous protein organization at single-molecule resolution in situ with super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM). Focusing on the Drosophila neuromuscular junction (NMJ), we find that the AZ cytomatrix (CAZ) is composed of units containing ~137 Bruchpilot (Brp) proteins, three quarters of which are organized into about 15 heptameric clusters. We test for a quantitative relationship between CAZ ultrastructure and neurotransmitter release properties by engaging Drosophila mutants and electrophysiology. Our results indicate that the precise nanoscopic organization of Brp distinguishes different physiological AZ states and link functional diversification to a heretofore unrecognized neuronal gradient of the CAZ ultrastructure.

Modeling of dislocation channel width evolution in irradiated metals

NASA Astrophysics Data System (ADS)

Doyle, Peter J.; Benensky, Kelsa M.; Zinkle, Steven J.

2018-02-01

Defect-free dislocation channel formation has been reported to promote plastic instability during tensile testing via localized plastic flow, leading to a distinct loss of ductility and strain hardening in many low-temperature irradiated materials. In order to study the underlying mechanisms governing dislocation channel width and formation, the channel formation process is modeled via a simple stochastic dislocation-jog process dependent upon grain size, defect cluster density, and defect size. Dislocations traverse a field of defect clusters and jog stochastically upon defect interaction, forming channels of low defect-density. Based upon prior molecular dynamics (MD) simulations and in-situ experimental transmission electron microscopy (TEM) observations, each dislocation encounter with a dislocation loop or stacking fault tetrahedron (SFT) is assumed to cause complete absorption of the defect cluster, prompting the dislocation to jog up or down by a distance equal to half the defect cluster diameter. Channels are predicted to form rapidly and are comparable to reported TEM measurements for many materials. Predicted channel widths are found to be most strongly dependent on mean defect size and correlated well with a power law dependence on defect diameter and density, and distance from the dislocation source. Due to the dependence of modeled channel width on defect diameter and density, maximum channel width is predicted to slowly increase as accumulated dose increases. The relatively weak predicted dependence of channel formation width with distance, in accordance with a diffusion analogy, implies that after only a few microns from the source, most channels observed via TEM analyses may not appear to vary with distance because of limitations in the field-of-view to a few microns. Further, examinations of the effect of the so-called "source-broadening" mechanism of channel formation showed that its effect is simply to add a minimum thickness to the channel without affecting channel dependence on the given parameters.

Scanning tunneling spectroscopy under large current flow through the sample.

PubMed

Maldonado, A; Guillamón, I; Suderow, H; Vieira, S

2011-07-01

We describe a method to make scanning tunneling microscopy/spectroscopy imaging at very low temperatures while driving a constant electric current up to some tens of mA through the sample. It gives a new local probe, which we term current driven scanning tunneling microscopy/spectroscopy. We show spectroscopic and topographic measurements under the application of a current in superconducting Al and NbSe(2) at 100 mK. Perspective of applications of this local imaging method includes local vortex motion experiments, and Doppler shift local density of states studies.

Localization microscopy of DNA in situ using Vybrant(®) DyeCycle™ Violet fluorescent probe: A new approach to study nuclear nanostructure at single molecule resolution.

PubMed

Żurek-Biesiada, Dominika; Szczurek, Aleksander T; Prakash, Kirti; Mohana, Giriram K; Lee, Hyun-Keun; Roignant, Jean-Yves; Birk, Udo J; Dobrucki, Jurek W; Cremer, Christoph

2016-05-01

Higher order chromatin structure is not only required to compact and spatially arrange long chromatids within a nucleus, but have also important functional roles, including control of gene expression and DNA processing. However, studies of chromatin nanostructures cannot be performed using conventional widefield and confocal microscopy because of the limited optical resolution. Various methods of superresolution microscopy have been described to overcome this difficulty, like structured illumination and single molecule localization microscopy. We report here that the standard DNA dye Vybrant(®) DyeCycle™ Violet can be used to provide single molecule localization microscopy (SMLM) images of DNA in nuclei of fixed mammalian cells. This SMLM method enabled optical isolation and localization of large numbers of DNA-bound molecules, usually in excess of 10(6) signals in one cell nucleus. The technique yielded high-quality images of nuclear DNA density, revealing subdiffraction chromatin structures of the size in the order of 100nm; the interchromatin compartment was visualized at unprecedented optical resolution. The approach offers several advantages over previously described high resolution DNA imaging methods, including high specificity, an ability to record images using a single wavelength excitation, and a higher density of single molecule signals than reported in previous SMLM studies. The method is compatible with DNA/multicolor SMLM imaging which employs simple staining methods suited also for conventional optical microscopy. Copyright © 2016. Published by Elsevier Inc.

Quantifying the cellular uptake of semiconductor quantum dot nanoparticles by analytical electron microscopy.

PubMed

Hondow, Nicole; Brown, M Rowan; Starborg, Tobias; Monteith, Alexander G; Brydson, Rik; Summers, Huw D; Rees, Paul; Brown, Andy

2016-02-01

Semiconductor quantum dot nanoparticles are in demand as optical biomarkers yet the cellular uptake process is not fully understood; quantification of numbers and the fate of internalized particles are still to be achieved. We have focussed on the characterization of cellular uptake of quantum dots using a combination of analytical electron microscopies because of the spatial resolution available to examine uptake at the nanoparticle level, using both imaging to locate particles and spectroscopy to confirm identity. In this study, commercially available quantum dots, CdSe/ZnS core/shell particles coated in peptides to target cellular uptake by endocytosis, have been investigated in terms of the agglomeration state in typical cell culture media, the traverse of particle agglomerates across U-2 OS cell membranes during endocytosis, the merging of endosomal vesicles during incubation of cells and in the correlation of imaging flow cytometry and transmission electron microscopy to measure the final nanoparticle dose internalized by the U-2 OS cells. We show that a combination of analytical transmission electron microscopy and serial block face scanning electron microscopy can provide a comprehensive description of the internalization of an initial exposure dose of nanoparticles by an endocytically active cell population and how the internalized, membrane bound nanoparticle load is processed by the cells. We present a stochastic model of an endosome merging process and show that this provides a data-driven modelling framework for the prediction of cellular uptake of engineered nanoparticles in general. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

[application of the analytical transmission electron microscopy techniques for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in mammalian cells].

PubMed

Shebanova, A S; Bogdanov, A G; Ismagulova, T T; Feofanov, A V; Semenyuk, P I; Muronets, V I; Erokhina, M V; Onishchenko, G E; Kirpichnikov, M P; Shaitan, K V

2014-01-01

This work represents the results of the study on applicability of the modern methods of analytical transmission electron microscopy for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in A549 cell, human lung adenocarcinoma cell line. A comparative analysis of images of the nanoparticles in the cells obtained in the bright field mode of transmission electron microscopy, under dark-field scanning transmission electron microscopy and high-angle annular dark field scanning transmission electron was performed. For identification of nanoparticles in the cells the analytical techniques, energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy, were compared when used in the mode of obtaining energy spectrum from different particles and element mapping. It was shown that the method for electron tomography is applicable to confirm that nanoparticles are localized in the sample but not coated by contamination. The possibilities and fields of utilizing different techniques for analytical transmission electron microscopy for detection, visualization and identification of nanoparticles in the biological samples are discussed.

Heat, temperature and Clausius inequality in a model for active Brownian particles

PubMed Central

Marconi, Umberto Marini Bettolo; Puglisi, Andrea; Maggi, Claudio

2017-01-01

Methods of stochastic thermodynamics and hydrodynamics are applied to a recently introduced model of active particles. The model consists of an overdamped particle subject to Gaussian coloured noise. Inspired by stochastic thermodynamics, we derive from the system’s Fokker-Planck equation the average exchanges of heat and work with the active bath and the associated entropy production. We show that a Clausius inequality holds, with the local (non-uniform) temperature of the active bath replacing the uniform temperature usually encountered in equilibrium systems. Furthermore, by restricting the dynamical space to the first velocity moments of the local distribution function we derive a hydrodynamic description where local pressure, kinetic temperature and internal heat fluxes appear and are consistent with the previous thermodynamic analysis. The procedure also shows under which conditions one obtains the unified coloured noise approximation (UCNA): such an approximation neglects the fast relaxation to the active bath and therefore yields detailed balance and zero entropy production. In the last part, by using multiple time-scale analysis, we provide a constructive method (alternative to UCNA) to determine the solution of the Kramers equation and go beyond the detailed balance condition determining negative entropy production. PMID:28429787

Heat, temperature and Clausius inequality in a model for active Brownian particles.

PubMed

Marconi, Umberto Marini Bettolo; Puglisi, Andrea; Maggi, Claudio

2017-04-21

Methods of stochastic thermodynamics and hydrodynamics are applied to a recently introduced model of active particles. The model consists of an overdamped particle subject to Gaussian coloured noise. Inspired by stochastic thermodynamics, we derive from the system's Fokker-Planck equation the average exchanges of heat and work with the active bath and the associated entropy production. We show that a Clausius inequality holds, with the local (non-uniform) temperature of the active bath replacing the uniform temperature usually encountered in equilibrium systems. Furthermore, by restricting the dynamical space to the first velocity moments of the local distribution function we derive a hydrodynamic description where local pressure, kinetic temperature and internal heat fluxes appear and are consistent with the previous thermodynamic analysis. The procedure also shows under which conditions one obtains the unified coloured noise approximation (UCNA): such an approximation neglects the fast relaxation to the active bath and therefore yields detailed balance and zero entropy production. In the last part, by using multiple time-scale analysis, we provide a constructive method (alternative to UCNA) to determine the solution of the Kramers equation and go beyond the detailed balance condition determining negative entropy production.

Invasive advance of an advantageous mutation: nucleation theory.

PubMed

O'Malley, Lauren; Basham, James; Yasi, Joseph A; Korniss, G; Allstadt, Andrew; Caraco, Thomas

2006-12-01

For sedentary organisms with localized reproduction, spatially clustered growth drives the invasive advance of a favorable mutation. We model competition between two alleles where recurrent mutation introduces a genotype with a rate of local propagation exceeding the resident's rate. We capture ecologically important properties of the rare invader's stochastic dynamics by assuming discrete individuals and local neighborhood interactions. To understand how individual-level processes may govern population patterns, we invoke the physical theory for nucleation of spatial systems. Nucleation theory discriminates between single-cluster and multi-cluster dynamics. A sufficiently low mutation rate, or a sufficiently small environment, generates single-cluster dynamics, an inherently stochastic process; a favorable mutation advances only if the invader cluster reaches a critical radius. For this mode of invasion, we identify the probability distribution of waiting times until the favored allele advances to competitive dominance, and we ask how the critical cluster size varies as propagation or mortality rates vary. Increasing the mutation rate or system size generates multi-cluster invasion, where spatial averaging produces nearly deterministic global dynamics. For this process, an analytical approximation from nucleation theory, called Avrami's Law, describes the time-dependent behavior of the genotype densities with remarkable accuracy.

Obtaining a W state from a Greenberger-Horne-Zeilinger state via stochastic local operations and classical communication with a rate approaching unity.

PubMed

Yu, Nengkun; Guo, Cheng; Duan, Runyao

2014-04-25

We introduce a notion of the entanglement transformation rate to characterize the asymptotic comparability of two multipartite pure entangled states under stochastic local operations and classical communication (SLOCC). For two well known SLOCC inequivalent three-qubit states |GHZ⟩=(1/2)(|000⟩+|111⟩) and |W⟩=(1/3)(|100⟩+|010⟩+|001⟩), we show that the entanglement transformation rate from |GHZ⟩ to |W⟩ is exactly 1. That means that we can obtain one copy of the W state from one copy of the Greenberg-Horne-Zeilinger (GHZ) state by SLOCC, asymptotically. We then apply similar techniques to obtain a lower bound on the entanglement transformation rates from an N-partite GHZ state to a class of Dicke states, and prove the tightness of this bound for some special cases which naturally generalize the |W⟩ state. A new lower bound on the tensor rank of the matrix permanent is also obtained by evaluating the tensor rank of Dicke states.

Debates—Stochastic subsurface hydrology from theory to practice: A geologic perspective

NASA Astrophysics Data System (ADS)

Fogg, Graham E.; Zhang, Yong

2016-12-01

A geologic perspective on stochastic subsurface hydrology offers insights on representativeness of prominent field experiments and their general relevance to other hydrogeologic settings. Although the gains in understanding afforded by some 30 years of research in stochastic hydrogeology have been important and even essential, adoption of the technologies and insights by practitioners has been limited, due in part to a lack of geologic context in both the field and theoretical studies. In general, unintentional, biased sampling of hydraulic conductivity (K) using mainly hydrologic, well-based methods has resulted in the tacit assumption by many in the community that the subsurface is much less heterogeneous than in reality. Origins of the bias range from perspectives that are limited by scale and the separation of disciplines (geology, soils, aquifer hydrology, groundwater hydraulics, etc.). Consequences include a misfit between stochastic hydrogeology research results and the needs of, for example, practitioners who are dealing with local plume site cleanup that is often severely hampered by very low velocities in the very aquitard facies that are commonly overlooked or missing from low-variance stochastic models or theories. We suggest that answers to many of the problems exposed by stochastic hydrogeology research can be found through greater geologic integration into the analyses, including the recognition of not only the nearly ubiquitously high variances of K but also the strong tendency for the good connectivity of the high-K facies when spatially persistent geologic unconformities are absent. We further suggest that although such integration may appear to make the contaminant transport problem more complex, expensive and intractable, it may in fact lead to greater simplification and more reliable, less expensive site characterizations and models.

A Stochastic Kinematic Model of Class Averaging in Single-Particle Electron Microscopy

PubMed Central

Park, Wooram; Midgett, Charles R.; Madden, Dean R.; Chirikjian, Gregory S.

2011-01-01

Single-particle electron microscopy is an experimental technique that is used to determine the 3D structure of biological macromolecules and the complexes that they form. In general, image processing techniques and reconstruction algorithms are applied to micrographs, which are two-dimensional (2D) images taken by electron microscopes. Each of these planar images can be thought of as a projection of the macromolecular structure of interest from an a priori unknown direction. A class is defined as a collection of projection images with a high degree of similarity, presumably resulting from taking projections along similar directions. In practice, micrographs are very noisy and those in each class are aligned and averaged in order to reduce the background noise. Errors in the alignment process are inevitable due to noise in the electron micrographs. This error results in blurry averaged images. In this paper, we investigate how blurring parameters are related to the properties of the background noise in the case when the alignment is achieved by matching the mass centers and the principal axes of the experimental images. We observe that the background noise in micrographs can be treated as Gaussian. Using the mean and variance of the background Gaussian noise, we derive equations for the mean and variance of translational and rotational misalignments in the class averaging process. This defines a Gaussian probability density on the Euclidean motion group of the plane. Our formulation is validated by convolving the derived blurring function representing the stochasticity of the image alignments with the underlying noiseless projection and comparing with the original blurry image. PMID:21660125

A Two-Step Method to Select Major Surge-Producing Extratropical Cyclones from a 10,000-Year Stochastic Catalog

NASA Astrophysics Data System (ADS)

Keshtpoor, M.; Carnacina, I.; Yablonsky, R. M.

2016-12-01

Extratropical cyclones (ETCs) are the primary driver of storm surge events along the UK and northwest mainland Europe coastlines. In an effort to evaluate the storm surge risk in coastal communities in this region, a stochastic catalog is developed by perturbing the historical storm seeds of European ETCs to account for 10,000 years of possible ETCs. Numerical simulation of the storm surge generated by the full 10,000-year stochastic catalog, however, is computationally expensive and may take several months to complete with available computational resources. A new statistical regression model is developed to select the major surge-generating events from the stochastic ETC catalog. This regression model is based on the maximum storm surge, obtained via numerical simulations using a calibrated version of the Delft3D-FM hydrodynamic model with a relatively coarse mesh, of 1750 historical ETC events that occurred over the past 38 years in Europe. These numerically-simulated surge values were regressed to the local sea level pressure and the U and V components of the wind field at the location of 196 tide gauge stations near the UK and northwest mainland Europe coastal areas. The regression model suggests that storm surge values in the area of interest are highly correlated to the U- and V-component of wind speed, as well as the sea level pressure. Based on these correlations, the regression model was then used to select surge-generating storms from the 10,000-year stochastic catalog. Results suggest that roughly 105,000 events out of 480,000 stochastic storms are surge-generating events and need to be considered for numerical simulation using a hydrodynamic model. The selected stochastic storms were then simulated in Delft3D-FM, and the final refinement of the storm population was performed based on return period analysis of the 1750 historical event simulations at each of the 196 tide gauges in preparation for Delft3D-FM fine mesh simulations.

Super-resolution chemical imaging with dynamic placement of plasmonic hotspots

NASA Astrophysics Data System (ADS)

Olson, Aeli P.; Ertsgaard, Christopher T.; McKoskey, Rachel M.; Rich, Isabel S.; Lindquist, Nathan C.

2015-08-01

We demonstrate dynamic placement of plasmonic "hotspots" for super-resolution chemical imaging via Surface Enhanced Raman Spectroscopy (SERS). A silver nanohole array surface was coated with biological samples and illuminated with a laser. Due to the large plasmonic field enhancements, blinking behavior of the SERS hotspots was observed and processed using a Stochastic Optical Reconstruction Microscopy (STORM) algorithm enabling localization to within 10 nm. However, illumination of the sample with a single static laser beam (i.e., a slightly defocused Gaussian beam) only produced SERS hotspots in fixed locations on the surface, leaving noticeable gaps in any final image. But, by using a spatial light modulator (SLM), the illumination profile of the beam could be altered, shifting any hotspots across the nanohole array surface in sub-wavelength steps. Therefore, by properly structuring an illuminating light field with the SLM, we show the possibility of positioning plasmonic hotspots over a metallic nanohole surface on-the-fly. Using this and our SERS-STORM imaging technique, we show potential for high-resolution chemical imaging without the noticeable gaps that were present with static laser illumination. Interestingly, even illuminating the surface with randomly shifting SLM phase profiles was sufficient to completely fill in a wide field of view for super-resolution SERS imaging of a single strand of 100-nm thick collagen protein fibrils. Images were then compared to those obtained with a scanning electron microscope (SEM). Additionally, we explored alternative methods of phase shifting other than holographic illumination through the SLM to create localization of hotspots necessary for SERS-STORM imaging.

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi

2014-01-01

In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

Next-generation endomyocardial biopsy: the potential of confocal and super-resolution microscopy.

PubMed

Crossman, David J; Ruygrok, Peter N; Hou, Yu Feng; Soeller, Christian

2015-03-01

Confocal laser scanning microscopy and super-resolution microscopy provide high-contrast and high-resolution fluorescent imaging, which has great potential to increase the diagnostic yield of endomyocardial biopsy (EMB). EMB is currently the gold standard for identification of cardiac allograft rejection, myocarditis, and infiltrative and storage diseases. However, standard analysis is dominated by low-contrast bright-field light and electron microscopy (EM); this lack of contrast makes quantification of pathological features difficult. For example, assessment of cardiac allograft rejection relies on subjective grading of H&E histology, which may lead to diagnostic variability between pathologists. This issue could be solved by utilising the high contrast provided by fluorescence methods such as confocal to quantitatively assess the degree of lymphocytic infiltrate. For infiltrative diseases such as amyloidosis, the nanometre resolution provided by EM can be diagnostic in identifying disease-causing fibrils. The recent advent of super-resolution imaging, particularly direct stochastic optical reconstruction microscopy (dSTORM), provides high-contrast imaging at resolution approaching that of EM. Moreover, dSTORM utilises conventional fluorescence dyes allowing for the same structures to be routinely imaged at the cellular scale and then at the nanoscale. The key benefit of these technologies is that the high contrast facilitates quantitative digital analysis and thereby provides a means to robustly assess critical pathological features. Ultimately, this technology has the ability to provide greater accuracy and precision to EMB assessment, which could result in better outcomes for patients.

Accounting for Limited Detection Efficiency and Localization Precision in Cluster Analysis in Single Molecule Localization Microscopy

PubMed Central

Shivanandan, Arun; Unnikrishnan, Jayakrishnan; Radenovic, Aleksandra

2015-01-01

Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques’ inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10 – 30nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley’s L(r) – r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization. PMID:25794150

Immunoelectron Microscopy of Cryofixed and Freeze-Substituted Plant Tissues.

PubMed

Takeuchi, Miyuki; Takabe, Keiji; Mineyuki, Yoshinobu

2016-01-01

Cryofixation and freeze-substitution techniques provide excellent preservation of plant ultrastructure. The advantage of cryofixation is not only in structural preservation, as seen in the smooth plasma membrane, but also in the speed in arresting cell activity. Immunoelectron microscopy reveals the subcellular localization of molecules within cells. Immunolabeling in combination with cryofixation and freeze-substitution techniques provides more detailed information on the immunoelectron-microscopic localization of molecules in the plant cell than can be obtained from chemically fixed tissues. Here, we introduce methods for immunoelectron microscopy of cryofixed and freeze-substituted plant tissues.

Estimation of Kubo number and correlation length of fluctuating magnetic fields and pressure in BOUT + + edge pedestal collapse simulation

NASA Astrophysics Data System (ADS)

Kim, Jaewook; Lee, W.-J.; Jhang, Hogun; Kaang, H. H.; Ghim, Y.-C.

2017-10-01

Stochastic magnetic fields are thought to be as one of the possible mechanisms for anomalous transport of density, momentum and heat across the magnetic field lines. Kubo number and Chirikov parameter are quantifications of the stochasticity, and previous studies show that perpendicular transport strongly depends on the magnetic Kubo number (MKN). If MKN is smaller than one, diffusion process will follow Rechester-Rosenbluth model; whereas if it is larger than one, percolation theory dominates the diffusion process. Thus, estimation of Kubo number plays an important role to understand diffusion process caused by stochastic magnetic fields. However, spatially localized experimental measurement of fluctuating magnetic fields in a tokamak is difficult, and we attempt to estimate MKNs using BOUT + + simulation data with pedestal collapse. In addition, we calculate correlation length of fluctuating pressures and Chirikov parameters to investigate variation correlation lengths in the simulation. We, then, discuss how one may experimentally estimate MKNs.

Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks.

PubMed

Gomez, Christophe; Hartung, Niklas

2018-01-01

Although the detection of metastases radically changes prognosis of and treatment decisions for a cancer patient, clinically undetectable micrometastases hamper a consistent classification into localized or metastatic disease. This chapter discusses mathematical modeling efforts that could help to estimate the metastatic risk in such a situation. We focus on two approaches: (1) a stochastic framework describing metastatic emission events at random times, formalized via Poisson processes, and (2) a deterministic framework describing the micrometastatic state through a size-structured density function in a partial differential equation model. Three aspects are addressed in this chapter. First, a motivation for the Poisson process framework is presented and modeling hypotheses and mechanisms are introduced. Second, we extend the Poisson model to account for secondary metastatic emission. Third, we highlight an inherent crosslink between the stochastic and deterministic frameworks and discuss its implications. For increased accessibility the chapter is split into an informal presentation of the results using a minimum of mathematical formalism and a rigorous mathematical treatment for more theoretically interested readers.

Natural Erosion of Sandstone as Shape Optimisation.

PubMed

Ostanin, Igor; Safonov, Alexander; Oseledets, Ivan

2017-12-11

Natural arches, pillars and other exotic sandstone formations have always been attracting attention for their unusual shapes and amazing mechanical balance that leave a strong impression of intelligent design rather than the result of a stochastic process. It has been recently demonstrated that these shapes could have been the result of the negative feedback between stress and erosion that originates in fundamental laws of friction between the rock's constituent particles. Here we present a deeper analysis of this idea and bridge it with the approaches utilized in shape and topology optimisation. It appears that the processes of natural erosion, driven by stochastic surface forces and Mohr-Coulomb law of dry friction, can be viewed within the framework of local optimisation for minimum elastic strain energy. Our hypothesis is confirmed by numerical simulations of the erosion using the topological-shape optimisation model. Our work contributes to a better understanding of stochastic erosion and feasible landscape formations that could be found on Earth and beyond.

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

NASA Astrophysics Data System (ADS)

Romanczuk, P.; Bär, M.; Ebeling, W.; Lindner, B.; Schimansky-Geier, L.

2012-03-01

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.

Assessment and visualization of uncertainty for countrywide soil organic matter map of Hungary using local entropy

NASA Astrophysics Data System (ADS)

Szatmári, Gábor; Pásztor, László

2016-04-01

Uncertainty is a general term expressing our imperfect knowledge in describing an environmental process and we are aware of it (Bárdossy and Fodor, 2004). Sampling, laboratory measurements, models and so on are subject to uncertainty. Effective quantification and visualization of uncertainty would be indispensable to stakeholders (e.g. policy makers, society). Soil related features and their spatial models should be stressfully targeted to uncertainty assessment because their inferences are further used in modelling and decision making process. The aim of our present study was to assess and effectively visualize the local uncertainty of the countrywide soil organic matter (SOM) spatial distribution model of Hungary using geostatistical tools and concepts. The Hungarian Soil Information and Monitoring System's SOM data (approximately 1,200 observations) and environmental related, spatially exhaustive secondary information (i.e. digital elevation model, climatic maps, MODIS satellite images and geological map) were used to model the countrywide SOM spatial distribution by regression kriging. It would be common to use the calculated estimation (or kriging) variance as a measure of uncertainty, however the normality and homoscedasticity hypotheses have to be refused according to our preliminary analysis on the data. Therefore, a normal score transformation and a sequential stochastic simulation approach was introduced to be able to model and assess the local uncertainty. Five hundred equally probable realizations (i.e. stochastic images) were generated. The number of the stochastic images is fairly enough to provide a model of uncertainty at each location, which is a complete description of uncertainty in geostatistics (Deutsch and Journel, 1998). Furthermore, these models can be applied e.g. to contour the probability of any events, which can be regarded as goal oriented digital soil maps and are of interest for agricultural management and decision making as well. A standardized measure of the local entropy was used to visualize uncertainty, where entropy values close to 1 correspond to high uncertainty, whilst values close to 0 correspond low uncertainty. The advantage of the usage of local entropy in this context is that it combines probabilities from multiple members into a single number for each location of the model. In conclusion, it is straightforward to use a sequential stochastic simulation approach to the assessment of uncertainty, when normality and homoscedasticity are violated. The visualization of uncertainty using the local entropy is effective and communicative to stakeholders because it represents the uncertainty through a single number within a [0, 1] scale. References: Bárdossy, Gy. & Fodor, J., 2004. Evaluation of Uncertainties and Risks in Geology. Springer-Verlag, Berlin Heidelberg. Deutsch, C.V. & Journel, A.G., 1998. GSLIB: geostatistical software library and user's guide. Oxford University Press, New York. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

The origin of life is a spatially localized stochastic transition

PubMed Central

2012-01-01

Background Life depends on biopolymer sequences as catalysts and as genetic material. A key step in the Origin of Life is the emergence of an autocatalytic system of biopolymers. Here we study computational models that address the way a living autocatalytic system could have emerged from a non-living chemical system, as envisaged in the RNA World hypothesis. Results We consider (i) a chemical reaction system describing RNA polymerization, and (ii) a simple model of catalytic replicators that we call the Two’s Company model. Both systems have two stable states: a non-living state, characterized by a slow spontaneous rate of RNA synthesis, and a living state, characterized by rapid autocatalytic RNA synthesis. The origin of life is a transition between these two stable states. The transition is driven by stochastic concentration fluctuations involving relatively small numbers of molecules in a localized region of space. These models are simulated on a two-dimensional lattice in which reactions occur locally on single sites and diffusion occurs by hopping of molecules to neighbouring sites. Conclusions If diffusion is very rapid, the system is well-mixed. The transition to life becomes increasingly difficult as the lattice size is increased because the concentration fluctuations that drive the transition become relatively smaller when larger numbers of molecules are involved. In contrast, when diffusion occurs at a finite rate, concentration fluctuations are local. The transition to life occurs in one local region and then spreads across the rest of the surface. The transition becomes easier with larger lattice sizes because there are more independent regions in which it could occur. The key observations that apply to our models and to the real world are that the origin of life is a rare stochastic event that is localized in one region of space due to the limited rate of diffusion of the molecules involved and that the subsequent spread across the surface is deterministic. It is likely that the time required for the deterministic spread is much shorter than the waiting time for the origin, in which case life evolves only once on a planet, and then rapidly occupies the whole surface. Reviewers Reviewed by Omer Markovitch (nominated by Doron Lancet), Claus Wilke, and Nobuto Takeuchi (nominated by Eugene Koonin). PMID:23176307

Localization of latency-associated nuclear antigen (LANA) on mitotic chromosomes

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

Rahayu, Retno; Ohsaki, Eriko; Omori, Hiroko

In latent infection of Kaposi's sarcoma-associated herpesvirus (KSHV), viral gene expression is extremely limited and copy numbers of viral genomes remain constant. Latency-associated nuclear antigen (LANA) is known to have a role in maintaining viral genome copy numbers in growing cells. Several studies have shown that LANA is localized in particular regions on mitotic chromosomes, such as centromeres/pericentromeres. We independently examined the distinct localization of LANA on mitotic chromosomes during mitosis, using super-resolution laser confocal microscopy and correlative fluorescence microscopy–electron microscopy (FM-EM) analyses. We found that the majority of LANA were not localized at particular regions such as telomeres/peritelomeres, centromeres/pericentromeres,more » and cohesion sites, but at the bodies of condensed chromosomes. Thus, LANA may undergo various interactions with the host factors on the condensed chromosomes in order to tether the viral genome to mitotic chromosomes and realize faithful viral genome segregation during cell division. - Highlights: • This is the first report showing LANA dots on mitotic chromosomes by fluorescent microscopy followed by electron microscopy. • LANA dots localized randomly on condensed chromosomes other than centromere/pericentromere and telomere/peritelomre. • Cellular mitotic checkpoint should not be always involved in the segregation of KSHV genomes in the latency.« less

On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models.

PubMed

Kuritz, K; Stöhr, D; Pollak, N; Allgöwer, F

2017-02-07

Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional "snapshot" data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantification of DNA-associated proteins inside eukaryotic cells using single-molecule localization microscopy

PubMed Central

Etheridge, Thomas J.; Boulineau, Rémi L.; Herbert, Alex; Watson, Adam T.; Daigaku, Yasukazu; Tucker, Jem; George, Sophie; Jönsson, Peter; Palayret, Matthieu; Lando, David; Laue, Ernest; Osborne, Mark A.; Klenerman, David; Lee, Steven F.; Carr, Antony M.

2014-01-01

Development of single-molecule localization microscopy techniques has allowed nanometre scale localization accuracy inside cells, permitting the resolution of ultra-fine cell structure and the elucidation of crucial molecular mechanisms. Application of these methodologies to understanding processes underlying DNA replication and repair has been limited to defined in vitro biochemical analysis and prokaryotic cells. In order to expand these techniques to eukaryotic systems, we have further developed a photo-activated localization microscopy-based method to directly visualize DNA-associated proteins in unfixed eukaryotic cells. We demonstrate that motion blurring of fluorescence due to protein diffusivity can be used to selectively image the DNA-bound population of proteins. We designed and tested a simple methodology and show that it can be used to detect changes in DNA binding of a replicative helicase subunit, Mcm4, and the replication sliding clamp, PCNA, between different stages of the cell cycle and between distinct genetic backgrounds. PMID:25106872

Nitrotyrosine localization to dermal nerves in borderline leprosy.

PubMed

Schön, T; Hernández-Pando, R; Baquera-Heredia, J; Negesse, Y; Becerril-Villanueva, L E; Eon-Contreras, J C L; Sundqvist, T; Britton, S

2004-03-01

Nerve damage is a common and disabling feature of leprosy, with unclear aetiology. It has been reported that the peroxidizing agents of myelin lipids-nitric oxide (NO) and peroxynitrite-are produced in leprosy skin lesions. To investigate the localization of nitrotyrosine (NT)-a local end-product of peroxynitrite-in leprosy lesions where dermal nerves are affected by a granulomatous reaction. We investigated by immunohistochemistry and immunoelectron microscopy the localization of the inducible NO synthase (iNOS) and NT in biopsies exhibiting dermal nerves from patients with untreated leprosy. There were abundant NT-positive and iNOS-positive macrophages in the borderline leprosy granulomas infiltrating peripheral nerves identified by light microscopy, S-100 and neurofilament immunostaining. Immunoelectron microscopy showed NT reactivity in neurofilament aggregates and in the cell wall of Mycobacterium leprae. Our results suggest that NO and peroxynitrite could be involved in the nerve damage following borderline leprosy.

Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

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

Marzouk, Youssef M.; Coles, T.; Spantini, A.

2013-09-30

The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local andmore » long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.« less

Hypoxic HepG2 cell adaptation decreases ATP synthase dimers and ATP production in inflated cristae by mitofilin down-regulation concomitant to MICOS clustering.

PubMed

Plecitá-Hlavatá, Lydie; Engstová, Hana; Alán, Lukáš; Špaček, Tomáš; Dlasková, Andrea; Smolková, Katarína; Špačková, Jitka; Tauber, Jan; Strádalová, Vendula; Malínský, Jan; Lessard, Mark; Bewersdorf, Joerg; Ježek, Petr

2016-05-01

The relationship of the inner mitochondrial membrane (IMM) cristae structure and intracristal space (ICS) to oxidative phosphorylation (oxphos) is not well understood. Mitofilin (subunit Mic60) of the mitochondrial contact site and cristae organizing system (MICOS) IMM complex is attached to the outer membrane (OMM) via the sorting and assembly machinery/topogenesis of mitochondrial outer membrane β-barrel proteins (SAM/TOB) complex and controls the shape of the cristae. ATP synthase dimers determine sharp cristae edges, whereas trimeric OPA1 tightens ICS outlets. Metabolism is altered during hypoxia, and we therefore studied cristae morphology in HepG2 cells adapted to 5% oxygen for 72 h. Three dimensional (3D), super-resolution biplane fluorescence photoactivation localization microscopy with Eos-conjugated, ICS-located lactamase-β indicated hypoxic ICS expansion with an unchanged OMM (visualized by Eos-mitochondrial fission protein-1). 3D direct stochastic optical reconstruction microscopy immunocytochemistry revealed foci of clustered mitofilin (but not MICOS subunit Mic19) in contrast to its even normoxic distribution. Mitofilin mRNA and protein decreased by ∼20%. ATP synthase dimers vs monomers and state-3/state-4 respiration ratios were lower during hypoxia. Electron microscopy confirmed ICS expansion (maximum in glycolytic cells), which was absent in reduced or OMM-detached cristae of OPA1- and mitofilin-silenced cells, respectively. Hypoxic adaptation is reported as rounding sharp cristae edges and expanding cristae width (ICS) by partial mitofilin/Mic60 down-regulation. Mitofilin-depleted MICOS detaches from SAM while remaining MICOS with mitofilin redistributes toward higher interdistances. This phenomenon causes partial oxphos dormancy in glycolytic cells via disruption of ATP synthase dimers.-Plecitá-Hlavatá, L., Engstová, H., Alán, L., Špaček, T., Dlasková, A., Smolková, K., Špačková, J., Tauber, J., Strádalová, V., Malínský, J., Lessard, M., Bewersdorf, J., Ježek, P. Hypoxic HepG2 cell adaptation decreases ATP synthase dimers and ATP production in inflated cristae by mitofilin down-regulation concomitant to MICOS clustering. © FASEB.

Local and Regional Determinants of an Uncommon Functional Group in Freshwater Lakes and Ponds

PubMed Central

McCann, Michael James

2015-01-01

A combination of local and regional factors and stochastic forces is expected to determine the occurrence of species and the structure of communities. However, in most cases, our understanding is incomplete, with large amounts of unexplained variation. Using functional groups rather than individual species may help explain the relationship between community composition and conditions. In this study, I used survey data from freshwater lakes and ponds to understand factors that determine the presence of the floating plant functional group in the northeast United States. Of the 176 water bodies surveyed, 104 (59.1%) did not contain any floating plant species. The occurrence of this functional group was largely determined by local abiotic conditions, which were spatially autocorrelated across the region. A model predicting the presence of the floating plant functional group performed similarly to the best species-specific models. Using a permutation test, I also found that the observed prevalence of floating plants is no different than expected by random assembly from a species pool of its size. These results suggest that the size of the species pool interacts with local conditions in determining the presence of a functional group. Nevertheless, a large amount of unexplained variation remains, attributable to either stochastic species occurrence or incomplete predictive models. The simple permutation approach in this study can be extended to test alternative models of community assembly. PMID:26121636

Polarization sensitive localization based super-resolution microscopy with a birefringent wedge

NASA Astrophysics Data System (ADS)

Sinkó, József; Gajdos, Tamás; Czvik, Elvira; Szabó, Gábor; Erdélyi, Miklós

2017-03-01

A practical method has been presented for polarization sensitive localization based super-resolution microscopy using a birefringent dual wedge. The measurement of the polarization degree at the single molecule level can reveal the chemical and physical properties of the local environment of the fluorescent dye molecule and can hence provide information about the sub-diffraction sized structure of biological samples. Polarization sensitive STORM imaging of the F-Actins proved correlation between the orientation of fluorescent dipoles and the axis of the fibril.

Photometry unlocks 3D information from 2D localization microscopy data.

PubMed

Franke, Christian; Sauer, Markus; van de Linde, Sebastian

2017-01-01

We developed a straightforward photometric method, temporal, radial-aperture-based intensity estimation (TRABI), that allows users to extract 3D information from existing 2D localization microscopy data. TRABI uses the accurate determination of photon numbers in different regions of the emission pattern of single emitters to generate a z-dependent photometric parameter. This method can determine fluorophore positions up to 600 nm from the focal plane and can be combined with biplane detection to further improve axial localization.

Mesoscopic description of random walks on combs

NASA Astrophysics Data System (ADS)

Méndez, Vicenç; Iomin, Alexander; Campos, Daniel; Horsthemke, Werner

2015-12-01

Combs are a simple caricature of various types of natural branched structures, which belong to the category of loopless graphs and consist of a backbone and branches. We study continuous time random walks on combs and present a generic method to obtain their transport properties. The random walk along the branches may be biased, and we account for the effect of the branches by renormalizing the waiting time probability distribution function for the motion along the backbone. We analyze the overall diffusion properties along the backbone and find normal diffusion, anomalous diffusion, and stochastic localization (diffusion failure), respectively, depending on the characteristics of the continuous time random walk along the branches, and compare our analytical results with stochastic simulations.

Perturbation of nuclear architecture by long-distance chromosome interactions.

PubMed

Dernburg, A F; Broman, K W; Fung, J C; Marshall, W F; Philips, J; Agard, D A; Sedat, J W

1996-05-31

Position-effect variegation (PEV) describes the stochastic transcriptional silencing of a gene positioned adjacent to heterochromatin. Using FISH, we have tested whether variegated expression of the eye-color gene brown in Drosophila is influenced by its nuclear localization. In embryonic nuclei, a heterochromatic insertion at the brown locus is always spatially isolated from other heterochromatin. However, during larval development this insertion physically associates with other heterochromatic regions on the same chromosome in a stochastic manner. These observations indicate that the brown gene is silenced by specific contact with centromeric heterochromatin. Moreover, they provide direct evidence for long-range chromosome interactions and their impact on three-dimensional nuclear architecture, while providing a cohesive explanation for the phenomenon of PEV.

Stochastic Formalism for Thermally Driven Distribution Frontier: A Nonempirical Approach to the Potential Escape Problem

NASA Astrophysics Data System (ADS)

Akashi, Ryosuke; Nagornov, Yuri S.

2018-06-01

We develop a non-empirical scheme to search for the minimum-energy escape paths from the minima of the potential surface to unknown saddle points nearby. A stochastic algorithm is constructed to move the walkers up the surface through the potential valleys. This method employs only the local gradient and diagonal part of the Hessian matrix of the potential. An application to a two-dimensional model potential is presented to demonstrate the successful finding of the paths to the saddle points. The present scheme could serve as a starting point toward first-principles simulation of rare events across the potential basins free from empirical collective variables.

Global sensitivity analysis in stochastic simulators of uncertain reaction networks.

PubMed

Navarro Jimenez, M; Le Maître, O P; Knio, O M

2016-12-28

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

A Learning Framework for Winner-Take-All Networks with Stochastic Synapses.

PubMed

Mostafa, Hesham; Cauwenberghs, Gert

2018-06-01

Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex distribution of the data. This raises the question of whether biological networks operate along similar principles to implement a probabilistic model of the environment through transformations of intrinsic noise processes. The intrinsic neural and synaptic noise processes in biological networks, however, are quite different from the noise processes used in current abstract generative networks. This, together with the discrete nature of spikes and local circuit interactions among the neurons, raises several difficulties when using recent generative modeling frameworks to train biologically motivated models. In this letter, we show that a biologically motivated model based on multilayer winner-take-all circuits and stochastic synapses admits an approximate analytical description. This allows us to use the proposed networks in a variational learning setting where stochastic backpropagation is used to optimize a lower bound on the data log likelihood, thereby learning a generative model of the data. We illustrate the generality of the proposed networks and learning technique by using them in a structured output prediction task and a semisupervised learning task. Our results extend the domain of application of modern stochastic network architectures to networks where synaptic transmission failure is the principal noise mechanism.

Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array

NASA Astrophysics Data System (ADS)

Wu, Xiaohua; Hu, Xiaosong; Moura, Scott; Yin, Xiaofeng; Pickert, Volker

2016-11-01

Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements, and accommodating the variability of solar power. First, the random-variable models are developed, including Markov Chain model of PEV mobility, as well as predictive models of home power demand and PV power supply. Second, a stochastic optimal control problem is mathematically formulated for managing the power flow among energy sources in the smart home. Finally, based on time-varying electricity price, we systematically examine the performance of the proposed control strategy. As a result, the electric cost is 493.6% less for a Tesla Model S with optimal stochastic dynamic programming (SDP) control relative to the no optimal control case, and it is by 175.89% for a Nissan Leaf.

Comparative analysis of the effectiveness of three immunization strategies in controlling disease outbreaks in realistic social networks.

PubMed

Xu, Zhijing; Zu, Zhenghu; Zheng, Tao; Zhang, Wendou; Xu, Qing; Liu, Jinjie

2014-01-01

The high incidence of emerging infectious diseases has highlighted the importance of effective immunization strategies, especially the stochastic algorithms based on local available network information. Present stochastic strategies are mainly evaluated based on classical network models, such as scale-free networks and small-world networks, and thus are insufficient. Three frequently referred stochastic immunization strategies-acquaintance immunization, community-bridge immunization, and ring vaccination-were analyzed in this work. The optimal immunization ratios for acquaintance immunization and community-bridge immunization strategies were investigated, and the effectiveness of these three strategies in controlling the spreading of epidemics were analyzed based on realistic social contact networks. The results show all the strategies have decreased the coverage of the epidemics compared to baseline scenario (no control measures). However the effectiveness of acquaintance immunization and community-bridge immunization are very limited, with acquaintance immunization slightly outperforming community-bridge immunization. Ring vaccination significantly outperforms acquaintance immunization and community-bridge immunization, and the sensitivity analysis shows it could be applied to controlling the epidemics with a wide infectivity spectrum. The effectiveness of several classical stochastic immunization strategies was evaluated based on realistic contact networks for the first time in this study. These results could have important significance for epidemic control research and practice.

Effects of deterministic and random refuge in a prey-predator model with parasite infection.

PubMed

Mukhopadhyay, B; Bhattacharyya, R

2012-09-01

Most natural ecosystem populations suffer from various infectious diseases and the resulting host-pathogen dynamics is dependent on host's characteristics. On the other hand, empirical evidences show that for most host pathogen systems, a part of the host population always forms a refuge. To study the role of refuge on the host-pathogen interaction, we study a predator-prey-pathogen model where the susceptible and the infected prey can undergo refugia of constant size to evade predator attack. The stability aspects of the model system is investigated from a local and global perspective. The study reveals that the refuge sizes for the susceptible and the infected prey are the key parameters that control possible predator extinction as well as species co-existence. Next we perform a global study of the model system using Lyapunov functions and show the existence of a global attractor. Finally we perform a stochastic extension of the basic model to study the phenomenon of random refuge arising from various intrinsic, habitat-related and environmental factors. The stochastic model is analyzed for exponential mean square stability. Numerical study of the stochastic model shows that increasing the refuge rates has a stabilizing effect on the stochastic dynamics. Copyright © 2012 Elsevier Inc. All rights reserved.

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

DOE PAGES

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-23

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes thatmore » the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.« less

Modelling Evolutionary Algorithms with Stochastic Differential Equations.

PubMed

Heredia, Jorge Pérez

2017-11-20

There has been renewed interest in modelling the behaviour of evolutionary algorithms (EAs) by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogues of the additive and multiplicative drift theorems from runtime analysis. In addition, we derive a new more general multiplicative drift theorem that also covers non-elitist EAs. This theorem simultaneously allows for positive and negative results, providing information on the algorithm's progress even when the problem cannot be optimised efficiently. Finally, we provide results for some well-known heuristics namely Random Walk (RW), Random Local Search (RLS), the (1+1) EA, the Metropolis Algorithm (MA), and the Strong Selection Weak Mutation (SSWM) algorithm.

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

NASA Astrophysics Data System (ADS)

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-01

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

Special issue on high-resolution optical imaging

NASA Astrophysics Data System (ADS)

Smith, Peter J. S.; Davis, Ilan; Galbraith, Catherine G.; Stemmer, Andreas

2013-09-01

The pace of development in the field of advanced microscopy is truly breath-taking, and is leading to major breakthroughs in our understanding of molecular machines and cell function. This special issue of Journal of Optics draws attention to a number of interesting approaches, ranging from fluorescence and imaging of unlabelled cells, to computational methods, all of which are describing the ever increasing detail of the dynamic behaviour of molecules in the living cell. This is a field which traditionally, and currently, demonstrates a marvellous interplay between the disciplines of physics, chemistry and biology, where apparent boundaries to resolution dissolve and living cells are viewed in ever more clarity. It is fertile ground for those interested in optics and non-conventional imaging to contribute high-impact outputs in the fields of cell biology and biomedicine. The series of articles presented here has been selected to demonstrate this interdisciplinarity and to encourage all those with a background in the physical sciences to 'dip their toes' into the exciting and dynamic discoveries surrounding cell function. Although single molecule super-resolution microscopy is commercially available, specimen preparation and interpretation of single molecule data remain a major challenge for scientists wanting to adopt the techniques. The paper by Allen and Davidson [1] provides a much needed detailed introduction to the practical aspects of stochastic optical reconstruction microscopy, including sample preparation, image acquisition and image analysis, as well as a brief description of the different variants of single molecule localization microscopy. Since super-resolution microscopy is no longer restricted to three-dimensional imaging of fixed samples, the review by Fiolka [2] is a timely introduction to techniques that have been successfully applied to four-dimensional live cell super-resolution microscopy. The combination of multiple high-resolution techniques, such as the combination of light sheet and structured illumination microscopy (SIM), which efficiently utilize photon budget and avoid illuminating regions of the specimen not currently being imaged, hold the greatest promise for future biological applications. Therefore, the combined setup for SIM and single molecule localization microscopy (SMLM) described by Rossberger et al [3] will be very helpful and stimulating to advanced microscopists in further modifying their setups. The SIM image helps in identifying artefacts in SMLM reconstruction, e.g. when two active fluorophores are close together and get rejected as 'out-of-focus'. This combined setup is another way to facilitate imaging live samples. The article by Thomas et al [4] presents another advance for biological super-resolution imaging with a new approach to reconstruct optically sectioned images using structured illumination. The method produces images with higher spatial resolution and greater signal to noise compared to existing approaches. This algorithm demonstrates great promise for reconstructing biological images where the signal intensities are inherently lower. Shevchuk et al [5] present a non-optic near field approach to imaging with a review of scanning ion-conductance microscopy. This is a powerful alternative approach for examining the surface dynamics of living cells including exo and endocytosis, unlabelled, and at the level of the single event. Here they present the first data on combining this approach with fluorescence confocal microscopy—adding that extra dimension. Different approaches to label-free live cell imaging are presented in the papers by Patel et al [6], Mehta and Oldenbourg [7], as well as Rogers and Zheludev [8]. All three papers bring home the excitement of looking at live cell dynamics without reporters—Patel et al [6] review both the potential of coherent anti-Stokes Raman scattering and biological applications, where specific biomolecules are detected on the basis of their biophysical properties. Polarized light microscopy as presented by Mehta and Oldenbourg [7], describe a novel implementation of this technology to detect dichroism, and demonstrate beautifully its use in imaging unlabelled microtubules, mitochondria and lipid droplets. Sub-wavelength light focusing provides another avenue to super-resolution, and this is presented by Rogers and Zheludev [8]. Speculating on further improvements, these authors expect a resolution of 0.15λ. To date, the method has not been applied to low contrast, squishy and motile biotargets, but is included here for the clear potential to drive label-free imaging in new directions. A similar logic lies behind the inclusion of Parsons et al [9] where ultraviolet coherent diffractive imaging is further developed. These authors have demonstrated a shrink-wrap technique which reduces the integration time by a factor of 5, bringing closer the time when we have lab based imaging systems based on extreme ultraviolet and soft x-ray sources using sophisticated phase retrieval algorithms. Real biological specimens have spatially varying refractive indices that inevitably lead to aberrations and image distortions. Global refractive index matching of the embedding medium has been an historic solution, but unfortunately is not practical for live cell imaging. Adaptive optics appears an attractive solution and Simmonds and Booth [10] demonstrate the theoretical benefits of applying several adaptive optical elements, placed in different conjugate planes, to create a kind of 'inverse specimen' that unwarps phase distortions of the sample—but these have yet to be tested on real specimens. A difficulty in single molecule localization microscopy has been the determination of whether or not two molecules are colocalized. Kim et al [11] present a method for correcting bleed-through during multi-colour, single molecule localization microscopy. Such methods are welcome standards when trying to quantifiably interpret how close two molecules actually are. Rees et al [12] provide an invaluable overview of key image processing steps in localization microscopy. This paper is an excellent starting point for anyone implementing localization algorithms and the Matlab software provided will be invaluable; a strong paper on which to conclude our overview of the excellent articles brought together in this issue. One aspect brought home in several of these articles is the volume of data now being collected by high resolution live cell imaging. Data processing and image reconstruction will continue to be pressure points in the further development of instrumentation and analyses. We would hope that the series of papers presented here will motivate software engineers, optical physicists and biologists to contribute to the further development of this exciting field. References [1] Allen J R et al 2013 J. Opt. 15 094001 [2] Fiolka R et al 2013 J. Opt. 15 094002 [3] Rossberger S et al 2013 J. Opt. 15 094003 [4] Thomas B et al 2013 J. Opt. 15 094004 [5] Shevchuk A et al 2013 J. Opt. 15 094005 [6] Patel I et al 2013 J. Opt. 15 094006 [7] Mehta S B et al 2013 J. Opt. 15 094007 [8] Rogers E T F et al 2013 J. Opt. 15 094008 [9] Parsons A D et al 2013 J. Opt. 15 094009 [10] Simmonds R et al 2013 J. Opt. 15 094010 [11] Kim D et al 2013 J. Opt. 15 094011 [12] Rees E J et al 2013 J. Opt. 15 094012

Multiscale study on stochastic reconstructions of shale samples

NASA Astrophysics Data System (ADS)

Lili, J.; Lin, M.; Jiang, W. B.

2016-12-01

Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared. The result indicates that the agreement between the original 3D sample and the generated stochastic realizations is excellent. This work is supported by "973" Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02) and the National Natural Science Foundation of China (Grant No. 41574129).

Thermally oxidized Inconel 600 and 690 nickel-based alloys characterizations by combination of global photoelectrochemistry and local near-field microscopy techniques (STM, STS, AFM, SKPFM)

NASA Astrophysics Data System (ADS)

Mechehoud, F.; Benaioun, N. E.; Hakiki, N. E.; Khelil, A.; Simon, L.; Bubendorff, J. L.

2018-03-01

Thermally oxidized nickel-based alloys are studied by scanning tunnelling microscopy (STM), scanning tunnelling spectroscopy (STS), atomic force microscopy (AFM), scanning kelvin probe force microscopy (SKPFM) and photoelectro-chemical techniques as a function of oxidation time at a fixed temperature of 623 K. By photoelectrochemistry measurements we identify the formation of three oxides NiO, Fe2O3, Cr2O3 and determine the corresponding gap values. We use these values as parameter for imaging the surface at high bias voltage by STM allowing the spatial localization and identification of both NiO, Fe2O3 oxide phases using STS measurements. Associated to Kelvin probe measurements we show also that STS allow to distinguished NiO from Cr2O3 and confirm that the Cr2O3 is not visible at the surface and localized at the oxide/steel interface.

Direct imaging of nanobubble Ostwald ripening using graphene liquid cell TEM

NASA Astrophysics Data System (ADS)

Xu, Cong; Chen, Qian; Granick, Steve

We directly image the growth, morphology evolution and interaction dynamics of gas nanobubbles in a thin liquid, which are relevant to many materials and electrochemical processes. Using the recently emergent liquid phase transmission electron microscopy (TEM), we resolve the dynamics of nanobubbles in situ at nm resolution in real time. We find that nanobubbles grow through an Ostwald ripening-like process, where adjacent bubbles stochastically fluctuate to disappear or enlarge. Capability of feature tracking enables us to characterize the motions and shape fluctuations of nanobubbles, providing insights into the gas-liquid interfacial fluctuations explored at the nanoscale.

Molecular engineering and measurements to test hypothesized mechanisms in single molecule conductance switching.

PubMed

Moore, Amanda M; Dameron, Arrelaine A; Mantooth, Brent A; Smith, Rachel K; Fuchs, Daniel J; Ciszek, Jacob W; Maya, Francisco; Yao, Yuxing; Tour, James M; Weiss, Paul S

2006-02-15

Six customized phenylene-ethynylene-based oligomers have been studied for their electronic properties using scanning tunneling microscopy to test hypothesized mechanisms of stochastic conductance switching. Previously suggested mechanisms include functional group reduction, functional group rotation, backbone ring rotation, neighboring molecule interactions, bond fluctuations, and hybridization changes. Here, we test these hypotheses experimentally by varying the molecular designs of the switches; the ability of the molecules to switch via each hypothetical mechanism is selectively engineered into or out of each molecule. We conclude that hybridization changes at the molecule-surface interface are responsible for the switching we observe.

Assembly Mechanism of the Contractile Ring for Cytokinesis by Fission Yeast

NASA Astrophysics Data System (ADS)

Vavylonis, Dimitrios; Wu, Jian-Qiu; Huang, Xiaolei; O'Shaughnessy, Ben; Pollard, Thomas

2008-03-01

Animals and fungi assemble a contractile ring of actin filaments and the motor protein myosin to separate into individual daughter cells during cytokinesis. We studied the mechanism of contractile ring assembly in fission yeast with high time resolution confocal microscopy, computational image analysis methods, and numerical simulations. Approximately 63 nodes containing myosin, broadly distributed around the cell equator, assembled into a ring through stochastic motions, making many starts, stops, and changes of direction as they condense into a ring. Estimates of node friction coefficients from the mean square displacement of stationary nodes imply forces for node movement are greater than ˜ 4 pN, similarly to forces by a few molecular motors. Skeletonization and topology analysis of images of cells expressing fluorescent actin filament markers showed transient linear elements extending in all directions from myosin nodes and establishing connections among them. We propose a model with traction between nodes depending on transient connections established by stochastic search and capture (``search, capture, pull and release''). Numerical simulations of the model using parameter values obtained from experiment succesfully condense nodes into a continuous ring.

Intermittent photocatalytic activity of single CdS nanoparticles

PubMed Central

Li, Zhimin; Jiang, Yingyan; Wang, Xian; Chen, Hong-Yuan; Tao, Nongjian; Wang, Wei

2017-01-01

Semiconductor photocatalysis holds promising keys to address various energy and environmental challenges. Most studies to date are based on ensemble analysis, which may mask critical photocatalytic kinetics in single nanocatalysts. Here we report a study of imaging photocatalytic hydrogen production of single CdS nanoparticles with a plasmonic microscopy in an in operando manner. Surprisingly, we find that the photocatalytic reaction switches on and off stochastically despite the fact that the illumination is kept constant. The on and off states follow truncated and full-scale power-law distributions in broad time scales spanning 3–4 orders of magnitude, respectively, which can be described with a statistical model involving stochastic reactions rates at multiple active sites. This phenomenon is analogous to fluorescence photoblinking, but the underlying mechanism is different. As individual nanocatalyst represents the elementary photocatalytic platform, the discovery of the intermittent nature of the photocatalysis provides insights into the fundamental photochemistry and photophysics of semiconductor nanomaterials, which is anticipated to substantially benefit broad application fields such as clean energy, pollution treatment, and chemical synthesis. PMID:28923941

The Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans

PubMed Central

Striegel, Deborah A.; Hara, Manami; Periwal, Vipul

2015-01-01

Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets. PMID:26266953

The Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans.

PubMed

Striegel, Deborah A; Hara, Manami; Periwal, Vipul

2015-08-01

Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets.

Scanning Probe Microscopy of Organic Solar Cells

NASA Astrophysics Data System (ADS)

Reid, Obadiah G.

Nanostructured composites of organic semiconductors are a promising class of materials for the manufacture of low-cost solar cells. Understanding how the nanoscale morphology of these materials affects their efficiency as solar energy harvesters is crucial to their eventual potential for large-scale deployment for primary power generation. In this thesis we describe the use of optoelectronic scanning-probe based microscopy methods to study this efficiency-structure relationship with nanoscale resolution. In particular, our objective is to make spatially resolved measurements of each step in the power conversion process from photons to an electric current, including charge generation, transport, and recombination processes, and correlate them with local device structure. We have achieved two aims in this work: first, to develop and apply novel electrically sensitive scanning probe microscopy experiments to study the optoelectronic materials and processes discussed above; and second, to deepen our understanding of the physics underpinning our experimental techniques. In the first case, we have applied conductive-, and photoconductive atomic force (cAFM & pcAFM) microscopy to measure both local photocurrent collection and dark charge transport properties in a variety of model and novel organic solar cell composites, including polymer/fullerene blends, and polymer-nanowire/fullerene blends, finding that local heterogeneity is the rule, and that improvements in the uniformity of specific beneficial nanostructures could lead to large increases in efficiency. We have used scanning Kelvin probe microscopy (SKPM) and time resolved-electrostatic force microscopy (trEFM) to characterize all-polymer blends, quantifying their sensitivity to photochemical degradation and the subsequent formation of local charge traps. We find that while trEFM provides a sensitive measure of local quantum efficiency, SKPM is generally unsuited to measurements of efficiency, less sensitive than trEFM, and of greater utility in identifying local changes in steady-state charge density that can be associated with charge trapping. In the second case, we have developed a new understanding of charge transport between a sharp AFM tip and planar substrates applicable to conductive and photoconductive atomic force microscopy, and shown that hole-only transport characteristics can be easily obtained including quantitative values of the charge carrier mobility. Finally, we have shown that intensity-dependent photoconductive atomic force microscopy measurements can be used to infer the 3D structure of organic photovoltaic materials, and gained new insight into the influence vertical composition of the these devices can have on their open-circuit voltage and its intensity dependence.

A hierarchical stress release model for synthetic seismicity

NASA Astrophysics Data System (ADS)

Bebbington, Mark

1997-06-01

We construct a stochastic dynamic model for synthetic seismicity involving stochastic stress input, release, and transfer in an environment of heterogeneous strength and interacting segments. The model is not fault-specific, having a number of adjustable parameters with physical interpretation, namely, stress relaxation, stress transfer, stress dissipation, segment structure, strength, and strength heterogeneity, which affect the seismicity in various ways. Local parameters are chosen to be consistent with large historical events, other parameters to reproduce bulk seismicity statistics for the fault as a whole. The one-dimensional fault is divided into a number of segments, each comprising a varying number of nodes. Stress input occurs at each node in a simple random process, representing the slow buildup due to tectonic plate movements. Events are initiated, subject to a stochastic hazard function, when the stress on a node exceeds the local strength. An event begins with the transfer of excess stress to neighboring nodes, which may in turn transfer their excess stress to the next neighbor. If the event grows to include the entire segment, then most of the stress on the segment is transferred to neighboring segments (or dissipated) in a characteristic event. These large events may themselves spread to other segments. We use the Middle America Trench to demonstrate that this model, using simple stochastic stress input and triggering mechanisms, can produce behavior consistent with the historical record over five units of magnitude. We also investigate the effects of perturbing various parameters in order to show how the model might be tailored to a specific fault structure. The strength of the model lies in this ability to reproduce the behavior of a general linear fault system through the choice of a relatively small number of parameters. It remains to develop a procedure for estimating the internal state of the model from the historical observations in order to use the model for forward prediction.

A Pumping Algorithm for Ergodic Stochastic Mean Payoff Games with Perfect Information

NASA Astrophysics Data System (ADS)

Boros, Endre; Elbassioni, Khaled; Gurvich, Vladimir; Makino, Kazuhisa

In this paper, we consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph G = (V = V B ∪ V W ∪ V R , E), with local rewards r: E to { R}, and three types of vertices: black V B , white V W , and random V R . The game is played by two players, White and Black: When the play is at a white (black) vertex v, White (Black) selects an outgoing arc (v,u). When the play is at a random vertex v, a vertex u is picked with the given probability p(v,u). In all cases, Black pays White the value r(v,u). The play continues forever, and White aims to maximize (Black aims to minimize) the limiting mean (that is, average) payoff. It was recently shown in [7] that BWR-games are polynomially equivalent with the classical Gillette games, which include many well-known subclasses, such as cyclic games, simple stochastic games (SSG's), stochastic parity games, and Markov decision processes. In this paper, we give a new algorithm for solving BWR-games in the ergodic case, that is when the optimal values do not depend on the initial position. Our algorithm solves a BWR-game by reducing it, using a potential transformation, to a canonical form in which the optimal strategies of both players and the value for every initial position are obvious, since a locally optimal move in it is optimal in the whole game. We show that this algorithm is pseudo-polynomial when the number of random nodes is constant. We also provide an almost matching lower bound on its running time, and show that this bound holds for a wider class of algorithms. Let us add that the general (non-ergodic) case is at least as hard as SSG's, for which no pseudo-polynomial algorithm is known.

Stochastic interpretation of the advection-diffusion equation and its relevance to bed load transport

NASA Astrophysics Data System (ADS)

Ancey, C.; Bohorquez, P.; Heyman, J.

2015-12-01

The advection-diffusion equation is one of the most widespread equations in physics. It arises quite often in the context of sediment transport, e.g., for describing time and space variations in the particle activity (the solid volume of particles in motion per unit streambed area). Phenomenological laws are usually sufficient to derive this equation and interpret its terms. Stochastic models can also be used to derive it, with the significant advantage that they provide information on the statistical properties of particle activity. These models are quite useful when sediment transport exhibits large fluctuations (typically at low transport rates), making the measurement of mean values difficult. Among these stochastic models, the most common approach consists of random walk models. For instance, they have been used to model the random displacement of tracers in rivers. Here we explore an alternative approach, which involves monitoring the evolution of the number of particles moving within an array of cells of finite length. Birth-death Markov processes are well suited to this objective. While the topic has been explored in detail for diffusion-reaction systems, the treatment of advection has received no attention. We therefore look into the possibility of deriving the advection-diffusion equation (with a source term) within the framework of birth-death Markov processes. We show that in the continuum limit (when the cell size becomes vanishingly small), we can derive an advection-diffusion equation for particle activity. Yet while this derivation is formally valid in the continuum limit, it runs into difficulty in practical applications involving cells or meshes of finite length. Indeed, within our stochastic framework, particle advection produces nonlocal effects, which are more or less significant depending on the cell size and particle velocity. Albeit nonlocal, these effects look like (local) diffusion and add to the intrinsic particle diffusion (dispersal due to velocity fluctuations), with the important consequence that local measurements depend on both the intrinsic properties of particle displacement and the dimensions of the measurement system.

Continuous quantum measurement in spin environments

NASA Astrophysics Data System (ADS)

Xie, Dong; Wang, An Min

2015-08-01

We derive a stochastic master equation (SME) which describes the decoherence dynamics of a system in spin environments conditioned on the measurement record. Markovian and non-Markovian nature of environment can be revealed by a spectroscopy method based on weak continuous quantum measurement. On account of that correlated environments can lead to a non-local open system which exhibits strong non-Markovian effects although the local dynamics are Markovian, the spectroscopy method can be used to demonstrate that there is correlation between two environments.

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

Faizal, Mir, E-mail: f2mir@uwaterloo.ca; Majumder, Barun, E-mail: barunbasanta@iitgn.ac.in

In this paper, we will incorporate the generalized uncertainty principle into field theories with Lifshitz scaling. We will first construct both bosonic and fermionic theories with Lifshitz scaling based on generalized uncertainty principle. After that we will incorporate the generalized uncertainty principle into a non-abelian gauge theory with Lifshitz scaling. We will observe that even though the action for this theory is non-local, it is invariant under local gauge transformations. We will also perform the stochastic quantization of this Lifshitz fermionic theory based generalized uncertainty principle.

Reducing microscopy-based malaria misdiagnosis in a low-resource area of Tanzania.

PubMed

Allen, Lisa K; Hatfield, Jennifer M; Manyama, Mange

2013-01-01

Misdiagnosis of malaria is a major problem in Africa leading not only to incorrect individual level treatment, but potentially the acceleration of the spread of drug resistance in low-transmission areas. In this paper we report on the outcomes of a simple intervention that utilized a social entrepreneurship approach (SEA) to reduce misdiagnosis associated with hospital-based microscopy of malaria in a low-transmission area of rural Tanzania. A pre-post assessment was conducted on patients presenting to the hospital outpatient department with malaria and non-malaria like symptoms in January 2009 (pre-intervention) and June 2009 (post-intervention). All participants were asked a health seeking behavior questionnaire and blood samples were taken for local and quality control microscopy. Multivariate logistic regression was conducted to determine magnitude of misdiagnosis with local microscopy pre- versus- post intervention. Local microscopy pre-intervention specificity was 29.5% (95% CI = 21.6% - 38.4%) whereas the post intervention specificity was 68.6% (95% CI = 60.2% - 76.2%). Both pre and post intervention sensitivity were difficult to determine due to an unexpected low number of true positive cases. The proportion of participants misdiagnosed pre-intervention was 70.2% (95%CI = 61.3%-78.0%) as compared to 30.6% (95%CI = 23.2%-38.8%) post-intervention. This resulted in a 39.6% reduction in misdiagnosis of malaria at the local hospital. The magnitude of misdiagnosis for the pre-intervention participants was 5.3 (95%CI = 3.1-9.3) that of the post-intervention participants. In conclusion, this study provides evidence that a simple intervention can meaningfully reduce the magnitude of microscopy-based misdiagnosis of malaria for those individuals seeking treatment for uncomplicated malaria. We anticipate that this intervention will facilitate a valuable and sustainable change in malaria diagnosis at the local hospital.

Replication Origins and Timing of Temporal Replication in Budding Yeast: How to Solve the Conundrum?

PubMed Central

Barberis, Matteo; Spiesser, Thomas W.; Klipp, Edda

2010-01-01

Similarly to metazoans, the budding yeast Saccharomyces cereviasiae replicates its genome with a defined timing. In this organism, well-defined, site-specific origins, are efficient and fire in almost every round of DNA replication. However, this strategy is neither conserved in the fission yeast Saccharomyces pombe, nor in Xenopus or Drosophila embryos, nor in higher eukaryotes, in which DNA replication initiates asynchronously throughout S phase at random sites. Temporal and spatial controls can contribute to the timing of replication such as Cdk activity, origin localization, epigenetic status or gene expression. However, a debate is going on to answer the question how individual origins are selected to fire in budding yeast. Two opposing theories were proposed: the “replicon paradigm” or “temporal program” vs. the “stochastic firing”. Recent data support the temporal regulation of origin activation, clustering origins into temporal blocks of early and late replication. Contrarily, strong evidences suggest that stochastic processes acting on origins can generate the observed kinetics of replication without requiring a temporal order. In mammalian cells, a spatiotemporal model that accounts for a partially deterministic and partially stochastic order of DNA replication has been proposed. Is this strategy the solution to reconcile the conundrum of having both organized replication timing and stochastic origin firing also for budding yeast? In this review we discuss this possibility in the light of our recent study on the origin activation, suggesting that there might be a stochastic component in the temporal activation of the replication origins, especially under perturbed conditions. PMID:21037857

Continuum models of cohesive stochastic swarms: The effect of motility on aggregation patterns

NASA Astrophysics Data System (ADS)

Hughes, Barry D.; Fellner, Klemens

2013-10-01

Mathematical models of swarms of moving agents with non-local interactions have many applications and have been the subject of considerable recent interest. For modest numbers of agents, cellular automata or related algorithms can be used to study such systems, but in the present work, instead of considering discrete agents, we discuss a class of one-dimensional continuum models, in which the agents possess a density ρ(x,t) at location x at time t. The agents are subject to a stochastic motility mechanism and to a global cohesive inter-agent force. The motility mechanisms covered include classical diffusion, nonlinear diffusion (which may be used to model, in a phenomenological way, volume exclusion or other short-range local interactions), and a family of linear redistribution operators related to fractional diffusion equations. A variety of exact analytic results are discussed, including equilibrium solutions and criteria for unimodality of equilibrium distributions, full time-dependent solutions, and transitions between asymptotic collapse and asymptotic escape. We address the behaviour of the system for diffusive motility in the low-diffusivity limit for both smooth and singular interaction potentials and show how this elucidates puzzling behaviour in fully deterministic non-local particle interaction models. We conclude with speculative remarks about extensions and applications of the models.

Improved Bayesian Infrasonic Source Localization for regional infrasound

DOE PAGES

Blom, Philip S.; Marcillo, Omar; Arrowsmith, Stephen J.

2015-10-20

The Bayesian Infrasonic Source Localization (BISL) methodology is examined and simplified providing a generalized method of estimating the source location and time for an infrasonic event and the mathematical framework is used therein. The likelihood function describing an infrasonic detection used in BISL has been redefined to include the von Mises distribution developed in directional statistics and propagation-based, physically derived celerity-range and azimuth deviation models. Frameworks for constructing propagation-based celerity-range and azimuth deviation statistics are presented to demonstrate how stochastic propagation modelling methods can be used to improve the precision and accuracy of the posterior probability density function describing themore » source localization. Infrasonic signals recorded at a number of arrays in the western United States produced by rocket motor detonations at the Utah Test and Training Range are used to demonstrate the application of the new mathematical framework and to quantify the improvement obtained by using the stochastic propagation modelling methods. Moreover, using propagation-based priors, the spatial and temporal confidence bounds of the source decreased by more than 40 per cent in all cases and by as much as 80 per cent in one case. Further, the accuracy of the estimates remained high, keeping the ground truth within the 99 per cent confidence bounds for all cases.« less

Localization microscopy of DNA in situ using Vybrant{sup ®} DyeCycle™ Violet fluorescent probe: A new approach to study nuclear nanostructure at single molecule resolution

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

Żurek-Biesiada, Dominika; Szczurek, Aleksander T.; Prakash, Kirti

Higher order chromatin structure is not only required to compact and spatially arrange long chromatids within a nucleus, but have also important functional roles, including control of gene expression and DNA processing. However, studies of chromatin nanostructures cannot be performed using conventional widefield and confocal microscopy because of the limited optical resolution. Various methods of superresolution microscopy have been described to overcome this difficulty, like structured illumination and single molecule localization microscopy. We report here that the standard DNA dye Vybrant{sup ®} DyeCycle™ Violet can be used to provide single molecule localization microscopy (SMLM) images of DNA in nuclei ofmore » fixed mammalian cells. This SMLM method enabled optical isolation and localization of large numbers of DNA-bound molecules, usually in excess of 10{sup 6} signals in one cell nucleus. The technique yielded high-quality images of nuclear DNA density, revealing subdiffraction chromatin structures of the size in the order of 100 nm; the interchromatin compartment was visualized at unprecedented optical resolution. The approach offers several advantages over previously described high resolution DNA imaging methods, including high specificity, an ability to record images using a single wavelength excitation, and a higher density of single molecule signals than reported in previous SMLM studies. The method is compatible with DNA/multicolor SMLM imaging which employs simple staining methods suited also for conventional optical microscopy. - Highlights: • Super-resolution imaging of nuclear DNA with Vybrant Violet and blue excitation. • 90nm resolution images of DNA structures in optically thick eukaryotic nuclei. • Enhanced resolution confirms the existence of DNA-free regions inside the nucleus. • Optimized imaging conditions enable multicolor super-resolution imaging.« less

Improved localization of cellular membrane receptors using combined fluorescence microscopy and simultaneous topography and recognition imaging

NASA Astrophysics Data System (ADS)

Duman, M.; Pfleger, M.; Zhu, R.; Rankl, C.; Chtcheglova, L. A.; Neundlinger, I.; Bozna, B. L.; Mayer, B.; Salio, M.; Shepherd, D.; Polzella, P.; Moertelmaier, M.; Kada, G.; Ebner, A.; Dieudonne, M.; Schütz, G. J.; Cerundolo, V.; Kienberger, F.; Hinterdorfer, P.

2010-03-01

The combination of fluorescence microscopy and atomic force microscopy has a great potential in single-molecule-detection applications, overcoming many of the limitations coming from each individual technique. Here we present a new platform of combined fluorescence and simultaneous topography and recognition imaging (TREC) for improved localization of cellular receptors. Green fluorescent protein (GFP) labeled human sodium-glucose cotransporter (hSGLT1) expressed Chinese Hamster Ovary (CHO) cells and endothelial cells (MyEnd) from mouse myocardium stained with phalloidin-rhodamine were used as cell systems to study AFM topography and fluorescence microscopy on the same surface area. Topographical AFM images revealed membrane features such as lamellipodia, cytoskeleton fibers, F-actin filaments and small globular structures with heights ranging from 20 to 30 nm. Combined fluorescence and TREC imaging was applied to detect density, distribution and localization of YFP-labeled CD1d molecules on α-galactosylceramide (αGalCer)-loaded THP1 cells. While the expression level, distribution and localization of CD1d molecules on THP1 cells were detected with fluorescence microscopy, the nanoscale distribution of binding sites was investigated with molecular recognition imaging by using a chemically modified AFM tip. Using TREC on the inverted light microscope, the recognition sites of cell receptors were detected in recognition images with domain sizes ranging from ~ 25 to ~ 160 nm, with the smaller domains corresponding to a single CD1d molecule.

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

PubMed Central

Kim, Dahan; Curthoys, Nikki M.; Parent, Matthew T.; Hess, Samuel T.

2015-01-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. PMID:26185614

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy.

PubMed

Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

2013-09-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined.

Improved localization of cellular membrane receptors using combined fluorescence microscopy and simultaneous topography and recognition imaging.

PubMed

Duman, M; Pfleger, M; Zhu, R; Rankl, C; Chtcheglova, L A; Neundlinger, I; Bozna, B L; Mayer, B; Salio, M; Shepherd, D; Polzella, P; Moertelmaier, M; Kada, G; Ebner, A; Dieudonne, M; Schütz, G J; Cerundolo, V; Kienberger, F; Hinterdorfer, P

2010-03-19

The combination of fluorescence microscopy and atomic force microscopy has a great potential in single-molecule-detection applications, overcoming many of the limitations coming from each individual technique. Here we present a new platform of combined fluorescence and simultaneous topography and recognition imaging (TREC) for improved localization of cellular receptors. Green fluorescent protein (GFP) labeled human sodium-glucose cotransporter (hSGLT1) expressed Chinese Hamster Ovary (CHO) cells and endothelial cells (MyEnd) from mouse myocardium stained with phalloidin-rhodamine were used as cell systems to study AFM topography and fluorescence microscopy on the same surface area. Topographical AFM images revealed membrane features such as lamellipodia, cytoskeleton fibers, F-actin filaments and small globular structures with heights ranging from 20 to 30 nm. Combined fluorescence and TREC imaging was applied to detect density, distribution and localization of YFP-labeled CD1d molecules on alpha-galactosylceramide (alphaGalCer)-loaded THP1 cells. While the expression level, distribution and localization of CD1d molecules on THP1 cells were detected with fluorescence microscopy, the nanoscale distribution of binding sites was investigated with molecular recognition imaging by using a chemically modified AFM tip. Using TREC on the inverted light microscope, the recognition sites of cell receptors were detected in recognition images with domain sizes ranging from approximately 25 to approximately 160 nm, with the smaller domains corresponding to a single CD1d molecule.

Cassette Series Designed for Live-Cell Imaging of Proteins and High Resolution Techniques in Yeast

PubMed Central

Young, Carissa L.; Raden, David L.; Caplan, Jeffrey; Czymmek, Kirk; Robinson, Anne S.

2012-01-01

During the past decade, it has become clear that protein function and regulation are highly dependent upon intracellular localization. Although fluorescent protein variants are ubiquitously used to monitor protein dynamics, localization, and abundance; fluorescent light microscopy techniques often lack the resolution to explore protein heterogeneity and cellular ultrastructure. Several approaches have been developed to identify, characterize, and monitor the spatial localization of proteins and complexes at the sub-organelle level; yet, many of these techniques have not been applied to yeast. Thus, we have constructed a series of cassettes containing codon-optimized epitope tags, fluorescent protein variants that cover the full spectrum of visible light, a TetCys motif used for FlAsH-based localization, and the first evaluation in yeast of a photoswitchable variant – mEos2 – to monitor discrete subpopulations of proteins via confocal microscopy. This series of modules, complete with six different selection markers, provides the optimal flexibility during live-cell imaging and multicolor labeling in vivo. Furthermore, high-resolution imaging techniques include the yeast-enhanced TetCys motif that is compatible with diaminobenzidine photooxidation used for protein localization by electron microscopy and mEos2 that is ideal for super-resolution microscopy. We have examined the utility of our cassettes by analyzing all probes fused to the C-terminus of Sec61, a polytopic membrane protein of the endoplasmic reticulum of moderate protein concentration, in order to directly compare fluorescent probes, their utility and technical applications. Our series of cassettes expand the repertoire of molecular tools available to advance targeted spatiotemporal investigations using multiple live-cell, super-resolution or electron microscopy imaging techniques. PMID:22473760

SNSMIL, a real-time single molecule identification and localization algorithm for super-resolution fluorescence microscopy

PubMed Central

Tang, Yunqing; Dai, Luru; Zhang, Xiaoming; Li, Junbai; Hendriks, Johnny; Fan, Xiaoming; Gruteser, Nadine; Meisenberg, Annika; Baumann, Arnd; Katranidis, Alexandros; Gensch, Thomas

2015-01-01

Single molecule localization based super-resolution fluorescence microscopy offers significantly higher spatial resolution than predicted by Abbe’s resolution limit for far field optical microscopy. Such super-resolution images are reconstructed from wide-field or total internal reflection single molecule fluorescence recordings. Discrimination between emission of single fluorescent molecules and background noise fluctuations remains a great challenge in current data analysis. Here we present a real-time, and robust single molecule identification and localization algorithm, SNSMIL (Shot Noise based Single Molecule Identification and Localization). This algorithm is based on the intrinsic nature of noise, i.e., its Poisson or shot noise characteristics and a new identification criterion, QSNSMIL, is defined. SNSMIL improves the identification accuracy of single fluorescent molecules in experimental or simulated datasets with high and inhomogeneous background. The implementation of SNSMIL relies on a graphics processing unit (GPU), making real-time analysis feasible as shown for real experimental and simulated datasets. PMID:26098742

Quantitative evaluation of software packages for single-molecule localization microscopy.

PubMed

Sage, Daniel; Kirshner, Hagai; Pengo, Thomas; Stuurman, Nico; Min, Junhong; Manley, Suliana; Unser, Michael

2015-08-01

The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.

Occupational hazards in hospitals: accidents, radiation, exposure to noxious chemicals, drug addiction and psychic problems, and assault.

PubMed Central

Gestal, J J

1987-01-01

Except for infectious diseases all the main occupational hazards affecting health workers are reviewed: accidents (explosions, fires, electrical accidents, and other sources of injury); radiation (stochastic and non-stochastic effects, protective measures, and personnel most at risk); exposure to noxious chemicals, whose effects may be either local (allergic eczema) or generalised (cancer, mutations), particular attention being paid to the hazards presented by formol, ethylene oxide, cytostatics, and anaesthetic gases; drug addiction (which is more common among health workers than the general population) and psychic problems associated with promotion, shift work, and emotional stress; and assault (various types of assault suffered by health workers, its causes, and the characterisation of the most aggressive patients). PMID:3307896

Regularity of random attractors for fractional stochastic reaction-diffusion equations on Rn

NASA Astrophysics Data System (ADS)

Gu, Anhui; Li, Dingshi; Wang, Bixiang; Yang, Han

2018-06-01

We investigate the regularity of random attractors for the non-autonomous non-local fractional stochastic reaction-diffusion equations in Hs (Rn) with s ∈ (0 , 1). We prove the existence and uniqueness of the tempered random attractor that is compact in Hs (Rn) and attracts all tempered random subsets of L2 (Rn) with respect to the norm of Hs (Rn). The main difficulty is to show the pullback asymptotic compactness of solutions in Hs (Rn) due to the noncompactness of Sobolev embeddings on unbounded domains and the almost sure nondifferentiability of the sample paths of the Wiener process. We establish such compactness by the ideas of uniform tail-estimates and the spectral decomposition of solutions in bounded domains.

Computing diffusivities from particle models out of equilibrium

NASA Astrophysics Data System (ADS)

Embacher, Peter; Dirr, Nicolas; Zimmer, Johannes; Reina, Celia

2018-04-01

A new method is proposed to numerically extract the diffusivity of a (typically nonlinear) diffusion equation from underlying stochastic particle systems. The proposed strategy requires the system to be in local equilibrium and have Gaussian fluctuations but it is otherwise allowed to undergo arbitrary out-of-equilibrium evolutions. This could be potentially relevant for particle data obtained from experimental applications. The key idea underlying the method is that finite, yet large, particle systems formally obey stochastic partial differential equations of gradient flow type satisfying a fluctuation-dissipation relation. The strategy is here applied to three classic particle models, namely independent random walkers, a zero-range process and a symmetric simple exclusion process in one space dimension, to allow the comparison with analytic solutions.

Edgeworth expansions of stochastic trading time

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann

2010-08-01

Under most local and stochastic volatility models the underlying forward is assumed to be a positive function of a time-changed Brownian motion. It relates nicely the implied volatility smile to the so-called activity rate in the market. Following Young and DeWitt-Morette (1986) [8], we propose to apply the Duru-Kleinert process-cum-time transformation in path integral to formulate the transition density of the forward. The method leads to asymptotic expansions of the transition density around a Gaussian kernel corresponding to the average activity in the market conditional on the forward value. The approximation is numerically illustrated for pricing vanilla options under the CEV model and the popular normal SABR model. The asymptotics can also be used for Monte Carlo simulations or backward integration schemes.

Stochastic Acceleration of Ions Driven by Pc1 Wave Packets

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Sibeck, D. G.; Tel'nikhin, A. A.; Kronberg, T. K.

2015-01-01

The stochastic motion of protons and He(sup +) ions driven by Pc1 wave packets is studied in the context of resonant particle heating. Resonant ion cyclotron heating typically occurs when wave powers exceed 10(exp -4) nT sq/Hz. Gyroresonance breaks the first adiabatic invariant and energizes keV ions. Cherenkov resonances with the electrostatic component of wave packets can also accelerate ions. The main effect of this interaction is to accelerate thermal protons to the local Alfven speed. The dependencies of observable quantities on the wave power and plasma parameters are determined, and estimates for the heating extent and rate of particle heating in these wave-particle interactions are shown to be in reasonable agreement with known empirical data.

A finite state, finite memory minimum principle, part 2. [a discussion of game theory, signaling, stochastic processes, and control theory

NASA Technical Reports Server (NTRS)

Sandell, N. R., Jr.; Athans, M.

1975-01-01

The development of the theory of the finite - state, finite - memory (FSFM) stochastic control problem is discussed. The sufficiency of the FSFM minimum principle (which is in general only a necessary condition) was investigated. By introducing the notion of a signaling strategy as defined in the literature on games, conditions under which the FSFM minimum principle is sufficient were determined. This result explicitly interconnects the information structure of the FSFM problem with its optimality conditions. The min-H algorithm for the FSFM problem was studied. It is demonstrated that a version of the algorithm always converges to a particular type of local minimum termed a person - by - person extremal.

Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy

PubMed Central

Jiang, Shenghang; Park, Seongjin; Challapalli, Sai Divya; Fei, Jingyi; Wang, Yong

2017-01-01

We report a robust nonparametric descriptor, J′(r), for quantifying the density of clustering molecules in single-molecule localization microscopy. J′(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that J′(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. Most importantly, the position of the J′(r) valley (rJm′) depends exclusively on the density of clustering molecules (ρc). Therefore, it is ideal for direct estimation of the clustering density of molecules in single-molecule localization microscopy. As an example, this descriptor was applied to estimate the clustering density of ptsG mRNA in E. coli bacteria. PMID:28636661

Software Tools for Stochastic Simulations of Turbulence

DTIC Science & Technology

2015-08-28

client interface to FTI. Specefic client programs using this interface include the weather forecasting code WRF ; the high energy physics code, FLASH...client programs using this interface include the weather forecasting code WRF ; the high energy physics code, FLASH; and two locally constructed fluid...45 4.4.2.2 FLASH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.4.2.3 WRF

Adaptive Dynamics, Control, and Extinction in Networked Populations

DTIC Science & Technology

2015-07-09

network geometries. From the pre-history of paths that go extinct, a density function is created from the prehistory of these paths, and a clear local...density plots of Fig. 3b. Using the IAMM to compute the most probable path and comparing it to the prehistory of extinction events on stochastic networks

Efficiency and large deviations in time-asymmetric stochastic heat engines

DOE PAGES

Gingrich, Todd R.; Rotskoff, Grant M.; Vaikuntanathan, Suriyanarayanan; ...

2014-10-24

In a stochastic heat engine driven by a cyclic non-equilibrium protocol, fluctuations in work and heat give rise to a fluctuating efficiency. Using computer simulations and tools from large deviation theory, we have examined these fluctuations in detail for a model two-state engine. We find in general that the form of efficiency probability distributions is similar to those described by Verley et al (2014 Nat. Commun. 5 4721), in particular featuring a local minimum in the long-time limit. In contrast to the time-symmetric engine protocols studied previously, however, this minimum need not occur at the value characteristic of a reversible Carnot engine. Furthermore, while the local minimum may reside at the global minimum of a large deviation rate function, it does not generally correspond to the least likely efficiency measured over finite time. Lastly, we introduce a general approximation for the finite-time efficiency distribution,more » $$P(\\eta )$$, based on large deviation statistics of work and heat, that remains very accurate even when $$P(\\eta )$$ deviates significantly from its large deviation form.« less

Stochastic Nonlinear Response of Woven CMCs

NASA Technical Reports Server (NTRS)

Kuang, C. Liu; Arnold, Steven M.

2013-01-01

It is well known that failure of a material is a locally driven event. In the case of ceramic matrix composites (CMCs), significant variations in the microstructure of the composite exist and their significance on both deformation and life response need to be assessed. Examples of these variations include changes in the fiber tow shape, tow shifting/nesting and voids within and between tows. In the present work, the influence of scale specific architectural features of woven ceramic composite are examined stochastically at both the macroscale (woven repeating unit cell (RUC)) and structural scale (idealized using multiple RUCs). The recently developed MultiScale Generalized Method of Cells methodology is used to determine the overall deformation response, proportional elastic limit (first matrix cracking), and failure under tensile loading conditions and associated probability distribution functions. Prior results showed that the most critical architectural parameter to account for is weave void shape and content with other parameters being less in severity. Current results show that statistically only the post-elastic limit region (secondary hardening modulus and ultimate tensile strength) is impacted by local uncertainties both at the macro and structural level.

Nanoscale protein architecture of the kidney glomerular basement membrane

PubMed Central

Suleiman, Hani; Zhang, Lei; Roth, Robyn; Heuser, John E; Miner, Jeffrey H; Shaw, Andrey S; Dani, Adish

2013-01-01

In multicellular organisms, proteins of the extracellular matrix (ECM) play structural and functional roles in essentially all organs, so understanding ECM protein organization in health and disease remains an important goal. Here, we used sub-diffraction resolution stochastic optical reconstruction microscopy (STORM) to resolve the in situ molecular organization of proteins within the kidney glomerular basement membrane (GBM), an essential mediator of glomerular ultrafiltration. Using multichannel STORM and STORM-electron microscopy correlation, we constructed a molecular reference frame that revealed a laminar organization of ECM proteins within the GBM. Separate analyses of domains near the N- and C-termini of agrin, laminin, and collagen IV in mouse and human GBM revealed a highly oriented macromolecular organization. Our analysis also revealed disruptions in this GBM architecture in a mouse model of Alport syndrome. These results provide the first nanoscopic glimpse into the organization of a complex ECM. DOI: http://dx.doi.org/10.7554/eLife.01149.001 PMID:24137544

Surface kinetic roughening caused by dental erosion: An atomic force microscopy study

NASA Astrophysics Data System (ADS)

Quartarone, Eliana; Mustarelli, Piercarlo; Poggio, Claudio; Lombardini, Marco

2008-05-01

Surface kinetic roughening takes place both in case of growth and erosion processes. Teeth surfaces are eroded by contact with acid drinks, such as those used to supplement mineral salts during sporting activities. Calcium-phosphate based (CPP-ACP) pastes are known to reduce the erosion process, and to favour the enamel remineralization. In this study we used atomic force microscopy (AFM) to investigate the surface roughening during dental erosion, and the mechanisms at the basis of the protection role exerted by a commercial CPP-ACP paste. We found a statistically significant difference (p<0.01) in the roughness of surfaces exposed and not exposed to the acid solutions. The treatment with the CPP-ACP paste determined a statistically significant reduction of the roughness values. By interpreting the AFM results in terms of fractal scaling concepts and continuum stochastic equations, we showed that the protection mechanism of the paste depends on the chemical properties of the acid solution.

Stimulated emission depletion microscopy resolves individual nitrogen vacancy centers in diamond nanocrystals.

PubMed

Arroyo-Camejo, Silvia; Adam, Marie-Pierre; Besbes, Mondher; Hugonin, Jean-Paul; Jacques, Vincent; Greffet, Jean-Jacques; Roch, Jean-François; Hell, Stefan W; Treussart, François

2013-12-23

Nitrogen-vacancy (NV) color centers in nanodiamonds are highly promising for bioimaging and sensing. However, resolving individual NV centers within nanodiamond particles and the controlled addressing and readout of their spin state has remained a major challenge. Spatially stochastic super-resolution techniques cannot provide this capability in principle, whereas coordinate-controlled super-resolution imaging methods, like stimulated emission depletion (STED) microscopy, have been predicted to fail in nanodiamonds. Here we show that, contrary to these predictions, STED can resolve single NV centers in 40-250 nm sized nanodiamonds with a resolution of ≈10 nm. Even multiple adjacent NVs located in single nanodiamonds can be imaged individually down to relative distances of ≈15 nm. Far-field optical super-resolution of NVs inside nanodiamonds is highly relevant for bioimaging applications of these fluorescent nanolabels. The targeted addressing and readout of individual NV(-) spins inside nanodiamonds by STED should also be of high significance for quantum sensing and information applications.

The journey of integrins and partners in a complex interactions landscape studied by super-resolution microscopy and single protein tracking

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

Rossier, Olivier; Giannone, Grégory; CNRS, Interdisciplinary Institute for Neuroscience, UMR 5297, F-33000 Bordeaux

Cells adjust their adhesive and cytoskeletal organizations according to changes in the biochemical and physical nature of their surroundings. In return, by adhering and generating forces on the extracellular matrix (ECM) cells organize their microenvironment. Integrin-dependent focal adhesions (FAs) are the converging zones integrating biochemical and biomechanical signals arising from the ECM and the actin cytoskeleton. Thus, integrin-mediated adhesion and mechanotransduction, the conversion of mechanical forces into biochemical signals, are involved in critical cellular functions such as migration, proliferation and differentiation, and their deregulation contributes to pathologies including cancer. A challenging problem is to decipher how stochastic protein movements andmore » interactions lead to formation of dynamic architecture such as integrin-dependent adhesive structures. In this review, we will describe recent advances made possible by super-resolution microscopies and single molecule tracking approaches that provided new understanding on the organization and the dynamics of integrins and intracellular regulators at the nanoscale in living cells.« less

The journey of integrins and partners in a complex interactions landscape studied by super-resolution microscopy and single protein tracking.

PubMed

Rossier, Olivier; Giannone, Grégory

2016-04-10

Cells adjust their adhesive and cytoskeletal organizations according to changes in the biochemical and physical nature of their surroundings. In return, by adhering and generating forces on the extracellular matrix (ECM) cells organize their microenvironment. Integrin-dependent focal adhesions (FAs) are the converging zones integrating biochemical and biomechanical signals arising from the ECM and the actin cytoskeleton. Thus, integrin-mediated adhesion and mechanotransduction, the conversion of mechanical forces into biochemical signals, are involved in critical cellular functions such as migration, proliferation and differentiation, and their deregulation contributes to pathologies including cancer. A challenging problem is to decipher how stochastic protein movements and interactions lead to formation of dynamic architecture such as integrin-dependent adhesive structures. In this review, we will describe recent advances made possible by super-resolution microscopies and single molecule tracking approaches that provided new understanding on the organization and the dynamics of integrins and intracellular regulators at the nanoscale in living cells. Copyright © 2015. Published by Elsevier Inc.

Correlating spin transport and electrode magnetization in a graphene spin valve: Simultaneous magnetic microscopy and non-local measurements

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

Berger, Andrew J., E-mail: berger.156@osu.edu; Page, Michael R.; Bhallamudi, Vidya P.

2015-10-05

Using simultaneous magnetic force microscopy and transport measurements of a graphene spin valve, we correlate the non-local spin signal with the magnetization of the device electrodes. The imaged magnetization states corroborate the influence of each electrode within a one-dimensional spin transport model and provide evidence linking domain wall pinning to additional features in the transport signal.

Imaging chromatin nanostructure with binding-activated localization microscopy based on DNA structure fluctuations

PubMed Central

Szczurek, Aleksander; Klewes, Ludger; Xing, Jun; Gourram, Amine; Birk, Udo; Knecht, Hans; Dobrucki, Jurek W.; Mai, Sabine

2017-01-01

Abstract Advanced light microscopy is an important tool for nanostructure analysis of chromatin. In this report we present a general concept for Single Molecule localization Microscopy (SMLM) super-resolved imaging of DNA-binding dyes based on modifying the properties of DNA and the dye. By careful adjustment of the chemical environment leading to local, reversible DNA melting and hybridization control over the fluorescence signal of the DNA-binding dye molecules can be introduced. We postulate a transient binding as the basis for our variation of binding-activated localization microscopy (BALM). We demonstrate that several intercalating and minor-groove binding DNA dyes can be used to register (optically isolate) only a few DNA-binding dye signals at a time. To highlight this DNA structure fluctuation-assisted BALM (fBALM), we applied it to measure, for the first time, nanoscale differences in nuclear architecture in model ischemia with an anticipated structural resolution of approximately 50 nm. Our data suggest that this approach may open an avenue for the enhanced microscopic analysis of chromatin nano-architecture and hence the microscopic analysis of nuclear structure aberrations occurring in various pathological conditions. It may also become possible to analyse nuclear nanostructure differences in different cell types, stages of development or environmental stress conditions. PMID:28082388

Ecological invasion, roughened fronts, and a competitor's extreme advance: integrating stochastic spatial-growth models.

PubMed

O'Malley, Lauren; Korniss, G; Caraco, Thomas

2009-07-01

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibits universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.

GW150914: Implications for the Stochastic Gravitational-Wave Background from Binary Black Holes

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, D. D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Bustillo, J. Calderón; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Canton, T. Dal; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R. T.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Haris, K.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-04-01

The LIGO detection of the gravitational wave transient GW150914, from the inspiral and merger of two black holes with masses ≳30 M⊙, suggests a population of binary black holes with relatively high mass. This observation implies that the stochastic gravitational-wave background from binary black holes, created from the incoherent superposition of all the merging binaries in the Universe, could be higher than previously expected. Using the properties of GW150914, we estimate the energy density of such a background from binary black holes. In the most sensitive part of the Advanced LIGO and Advanced Virgo band for stochastic backgrounds (near 25 Hz), we predict ΩGW(f =25 Hz )=1. 1-0.9+2.7×10-9 with 90% confidence. This prediction is robustly demonstrated for a variety of formation scenarios with different parameters. The differences between models are small compared to the statistical uncertainty arising from the currently poorly constrained local coalescence rate. We conclude that this background is potentially measurable by the Advanced LIGO and Advanced Virgo detectors operating at their projected final sensitivity.

Tomographic reconstruction of atmospheric turbulence with the use of time-dependent stochastic inversion.

PubMed

Vecherin, Sergey N; Ostashev, Vladimir E; Ziemann, A; Wilson, D Keith; Arnold, K; Barth, M

2007-09-01

Acoustic travel-time tomography allows one to reconstruct temperature and wind velocity fields in the atmosphere. In a recently published paper [S. Vecherin et al., J. Acoust. Soc. Am. 119, 2579 (2006)], a time-dependent stochastic inversion (TDSI) was developed for the reconstruction of these fields from travel times of sound propagation between sources and receivers in a tomography array. TDSI accounts for the correlation of temperature and wind velocity fluctuations both in space and time and therefore yields more accurate reconstruction of these fields in comparison with algebraic techniques and regular stochastic inversion. To use TDSI, one needs to estimate spatial-temporal covariance functions of temperature and wind velocity fluctuations. In this paper, these spatial-temporal covariance functions are derived for locally frozen turbulence which is a more general concept than a widely used hypothesis of frozen turbulence. The developed theory is applied to reconstruction of temperature and wind velocity fields in the acoustic tomography experiment carried out by University of Leipzig, Germany. The reconstructed temperature and velocity fields are presented and errors in reconstruction of these fields are studied.

GW150914: Implications for the Stochastic Gravitational-Wave Background from Binary Black Holes.

PubMed

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Chow, J H; Christensen, N; Chu, Q; Chua, S; Chung, S; Ciani, G; Clara, F; Clark, J A; Cleva, F; Coccia, E; Cohadon, P-F; Colla, A; Collette, C G; Cominsky, L; Constancio, M; Conte, A; Conti, L; Cook, D; Corbitt, T R; Cornish, N; Corsi, A; Cortese, S; Costa, C A; Coughlin, M W; Coughlin, S B; Coulon, J-P; Countryman, S T; Couvares, P; Cowan, E E; Coward, D M; Cowart, M J; Coyne, D C; Coyne, R; Craig, K; Creighton, J D E; Cripe, J; Crowder, S G; Cumming, A; Cunningham, L; Cuoco, E; Canton, T Dal; Danilishin, S L; D'Antonio, S; Danzmann, K; Darman, N S; Dattilo, V; Dave, I; Daveloza, H P; Davier, M; Davies, G S; Daw, E J; Day, R; DeBra, D; Debreczeni, G; Degallaix, J; De Laurentis, M; Deléglise, S; Del Pozzo, W; Denker, T; Dent, T; Dereli, H; Dergachev, V; DeRosa, R T; De Rosa, R; DeSalvo, R; Dhurandhar, S; Díaz, M C; Di Fiore, L; Di Giovanni, M; Di Lieto, A; Di Pace, S; Di Palma, I; Di Virgilio, A; Dojcinoski, G; Dolique, V; Donovan, F; Dooley, K L; Doravari, S; Douglas, R; Downes, T P; Drago, M; Drever, R W P; Driggers, J C; Du, Z; Ducrot, M; Dwyer, S E; Edo, T B; Edwards, M C; Effler, A; Eggenstein, H-B; Ehrens, P; Eichholz, J; Eikenberry, S S; Engels, W; Essick, R C; Etzel, T; Evans, M; Evans, T M; Everett, R; Factourovich, M; Fafone, V; Fair, H; Fairhurst, S; Fan, X; Fang, Q; Farinon, S; Farr, B; Farr, W M; Favata, M; Fays, M; Fehrmann, H; Fejer, M M; Ferrante, I; Ferreira, E C; Ferrini, F; Fidecaro, F; Fiori, I; Fiorucci, D; Fisher, R P; Flaminio, R; Fletcher, M; Fournier, J-D; Franco, S; Frasca, S; Frasconi, F; Frei, Z; Freise, A; Frey, R; Frey, V; Fricke, T T; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gabbard, H A G; Gair, J R; Gammaitoni, L; Gaonkar, S G; Garufi, F; Gatto, A; Gaur, G; Gehrels, N; Gemme, G; Gendre, B; Genin, E; Gennai, A; George, J; Gergely, L; Germain, V; Ghosh, Archisman; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, K; Glaefke, A; Goetz, E; Goetz, R; Gondan, L; González, G; Castro, J M Gonzalez; Gopakumar, A; Gordon, N A; Gorodetsky, M L; Gossan, S E; Gosselin, M; Gouaty, R; Graef, C; Graff, P B; Granata, M; Grant, A; Gras, S; Gray, C; Greco, G; Green, A C; Groot, P; Grote, H; Grunewald, S; Guidi, G M; Guo, X; Gupta, A; Gupta, M K; Gushwa, K E; Gustafson, E K; Gustafson, R; Hacker, J J; Hall, B R; Hall, E D; Hammond, G; Haney, M; Hanke, M M; Hanks, J; Hanna, C; Hannam, M D; Hanson, J; Hardwick, T; Haris, K; Harms, J; Harry, G M; Harry, I W; Hart, M J; Hartman, M T; Haster, C-J; Haughian, K; Heidmann, A; Heintze, M C; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Hennig, J; Heptonstall, A W; Heurs, M; Hild, S; Hoak, D; Hodge, K A; Hofman, D; Hollitt, S E; Holt, K; Holz, D E; Hopkins, P; Hosken, D J; Hough, J; Houston, E A; Howell, E J; Hu, Y M; Huang, S; Huerta, E A; Huet, D; Hughey, B; Husa, S; Huttner, S H; Huynh-Dinh, T; Idrisy, A; Indik, N; Ingram, D R; Inta, R; Isa, H N; Isac, J-M; Isi, M; Islas, G; Isogai, T; Iyer, B R; Izumi, K; Jacqmin, T; Jang, H; Jani, K; Jaranowski, P; Jawahar, S; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; Kalaghatgi, C V; Kalogera, V; Kandhasamy, S; Kang, G; Kanner, J B; Karki, S; Kasprzack, M; Katsavounidis, E; Katzman, W; Kaufer, S; Kaur, T; Kawabe, K; Kawazoe, F; Kéfélian, F; Kehl, M S; Keitel, D; Kelley, D B; Kells, W; Kennedy, R; Key, J S; Khalaidovski, A; Khalili, F Y; Khan, I; Khan, S; Khan, Z; Khazanov, E A; Kijbunchoo, N; Kim, C; Kim, J; Kim, K; Kim, Nam-Gyu; Kim, Namjun; Kim, Y-M; King, E J; King, P J; Kinzel, D L; Kissel, J S; Kleybolte, L; Klimenko, S; Koehlenbeck, S M; Kokeyama, K; Koley, S; Kondrashov, V; Kontos, A; Korobko, M; Korth, W Z; Kowalska, I; Kozak, D B; Kringel, V; Królak, A; Krueger, C; Kuehn, G; Kumar, P; Kuo, L; Kutynia, A; Lackey, B D; Landry, M; Lange, J; Lantz, B; Lasky, P D; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lebigot, E O; Lee, C H; Lee, H K; Lee, H M; Lee, K; Lenon, A; Leonardi, M; Leong, J R; Leroy, N; Letendre, N; Levin, Y; Levine, B M; Li, T G F; Libson, A; Littenberg, T B; Lockerbie, N A; Logue, J; Lombardi, A L; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lück, H; Lundgren, A P; Luo, J; Lynch, R; Ma, Y; MacDonald, T; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña-Sandoval, F; Magee, R M; Mageswaran, M; Majorana, E; Maksimovic, I; Malvezzi, V; Man, N; Mandel, I; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A S; Maros, E; Martelli, F; Martellini, L; Martin, I W; Martin, R M; Martynov, D V; Marx, J N; Mason, K; Masserot, A; Massinger, T J; Masso-Reid, M; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; Mazzolo, G; McCarthy, R; McClelland, D E; McCormick, S; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McWilliams, S T; Meacher, D; Meadors, G D; Meidam, J; Melatos, A; Mendell, G; Mendoza-Gandara, D; Mercer, R A; Merilh, E; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Meyers, P M; Mezzani, F; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, J; Millhouse, M; Minenkov, Y; Ming, J; Mirshekari, S; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moggi, A; Mohan, M; Mohapatra, S R P; Montani, M; Moore, B C; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mossavi, K; Mours, B; Mow-Lowry, C M; Mueller, C L; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Murphy, D J; Murray, P G; Mytidis, A; Nardecchia, I; Naticchioni, L; Nayak, R K; Necula, V; Nedkova, K; Nelemans, G; Neri, M; Neunzert, A; Newton, G; Nguyen, T T; Nielsen, A B; Nissanke, S; Nitz, A; Nocera, F; Nolting, D; Normandin, M E N; Nuttall, L K; Oberling, J; Ochsner, E; O'Dell, J; Oelker, E; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Ottens, R S; Overmier, H; Owen, B J; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Paris, H R; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patricelli, B; Patrick, Z; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perreca, A; Phelps, M; Piccinni, O; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pitkin, M; Poggiani, R; Popolizio, P; Post, A; Powell, J; Prasad, J; Predoi, V; Premachandra, S S; Prestegard, T; Price, L R; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Qin, J; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rakhmanov, M; Rapagnani, P; Raymond, V; Razzano, M; Re, V; Read, J; Reed, C M; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Rew, H; Reyes, S D; Ricci, F; Riles, K; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romanov, G; Romie, J H; Rosińska, D; Rowan, S; Rüdiger, A; Ruggi, P; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sanchez, E J; Sandberg, V; Sandeen, B; Sanders, J R; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Schilling, R; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schutz, B F; Scott, J; Scott, S M; Sellers, D; Sentenac, D; Sequino, V; Sergeev, A; Serna, G; Setyawati, Y; Sevigny, A; Shaddock, D A; Shah, S; Shahriar, M S; Shaltev, M; Shao, Z; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sigg, D; Silva, A D; Simakov, D; Singer, A; Singer, L P; Singh, A; Singh, R; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, J R; Smith, N D; Smith, R J E; Son, E J; Sorazu, B; Sorrentino, F; Souradeep, T; Srivastava, A K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stephens, B C; Stone, R; Strain, K A; Straniero, N; Stratta, G; Strauss, N A; Strigin, S; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Talukder, D; Tanner, D B; Tápai, M; Tarabrin, S P; Taracchini, A; Taylor, R; Theeg, T; Thirugnanasambandam, M P; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thorne, K S; Thrane, E; Tiwari, S; Tiwari, V; Tokmakov, K V; Tomlinson, C; Tonelli, M; Torres, C V; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trifirò, D; Tringali, M C; Trozzo, L; Tse, M; Turconi, M; Tuyenbayev, D; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Vass, S; Vasúth, M; Vaulin, R; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Verkindt, D; Vetrano, F; Viceré, A; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Voss, D; Vousden, W D; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, M; Wang, X; Wang, Y; Ward, R L; Warner, J; Was, M; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Welborn, T; Wen, L; Weßels, P; Westphal, T; Wette, K; Whelan, J T; White, D J; Whiting, B F; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Worden, J; Wright, J L; Wu, G; Yablon, J; Yam, W; Yamamoto, H; Yancey, C C; Yap, M J; Yu, H; Yvert, M; Zadrożny, A; Zangrando, L; Zanolin, M; Zendri, J-P; Zevin, M; Zhang, F; Zhang, L; Zhang, M; Zhang, Y; Zhao, C; Zhou, M; Zhou, Z; Zhu, X J; Zucker, M E; Zuraw, S E; Zweizig, J

2016-04-01

The LIGO detection of the gravitational wave transient GW150914, from the inspiral and merger of two black holes with masses ≳30M_{⊙}, suggests a population of binary black holes with relatively high mass. This observation implies that the stochastic gravitational-wave background from binary black holes, created from the incoherent superposition of all the merging binaries in the Universe, could be higher than previously expected. Using the properties of GW150914, we estimate the energy density of such a background from binary black holes. In the most sensitive part of the Advanced LIGO and Advanced Virgo band for stochastic backgrounds (near 25 Hz), we predict Ω_{GW}(f=25  Hz)=1.1_{-0.9}^{+2.7}×10^{-9} with 90% confidence. This prediction is robustly demonstrated for a variety of formation scenarios with different parameters. The differences between models are small compared to the statistical uncertainty arising from the currently poorly constrained local coalescence rate. We conclude that this background is potentially measurable by the Advanced LIGO and Advanced Virgo detectors operating at their projected final sensitivity.

Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics

NASA Astrophysics Data System (ADS)

Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.

Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.

High-resolution imaging by scanning electron microscopy of semithin sections in correlation with light microscopy.

PubMed

Koga, Daisuke; Kusumi, Satoshi; Shodo, Ryusuke; Dan, Yukari; Ushiki, Tatsuo

2015-12-01

In this study, we introduce scanning electron microscopy (SEM) of semithin resin sections. In this technique, semithin sections were adhered on glass slides, stained with both uranyl acetate and lead citrate, and observed with a backscattered electron detector at a low accelerating voltage. As the specimens are stained in the same manner as conventional transmission electron microscopy (TEM), the contrast of SEM images of semithin sections was similar to TEM images of ultrathin sections. Using this technique, wide areas of semithin sections were also observed by SEM, without the obstruction of grids, which was inevitable for traditional TEM. This study also applied semithin section SEM to correlative light and electron microscopy. Correlative immunofluorescence microscopy and immune-SEM were performed in semithin sections of LR white resin-embedded specimens using a FluoroNanogold-labeled secondary antibody. Because LR white resin is hydrophilic and electron stable, this resin is suitable for immunostaining and SEM observation. Using correlative microscopy, the precise localization of the primary antibody was demonstrated by fluorescence microscopy and SEM. This method has great potential for studies examining the precise localization of molecules, including Golgi- and ER-associated proteins, in correlation with LM and SEM. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Molecular logic behind the three-way stochastic choices that expand butterfly colour vision.

PubMed

Perry, Michael; Kinoshita, Michiyo; Saldi, Giuseppe; Huo, Lucy; Arikawa, Kentaro; Desplan, Claude

2016-07-14

Butterflies rely extensively on colour vision to adapt to the natural world. Most species express a broad range of colour-sensitive Rhodopsin proteins in three types of ommatidia (unit eyes), which are distributed stochastically across the retina. The retinas of Drosophila melanogaster use just two main types, in which fate is controlled by the binary stochastic decision to express the transcription factor Spineless in R7 photoreceptors. We investigated how butterflies instead generate three stochastically distributed ommatidial types, resulting in a more diverse retinal mosaic that provides the basis for additional colour comparisons and an expanded range of colour vision. We show that the Japanese yellow swallowtail (Papilio xuthus, Papilionidae) and the painted lady (Vanessa cardui, Nymphalidae) butterflies have a second R7-like photoreceptor in each ommatidium. Independent stochastic expression of Spineless in each R7-like cell results in expression of a blue-sensitive (Spineless(ON)) or an ultraviolet (UV)-sensitive (Spineless(OFF)) Rhodopsin. In P. xuthus these choices of blue/blue, blue/UV or UV/UV sensitivity in the two R7 cells are coordinated with expression of additional Rhodopsin proteins in the remaining photoreceptors, and together define the three types of ommatidia. Knocking out spineless using CRISPR/Cas9 (refs 5, 6) leads to the loss of the blue-sensitive fate in R7-like cells and transforms retinas into homogeneous fields of UV/UV-type ommatidia, with corresponding changes in other coordinated features of ommatidial type. Hence, the three possible outcomes of Spineless expression define the three ommatidial types in butterflies. This developmental strategy allowed the deployment of an additional red-sensitive Rhodopsin in P. xuthus, allowing for the evolution of expanded colour vision with a greater variety of receptors. This surprisingly simple mechanism that makes use of two binary stochastic decisions coupled with local coordination may prove to be a general means of generating an increased diversity of developmental outcomes.

Statistical signatures of a targeted search by bacteria

NASA Astrophysics Data System (ADS)

Jashnsaz, Hossein; Anderson, Gregory G.; Pressé, Steve

2017-12-01

Chemoattractant gradients are rarely well-controlled in nature and recent attention has turned to bacterial chemotaxis toward typical bacterial food sources such as food patches or even bacterial prey. In environments with localized food sources reminiscent of a bacterium’s natural habitat, striking phenomena—such as the volcano effect or banding—have been predicted or expected to emerge from chemotactic models. However, in practice, from limited bacterial trajectory data it is difficult to distinguish targeted searches from an untargeted search strategy for food sources. Here we use a theoretical model to identify statistical signatures of a targeted search toward point food sources, such as prey. Our model is constructed on the basis that bacteria use temporal comparisons to bias their random walk, exhibit finite memory and are subject to random (Brownian) motion as well as signaling noise. The advantage with using a stochastic model-based approach is that a stochastic model may be parametrized from individual stochastic bacterial trajectories but may then be used to generate a very large number of simulated trajectories to explore average behaviors obtained from stochastic search strategies. For example, our model predicts that a bacterium’s diffusion coefficient increases as it approaches the point source and that, in the presence of multiple sources, bacteria may take substantially longer to locate their first source giving the impression of an untargeted search strategy.

Image recovery by removing stochastic artefacts identified as local asymmetries

NASA Astrophysics Data System (ADS)

Osterloh, K.; Bücherl, T.; Zscherpel, U.; Ewert, U.

2012-04-01

Stochastic artefacts are frequently encountered in digital radiography and tomography with neutrons. Most obviously, they are caused by ubiquitous scattered radiation hitting the CCD-sensor. They appear as scattered dots and, at higher frequency of occurrence, they may obscure the image. Some of these dotted interferences vary with time, however, a large portion of them remains persistent so the problem cannot be resolved by collecting stacks of images and to merge them to a median image. The situation becomes even worse in computed tomography (CT) where each artefact causes a circular pattern in the reconstructed plane. Therefore, these stochastic artefacts have to be removed completely and automatically while leaving the original image content untouched. A simplified image acquisition and artefact removal tool was developed at BAM and is available to interested users. Furthermore, an algorithm complying with all the requirements mentioned above was developed that reliably removes artefacts that could even exceed the size of a single pixel without affecting other parts of the image. It consists of an iterative two-step algorithm adjusting pixel values within a 3 × 3 matrix inside of a 5 × 5 kernel and the centre pixel only within a 3 × 3 kernel, resp. It has been applied to thousands of images obtained from the NECTAR facility at the FRM II in Garching, Germany, without any need of a visual control. In essence, the procedure consists of identifying and tackling asymmetric intensity distributions locally with recording each treatment of a pixel. Searching for the local asymmetry with subsequent correction rather than replacing individually identified pixels constitutes the basic idea of the algorithm. The efficiency of the proposed algorithm is demonstrated with a severely spoiled example of neutron radiography and tomography as compared with median filtering, the most convenient alternative approach by visual check, histogram and power spectra analysis.

Dynamically Consistent Parameterization of Mesoscale Eddies This work aims at parameterization of eddy effects for use in non-eddy-resolving ocean models and focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones.

NASA Astrophysics Data System (ADS)

Berloff, P. S.

2016-12-01

This work aims at developing a framework for dynamically consistent parameterization of mesoscale eddy effects for use in non-eddy-resolving ocean circulation models. The proposed eddy parameterization framework is successfully tested on the classical, wind-driven double-gyre model, which is solved both with explicitly resolved vigorous eddy field and in the non-eddy-resolving configuration with the eddy parameterization replacing the eddy effects. The parameterization focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones. The parameterization locally approximates transient eddy flux divergence by spatially localized and temporally periodic forcing, referred to as the plunger, and focuses on the linear-dynamics flow solution induced by it. The nonlinear self-interaction of this solution, referred to as the footprint, characterizes and quantifies the induced eddy forcing exerted on the large-scale flow. We find that spatial pattern and amplitude of each footprint strongly depend on the underlying large-scale flow, and the corresponding relationships provide the basis for the eddy parameterization and its closure on the large-scale flow properties. Dependencies of the footprints on other important parameters of the problem are also systematically analyzed. The parameterization utilizes the local large-scale flow information, constructs and scales the corresponding footprints, and then sums them up over the gyres to produce the resulting eddy forcing field, which is interactively added to the model as an extra forcing. Thus, the assumed ensemble of plunger solutions can be viewed as a simple model for the cumulative effect of the stochastic eddy forcing. The parameterization framework is implemented in the simplest way, but it provides a systematic strategy for improving the implementation algorithm.

Multiple mechanisms of early plant community assembly with stochasticity driving the process.

PubMed

Marteinsdóttir, Bryndís; Svavarsdóttir, Kristín; Thórhallsdóttir, Thóra Ellen

2018-01-01

Initial plant establishment is one of the most critical phases in ecosystem development, where an early suite of physical (environmental filtering), biological (seed limitation, species interactions) and stochastic factors may affect successional trajectories and rates. While functional traits are commonly used to study processes that influence plant community assembly in late successional communities, few studies have applied them to primary succession. The objective here was to determine the importance of these factors in shaping early plant community assembly on a glacial outwash plain, Skeiðarársandur, in SE Iceland using a trait based approach. We used data on vascular plant assemblages at two different spatial scales (community and neighborhood) sampled in 2005 and 2012, and compiled a dataset on seven functional traits linked to species dispersal abilities, establishment, and persistence for all species within these assemblages. Trait-based null model analyses were used to determine the processes that influenced plant community assembly from the regional species pool into local communities, and to determine if the importance of these processes in community assembly was dependent on local environment or changed with time. On the community scale, for most traits, random processes dominated the assembly from the regional species pool. However, in some communities, there was evidence of non-random assembly in relation to traits linked to species dispersal abilities, persistence, and establishment. On the neighborhood scale, assembly was mostly random. The relative importance of different processes varied spatially and temporally and the variation was linked to local soil conditions. While stochasticity dominated assembly patterns of our early successional communities, there was evidence of both seed limitation and environmental filtering. Our results indicated that as soil conditions improved, environmental constraints on assembly became weaker and the assembly became more dependent on species availability. © 2017 by the Ecological Society of America.

Membrane curvature and the Tol-Pal complex determine polar localization of the chemoreceptor Tar in E. coli.

PubMed

Saaki, Terrens N V; Strahl, Henrik; Hamoen, Leendert W

2018-02-20

Chemoreceptors are localized at the cell poles of Escherichia coli and other rod-shaped bacteria. Over the years different mechanisms have been put forward to explain this polar localization; from stochastic clustering, membrane curvature driven localization, interactions with the Tol-Pal complex, to nucleoid exclusion. To evaluate these mechanisms, we monitored the cellular localization of the aspartate chemoreceptor Tar in different deletion mutants. We did not find any indication for either stochastic cluster formation or nucleoid exclusion. However, the presence of a functional Tol-Pal complex appeared to be essential to retain Tar at cell poles. Interestingly, Tar still accumulated at midcell in tol and in pal deletion mutants. In these mutants, the protein appears to gather at the base of division septa, a region characterised by strong membrane curvature. Chemoreceptors, like Tar, form trimer-of-dimers that bend the cell membrane due to a rigid tripod structure. The curvature approaches the curvature of the cell membrane generated during cell division, and localization of chemoreceptor tripods at curved membrane areas is therefore energetically favourable as it lowers membrane tension. Indeed, when we introduced mutations in Tar that abolish the rigid tripod structure, the protein was no longer able to accumulate at midcell or cell poles. These findings favour a model where chemoreceptor localization in E. coli is driven by strong membrane curvature and association with the Tol-Pal complex. Importance Bacteria have exquisite mechanisms to sense and to adapt to the environment they live in. One such mechanism involves the chemotaxis signal transduction pathway, in which chemoreceptors specifically bind certain attracting or repelling molecules and transduce the signals to the cell. In different rod-shaped bacteria, these chemoreceptors localize specifically to cell poles. Here, we examined the polar localization of the aspartate chemoreceptor Tar in E. coli , and found that membrane curvature at cell division sites and the Tol-Pal protein complex, localize Tar at cell division sites, the future cell poles. This study shows how membrane curvature can guide localization of proteins in a cell. Copyright © 2018 American Society for Microbiology.

Classical and quantum localization and delocalization in the Fermi accelerator, kicked rotor and two-sided kicked rotor models

NASA Astrophysics Data System (ADS)

Zaslavsky, M.

1996-06-01

The phenomena of dynamical localization, both classical and quantum, are studied in the Fermi accelerator model. The model consists of two vertical oscillating walls and a ball bouncing between them. The classical localization boundary is calculated in the case of ``sinusoidal velocity transfer'' [A. J. Lichtenberg and M. A. Lieberman, Regular and Stochastic Motion (Springer-Verlag, Berlin, 1983)] on the basis of the analysis of resonances. In the case of the ``sawtooth'' wall velocity we show that the quantum localization is determined by the analytical properties of the canonical transformations to the action and angle coordinates of the unperturbed Hamiltonian, while the existence of the classical localization is determined by the number of continuous derivatives of the distance between the walls with respect to time.

Genetically encoded sensors and fluorescence microscopy for anticancer research

NASA Astrophysics Data System (ADS)

Zagaynova, Elena V.; Shirmanova, Marina V.; Sergeeva, Tatiana F.; Klementieva, Natalia V.; Mishin, Alexander S.; Gavrina, Alena I.; Zlobovskay, Olga A.; Furman, Olga E.; Dudenkova, Varvara V.; Perelman, Gregory S.; Lukina, Maria M.; Lukyanov, Konstantin A.

2017-02-01

Early response of cancer cells to chemical compounds and chemotherapeutic drugs were studied using novel fluorescence tools and microscopy techniques. We applied confocal microscopy, two-photon fluorescence lifetime imaging microscopy and super-resolution localization-based microscopy to assess structural and functional changes in cancer cells in vitro. The dynamics of energy metabolism, intracellular pH, caspase-3 activation during staurosporine-induced apoptosis as well as actin cytoskeleton rearrangements under chemotherapy were evaluated. We have showed that new genetically encoded sensors and advanced fluorescence microscopy methods provide an efficient way for multiparameter analysis of cell activities

Organic nanofibers from squarylium dyes: local morphology, optical, and electrical properties

NASA Astrophysics Data System (ADS)

Balzer, Frank; Schiek, Manuela; Osadnik, Andreas; Lützen, Arne; Rubahn, Horst-Günter

2012-02-01

Environmentally stable, non-toxic squarylium dyes with strong absorption maxima in the red and near infrared spectral region are known for almost fifty years. Despite the fact that their optoelectronic properties distinguish them as promising materials for organics based photovoltaic cells, they have regained attention only very recently. For their application in heterojunction solar cells knowledge of their nanoscopic morphology as well as nanoscopic electrical properties is paramount. In this paper thin films from two different squarylium dyes, from squarylium (SQ) and from hydroxy-squarylium (SQOH) are investigated. The thin films are either solution casted or vacuum sublimed onto substrates such as muscovite mica, which are known to promote self-assembly into oriented, crystalline nanostructures such as nanofibers. Local characterization is performed via (polarized) optical microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and Kelvin probe force microscopy (KPFM).

On the intrinsic timescales of temporal variability in measurements of the surface solar radiation

NASA Astrophysics Data System (ADS)

Bengulescu, Marc; Blanc, Philippe; Wald, Lucien

2018-01-01

This study is concerned with the intrinsic temporal scales of the variability in the surface solar irradiance (SSI). The data consist of decennial time series of daily means of the SSI obtained from high-quality measurements of the broadband solar radiation impinging on a horizontal plane at ground level, issued from different Baseline Surface Radiation Network (BSRN) ground stations around the world. First, embedded oscillations sorted in terms of increasing timescales of the data are extracted by empirical mode decomposition (EMD). Next, Hilbert spectral analysis is applied to obtain an amplitude-modulation-frequency-modulation (AM-FM) representation of the data. The time-varying nature of the characteristic timescales of variability, along with the variations in the signal intensity, are thus revealed. A novel, adaptive null hypothesis based on the general statistical characteristics of noise is employed in order to discriminate between the different features of the data, those that have a deterministic origin and those being realizations of various stochastic processes. The data have a significant spectral peak corresponding to the yearly variability cycle and feature quasi-stochastic high-frequency variability components, irrespective of the geographical location or of the local climate. Moreover, the amplitude of this latter feature is shown to be modulated by variations in the yearly cycle, which is indicative of nonlinear multiplicative cross-scale couplings. The study has possible implications on the modeling and the forecast of the surface solar radiation, by clearly discriminating the deterministic from the quasi-stochastic character of the data, at different local timescales.

Super-Resolution Imaging of Molecular Emission Spectra and Single Molecule Spectral Fluctuations

PubMed Central

Mlodzianoski, Michael J.; Curthoys, Nikki M.; Gunewardene, Mudalige S.; Carter, Sean; Hess, Samuel T.

2016-01-01

Localization microscopy can image nanoscale cellular details. To address biological questions, the ability to distinguish multiple molecular species simultaneously is invaluable. Here, we present a new version of fluorescence photoactivation localization microscopy (FPALM) which detects the emission spectrum of each localized molecule, and can quantify changes in emission spectrum of individual molecules over time. This information can allow for a dramatic increase in the number of different species simultaneously imaged in a sample, and can create super-resolution maps showing how single molecule emission spectra vary with position and time in a sample. PMID:27002724

Axial Colocalization of Single Molecules with Nanometer Accuracy Using Metal-Induced Energy Transfer.

PubMed

Isbaner, Sebastian; Karedla, Narain; Kaminska, Izabela; Ruhlandt, Daja; Raab, Mario; Bohlen, Johann; Chizhik, Alexey; Gregor, Ingo; Tinnefeld, Philip; Enderlein, Jörg; Tsukanov, Roman

2018-04-11

Single-molecule localization based super-resolution microscopy has revolutionized optical microscopy and routinely allows for resolving structural details down to a few nanometers. However, there exists a rather large discrepancy between lateral and axial localization accuracy, the latter typically three to five times worse than the former. Here, we use single-molecule metal-induced energy transfer (smMIET) to localize single molecules along the optical axis, and to measure their axial distance with an accuracy of 5 nm. smMIET relies only on fluorescence lifetime measurements and does not require additional complex optical setups.

Violation of local realism with freedom of choice

PubMed Central

Scheidl, Thomas; Ursin, Rupert; Kofler, Johannes; Ramelow, Sven; Ma, Xiao-Song; Herbst, Thomas; Ratschbacher, Lothar; Fedrizzi, Alessandro; Langford, Nathan K.; Jennewein, Thomas; Zeilinger, Anton

2010-01-01

Bell’s theorem shows that local realistic theories place strong restrictions on observable correlations between different systems, giving rise to Bell’s inequality which can be violated in experiments using entangled quantum states. Bell’s theorem is based on the assumptions of realism, locality, and the freedom to choose between measurement settings. In experimental tests, “loopholes” arise which allow observed violations to still be explained by local realistic theories. Violating Bell’s inequality while simultaneously closing all such loopholes is one of the most significant still open challenges in fundamental physics today. In this paper, we present an experiment that violates Bell’s inequality while simultaneously closing the locality loophole and addressing the freedom-of-choice loophole, also closing the latter within a reasonable set of assumptions. We also explain that the locality and freedom-of-choice loopholes can be closed only within nondeterminism, i.e., in the context of stochastic local realism. PMID:21041665

Violation of local realism with freedom of choice.

PubMed

Scheidl, Thomas; Ursin, Rupert; Kofler, Johannes; Ramelow, Sven; Ma, Xiao-Song; Herbst, Thomas; Ratschbacher, Lothar; Fedrizzi, Alessandro; Langford, Nathan K; Jennewein, Thomas; Zeilinger, Anton

2010-11-16

Bell's theorem shows that local realistic theories place strong restrictions on observable correlations between different systems, giving rise to Bell's inequality which can be violated in experiments using entangled quantum states. Bell's theorem is based on the assumptions of realism, locality, and the freedom to choose between measurement settings. In experimental tests, "loopholes" arise which allow observed violations to still be explained by local realistic theories. Violating Bell's inequality while simultaneously closing all such loopholes is one of the most significant still open challenges in fundamental physics today. In this paper, we present an experiment that violates Bell's inequality while simultaneously closing the locality loophole and addressing the freedom-of-choice loophole, also closing the latter within a reasonable set of assumptions. We also explain that the locality and freedom-of-choice loopholes can be closed only within nondeterminism, i.e., in the context of stochastic local realism.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

Local infrasound is widely used to constrain source parameters of near-surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3-D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere-dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

Self-interference 3D super-resolution microscopy for deep tissue investigations.

PubMed

Bon, Pierre; Linarès-Loyez, Jeanne; Feyeux, Maxime; Alessandri, Kevin; Lounis, Brahim; Nassoy, Pierre; Cognet, Laurent

2018-06-01

Fluorescence localization microscopy has achieved near-molecular resolution capable of revealing ultra-structures, with a broad range of applications, especially in cellular biology. However, it remains challenging to attain such resolution in three dimensions and inside biological tissues beyond the first cell layer. Here we introduce SELFI, a framework for 3D single-molecule localization within multicellular specimens and tissues. The approach relies on self-interference generated within the microscope's point spread function (PSF) to simultaneously encode equiphase and intensity fluorescence signals, which together provide the 3D position of an emitter. We combined SELFI with conventional localization microscopy to visualize F-actin 3D filament networks and reveal the spatial distribution of the transcription factor OCT4 in human induced pluripotent stem cells at depths up to 50 µm inside uncleared tissue spheroids. SELFI paves the way to nanoscale investigations of native cellular processes in intact tissues.

Multi-color localization microscopy of fixed cells as a promising tool to study organization of bacterial cytoskeleton

NASA Astrophysics Data System (ADS)

Vedyaykin, A. D.; Gorbunov, V. V.; Sabantsev, A. V.; Polinovskaya, V. S.; Vishnyakov, I. E.; Melnikov, A. S.; Serdobintsev, P. Yu; Khodorkovskii, M. A.

2015-11-01

Localization microscopy allows visualization of biological structures with resolution well below the diffraction limit. Localization microscopy was used to study FtsZ organization in Escherichia coli previously in combination with fluorescent protein labeling, but the fact that fluorescent chimeric protein was unable to rescue temperature-sensitive ftsZ mutants suggests that obtained images may not represent native FtsZ structures faithfully. Indirect immunolabeling of FtsZ not only overcomes this problem, but also allows the use of the powerful visualization methods arsenal available for different structures in fixed cells. In this work we simultaneously obtained super-resolution images of FtsZ structures and diffraction-limited or super-resolution images of DNA and cell surface in E. coli, which allows for the study of the spatial arrangement of FtsZ structures with respect to the nucleoid positions and septum formation.

Superresolution Imaging of Human Cytomegalovirus vMIA Localization in Sub-Mitochondrial Compartments

PubMed Central

Bhuvanendran, Shivaprasad; Salka, Kyle; Rainey, Kristin; Sreetama, Sen Chandra; Williams, Elizabeth; Leeker, Margretha; Prasad, Vidhya; Boyd, Jonathan; Patterson, George H.; Jaiswal, Jyoti K.; Colberg-Poley, Anamaris M.

2014-01-01

The human cytomegalovirus (HCMV) viral mitochondria-localized inhibitor of apoptosis (vMIA) protein, traffics to mitochondria-associated membranes (MAM), where the endoplasmic reticulum (ER) contacts the outer mitochondrial membrane (OMM). vMIA association with the MAM has not been visualized by imaging. Here, we have visualized this by using a combination of confocal and superresolution imaging. Deconvolution of confocal microscopy images shows vMIA localizes away from mitochondrial matrix at the Mitochondria-ER interface. By gated stimulated emission depletion (GSTED) imaging, we show that along this interface vMIA is distributed in clusters. Through multicolor, multifocal structured illumination microscopy (MSIM), we find vMIA clusters localize away from MitoTracker Red, indicating its OMM localization. GSTED and MSIM imaging show vMIA exists in clusters of ~100–150 nm, which is consistent with the cluster size determined by Photoactivated Localization Microscopy (PALM). With these diverse superresolution approaches, we have imaged the clustered distribution of vMIA at the OMM adjacent to the ER. Our findings directly compare the relative advantages of each of these superresolution imaging modalities for imaging components of the MAM and sub-mitochondrial compartments. These studies establish the ability of superresolution imaging to provide valuable insight into viral protein location, particularly in the sub-mitochondrial compartments, and into their clustered organization. PMID:24721787

Superresolution Microscopy of the Nuclear Envelope and Associated Proteins.

PubMed

Xie, Wei; Horn, Henning F; Wright, Graham D

2016-01-01

Superresolution microscopy is undoubtedly one of the most exciting technologies since the invention of the optical microscope. Capable of nanometer-scale resolution to surpass the diffraction limit and coupled with the versatile labeling techniques available, it is revolutionizing the study of cell biology. Our understanding of the nucleus, the genetic and architectural center of the cell, has gained great advancements through the application of various superresolution microscopy techniques. This chapter describes detailed procedures of multichannel superresolution imaging of the mammalian nucleus, using structured illumination microscopy and single-molecule localization microscopy.

A Microfluidic Platform for Correlative Live-Cell and Super-Resolution Microscopy

PubMed Central

Tam, Johnny; Cordier, Guillaume Alan; Bálint, Štefan; Sandoval Álvarez, Ángel; Borbely, Joseph Steven; Lakadamyali, Melike

2014-01-01

Recently, super-resolution microscopy methods such as stochastic optical reconstruction microscopy (STORM) have enabled visualization of subcellular structures below the optical resolution limit. Due to the poor temporal resolution, however, these methods have mostly been used to image fixed cells or dynamic processes that evolve on slow time-scales. In particular, fast dynamic processes and their relationship to the underlying ultrastructure or nanoscale protein organization cannot be discerned. To overcome this limitation, we have recently developed a correlative and sequential imaging method that combines live-cell and super-resolution microscopy. This approach adds dynamic background to ultrastructural images providing a new dimension to the interpretation of super-resolution data. However, currently, it suffers from the need to carry out tedious steps of sample preparation manually. To alleviate this problem, we implemented a simple and versatile microfluidic platform that streamlines the sample preparation steps in between live-cell and super-resolution imaging. The platform is based on a microfluidic chip with parallel, miniaturized imaging chambers and an automated fluid-injection device, which delivers a precise amount of a specified reagent to the selected imaging chamber at a specific time within the experiment. We demonstrate that this system can be used for live-cell imaging, automated fixation, and immunostaining of adherent mammalian cells in situ followed by STORM imaging. We further demonstrate an application by correlating mitochondrial dynamics, morphology, and nanoscale mitochondrial protein distribution in live and super-resolution images. PMID:25545548

Unconventional Imaging Methods to Capture Transient Structures during Actomyosin Interaction.

PubMed

Katayama, Eisaku; Kodera, Noriyuki

2018-05-08

Half a century has passed since the cross-bridge structure was recognized as the molecular machine that generates muscle tension. Despite various approaches by a number of scientists, information on the structural changes in the myosin heads, particularly its transient configurations, remains scant even now, in part because of their small size and rapid stochastic movements during the power stroke. Though progress in cryo-electron microscopy is eagerly awaited as the ultimate means to elucidate structural details, the introduction of some unconventional methods that provide high-contrast raw images of the target protein assemblies is quite useful, if available, to break the current impasse. Quick-freeze deep⁻etch⁻replica electron microscopy coupled with dedicated image analysis procedures, and high-speed atomic-force microscopy are two such candidates. We have applied the former to visualize actin-associated myosin heads under in vitro motility assay conditions, and found that they take novel configurations similar to the SH1⁻SH2-crosslinked myosin that we characterized recently. By incorporating biochemical and biophysical results, we have revised the cross-bridge mechanism to involve the new conformer as an important main player. The latter “microscopy” is unique and advantageous enabling continuous observation of various protein assemblies as they function. Direct observation of myosin-V’s movement along actin filaments revealed several unexpected behaviors such as foot-stomping of the leading head and unwinding of the coiled-coil tail. The potential contribution of these methods with intermediate spatial resolution is discussed.

Complexity reduction of rate-equations models for two-choice decision-making.

PubMed

Carrillo, José Antonio; Cordier, Stéphane; Deco, Gustavo; Mancini, Simona

2013-01-01

We are concerned with the complexity reduction of a stochastic system of differential equations governing the dynamics of a neuronal circuit describing a decision-making task. This reduction is based on the slow-fast behavior of the problem and holds on the whole phase space and not only locally around the spontaneous state. Macroscopic quantities, such as performance and reaction times, computed applying this reduction are in agreement with previous works in which the complexity reduction is locally performed at the spontaneous point by means of a Taylor expansion.

A comparison of DEA and SFA using micro- and macro-level perspectives: Efficiency of Chinese local banks

NASA Astrophysics Data System (ADS)

Silva, Thiago Christiano; Tabak, Benjamin Miranda; Cajueiro, Daniel Oliveira; Dias, Marina Villas Boas

2017-03-01

This study investigates to which extent results produced by a single frontier model are reliable, based on the application of data envelopment analysis and stochastic frontier approach to a sample of Chinese local banks. Our findings show they produce a consistent trend on global efficiency scores over the years. However, rank correlations indicate they diverge with respect to individual performance diagnoses. Therefore, these models provide steady information on the efficiency of the banking system as a whole, but they become divergent at the individual level.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

ERIC Educational Resources Information Center

Snijders, Tom A. B.; Steglich, Christian E. G.

2015-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

Important parameters for smoke plume rise simulation with Daysmoke

Treesearch

L. Liu; G.L. Achtemeier; S.L. Goodrick; W. Jackson

2010-01-01

Daysmoke is a local smoke transport model and has been used to provide smoke plume rise information. It includes a large number of parameters describing the dynamic and stochastic processes of particle upward movement, fallout, fluctuation, and burn emissions. This study identifies the important parameters for Daysmoke simulations of plume rise and seeks to understand...

Two-Photon Excitation Microscopy for the Study of Living Cells and Tissues

PubMed Central

Benninger, Richard K.P.; Piston, David W.

2013-01-01

Two-photon excitation microscopy is an alternative to confocal microscopy that provides advantages for three-dimensional and deep tissue imaging. This unit will describe the basic physical principles behind two-photon excitation and discuss the advantages and limitations of its use in laser-scanning microscopy. The principal advantages of two-photon microscopy are reduced phototoxicity, increased imaging depth, and the ability to initiate highly localized photochemistry in thick samples. Practical considerations for the application of two-photon microscopy will then be discussed, including recent technological advances. This unit will conclude with some recent applications of two-photon microscopy that highlight the key advantages over confocal microscopy and the types of experiments which would benefit most from its application. PMID:23728746

Receptor dimer stabilization by hierarchical plasma membrane microcompartments regulates cytokine signaling

PubMed Central

You, Changjiang; Marquez-Lago, Tatiana T.; Richter, Christian Paolo; Wilmes, Stephan; Moraga, Ignacio; Garcia, K. Christopher; Leier, André; Piehler, Jacob

2016-01-01

The interaction dynamics of signaling complexes is emerging as a key determinant that regulates the specificity of cellular responses. We present a combined experimental and computational study that quantifies the consequences of plasma membrane microcompartmentalization for the dynamics of type I interferon receptor complexes. By using long-term dual-color quantum dot (QD) tracking, we found that the lifetime of individual ligand-induced receptor heterodimers depends on the integrity of the membrane skeleton (MSK), which also proved important for efficient downstream signaling. By pair correlation tracking and localization microscopy as well as by fast QD tracking, we identified a secondary confinement within ~300-nm-sized zones. A quantitative spatial stochastic diffusion-reaction model, entirely parameterized on the basis of experimental data, predicts that transient receptor confinement by the MSK meshwork allows for rapid reassociation of dissociated receptor dimers. Moreover, the experimentally observed apparent stabilization of receptor dimers in the plasma membrane was reproduced by simulations of a refined, hierarchical compartment model. Our simulations further revealed that the two-dimensional association rate constant is a key parameter for controlling the extent of MSK-mediated stabilization of protein complexes, thus ensuring the specificity of this effect. Together, experimental evidence and simulations support the hypothesis that passive receptor confinement by MSK-based microcompartmentalization promotes maintenance of signaling complexes in the plasma membrane. PMID:27957535

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

Localizer: fast, accurate, open-source, and modular software package for superresolution microscopy

PubMed Central

Duwé, Sam; Neely, Robert K.; Zhang, Jin

2012-01-01

Abstract. We present Localizer, a freely available and open source software package that implements the computational data processing inherent to several types of superresolution fluorescence imaging, such as localization (PALM/STORM/GSDIM) and fluctuation imaging (SOFI/pcSOFI). Localizer delivers high accuracy and performance and comes with a fully featured and easy-to-use graphical user interface but is also designed to be integrated in higher-level analysis environments. Due to its modular design, Localizer can be readily extended with new algorithms as they become available, while maintaining the same interface and performance. We provide front-ends for running Localizer from Igor Pro, Matlab, or as a stand-alone program. We show that Localizer performs favorably when compared with two existing superresolution packages, and to our knowledge is the only freely available implementation of SOFI/pcSOFI microscopy. By dramatically improving the analysis performance and ensuring the easy addition of current and future enhancements, Localizer strongly improves the usability of superresolution imaging in a variety of biomedical studies. PMID:23208219

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

Tipireddy, R.; Stinis, P.; Tartakovsky, A. M.

In this paper, we present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support ourmore » construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Lastly, our results show that highly accurate global solutions can be obtained with significantly reduced computational costs.« less

A shifted hyperbolic augmented Lagrangian-based artificial fish two-swarm algorithm with guaranteed convergence for constrained global optimization

NASA Astrophysics Data System (ADS)

Rocha, Ana Maria A. C.; Costa, M. Fernanda P.; Fernandes, Edite M. G. P.

2016-12-01

This article presents a shifted hyperbolic penalty function and proposes an augmented Lagrangian-based algorithm for non-convex constrained global optimization problems. Convergence to an ?-global minimizer is proved. At each iteration k, the algorithm requires the ?-global minimization of a bound constrained optimization subproblem, where ?. The subproblems are solved by a stochastic population-based metaheuristic that relies on the artificial fish swarm paradigm and a two-swarm strategy. To enhance the speed of convergence, the algorithm invokes the Nelder-Mead local search with a dynamically defined probability. Numerical experiments with benchmark functions and engineering design problems are presented. The results show that the proposed shifted hyperbolic augmented Lagrangian compares favorably with other deterministic and stochastic penalty-based methods.

Electronic excitation and quenching of atoms at insulator surfaces

NASA Technical Reports Server (NTRS)

Swaminathan, P. K.; Garrett, Bruce C.; Murthy, C. S.

1988-01-01

A trajectory-based semiclassical method is used to study electronically inelastic collisions of gas atoms with insulator surfaces. The method provides for quantum-mechanical treatment of the internal electronic dynamics of a localized region involving the gas/surface collision, and a classical treatment of all the nuclear degrees of freedom (self-consistently and in terms of stochastic trajectories), and includes accurate simulation of the bath-temperature effects. The method is easy to implement and has a generality that holds promise for many practical applications. The problem of electronically inelastic dynamics is solved by computing a set of stochastic trajectories that on thermal averaging directly provide electronic transition probabilities at a given temperature. The theory is illustrated by a simple model of a two-state gas/surface interaction.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

PubMed Central

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

Empirical likelihood-based tests for stochastic ordering

PubMed Central

BARMI, HAMMOU EL; MCKEAGUE, IAN W.

2013-01-01

This paper develops an empirical likelihood approach to testing for the presence of stochastic ordering among univariate distributions based on independent random samples from each distribution. The proposed test statistic is formed by integrating a localized empirical likelihood statistic with respect to the empirical distribution of the pooled sample. The asymptotic null distribution of this test statistic is found to have a simple distribution-free representation in terms of standard Brownian bridge processes. The approach is used to compare the lengths of rule of Roman Emperors over various historical periods, including the “decline and fall” phase of the empire. In a simulation study, the power of the proposed test is found to improve substantially upon that of a competing test due to El Barmi and Mukerjee. PMID:23874142

Inversion method based on stochastic optimization for particle sizing.

PubMed

Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix

2016-08-01

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

Spontaneous Ca2+ sparks and Ca2+ homeostasis in a minimal model of permeabilized ventricular myocytes

PubMed Central

Hartman, Jana M.; Sobie, Eric A.

2010-01-01

Many issues remain unresolved concerning how local, subcellular Ca2+ signals interact with bulk cellular concentrations to maintain homeostasis in health and disease. To aid in the interpretation of data obtained in quiescent ventricular myocytes, we present here a minimal whole cell model that accounts for both localized (subcellular) and global (cellular) aspects of Ca2+ signaling. Using a minimal formulation of the distribution of local [Ca2+] associated with a large number of Ca2+-release sites, the model simulates both random spontaneous Ca2+ sparks and the changes in myoplasmic and sarcoplasmic reticulum (SR) [Ca2+] that result from the balance between stochastic release and reuptake into the SR. Ca2+-release sites are composed of clusters of two-state ryanodine receptors (RyRs) that exhibit activation by local cytosolic [Ca2+] but no inactivation or regulation by luminal Ca2+. Decreasing RyR open probability in the model causes a decrease in aggregate release flux and an increase in SR [Ca2+], regardless of whether RyR inhibition is mediated by a decrease in RyR open dwell time or an increase in RyR closed dwell time. The same balance of stochastic release and reuptake can be achieved, however, by either high-frequency/short-duration or low-frequency/long-duration Ca2+ sparks. The results are well correlated with recent experimental observations using pharmacological RyR inhibitors and clarify those aspects of the release-reuptake balance that are inherent to the coupling between local and global Ca2+ signals and those aspects that depend on molecular-level details. The model of Ca2+ sparks and homeostasis presented here can be a useful tool for understanding changes in cardiac Ca2+ release resulting from drugs, mutations, or acquired diseases. PMID:20852058

Scattering (stochastic) recoupling of a coupled ten-stripe AlGaAs-GaAs-InGaAs quantum-well heterostructure laser

NASA Astrophysics Data System (ADS)

Kellogg, D. A.; Holonyak, N.

2001-04-01

Data are presented on coupled ten-stripe AlGaAs-GaAs-InGaAs quantum well heterostructure (QWH) lasers recoupled stochastically at the cleaved end mirrors. Recoupling of neighboring elements of a ten-stripe laser is accomplished by the scattering (random feedback) afforded by applying ˜10-μm-diam Al powder or 0.3 μm α-Al2O3 polishing compound in microscopy immersion oil or in epoxy at the cleaved ends (mirrors). Data on QWH samples with the end mirrors coated with the scatterer (Al or Al2O3 powder in "liquid") exhibit spectral and far-field broadening, as well as increased laser threshold because of the reduced cavity Q. Single mode operation is possible with the conventional evanescent wave coupling of the ten-stripe QWH and is destroyed, even the laser operation itself, with the scattering recoupling (dephasing) at the end mirrors, which is reversible (removable). The narrow ten-stripe QWH laser with strong end-mirror scattering, a long amplifier with random feedback, indicates that a photopumped III-V or II-VI powder (a random "wall" cavity) has little or no merit.

Wavefront correction using machine learning methods for single molecule localization microscopy

NASA Astrophysics Data System (ADS)

Tehrani, Kayvan F.; Xu, Jianquan; Kner, Peter

2015-03-01

Optical Aberrations are a major challenge in imaging biological samples. In particular, in single molecule localization (SML) microscopy techniques (STORM, PALM, etc.) a high Strehl ratio point spread function (PSF) is necessary to achieve sub-diffraction resolution. Distortions in the PSF shape directly reduce the resolution of SML microscopy. The system aberrations caused by the imperfections in the optics and instruments can be compensated using Adaptive Optics (AO) techniques prior to imaging. However, aberrations caused by the biological sample, both static and dynamic, have to be dealt with in real time. A challenge for wavefront correction in SML microscopy is a robust optimization approach in the presence of noise because of the naturally high fluctuations in photon emission from single molecules. Here we demonstrate particle swarm optimization for real time correction of the wavefront using an intensity independent metric. We show that the particle swarm algorithm converges faster than the genetic algorithm for bright fluorophores.

Nanodiamond Landmarks for Subcellular Multimodal Optical and Electron Imaging

PubMed Central

Zurbuchen, Mark A.; Lake, Michael P.; Kohan, Sirus A.; Leung, Belinda; Bouchard, Louis-S.

2013-01-01

There is a growing need for biolabels that can be used in both optical and electron microscopies, are non-cytotoxic, and do not photobleach. Such biolabels could enable targeted nanoscale imaging of sub-cellular structures, and help to establish correlations between conjugation-delivered biomolecules and function. Here we demonstrate a sub-cellular multi-modal imaging methodology that enables localization of inert particulate probes, consisting of nanodiamonds having fluorescent nitrogen-vacancy centers. These are functionalized to target specific structures, and are observable by both optical and electron microscopies. Nanodiamonds targeted to the nuclear pore complex are rapidly localized in electron-microscopy diffraction mode to enable “zooming-in” to regions of interest for detailed structural investigations. Optical microscopies reveal nanodiamonds for in-vitro tracking or uptake-confirmation. The approach is general, works down to the single nanodiamond level, and can leverage the unique capabilities of nanodiamonds, such as biocompatibility, sensitive magnetometry, and gene and drug delivery. PMID:24036840

Extracellular localization of the diterpene sclareol in clary sage (Salvia sclarea L., Lamiaceae).

PubMed

Caissard, Jean-Claude; Olivier, Thomas; Delbecque, Claire; Palle, Sabine; Garry, Pierre-Philippe; Audran, Arthur; Valot, Nadine; Moja, Sandrine; Nicolé, Florence; Magnard, Jean-Louis; Legrand, Sylvain; Baudino, Sylvie; Jullien, Frédéric

2012-01-01

Sclareol is a high-value natural product obtained by solid/liquid extraction of clary sage (Salvia sclarea L.) inflorescences. Because processes of excretion and accumulation of this labdane diterpene are unknown, the aim of this work was to gain knowledge on its sites of accumulation in planta. Samples were collected in natura or during different steps of the industrial process of extraction (steam distillation and solid/liquid extraction). Samples were then analysed with a combination of complementary analytical techniques (gas chromatography coupled to a mass spectrometer, polarized light microscopy, environmental scanning electron microscopy, two-photon fluorescence microscopy, second harmonic generation microscopy). According to the literature, it is hypothesized that sclareol is localized in oil pockets of secretory trichomes. This study demonstrates that this is not the case and that sclareol accumulates in a crystalline epicuticular form, mostly on calyces.

Extracellular Localization of the Diterpene Sclareol in Clary Sage (Salvia sclarea L., Lamiaceae)

PubMed Central

Caissard, Jean-Claude; Olivier, Thomas; Delbecque, Claire; Palle, Sabine; Garry, Pierre-Philippe; Audran, Arthur; Valot, Nadine; Moja, Sandrine; Nicolé, Florence; Magnard, Jean-Louis; Legrand, Sylvain; Baudino, Sylvie; Jullien, Frédéric

2012-01-01

Sclareol is a high-value natural product obtained by solid/liquid extraction of clary sage (Salvia sclarea L.) inflorescences. Because processes of excretion and accumulation of this labdane diterpene are unknown, the aim of this work was to gain knowledge on its sites of accumulation in planta. Samples were collected in natura or during different steps of the industrial process of extraction (steam distillation and solid/liquid extraction). Samples were then analysed with a combination of complementary analytical techniques (gas chromatography coupled to a mass spectrometer, polarized light microscopy, environmental scanning electron microscopy, two-photon fluorescence microscopy, second harmonic generation microscopy). According to the literature, it is hypothesized that sclareol is localized in oil pockets of secretory trichomes. This study demonstrates that this is not the case and that sclareol accumulates in a crystalline epicuticular form, mostly on calyces. PMID:23133579

Anderson localization of graphene by helium ion irradiation

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

Naitou, Y., E-mail: yu-naitou@aist.go.jp; Ogawa, S.

Irradiation of a single-layer graphene (SLG) with accelerated helium ions (He{sup +}) controllably generates defect distributions, which create a charge carrier scattering source within the SLG. We report direct experimental observation of metal-insulator transition in SLG on SiO{sub 2}/Si substrates induced by Anderson localization. This transition was investigated using scanning capacitance microscopy by monitoring the He{sup +} dose conditions on the SLG. The experimental data show that a defect density of more than ∼1.2% induced Anderson localization. We also investigated the localization length by determining patterned placement of the defects and estimated the length to be several dozen nanometers. Thesemore » findings provide valuable insight for patterning and designing graphene-based nanostructures using helium ion microscopy.« less

Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images.

PubMed

Basset, Antoine; Boulanger, Jérôme; Salamero, Jean; Bouthemy, Patrick; Kervrann, Charles

2015-11-01

Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) automatically selects the optimal scale corresponding to the most frequent spot size in the image. Four criteria are proposed and compared to determine the optimal scale in a scale-space framework. Then, the segmentation stage amounts to thresholding the LoG of the intensity image. In contrast to other methods, the threshold is locally adapted given a probability of false alarm (PFA) specified by the user for the whole set of images to be processed. The local threshold is automatically derived from the PFA value and local image statistics estimated in a window whose size is not a critical parameter. We also propose a new data set for benchmarking, consisting of six collections of one hundred images each, which exploits backgrounds extracted from real microscopy images. We have carried out an extensive comparative evaluation on several data sets with ground-truth, which demonstrates that ATLAS outperforms existing methods. ATLAS does not need any fine parameter tuning and requires very low computation time. Convincing results are also reported on real total internal reflection fluorescence microscopy images.

Nobel Prize Recipient Eric Betzig Presents Lecture on Efforts to Improve High-Resolution Microscopy | Poster

Cancer.gov

Eric Betzig, Ph.D., a 2014 recipient of the Nobel Prize in Chemistry and a scientist at Janelia Research Campus (JRC), Howard Hughes Medical Institute, in Ashburn, Va., visited NCI at Frederick on Sept. 10 to present a Distinguished Scientist lecture and discuss the latest high-resolution microscopy techniques. Betzig co-invented photoactivation localization microscopy (PALM)

Cellular automata modeling depicts degradation of cellulosic material by a cellulase system with single-molecule resolution.

PubMed

Eibinger, Manuel; Zahel, Thomas; Ganner, Thomas; Plank, Harald; Nidetzky, Bernd

2016-01-01

Enzymatic hydrolysis of cellulose involves the spatiotemporally correlated action of distinct polysaccharide chain cleaving activities confined to the surface of an insoluble substrate. Because cellulases differ in preference for attacking crystalline compared to amorphous cellulose, the spatial distribution of structural order across the cellulose surface imposes additional constraints on the dynamic interplay between the enzymes. Reconstruction of total system behavior from single-molecule activity parameters is a longstanding key goal in the field. We have developed a stochastic, cellular automata-based modeling approach to describe degradation of cellulosic material by a cellulase system at single-molecule resolution. Substrate morphology was modeled to represent the amorphous and crystalline phases as well as the different spatial orientations of the polysaccharide chains. The enzyme system model consisted of an internally chain-cleaving endoglucanase (EG) as well as two processively acting, reducing and non-reducing chain end-cleaving cellobiohydrolases (CBHs). Substrate preference (amorphous: EG, CBH II; crystalline: CBH I) and characteristic frequencies for chain cleavage, processive movement, and dissociation were assigned from biochemical data. Once adsorbed, enzymes were allowed to reach surface-exposed substrate sites through "random-walk" lateral diffusion or processive motion. Simulations revealed that slow dissociation of processive enzymes at obstacles obstructing further movement resulted in local jamming of the cellulases, with consequent delay in the degradation of the surface area affected. Exploiting validation against evidence from atomic force microscopy imaging as a unique opportunity opened up by the modeling approach, we show that spatiotemporal characteristics of cellulose surface degradation by the system of synergizing cellulases were reproduced quantitatively at the nanometer resolution of the experimental data. This in turn gave useful prediction of the soluble sugar release rate. Salient dynamic features of cellulose surface degradation by different cellulases acting in synergy were reproduced in simulations in good agreement with evidence from high-resolution visualization experiments. Due to the single-molecule resolution of the modeling approach, the utility of the presented model lies not only in predicting system behavior but also in elucidating inherently complex (e.g., stochastic) phenomena involved in enzymatic cellulose degradation. Thus, it creates synergy with experiment to advance the mechanistic understanding for improved application.

Drop Breakup in Fixed Bed Flows as Model Stochastic Flow Fields

NASA Technical Reports Server (NTRS)

Shaqfeh, Eric S. G.; Mosler, Alisa B.; Patel, Prateek

1999-01-01

We examine drop breakup in a class of stochastic flow fields as a model for the flow through fixed fiber beds and to elucidate the general mechanisms whereby drops breakup in disordered, Lagrangian unsteady flows. Our study consists of two parallel streams of investigation. First, large scale numerical simulations of drop breakup in a class of anisotropic Gaussian fields will be presented. These fields are generated spectrally and have been shown in a previous publication to be exact representations of the flow in a dilute disordered bed of fibers if close interactions between the fibers and the drops are dynamically unimportant. In these simulations the drop shape is represented by second and third order small deformation theories which have been shown to be excellent for the prediction of drop breakup in steady strong flows. We show via these simulations that the mechanisms of drop breakup in these flows are quite different than in steady flows. The predominant mechanism of breakup appears to be very short lived twist breakups. Moreover, the occurrence of breakup events is poorly predicted by either the strength of the local flow in which the drop finds itself at breakup, or the degree of deformation that the drop achieves prior to breakup. It is suggested that a correlation function of both is necessary to be predictive of breakup events. In the second part of our research experiments are presented where the drop deformation and breakup in PDMS/polyisobutylene emulsions is considered. We consider very dilute emulsions such that coalescence is unimportant. The flows considered are simple shear and the flow through fixed fiber beds. Turbidity, small angle light scattering, dichroism and microscopy are used to interrogate the drop deformation process in both flows. It is demonstrated that breakup at very low capillary numbers occurs in both flows but larger drop deformation occurs in the fixed bed flow. Moreover, it is witnessed that breakup in the bed occurs continuously during flow and apparently with uniform probability through the bed length. The drop deformations witnessed in our experiments are larger than those predicted by the numerical simulations, and future plans to investigate these differences are discussed.

Functional Scanning Probe Imaging of Nanostructured Solar Energy Materials.

PubMed

Giridharagopal, Rajiv; Cox, Phillip A; Ginger, David S

2016-09-20

From hybrid perovskites to semiconducting polymer/fullerene blends for organic photovoltaics, many new materials being explored for energy harvesting and storage exhibit performance characteristics that depend sensitively on their nanoscale morphology. At the same time, rapid advances in the capability and accessibility of scanning probe microscopy methods over the past decade have made it possible to study processing/structure/function relationships ranging from photocurrent collection to photocarrier lifetimes with resolutions on the scale of tens of nanometers or better. Importantly, such scanning probe methods offer the potential to combine measurements of local structure with local function, and they can be implemented to study materials in situ or devices in operando to better understand how materials evolve in time in response to an external stimulus or environmental perturbation. This Account highlights recent advances in the development and application of scanning probe microscopy methods that can help address such questions while filling key gaps between the capabilities of conventional electron microscopy and newer super-resolution optical methods. Focusing on semiconductor materials for solar energy applications, we highlight a range of electrical and optoelectronic scanning probe microscopy methods that exploit the local dynamics of an atomic force microscope tip to probe key properties of the solar cell material or device structure. We discuss how it is possible to extract relevant device properties using noncontact scanning probe methods as well as how these properties guide materials development. Specifically, we discuss intensity-modulated scanning Kelvin probe microscopy (IM-SKPM), time-resolved electrostatic force microscopy (trEFM), frequency-modulated electrostatic force microscopy (FM-EFM), and cantilever ringdown imaging. We explain these developments in the context of classic atomic force microscopy (AFM) methods that exploit the physics of cantilever motion and photocarrier generation to provide robust, nanoscale measurements of materials physics that are correlated with device operation. We predict that the multidimensional data sets made possible by these types of methods will become increasingly important as advances in data science expand capabilities and opportunities for image correlation and discovery.

Sub-diffraction-limit localization imaging of a plasmonic nanoparticle pair with wavelength-resolved dark-field microscopy.

PubMed

Wei, Lin; Ma, Yanhong; Zhu, Xupeng; Xu, Jianghong; Wang, Yaxin; Duan, Huigao; Xiao, Lehui

2017-06-29

In this work, with wavelength-resolved dark-field microscopy, the center-of-mass localization information from nanoparticle pairs (i.e., spherical (45 nm in diameter) and rod (45 × 70 nm) shaped gold nanoparticle pairs with different gap distances and orientations) was explored and compared with the results determined by scanning electron microscopy (SEM) measurements. When the gap distance was less than 20 nm, the scattering spectrum of the nanoparticle pair was seriously modulated by the plasmonic coupling effect. The measured coordinate information determined by the optical method (Gaussian fitting) was not consistent with the true results determined by SEM measurement. A good correlation between the optical and SEM measurements was achieved when the gap distance was further increased (e.g., 20, 40 and 60 nm). Under these conditions, well-defined scattering peaks assigned to the corresponding individual nanoparticles could be distinguished from the obtained scattering spectrum. These results would afford valuable information for the studies on single plasmonic nanoparticle imaging applications with the optical microscopy method such as super-localization imaging, high precision single particle tracking in a crowding environment and so on.

Scanning tunneling microscopy current from localized basis orbital density functional theory

NASA Astrophysics Data System (ADS)

Gustafsson, Alexander; Paulsson, Magnus

2016-03-01

We present a method capable of calculating elastic scanning tunneling microscopy (STM) currents from localized atomic orbital density functional theory (DFT). To overcome the poor accuracy of the localized orbital description of the wave functions far away from the atoms, we propagate the wave functions, using the total DFT potential. From the propagated wave functions, the Bardeen's perturbative approach provides the tunneling current. To illustrate the method we investigate carbon monoxide adsorbed on a Cu(111) surface and recover the depression/protrusion observed experimentally with normal/CO-functionalized STM tips. The theory furthermore allows us to discuss the significance of s - and p -wave tips.

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Roth, Dan; Wilkins, David C.

2001-01-01

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

The Role of Population Origin and Microenvironment in Seedling Emergence and Early Survival in Mediterranean Maritime Pine (Pinus pinaster Aiton)

PubMed Central

Vizcaíno-Palomar, Natalia; Revuelta-Eugercios, Bárbara; Zavala, Miguel A.; Alía, Ricardo; González-Martínez, Santiago C.

2014-01-01

Understanding tree recruitment is needed to forecast future forest distribution. Many studies have reported the relevant ecological factors that affect recruitment success in trees, but the potential for genetic-based differences in recruitment has often been neglected. In this study, we established a semi-natural reciprocal sowing experiment to test for local adaptation and microenvironment effects (evaluated here by canopy cover) in the emergence and early survival of maritime pine (Pinus pinaster Aiton), an emblematic Mediterranean forest tree. A novel application of molecular markers was also developed to test for family selection and, thus, for potential genetic change over generations. Overall, we did not find evidence to support local adaptation at the recruitment stage in our semi-natural experiment. Moreover, only weak family selection (if any) was found, suggesting that in stressful environments with low survival, stochastic processes and among-year climate variability may drive recruitment. Nevertheless, our study revealed that, at early stages of recruitment, microenvironments may favor the population with the best adapted life strategy, irrespectively of its (local or non-local) origin. We also found that emergence time is a key factor for seedling survival in stressful Mediterranean environments. Our study highlights the complexity of the factors influencing the early stages of establishment of maritime pine and provides insights into possible management actions aimed at environmental change impact mitigation. In particular, we found that the high stochasticity of the recruitment process in stressful environments and the differences in population-specific adaptive strategies may difficult assisted migration schemes. PMID:25286410

The role of population origin and microenvironment in seedling emergence and early survival in Mediterranean maritime pine (Pinus pinaster Aiton).

PubMed

Vizcaíno-Palomar, Natalia; Revuelta-Eugercios, Bárbara; Zavala, Miguel A; Alía, Ricardo; González-Martínez, Santiago C

2014-01-01

Understanding tree recruitment is needed to forecast future forest distribution. Many studies have reported the relevant ecological factors that affect recruitment success in trees, but the potential for genetic-based differences in recruitment has often been neglected. In this study, we established a semi-natural reciprocal sowing experiment to test for local adaptation and microenvironment effects (evaluated here by canopy cover) in the emergence and early survival of maritime pine (Pinus pinaster Aiton), an emblematic Mediterranean forest tree. A novel application of molecular markers was also developed to test for family selection and, thus, for potential genetic change over generations. Overall, we did not find evidence to support local adaptation at the recruitment stage in our semi-natural experiment. Moreover, only weak family selection (if any) was found, suggesting that in stressful environments with low survival, stochastic processes and among-year climate variability may drive recruitment. Nevertheless, our study revealed that, at early stages of recruitment, microenvironments may favor the population with the best adapted life strategy, irrespectively of its (local or non-local) origin. We also found that emergence time is a key factor for seedling survival in stressful Mediterranean environments. Our study highlights the complexity of the factors influencing the early stages of establishment of maritime pine and provides insights into possible management actions aimed at environmental change impact mitigation. In particular, we found that the high stochasticity of the recruitment process in stressful environments and the differences in population-specific adaptive strategies may difficult assisted migration schemes.

DNA motif alignment by evolving a population of Markov chains.

PubMed

Bi, Chengpeng

2009-01-30

Deciphering cis-regulatory elements or de novo motif-finding in genomes still remains elusive although much algorithmic effort has been expended. The Markov chain Monte Carlo (MCMC) method such as Gibbs motif samplers has been widely employed to solve the de novo motif-finding problem through sequence local alignment. Nonetheless, the MCMC-based motif samplers still suffer from local maxima like EM. Therefore, as a prerequisite for finding good local alignments, these motif algorithms are often independently run a multitude of times, but without information exchange between different chains. Hence it would be worth a new algorithm design enabling such information exchange. This paper presents a novel motif-finding algorithm by evolving a population of Markov chains with information exchange (PMC), each of which is initialized as a random alignment and run by the Metropolis-Hastings sampler (MHS). It is progressively updated through a series of local alignments stochastically sampled. Explicitly, the PMC motif algorithm performs stochastic sampling as specified by a population-based proposal distribution rather than individual ones, and adaptively evolves the population as a whole towards a global maximum. The alignment information exchange is accomplished by taking advantage of the pooled motif site distributions. A distinct method for running multiple independent Markov chains (IMC) without information exchange, or dubbed as the IMC motif algorithm, is also devised to compare with its PMC counterpart. Experimental studies demonstrate that the performance could be improved if pooled information were used to run a population of motif samplers. The new PMC algorithm was able to improve the convergence and outperformed other popular algorithms tested using simulated and biological motif sequences.

Local Magnetoelectric Effect in La-Doped BiFeO3 Multiferroic Thin Films Revealed by Magnetic-Field-Assisted Scanning Probe Microscopy

NASA Astrophysics Data System (ADS)

Pan, Dan-Feng; Zhou, Ming-Xiu; Lu, Zeng-Xing; Zhang, Hao; Liu, Jun-Ming; Wang, Guang-Hou; Wan, Jian-Guo

2016-06-01

Multiferroic La-doped BiFeO3 thin films have been prepared by a sol-gel plus spin-coating process, and the local magnetoelectric coupling effect has been investigated by the magnetic-field-assisted scanning probe microscopy connected with a ferroelectric analyzer. The local ferroelectric polarization response to external magnetic fields is observed and a so-called optimized magnetic field of ~40 Oe is obtained, at which the ferroelectric polarization reaches the maximum. Moreover, we carry out the magnetic-field-dependent surface conductivity measurements and illustrate the origin of local magnetoresistance in the La-doped BiFeO3 thin films, which is closely related to the local ferroelectric polarization response to external magnetic fields. This work not only provides a useful technique to characterize the local magnetoelectric coupling for a wide range of multiferroic materials but also is significant for deeply understanding the local multiferroic behaviors in the BiFeO3-based systems.

Differential localization of SAP102 and PSD-95 is revealed in hippocampal spines using super-resolution light microscopy.

PubMed

Zheng, Chan-Ying; Wang, Ya-Xia; Kachar, Bechara; Petralia, Ronald S

2011-01-01

Synapse-associated protein 102 (SAP102) and postsynaptic density 95 (PSD-95) are two major cytoskeleton proteins in the postsynaptic density (PSD). Both of them belong to the membrane-associated guanylate kinase (MAGUK) family, which clusters and anchors glutamate receptors and other proteins at synapses. In our previous study, we found that SAP102 and PSD-95 have different distributions, using combined light/electron microscopy (LM/EM) methods.1 Here, we double labeled endogenous SAP102 and PSD-95 in mature hippocampal neurons, and then took images by two different kinds of super resolution microscopy-Stimulated Emission Depletion microscopy (STED) and DeltaVision OMX 3D super resolution microscopy. We found that our 2D and 3D super resolution data were consistent with our previous LM/EM data, showing significant differences in the localization of SAP102 and PSD-95 in spines: SAP102 is distributed in both the PSD and cytoplasm of spines, while PSD-95 is concentrated only in the PSD area. These results indicate functional differences between SAP102 and PSD-95 in synaptic organization and plasticity.

Molecular counting of membrane receptor subunits with single-molecule localization microscopy

NASA Astrophysics Data System (ADS)

Krüger, Carmen; Fricke, Franziska; Karathanasis, Christos; Dietz, Marina S.; Malkusch, Sebastian; Hummer, Gerhard; Heilemann, Mike

2017-02-01

We report on quantitative single-molecule localization microscopy, a method that next to super-resolved images of cellular structures provides information on protein copy numbers in protein clusters. This approach is based on the analysis of blinking cycles of single fluorophores, and on a model-free description of the distribution of the number of blinking events. We describe the experimental and analytical procedures, present cellular data of plasma membrane proteins and discuss the applicability of this method.

Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan

2012-10-26

Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks.

Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing

PubMed Central

2012-01-01

Background Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Results Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. Conclusion If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks. PMID:23101662

Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches

NASA Astrophysics Data System (ADS)

Egging, Rudolf Gerardus

This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in shorter solution times relative to solving the extensive-forms. Larger problems, up to 117,481 variables, were solved in extensive-form, but not when applying BD due to numerical issues. It is discussed how BD could significantly reduce the solution time of large-scale stochastic models, but various challenges remain and more research is needed to assess the potential of Benders decomposition for solving large-scale stochastic MCP. 1 www.gecforum.org

The nature and role of advection in advection-diffusion equations used for modelling bed load transport

NASA Astrophysics Data System (ADS)

Ancey, Christophe; Bohorquez, Patricio; Heyman, Joris

2016-04-01

The advection-diffusion equation arises quite often in the context of sediment transport, e.g., for describing time and space variations in the particle activity (the solid volume of particles in motion per unit streambed area). Stochastic models can also be used to derive this equation, with the significant advantage that they provide information on the statistical properties of particle activity. Stochastic models are quite useful when sediment transport exhibits large fluctuations (typically at low transport rates), making the measurement of mean values difficult. We develop an approach based on birth-death Markov processes, which involves monitoring the evolution of the number of particles moving within an array of cells of finite length. While the topic has been explored in detail for diffusion-reaction systems, the treatment of advection has received little attention. We show that particle advection produces nonlocal effects, which are more or less significant depending on the cell size and particle velocity. Albeit nonlocal, these effects look like (local) diffusion and add to the intrinsic particle diffusion (dispersal due to velocity fluctuations), with the important consequence that local measurements depend on both the intrinsic properties of particle displacement and the dimensions of the measurement system.

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

NASA Astrophysics Data System (ADS)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Metapopulation extinction risk: dispersal's duplicity.

PubMed

Higgins, Kevin

2009-09-01

Metapopulation extinction risk is the probability that all local populations are simultaneously extinct during a fixed time frame. Dispersal may reduce a metapopulation's extinction risk by raising its average per-capita growth rate. By contrast, dispersal may raise a metapopulation's extinction risk by reducing its average population density. Which effect prevails is controlled by habitat fragmentation. Dispersal in mildly fragmented habitat reduces a metapopulation's extinction risk by raising its average per-capita growth rate without causing any appreciable drop in its average population density. By contrast, dispersal in severely fragmented habitat raises a metapopulation's extinction risk because the rise in its average per-capita growth rate is more than offset by the decline in its average population density. The metapopulation model used here shows several other interesting phenomena. Dispersal in sufficiently fragmented habitat reduces a metapopulation's extinction risk to that of a constant environment. Dispersal between habitat fragments reduces a metapopulation's extinction risk insofar as local environments are asynchronous. Grouped dispersal raises the effective habitat fragmentation level. Dispersal search barriers raise metapopulation extinction risk. Nonuniform dispersal may reduce the effective fraction of suitable habitat fragments below the extinction threshold. Nonuniform dispersal may make demographic stochasticity a more potent metapopulation extinction force than environmental stochasticity.

System theoretic models for high density VLSI structures

NASA Astrophysics Data System (ADS)

Dickinson, Bradley W.; Hopkins, William E., Jr.

This research project involved the development of mathematical models for analysis, synthesis, and simulation of large systems of interacting devices. The work was motivated by problems that may become important in high density VLSI chips with characteristic feature sizes less than 1 micron: it is anticipated that interactions of neighboring devices will play an important role in the determination of circuit properties. It is hoped that the combination of high device densities and such local interactions can somehow be exploited to increase circuit speed and to reduce power consumption. To address these issues from the point of view of system theory, research was pursued in the areas of nonlinear and stochastic systems and into neural network models. Statistical models were developed to characterize various features of the dynamic behavior of interacting systems. Random process models for studying the resulting asynchronous modes of operation were investigated. The local interactions themselves may be modeled as stochastic effects. The resulting behavior was investigated through the use of various scaling limits, and by a combination of other analytical and simulation techniques. Techniques arising in a variety of disciplines where models of interaction were formulated and explored were considered and adapted for use.

Relaxation and coarsening of weakly-interacting breathers in a simplified DNLS chain

NASA Astrophysics Data System (ADS)

Iubini, Stefano; Politi, Antonio; Politi, Paolo

2017-07-01

The discrete nonlinear Schrödinger (DNLS) equation displays a parameter region characterized by the presence of localized excitations (breathers). While their formation is well understood and it is expected that the asymptotic configuration comprises a single breather on top of a background, it is not clear why the dynamics of a multi-breather configuration is essentially frozen. In order to investigate this question, we introduce simple stochastic models, characterized by suitable conservation laws. We focus on the role of the coupling strength between localized excitations and background. In the DNLS model, higher breathers interact more weakly, as a result of their faster rotation. In our stochastic models, the strength of the coupling is controlled directly by an amplitude-dependent parameter. In the case of a power-law decrease, the associated coarsening process undergoes a slowing down if the decay rate is larger than a critical value. In the case of an exponential decrease, a freezing effect is observed that is reminiscent of the scenario observed in the DNLS. This last regime arises spontaneously when direct energy diffusion between breathers and background is blocked below a certain threshold.

Organization of the cytokeratin network in an epithelial cell.

PubMed

Portet, Stéphanie; Arino, Ovide; Vassy, Jany; Schoëvaërt, Damien

2003-08-07

The cytoskeleton is a dynamic three-dimensional structure mainly located in the cytoplasm. It is involved in many cell functions such as mechanical signal transduction and maintenance of cell integrity. Among the three cytoskeletal components, intermediate filaments (the cytokeratin in epithelial cells) are the best candidates for this mechanical role. A model of the establishment of the cytokeratin network of an epithelial cell is proposed to study the dependence of its structural organization on extracellular mechanical environment. To implicitly describe the latter and its effects on the intracellular domain, we use mechanically regulated protein synthesis. Our model is a hybrid of a partial differential equation of parabolic type, governing the evolution of the concentration of cytokeratin, and a set of stochastic differential equations describing the dynamics of filaments. Each filament is described by a stochastic differential equation that reflects both the local interactions with the environment and the non-local interactions via the past history of the filament. A three-dimensional simulation model is derived from this mathematical model. This simulation model is then used to obtain examples of cytokeratin network architectures under given mechanical conditions, and to study the influence of several parameters.

Influence of Microphysical Variability on Stochastic Condensation in Turbulent Clouds

NASA Astrophysics Data System (ADS)

Desai, N.; Chandrakar, K. K.; Chang, K.; Glienke, S.; Cantrell, W. H.; Fugal, J. P.; Shaw, R. A.

2017-12-01

We investigate the influence of variability in droplet number concentration and radius on the evolution of cloud droplet size distributions. Measurements are made on the centimeter scale using digitial inline holography, both in a controlled laboratory setting and in the field using HOLODEC measurements from CSET. We created steady state cloud conditions in the laboratory Pi Chamber, in which a turbulent cloud can be sustained for long periods of time. Using holographic imaging, we directly observe the variations in local number concentration and droplet size distribution and, thereby, the integral radius. We interpret the measurements in the context of stochastic condensation theory to determine how fluctuations in integral radius contribute to droplet growth. We find that the variability in integral radius is primarily driven by variations in the droplet number concentration and not the droplet radius. This variability does not contribute significantly to the mean droplet growth rate, but contributes significantly to the rate of increase of the size distribution width. We compare these results with in-situ measurements and find evidence for microphysical signatures of stochastic condensation. The results suggest that supersaturation fluctuations lead to broader size distributions and allow droplets to reach the collision-coalescence stage.

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

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

D'Elia, M.; Edwards, H. C.; Hu, J.

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

PubMed

Chang, Joshua; Paydarfar, David

2014-12-01

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

DOE PAGES

D'Elia, M.; Edwards, H. C.; Hu, J.; ...

2018-01-18

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

The Influence of Turbulent Coherent Structure on Suspended Sediment Transport

NASA Astrophysics Data System (ADS)

Huang, S. H.; Tsai, C.

2017-12-01

The anomalous diffusion of turbulent sedimentation has received more and more attention in recent years. With the advent of new instruments and technologies, researchers have found that sediment behavior may deviate from Fickian assumptions when particles are heavier. In particle-laden flow, bursting phenomena affects instantaneous local concentrations, and seems to carry suspended particles for a longer distance. Instead of the pure diffusion process in an analogy to Brownian motion, Levy flight which allows particles to move in response to bursting phenomena is suspected to be more suitable for describing particle movement in turbulence. And the fractional differential equation is a potential candidate to improve the concentration profile. However, stochastic modeling (the Differential Chapmen-Kolmogorov Equation) also provides an alternative mathematical framework to describe system transits between different states through diffusion/the jump processes. Within this framework, the stochastic particle tracking model linked with advection diffusion equation is a powerful tool to simulate particle locations in the flow field. By including the jump process to this model, a more comprehensive description for suspended sediment transport can be provided with a better physical insight. This study also shows the adaptability and expandability of the stochastic particle tracking model for suspended sediment transport modeling.

Effects of stochastic field lines on the pressure driven MHD instabilities in the Large Helical Device

NASA Astrophysics Data System (ADS)

Ohdachi, Satoshi; Watanabe, Kiyomasa; Sakakibara, Satoru; Suzuki, Yasuhiro; Tsuchiya, Hayato; Ming, Tingfeng; Du, Xiaodi; LHD Expriment Group Team

2014-10-01

In the Large Helical Device (LHD), the plasma is surrounded by the so-called magnetic stochastic region, where the Kolmogorov length of the magnetic field lines is very short, from several tens of meters and to thousands meters. Finite pressure gradient are formed in this region and MHD instabilities localized in this region is observed since the edge region of the LHD is always unstable against the pressure driven mode. Therefore, the saturation level of the instabilities is the key issue in order to evaluate the risk of this kind of MHD instabilities. The saturation level depends on the pressure gradient and on the magnetic Reynolds number; there results are similar to the MHD mode in the closed magnetic surface region. The saturation level in the stochastic region is affected also by the stocasticity itself. Parameter dependence of the saturation level of the MHD activities in the region is discussed in detail. It is supported by NIFS budget code ULPP021, 028 and is also partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research 26249144, by the JSPS-NRF-NSFC A3 Foresight Program NSFC: No. 11261140328.

Collective stochastic coherence in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Sancristóbal, Belén; Rebollo, Beatriz; Boada, Pol; Sanchez-Vives, Maria V.; Garcia-Ojalvo, Jordi

2016-09-01

Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can show substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level coexists with regular oscillations at the global level is still unclear. Here we show that a combination of stochastic recurrence-based initiation with deterministic refractoriness in an excitable network can reconcile these two features, leading to maximum collective coherence for an intermediate noise level. We report this behaviour in the slow oscillation regime exhibited by a cerebral cortex network under dynamical conditions resembling slow-wave sleep and anaesthesia. Computational analysis of a biologically realistic network model reveals that an intermediate level of background noise leads to quasi-regular dynamics. We verify this prediction experimentally in cortical slices subject to varying amounts of extracellular potassium, which modulates neuronal excitability and thus synaptic noise. The model also predicts that this effectively regular state should exhibit noise-induced memory of the spatial propagation profile of the collective oscillations, which is also verified experimentally. Taken together, these results allow us to construe the high regularity observed experimentally in the brain as an instance of collective stochastic coherence.

An information-theoretic approach to designing the plane spacing for multifocal plane microscopy

PubMed Central

Tahmasbi, Amir; Ram, Sripad; Chao, Jerry; Abraham, Anish V.; Ward, E. Sally; Ober, Raimund J.

2015-01-01

Multifocal plane microscopy (MUM) is a 3D imaging modality which enables the localization and tracking of single molecules at high spatial and temporal resolution by simultaneously imaging distinct focal planes within the sample. MUM overcomes the depth discrimination problem of conventional microscopy and allows high accuracy localization of a single molecule in 3D along the z-axis. An important question in the design of MUM experiments concerns the appropriate number of focal planes and their spacings to achieve the best possible 3D localization accuracy along the z-axis. Ideally, it is desired to obtain a 3D localization accuracy that is uniform over a large depth and has small numerical values, which guarantee that the single molecule is continuously detectable. Here, we address this concern by developing a plane spacing design strategy based on the Fisher information. In particular, we analyze the Fisher information matrix for the 3D localization problem along the z-axis and propose spacing scenarios termed the strong coupling and the weak coupling spacings, which provide appropriate 3D localization accuracies. Using these spacing scenarios, we investigate the detectability of the single molecule along the z-axis and study the effect of changing the number of focal planes on the 3D localization accuracy. We further review a software module we recently introduced, the MUMDesignTool, that helps to design the plane spacings for a MUM setup. PMID:26113764

Characterization of the 20 kHz transient MHD burst at the fast U-3M confinement modification stage

NASA Astrophysics Data System (ADS)

Dreval, M. B.; Pavlichenko, R. O.; Shapoval, A. M.; Pashnev, V. K.; Sorokovoy, E. L.; Slavnyj, A. S.; Beletskii, A. A.; Mironov, Yu K.; Romanov, V. S.; Kulaga, A. E.; Zamanov, N. V.

2018-05-01

In the URAGAN-3M (U-3M) torsatron the low-frequency transient 20–30 kHz mode is observed during the plasma confinement transition that occurs at a plasma current value of about 1 kA. The burst of this mode is always accompanied by the fast jump of the Alfvén eigenmode frequency. The transient 20–30 kHz mode contains two parts. The non-rotating part of the mode has higher amplitude and is localized in the stochastic region of the plasma. It is observed only in the vicinity of the radio-frequency antenna used for plasma production and does not propagate along the torus because of fast losses. Its high amplitude indicates that the major part of the 20–30 kHz mode is excited in the stochastic region near the antenna. In contrast, the second rotating part of the mode is localized everywhere along the torus near the plasma edge (ρ = 0.8–1). This is the n/m = 1/2 mode that rotates in the electron diamagnetic direction. It is observed in different toroidal cross-sections by various diagnostics (magnetic probe array, optics, Langmuir probe). Appearance of the 1/2 rational surface at the stochastic magnetic field line region near the plasma edge at 1 kA plasma current stage can be responsible for the mode generation. Modification of electron component gradients in the mode generation region near the antenna and the drop of the fast ion concentration (above 1 keV) in this region are observed simultaneously with the mode generation. The mode can be exited by the strong transient plasma gradients generated in the vicinity of the rational surface by the antenna.

Adaptiveness in monotone pseudo-Boolean optimization and stochastic neural computation.

PubMed

Grossi, Giuliano

2009-08-01

Hopfield neural network (HNN) is a nonlinear computational model successfully applied in finding near-optimal solutions of several difficult combinatorial problems. In many cases, the network energy function is obtained through a learning procedure so that its minima are states falling into a proper subspace (feasible region) of the search space. However, because of the network nonlinearity, a number of undesirable local energy minima emerge from the learning procedure, significantly effecting the network performance. In the neural model analyzed here, we combine both a penalty and a stochastic process in order to enhance the performance of a binary HNN. The penalty strategy allows us to gradually lead the search towards states representing feasible solutions, so avoiding oscillatory behaviors or asymptotically instable convergence. Presence of stochastic dynamics potentially prevents the network to fall into shallow local minima of the energy function, i.e., quite far from global optimum. Hence, for a given fixed network topology, the desired final distribution on the states can be reached by carefully modulating such process. The model uses pseudo-Boolean functions both to express problem constraints and cost function; a combination of these two functions is then interpreted as energy of the neural network. A wide variety of NP-hard problems fall in the class of problems that can be solved by the model at hand, particularly those having a monotonic quadratic pseudo-Boolean function as constraint function. That is, functions easily derived by closed algebraic expressions representing the constraint structure and easy (polynomial time) to maximize. We show the asymptotic convergence properties of this model characterizing its state space distribution at thermal equilibrium in terms of Markov chain and give evidence of its ability to find high quality solutions on benchmarks and randomly generated instances of two specific problems taken from the computational graph theory.

Efficacy of a numerical value of a fixed-effect estimator in stochastic frontier analysis as an indicator of hospital production structure.

PubMed

Kawaguchi, Hiroyuki; Hashimoto, Hideki; Matsuda, Shinya

2012-09-22

The casemix-based payment system has been adopted in many countries, although it often needs complementary adjustment taking account of each hospital's unique production structure such as teaching and research duties, and non-profit motives. It has been challenging to numerically evaluate the impact of such structural heterogeneity on production, separately of production inefficiency. The current study adopted stochastic frontier analysis and proposed a method to assess unique components of hospital production structures using a fixed-effect variable. There were two stages of analyses in this study. In the first stage, we estimated the efficiency score from the hospital production function using a true fixed-effect model (TFEM) in stochastic frontier analysis. The use of a TFEM allowed us to differentiate the unobserved heterogeneity of individual hospitals as hospital-specific fixed effects. In the second stage, we regressed the obtained fixed-effect variable for structural components of hospitals to test whether the variable was explicitly related to the characteristics and local disadvantages of the hospitals. In the first analysis, the estimated efficiency score was approximately 0.6. The mean value of the fixed-effect estimator was 0.784, the standard deviation was 0.137, the range was between 0.437 and 1.212. The second-stage regression confirmed that the value of the fixed effect was significantly correlated with advanced technology and local conditions of the sample hospitals. The obtained fixed-effect estimator may reflect hospitals' unique structures of production, considering production inefficiency. The values of fixed-effect estimators can be used as evaluation tools to improve fairness in the reimbursement system for various functions of hospitals based on casemix classification.

Formation and distribution of fragments in the spontaneous fission of 240Pu

NASA Astrophysics Data System (ADS)

Sadhukhan, Jhilam; Zhang, Chunli; Nazarewicz, Witold; Schunck, Nicolas

2017-12-01

Background: Fission is a fundamental decay mode of heavy atomic nuclei. The prevalent theoretical approach is based on mean-field theory and its extensions where fission is modeled as a large amplitude motion of a nucleus in a multidimensional collective space. One of the important observables characterizing fission is the charge and mass distribution of fission fragments. Purpose: The goal of this Rapid Communication is to better understand the structure of fission fragment distributions by investigating the competition between the static structure of the collective manifold and the stochastic dynamics. In particular, we study the characteristics of the tails of yield distributions, which correspond to very asymmetric fission into a very heavy and a very light fragment. Methods: We use the stochastic Langevin framework to simulate the nuclear evolution after the system tunnels through the multidimensional potential barrier. For a representative sample of different initial configurations along the outer turning-point line, we define effective fission paths by computing a large number of Langevin trajectories. We extract the relative contribution of each such path to the fragment distribution. We then use nucleon localization functions along effective fission pathways to analyze the characteristics of prefragments at prescission configurations. Results: We find that non-Newtonian Langevin trajectories, strongly impacted by the random force, produce the tails of the fission fragment distribution of 240Pu. The prefragments deduced from nucleon localizations are formed early and change little as the nucleus evolves towards scission. On the other hand, the system contains many nucleons that are not localized in the prefragments even near the scission point. Such nucleons are distributed rapidly at scission to form the final fragments. Fission prefragments extracted from direct integration of the density and from the localization functions typically differ by more than 30 nucleons even near scission. Conclusions: Our Rapid Communication shows that only theoretical models of fission that account for some form of stochastic dynamics can give an accurate description of the structure of fragment distributions. In particular, it should be nearly impossible to predict the tails of these distributions within the standard formulation of time-dependent density-functional theory. At the same time, the large number of nonlocalized nucleons during fission suggests that adiabatic approaches where the interplay between intrinsic excitations and collective dynamics is neglected are ill suited to describe fission fragment properties, in particular, their excitation energy.

Mapping the local reaction kinetics by PEEM: CO oxidation on individual (100)-type grains of Pt foil

PubMed Central

Vogel, D.; Spiel, C.; Suchorski, Y.; Urich, A.; Schlögl, R.; Rupprechter, G.

2011-01-01

The locally-resolved reaction kinetics of CO oxidation on individual (100)-type grains of a polycrystalline Pt foil was monitored in situ using photoemission electron microscopy (PEEM). Reaction-induced surface morphology changes were studied by optical differential interference contrast microscopy and atomic force microscopy (AFM). Regions of high catalytic activity, low activity and bistability in a (p,T)-parameter space were determined, allowing to establish a local kinetic phase diagram for CO oxidation on (100) facets of Pt foil. PEEM observations of the reaction front propagation on Pt(100) domains reveal a high degree of propagation anisotropy both for oxygen and CO fronts on the apparently isotropic Pt(100) surface. The anisotropy vanishes for oxygen fronts at temperatures above 465 K, but is maintained for CO fronts at all temperatures studied, i.e. in the range of 417 to 513 K. A change in the front propagation mechanism is proposed to explain the observed effects. PMID:22140277

Localized electronic structures of graphene oxide studied using scanning tunneling microscopy and spectroscopy.

PubMed

Katano, Satoshi; Wei, Tao; Sasajima, Takumi; Kasama, Ryuhei; Uehara, Yoichi

2018-06-21

We have used scanning tunneling microscopy (STM) to elucidate the nanoscale electronic structures of graphene oxide (GO). The unreduced GO layer was imaged using STM without reduction processes when deposited on a Au(111) surface covered with an octanethiolate self-assembled monolayer (C8S-SAM). The STM image of the GO sheet exhibits a grainy structure having a thickness of about 1 nm, which is in good agreement with the previous results obtained using atomic force microscopy (AFM). We found that the C8S-SAM suppresses the adsorption of water remaining on the substrate, which would be important to accomplish the nanoscale imaging of the unreduced GO by STM. Furthermore, we successfully detected the π and π* states localized in the GO sheet using scanning tunneling spectroscopy (STS). The π-π* gap energy and the gap center are not uniform within the GO sheet, indicating the existence of various sizes of the sp2 domain and evidence for the local electronic doping by the substituents.

Nanoscale observation of local bound charges of patterned protein arrays by scanning force microscopy

NASA Astrophysics Data System (ADS)

Oh, Y. J.; Jo, W.; Kim, S.; Park, S.; Kim, Y. S.

2008-09-01

A protein patterned surface using micro-contact printing methods has been investigated by scanning force microscopy. Electrostatic force microscopy (EFM) was utilized for imaging the topography and detecting the electrical properties such as the local bound charge distribution of the patterned proteins. It was found that the patterned IgG proteins are arranged down to 1 µm, and the 90° rotation of patterned anti-IgG proteins was successfully undertaken. Through the estimation of the effective areas, it was possible to determine the local bound charges of patterned proteins which have opposite electrostatic force behaviors. Moreover, we studied the binding probability between IgG and anti-IgG in a 1 µm2 MIMIC system by topographic and electrostatic signals for applicable label-free detections. We showed that the patterned proteins can be used for immunoassay of proteins on the functional substrate, and that they can also be used for bioelectronics device application, indicating distinct advantages with regard to accuracy and a label-free detection.

Rapid microwave fixation of rat mast cells. I. Localization of granule chymase with an ultrastructural postembedding immunogold technique.

PubMed

Login, G R; Galli, S J; Morgan, E; Arizono, N; Schwartz, L B; Dvorak, A M

1987-11-01

We defined the ultrastructural localization of chymase in rat peritoneal mast cells using standard aldehyde fixation and a newly described microwave fixation method (Login GR, Dvorak AM: Microwave energy fixation for electron microscopy. Am J Pathol 120: 230, 1985; Login GR, Stavinoha WB, Dvorak AM: Ultrafast microwave energy fixation for electron microscopy. J Histochem Cytochem 34:381, 1986) and postembedding immunogold labeling. Thin sections were exposed first to goat IgG anti-rat chymase and second to gold-conjugated rabbit Ig directed against goat IgG. By transmission electron microscopy, gold particles were localized to the matrix of cytoplasmic granules. Control sections treated with nonimmune sera did not exhibit labeling of mast cells. Thin sections treated simultaneously with purified rat mast cell chymase and anti-chymase antibody in competition studies, showed a marked reduction in granule staining. These findings demonstrate that a microwave fixation method can be used to rapidly fix cell suspensions for postembedding immunocytochemical studies.

Molecular matter waves - tools and applications

NASA Astrophysics Data System (ADS)

Juffmann, Thomas; Sclafani, Michele; Knobloch, Christian; Cheshnovsky, Ori; Arndt, Markus

2013-05-01

Fluorescence microscopy allows us to visualize the gradual emergence of a deterministic far-field matter-wave diffraction pattern from stochastically arriving single molecules. We create a slow beam of phthalocyanine molecules via laser desorption from a glass window. The small source size provides the transverse coherence required to observe an interference pattern in the far-field behind an ultra-thin nanomachined grating. There the molecules are deposited onto a quartz window and can be imaged in situ and in real time with single molecule sensitivity. This new setup not only allows for a textbook demonstration of quantum interference, but also enables quantitative explorations of the van der Waals interaction between molecules and material gratings.

Kinetic Monte Carlo simulations of travelling pulses and spiral waves in the lattice Lotka-Volterra model.

PubMed

Makeev, Alexei G; Kurkina, Elena S; Kevrekidis, Ioannis G

2012-06-01

Kinetic Monte Carlo simulations are used to study the stochastic two-species Lotka-Volterra model on a square lattice. For certain values of the model parameters, the system constitutes an excitable medium: travelling pulses and rotating spiral waves can be excited. Stable solitary pulses travel with constant (modulo stochastic fluctuations) shape and speed along a periodic lattice. The spiral waves observed persist sometimes for hundreds of rotations, but they are ultimately unstable and break-up (because of fluctuations and interactions between neighboring fronts) giving rise to complex dynamic behavior in which numerous small spiral waves rotate and interact with each other. It is interesting that travelling pulses and spiral waves can be exhibited by the model even for completely immobile species, due to the non-local reaction kinetics.

Controlling multiple plasma channels created by a high-power femtosecond laser pulse

NASA Astrophysics Data System (ADS)

Kosareva, O. G.; Luo, Q.

2005-10-01

Femtosecond light filaments are comparatively long regions of the spatially and temporally localized radiation zones, which generate free electrons in the medium. At high pulse peak power multiple filaments are produced leading to stochastic plasma channels (Mlejnek et al.: PRL 83, 2938 (1999)). In both atmospheric long-distance propagation (Sprangle et al., PRE 66, 046418 (2002), Kasparian et al, Science 301, 61 (2003)) and focusing the radiation into condensed matter important issues are production of elongated plasma channels, as well as high conversion efficiency to the white light. We control stochastic plasma channels by changing the initial beam size or shape. The result is the increase in the plasma density and white light signal. Control by regular small-scale perturbations allows us to suppress atmospheric turbulence in air and create an array of well-arranged filaments in fused silica.

Gradient-based stochastic estimation of the density matrix

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton

2018-03-01

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.

Conservation laws and symmetries in stochastic thermodynamics.

PubMed

Polettini, Matteo; Bulnes-Cuetara, Gregory; Esposito, Massimiliano

2016-11-01

Phenomenological nonequilibrium thermodynamics describes how fluxes of conserved quantities, such as matter, energy, and charge, flow from outer reservoirs across a system and how they irreversibly degrade from one form to another. Stochastic thermodynamics is formulated in terms of probability fluxes circulating in the system's configuration space. The consistency of the two frameworks is granted by the condition of local detailed balance, which specifies the amount of physical quantities exchanged with the reservoirs during single transitions between configurations. We demonstrate that the topology of the configuration space crucially determines the number of independent thermodynamic affinities (forces) that the reservoirs generate across the system and provides a general algorithm that produces the fundamental affinities and their conjugate currents contributing to the total dissipation, based on the interplay between macroscopic conservations laws for the currents and microscopic symmetries of the affinities.

Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process.

PubMed

Greenman, C D; Cooke, S L; Marshall, J; Stratton, M R; Campbell, P J

2016-01-01

Breakage-fusion-bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. Here we study the evolution space of breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are [Formula: see text] qualitatively distinct evolutions involving [Formula: see text] breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the process to show these evolutions are not equally likely, and also describe how amplicons become localized. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples.

Photon Localization and Dicke Superradiance in Atomic Gases

NASA Astrophysics Data System (ADS)

Akkermans, E.; Gero, A.; Kaiser, R.

2008-09-01

Photon propagation in a gas of N atoms is studied using an effective Hamiltonian describing photon-mediated atomic dipolar interactions. The density P(Γ) of photon escape rates is determined from the spectrum of the N×N random matrix Γij=sin⁡(xij)/xij, where xij is the dimensionless random distance between any two atoms. Varying disorder and system size, a scaling behavior is observed for the escape rates. It is explained using microscopic calculations and a stochastic model which emphasizes the role of cooperative effects in photon localization and provides an interesting relation with statistical properties of “small world networks.”

Sequential Immunofluorescent Light Microscopy and Electron Microscopy of Recombination Nodules During Meiotic Prophase I.

PubMed

Anderson, Lorinda K

2017-01-01

Immunolocalization using either fluorescence for light microscopy (LM) or gold particles for electron microscopy (EM) has become a common tool to pinpoint proteins involved in recombination during meiotic prophase. Each method has its advantages and disadvantages. For example, LM immunofluorescence is comparatively easier and higher throughput compared to immunogold EM localization. In addition, immunofluorescence has the advantages that a faint signal can often be enhanced by longer exposure times and colocalization using two (or more) probes with different absorbance and emission spectra is straightforward. However, immunofluorescence is not useful if the object of interest does not label with an antibody probe and is below the resolution of the LM. In comparison, immunogold EM localization is higher resolution than immunofluorescent LM localization, and individual nuclear structures, such as recombination nodules, can be identified by EM regardless of whether they are labeled or not. However, immunogold localization has other disadvantages including comparatively low signal-to-noise ratios, more difficult colocalization using gold particles of different sizes, and the inability to evaluate labeling efficiency before examining the sample using EM (a more expensive and time-consuming technique than LM). Here we describe a method that takes advantage of the good points of both immunofluorescent LM and EM to analyze two classes of late recombination nodules (RNs), only one of which labels with antibodies to MLH1 protein, a marker of crossovers. The method can be used readily with other antibodies to analyze early recombination nodules or other prophase I structures.

Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks.

PubMed

Ramaswamy, Rajesh; Sbalzarini, Ivo F; González-Segredo, Nélido

2011-01-28

Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.

COPII-coated membranes function as transport carriers of intracellular procollagen I

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

Gorur, Amita; Yuan, Lin; Kenny, Samuel J.

The coat protein complex II (COPII) is essential for the transport of large cargo, such as 300-nm procollagen I (PC1) molecules, from the endoplasmic reticulum (ER) to the Golgi. Previous work has shown that the CUL3-KLHL12 complex increases the size of COPII vesicles at ER exit sites to more than 300 nm in diameter and accelerates the secretion of PC1. However, the role of large COPII vesicles as PC1 transport carriers was not unambiguously demonstrated. In this study, using stochastic optical reconstruction microscopy, correlated light electron microscopy, and live-cell imaging, we demonstrate the existence of mobile COPII-coated vesicles that completelymore » encapsulate the cargo PC1 and are physically separated from ER. We also developed a cell-free COPII vesicle budding reaction that reconstitutes the capture of PC1 into large COPII vesicles. This process requires COPII proteins and the GTPase activity of the COPII subunit SAR1. We conclude that large COPII vesicles are bona fide carriers of PC1.« less

Recruitment dynamics of ESCRT-III and Vps4 to endosomes and implications for reverse membrane budding

PubMed Central

Bykov, Yury S; Sprenger, Simon; Pakdel, Mehrshad; Vogel, Georg F; Jih, Gloria; Skillern, Wesley; Behrouzi, Reza; Babst, Markus; Schmidt, Oliver; Hess, Michael W; Briggs, John AG

2017-01-01

The ESCRT machinery mediates reverse membrane scission. By quantitative fluorescence lattice light-sheet microscopy, we have shown that ESCRT-III subunits polymerize rapidly on yeast endosomes, together with the recruitment of at least two Vps4 hexamers. During their 3–45 s lifetimes, the ESCRT-III assemblies accumulated 75–200 Snf7 and 15–50 Vps24 molecules. Productive budding events required at least two additional Vps4 hexamers. Membrane budding was associated with continuous, stochastic exchange of Vps4 and ESCRT-III components, rather than steady growth of fixed assemblies, and depended on Vps4 ATPase activity. An all-or-none step led to final release of ESCRT-III and Vps4. Tomographic electron microscopy demonstrated that acute disruption of Vps4 recruitment stalled membrane budding. We propose a model in which multiple Vps4 hexamers (four or more) draw together several ESCRT-III filaments. This process induces cargo crowding and inward membrane buckling, followed by constriction of the nascent bud neck and ultimately ILV generation by vesicle fission. PMID:29019322

Identification and chemical characterization of particulate matter from wave soldering processes at a printed circuit board manufacturing company.

PubMed

Szoboszlai, Z; Kertész, Zs; Szikszai, Z; Angyal, A; Furu, E; Török, Zs; Daróczi, L; Kiss, A Z

2012-02-15

In this case study, the elemental composition and mass size distribution of indoor aerosol particles were determined in a working environment where soldering of printed circuit boards (PCB) took place. Single particle analysis using ion and electron microscopy was carried out to obtain more detailed and reliable data about the origin of these particles. As a result, outdoor and indoor aerosol sources such as wave soldering, fluxing processes, workers' activity, mineral dust, biomass burning, fertilizing and other anthropogenic sources could be separated. With the help of scanning electron microscopy, characteristic particle types were identified. On the basis of the mass size distribution data, a stochastic lung deposition model was used to calculate the total and regional deposition efficiencies of the different types of particles within the human respiratory system. The information presented in this study aims to give insights into the detailed characteristics and the health impact of aerosol particles in a working environment where different kinds of soldering activity take place. Copyright © 2011 Elsevier B.V. All rights reserved.

The endocytic recycling compartment maintains cargo segregation acquired upon exit from the sorting endosome

PubMed Central

Xie, Shuwei; Bahl, Kriti; Reinecke, James B.; Hammond, Gerald R. V.; Naslavsky, Naava; Caplan, Steve

2016-01-01

The endocytic recycling compartment (ERC) is a series of perinuclear tubular and vesicular membranes that regulates recycling to the plasma membrane. Despite evidence that cargo is sorted at the early/sorting endosome (SE), whether cargo mixes downstream at the ERC or remains segregated is an unanswered question. Here we use three-dimensional (3D) structured illumination microscopy and dual-channel and 3D direct stochastic optical reconstruction microscopy (dSTORM) to obtain new information about ERC morphology and cargo segregation. We show that cargo internalized either via clathrin-mediated endocytosis (CME) or independently of clathrin (CIE) remains segregated in the ERC, likely on distinct carriers. This suggests that no further sorting occurs upon cargo exit from SE. Moreover, 3D dSTORM data support a model in which some but not all ERC vesicles are tethered by contiguous “membrane bridges.” Furthermore, tubular recycling endosomes preferentially traffic CIE cargo and may originate from SE membranes. These findings support a significantly altered model for endocytic recycling in mammalian cells in which sorting occurs in peripheral endosomes and segregation is maintained at the ERC. PMID:26510502

Electrochemical detection of a single cytomegalovirus at an ultramicroelectrode and its antibody anchoring

PubMed Central

Dick, Jeffrey E.; Hilterbrand, Adam T.; Boika, Aliaksei; Upton, Jason W.; Bard, Allen J.

2015-01-01

We report observations of stochastic collisions of murine cytomegalovirus (MCMV) on ultramicroelectrodes (UMEs), extending the observation of discrete collision events on UMEs to biologically relevant analytes. Adsorption of an antibody specific for a virion surface glycoprotein allowed differentiation of MCMV from MCMV bound by antibody from the collision frequency decrease and current magnitudes in the electrochemical collision experiments, which shows the efficacy of the method to size viral samples. To add selectivity to the technique, interactions between MCMV, a glycoprotein-specific primary antibody to MCMV, and polystyrene bead “anchors,” which were functionalized with a secondary antibody specific to the Fc region of the primary antibody, were used to affect virus mobility. Bead aggregation was observed, and the extent of aggregation was measured using the electrochemical collision technique. Scanning electron microscopy and optical microscopy further supported aggregate shape and extent of aggregation with and without MCMV. This work extends the field of collisions to biologically relevant antigens and provides a novel foundation upon which qualitative sensor technology might be built for selective detection of viruses and other biologically relevant analytes. PMID:25870261

COPII-coated membranes function as transport carriers of intracellular procollagen I

DOE PAGES

Gorur, Amita; Yuan, Lin; Kenny, Samuel J.; ...

2017-04-20

The coat protein complex II (COPII) is essential for the transport of large cargo, such as 300-nm procollagen I (PC1) molecules, from the endoplasmic reticulum (ER) to the Golgi. Previous work has shown that the CUL3-KLHL12 complex increases the size of COPII vesicles at ER exit sites to more than 300 nm in diameter and accelerates the secretion of PC1. However, the role of large COPII vesicles as PC1 transport carriers was not unambiguously demonstrated. In this study, using stochastic optical reconstruction microscopy, correlated light electron microscopy, and live-cell imaging, we demonstrate the existence of mobile COPII-coated vesicles that completelymore » encapsulate the cargo PC1 and are physically separated from ER. We also developed a cell-free COPII vesicle budding reaction that reconstitutes the capture of PC1 into large COPII vesicles. This process requires COPII proteins and the GTPase activity of the COPII subunit SAR1. We conclude that large COPII vesicles are bona fide carriers of PC1.« less

PSD microscopy: a new technique for adaptive local scanning of microscale objects.

PubMed

Rahimi, Mehdi; Shen, Yantao

2017-01-01

A position-sensitive detector/device (PSD) is a sensor that is capable of tracking the location of a laser beam on its surface. PSDs are used in many scientific instruments and technical applications including but not limited to atomic force microscopy, human eye movement monitoring, mirrors or machine tool alignment, vibration analysis, beam position control and so on. This work intends to propose a new application using the PSD. That is a new microscopy system called scanning PSD microscopy. The working mechanism is about putting an object on the surface of the PSD and fast scanning its area with a laser beam. To achieve a high degree of accuracy and precision, a reliable framework was designed using the PSD. In this work, we first tried to improve the PSD reading and its measurement performance. This was done by minimizing the effects of noise, distortion and other disturbing parameters. After achieving a high degree of confidence, the microscopy system can be implemented based on the improved PSD measurement performance. Later to improve the scanning efficiency, we developed an adaptive local scanning system to scan the whole area of the PSD in a short matter of time. It was validated that our comprehensive and adaptive local scanning method can shorten the scanning time in order of hundreds of times in comparison with the traditional raster scanning without losing any important information about the scanned 2D objects. Methods are also introduced to scan very complicated objects with bifurcations and crossings. By incorporating all these methods, the new microscopy system is capable of scanning very complicated objects in the matter of a few seconds with a resolution that is in order of a few micrometers.

A Barcoding Strategy Enabling Higher-Throughput Library Screening by Microscopy.

PubMed

Chen, Robert; Rishi, Harneet S; Potapov, Vladimir; Yamada, Masaki R; Yeh, Vincent J; Chow, Thomas; Cheung, Celia L; Jones, Austin T; Johnson, Terry D; Keating, Amy E; DeLoache, William C; Dueber, John E

2015-11-20

Dramatic progress has been made in the design and build phases of the design-build-test cycle for engineering cells. However, the test phase usually limits throughput, as many outputs of interest are not amenable to rapid analytical measurements. For example, phenotypes such as motility, morphology, and subcellular localization can be readily measured by microscopy, but analysis of these phenotypes is notoriously slow. To increase throughput, we developed microscopy-readable barcodes (MiCodes) composed of fluorescent proteins targeted to discernible organelles. In this system, a unique barcode can be genetically linked to each library member, making possible the parallel analysis of phenotypes of interest via microscopy. As a first demonstration, we MiCoded a set of synthetic coiled-coil leucine zipper proteins to allow an 8 × 8 matrix to be tested for specific interactions in micrographs consisting of mixed populations of cells. A novel microscopy-readable two-hybrid fluorescence localization assay for probing candidate interactions in the cytosol was also developed using a bait protein targeted to the peroxisome and a prey protein tagged with a fluorescent protein. This work introduces a generalizable, scalable platform for making microscopy amenable to higher-throughput library screening experiments, thereby coupling the power of imaging with the utility of combinatorial search paradigms.

Relative permittivity and Hubbard U of pentacene extracted from scanning tunneling microscopy studies of p-doped films

NASA Astrophysics Data System (ADS)

Ha, Sieu D.; Qi, Yabing; Kahn, Antoine

2010-08-01

Temperature-dependent I- V measurements determine that pentacene is effectively p-doped by tetrafluoro-tetracyanoquinodimethane (F 4-TCNQ). It has been shown by scanning tunneling microscopy (STM) that the donated hole is localized by the ionized dopant counter potential, and that the hole can be visualized [4]. Here, it is argued that the effect of the localized hole on STM images should depend on distance as 1/ ɛr, as per the Coulomb potential. By fitting line profiles of localized hole features to the Coulomb potential, it is shown that approximate values for the relative permittivity and Hubbard U of pentacene can be extracted.

Biofilm formation and local electrostatic force characteristics of Escherichia coli O157:H7 observed by electrostatic force microscopy

NASA Astrophysics Data System (ADS)

Oh, Y. J.; Jo, W.; Yang, Y.; Park, S.

2007-04-01

The authors report growth media dependence of electrostatic force characteristics in Escherichia coli O157:H7 biofilm through local measurement by electrostatic force microscopy (EFM). The difference values of electrostatic interaction between the bacterial surface and the abiotic surface show an exponential decay behavior during biofilm development. In the EFM data, the biofilm in the low nutrient media shows a faster decay than the biofilm in the rich media. The surface potential in the bacterial cells was changed from 957to149mV. Local characterization of extracellular materials extracted from the bacteria reveals the progress of the biofilm formation and functional complexities.

Local extinction of dragonfly and damselfly populations in low- and high-quality habitat patches.

PubMed

Suhonen, Jukka; Hilli-Lukkarinen, Milla; Korkeamäki, Esa; Kuitunen, Markku; Kullas, Johanna; Penttinen, Jouni; Salmela, Jukka

2010-08-01

Understanding the risk of extinction of a single population is an important problem in both theoretical and applied ecology. Local extinction risk depends on several factors, including population size, demographic or environmental stochasticity, natural catastrophe, or the loss of genetic diversity. The probability of local extinction may also be higher in low-quality sink habitats than in high-quality source habitats. We tested this hypothesis by comparing local extinction rates of 15 species of Odonata (dragonflies and damselflies) between 1930-1975 and 1995-2003 in central Finland. Local extinction rates were higher in low-quality than in high-quality habitats. Nevertheless, for the three most common species there were no differences in extinction rates between low- and high-quality habitats. Our results suggest that a good understanding of habitat quality is crucial for the conservation of species in heterogeneous landscapes.

Characterization of Antisticking Layers for UV Nanoimprint Lithography Molds with Scanning Probe Microscopy

NASA Astrophysics Data System (ADS)

Masaaki Kurihara,; Sho Hatakeyama,; Noriko Yamada,; Takeya Shimomura,; Takaharu Nagai,; Kouji Yoshida,; Tatsuya Tomita,; Morihisa Hoga,; Naoya Hayashi,; Hiroyuki Ohtani,; Masamichi Fujihira,

2010-06-01

Antisticking layers (ASLs) on UV nanoimprint lithography (UV-NIL) molds were characterized by scanning probe microscopies (SPMs) in addition to macroscopic analyses of work of adhesion and separation force. Local physical properties of the ASLs were measured by atomic force microscopy (AFM) and friction force microscopy (FFM). The behavior of local adhesive forces measured with AFM on several surfaces was consistent with that of work of adhesion obtained from contact angle. The ASLs were coated by two different processes, i.e., one is a vapor-phase process and the other a spin-coating process. The homogeneity of the ASLs prepared by the vapor-phase process was better than that of those prepared by the spin-coating process. In addition, we measured the thicknesses of ASL patterns prepared by a lift-off method to investigate the effect of the ASL thicknesses on critical dimensions of the molds with ASLs and found that this effect is not negligible.

Intracerebral Injections and Ultrastructural Analysis of High-Pressure Frozen Brain Tissue.

PubMed

Weil, Marie-Theres; Ruhwedel, Torben; Möbius, Wiebke; Simons, Mikael

2017-01-03

Intracerebral injections are an invasive method to bypass the blood brain barrier and are widely used to study molecular and cellular mechanisms of the central nervous system. The administered substances are injected directly at the site of interest, executing their effect locally. By combining injections in the rat brain with state-of-the-art electron microscopy, subtle changes in ultrastructure of the nervous tissue can be detected prior to overt damage or disease. The protocol presented here involves stereotactic injection into the corpus callosum of Lewis rats and the cryopreparation of freshly dissected tissue for electron microscopy. The localization of the injection site in tissue sections during the sample preparation for transmission electron microscopy is explained and possible artifacts of the method are indicated. With the help of this powerful combination of injections and electron microscopy, subtle effects of the applied substances on the biology of neural cells can be identified and monitored over time. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California

Treesearch

Nik J. Cunniffe; Richard C. Cobb; Ross K. Meentemeyer; David M. Rizzo; Christopher A. Gilligan

2016-01-01

Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially-explicit model parameterized using data on...

Global Topology Optimisation

DTIC Science & Technology

2016-10-31

statistical physics. Sec. IV includes several examples of the application of the stochastic method, including matching of a shape to a fixed design, and...an important part of any future application of this method. Second, re-initialization of the level set can lead to small but significant movements of...of engineering design problems [6, 17]. However, many of the relevant applications involve non-convex optimisation problems with multiple locally

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

D’Arrigo, A., E-mail: antonio.darrigo@dmfci.unict.it; Dipartimento di Fisica e Astronomia, Università degli Studi Catania, Via Santa Sofia 64, 95123 Catania; Centro Siciliano di Fisica Nucleare e Struttura della Materia

We investigate the phenomenon of bipartite entanglement revivals under purely local operations in systems subject to local and independent classical noise sources. We explain this apparent paradox in the physical ensemble description of the system state by introducing the concept of “hidden” entanglement, which indicates the amount of entanglement that cannot be exploited due to the lack of classical information on the system. For this reason this part of entanglement can be recovered without the action of non-local operations or back-transfer process. For two noninteracting qubits under a low-frequency stochastic noise, we show that entanglement can be recovered by localmore » pulses only. We also discuss how hidden entanglement may provide new insights about entanglement revivals in non-Markovian dynamics.« less

Localization Transition Induced by Learning in Random Searches

NASA Astrophysics Data System (ADS)

Falcón-Cortés, Andrea; Boyer, Denis; Giuggioli, Luca; Majumdar, Satya N.

2017-10-01

We solve an adaptive search model where a random walker or Lévy flight stochastically resets to previously visited sites on a d -dimensional lattice containing one trapping site. Because of reinforcement, a phase transition occurs when the resetting rate crosses a threshold above which nondiffusive stationary states emerge, localized around the inhomogeneity. The threshold depends on the trapping strength and on the walker's return probability in the memoryless case. The transition belongs to the same class as the self-consistent theory of Anderson localization. These results show that similarly to many living organisms and unlike the well-studied Markovian walks, non-Markov movement processes can allow agents to learn about their environment and promise to bring adaptive solutions in search tasks.

MAP Fault Localization Based on Wide Area Synchronous Phasor Measurement Information

NASA Astrophysics Data System (ADS)

Zhang, Yagang; Wang, Zengping

2015-02-01

In the research of complicated electrical engineering, the emergence of phasor measurement units (PMU) is a landmark event. The establishment and application of wide area measurement system (WAMS) in power system has made widespread and profound influence on the safe and stable operation of complicated power system. In this paper, taking full advantage of wide area synchronous phasor measurement information provided by PMUs, we have carried out precise fault localization based on the principles of maximum posteriori probability (MAP). Large numbers of simulation experiments have confirmed that the results of MAP fault localization are accurate and reliable. Even if there are interferences from white Gaussian stochastic noise, the results from MAP classification are also identical to the actual real situation.

Line-edge roughness performance targets for EUV lithography

NASA Astrophysics Data System (ADS)

Brunner, Timothy A.; Chen, Xuemei; Gabor, Allen; Higgins, Craig; Sun, Lei; Mack, Chris A.

2017-03-01

Our paper will use stochastic simulations to explore how EUV pattern roughness can cause device failure through rare events, so-called "black swans". We examine the impact of stochastic noise on the yield of simple wiring patterns with 36nm pitch, corresponding to 7nm node logic, using a local Critical Dimension (CD)-based fail criteria Contact hole failures are examined in a similar way. For our nominal EUV process, local CD uniformity variation and local Pattern Placement Error variation was observed, but no pattern failures were seen in the modest (few thousand) number of features simulated. We degraded the image quality by incorporating Moving Standard Deviation (MSD) blurring to degrade the Image Log-Slope (ILS), and were able to find conditions where pattern failures were observed. We determined the Line Width Roughness (LWR) value as a function of the ILS. By use of an artificial "step function" image degraded by various MSD blur, we were able to extend the LWR vs ILS curve into regimes that might be available for future EUV imagery. As we decreased the image quality, we observed LWR grow and also began to see pattern failures. For high image quality, we saw CD distributions that were symmetrical and close to Gaussian in shape. Lower image quality caused CD distributions that were asymmetric, with "fat tails" on the low CD side (under-exposed) which were associated with pattern failures. Similar non-Gaussian CD distributions were associated with image conditions that caused missing contact holes, i.e. CD=0.

Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China.

PubMed

Gao, Xueping; Liu, Yinzhu; Sun, Bowen

2018-06-05

The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.

A novel PGC-1α isoform in brain localizes to mitochondria and associates with PINK1 and VDAC

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

Choi, Joungil, E-mail: jochoi@som.umaryland.edu; Veterans Affairs Medical Center, Baltimore, MD 21201; Batchu, Vera Venkatanaresh Kumar

2013-06-14

Highlights: •Novel 35 kDa PGC-1α localizes to mitochondrial inner membrane and matrix in brain. •Mitochondrial localization of 35 kDa PGC-1α depends on VDAC protein. •Mitochondrial localization of 35 kDa PGC-1α depends on membrane potential. •The 35 kDa PGC-1α associates and colocalizes with PINK in brain mitochondria. -- Abstract: Peroxisome proliferator-activated receptor-gamma co-activator 1α (PGC-1α) and PTEN-induced putative kinase 1 (PINK1) are powerful regulators of mitochondrial function. Here, we report that a previously unrecognized, novel 35 kDa PGC-1α isoform localizes to the mitochondrial inner membrane and matrix in brain as determined by protease protection and carbonate extraction assays, as well asmore » by immunoelectron microscopy. Immunoelectron microscopy and import experiments in vitro revealed that 35 kDa PGC-1α colocalizes and interacts with the voltage-dependent anion channel (VDAC), and that its import depends on VDAC. Valinomycin treatment which depolarizes the membrane potential, abolished mitochondrial localization of the 35 kDa PGC-1α. Using blue native-PAGE, co-immunoprecipitation, and immunoelectron microscopy analyses, we found that the 35 kDa PGC-1α binds and colocalizes with PINK1 in brain mitochondria. This is the first report regarding mitochondrial localization of a novel 35 kDa PGC-1α isoform and its association with PINK1, suggesting possible regulatory roles for mitochondrial function in the brain.« less

Scanning electrochemical microscopy (SECM) as a tool in biosensor research.

PubMed

Stoica, Leonard; Neugebauer, Sebastian; Schuhmann, Wolfgang

2008-01-01

Scanning electrochemical microscopy (SECM) is discussed as a versatile tool to provide localized (electro)chemical information in the context of biosensor research. Advantages of localized electrochemical measurements will be discussed and a brief introduction to SECM and its operation modes will be given. Experimental challenges of the different detection modes of SECM and its applicability for different fields in biosensor research are discussed. Among these are the evaluation of immobilization techniques by probing the local distribution of biological activity, the visualization of diffusion profiles of reactants, cofactors, mediators, and products, and the elucidation of (local) kinetic parameters. The combination of SECM with other scanning-probe techniques allows to maximize the information on a given biosensing system. The potential of SECM as a tool in micro-fabrication aiming for the fabrication of microstructured biosensors will be shortly discussed.

Local delivery of fluorescent dye for fiber-optics confocal microscopy of the living heart.

PubMed

Huang, Chao; Kaza, Aditya K; Hitchcock, Robert W; Sachse, Frank B

2014-01-01

Fiber-optics confocal microscopy (FCM) is an emerging imaging technology with various applications in basic research and clinical diagnosis. FCM allows for real-time in situ microscopy of tissue at sub-cellular scale. Recently FCM has been investigated for cardiac imaging, in particular, for discrimination of cardiac tissue during pediatric open-heart surgery. FCM relies on fluorescent dyes. The current clinical approach of dye delivery is based on systemic injection, which is associated with high dye consumption, and adverse clinical events. In this study, we investigated approaches for local dye delivery during FCM imaging based on dye carriers attached to the imaging probe. Using three-dimensional confocal microscopy, automated bench tests, and FCM imaging we quantitatively characterized dye release of carriers composed of open-pore foam only and foam loaded with agarose hydrogel. In addition, we compared local dye delivery with a model of systemic dye delivery in the isolated perfused rodent heart. We measured the signal-to-noise ratio (SNR) of images acquired in various regions of the heart. Our evaluations showed that foam-agarose dye carriers exhibited a prolonged dye release vs. foam-only carriers. Foam-agarose dye carriers allowed reliable imaging of 5-9 lines, which is comparable to 4-8 min of continuous dye release. Our study in the living heart revealed that the SNR of FCM images using local and systemic dye delivery is not different. However, we observed differences in the imaged tissue microstructure with the two approaches. Structural features characteristic of microvasculature were solely observed for systemic dye delivery. Our findings suggest that local dye delivery approach for FCM imaging constitutes an important alternative to systemic dye delivery. We suggest that the approach for local dye delivery will facilitate clinical translation of FCM, for instance, for FCM imaging during pediatric heart surgery.

Microscopy and microanalysis 1996

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

Bailey, G.W.; Corbett, J.M.; Dimlich, R.V.W.

1996-12-31

The Proceedings of this Annual Meeting contain paper of members from the three societies. These proceedings emphasizes the common research interests and attempts to eliminate some unwanted overlap. Topics covered are: microscopic analysis of animals with altered gene expression and in-situ gene and antibody localizations, high-resolution elemental mapping of nucleoprofein interactions, plant biology and pathology, quantitative HREM analysis of perfect and defected materials, computational methods for TEM image analysis, high-resolution FESM in materials research, frontiers in polymer microscopy and microanalysis, oxidation and corrosion, micro XRD and XRF, molecular microspectroscopy and spectral imaging, advances in confocal and multidimensional light microscopy, analyticalmore » electron microscopy in biology, correlative microscopy in biological sciences, grain-boundary microengineering, surfaces and interfaces, telepresence microscopy in education and research, MSA educational outreach, quantitative electron probe microanalysis, frontiers of analytical electron microscopy, critical issues in ceramic microstructures, dynamic organization of the cell, pathology, microbiology, high-resolution biological and cryo SEM, and scanning-probe microscopy.« less

Platinum replica electron microscopy: Imaging the cytoskeleton globally and locally.

PubMed

Svitkina, Tatyana M

2017-05-01

Structural studies reveal how smaller components of a system work together as a whole. However, combining high resolution of details with full coverage of the whole is challenging. In cell biology, light microscopy can image many cells in their entirety, but at a lower resolution, whereas electron microscopy affords very high resolution, but usually at the expense of the sample size and coverage. Structural analyses of the cytoskeleton are especially demanding, because cytoskeletal networks are unresolvable by light microscopy due to their density and intricacy, whereas their proper preservation is a challenge for electron microscopy. Platinum replica electron microscopy can uniquely bridge the gap between the "comfort zones" of light and electron microscopy by allowing high resolution imaging of the cytoskeleton throughout the entire cell and in many cells in the population. This review describes the principles and applications of platinum replica electron microscopy for studies of the cytoskeleton. Copyright © 2017 Elsevier Ltd. All rights reserved.

Platinum Replica Electron Microscopy: Imaging the Cytoskeleton Globally and Locally

PubMed Central

SVITKINA, Tatyana M.

2017-01-01

Structural studies reveal how smaller components of a system work together as a whole. However, combining high resolution of details with full coverage of the whole is challenging. In cell biology, light microscopy can image many cells in their entirety, but at a lower resolution, whereas electron microscopy affords very high resolution, but usually at the expense of the sample size and coverage. Structural analyses of the cytoskeleton are especially demanding, because cytoskeletal networks are unresolvable by light microscopy due to their density and intricacy, whereas their proper preservation is a challenge for electron microscopy. Platinum replica electron microscopy can uniquely bridge the gap between the “comfort zones” of light and electron microscopy by allowing high resolution imaging of the cytoskeleton throughout the entire cell and in many cells in the population. This review describes the principles and applications of platinum replica electron microscopy for studies of the cytoskeleton. PMID:28323208

Progress in the Correlative Atomic Force Microscopy and Optical Microscopy

PubMed Central

Zhou, Lulu; Cai, Mingjun; Tong, Ti; Wang, Hongda

2017-01-01

Atomic force microscopy (AFM) has evolved from the originally morphological imaging technique to a powerful and multifunctional technique for manipulating and detecting the interactions between molecules at nanometer resolution. However, AFM cannot provide the precise information of synchronized molecular groups and has many shortcomings in the aspects of determining the mechanism of the interactions and the elaborate structure due to the limitations of the technology, itself, such as non-specificity and low imaging speed. To overcome the technical limitations, it is necessary to combine AFM with other complementary techniques, such as fluorescence microscopy. The combination of several complementary techniques in one instrument has increasingly become a vital approach to investigate the details of the interactions among molecules and molecular dynamics. In this review, we reported the principles of AFM and optical microscopy, such as confocal microscopy and single-molecule localization microscopy, and focused on the development and use of correlative AFM and optical microscopy. PMID:28441775

Functional Scanning Probe Imaging of Nanostructured Solar Energy Materials

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

Giridharagopal, Rajiv; Cox, Phillip A.; Ginger, David S.

From hybrid perovskites to semiconducting polymer/fullerene blends for organic photovoltaics, many new materials being explored for energy harvesting and storage exhibit performance characteristics that depend sensitively on their nanoscale morphology. At the same time, rapid advances in the capability and accessibility of scanning probe microscopy methods over the past decade have made it possible to study processing/structure/function relationships ranging from photocurrent collection to photocarrier lifetimes with resolutions on the scale of tens of nanometers or better. Importantly, such scanning probe methods offer the potential to combine measurements of local structure with local function, and they can be implemented to studymore » materials in situ or devices in operando to better understand how materials evolve in time in response to an external stimulus or environmental perturbation. This Account highlights recent advances in the development and application of scanning probe microscopy methods that can help address such questions while filling key gaps between the capabilities of conventional electron microscopy and newer super-resolution optical methods. Focusing on semiconductor materials for solar energy applications, we highlight a range of electrical and optoelectronic scanning probe microscopy methods that exploit the local dynamics of an atomic force microscope tip to probe key properties of the solar cell material or device structure. We discuss how it is possible to extract relevant device properties using noncontact scanning probe methods as well as how these properties guide materials development. Specifically, we discuss intensity-modulated scanning Kelvin probe microscopy (IM-SKPM), time-resolved electrostatic force microscopy (trEFM), frequency-modulated electrostatic force microscopy (FM-EFM), and cantilever ringdown imaging. We explain these developments in the context of classic atomic force microscopy (AFM) methods that exploit the physics of cantilever motion and photocarrier generation to provide robust, nanoscale measurements of materials physics that are correlated with device operation. We predict that the multidimensional data sets made possible by these types of methods will become increasingly important as advances in data science expand capabilities and opportunities for image correlation and discovery.« less

Functional Scanning Probe Imaging of Nanostructured Solar Energy Materials

DOE PAGES

Giridharagopal, Rajiv; Cox, Phillip A.; Ginger, David S.

2016-08-30

From hybrid perovskites to semiconducting polymer/fullerene blends for organic photovoltaics, many new materials being explored for energy harvesting and storage exhibit performance characteristics that depend sensitively on their nanoscale morphology. At the same time, rapid advances in the capability and accessibility of scanning probe microscopy methods over the past decade have made it possible to study processing/structure/function relationships ranging from photocurrent collection to photocarrier lifetimes with resolutions on the scale of tens of nanometers or better. Importantly, such scanning probe methods offer the potential to combine measurements of local structure with local function, and they can be implemented to studymore » materials in situ or devices in operando to better understand how materials evolve in time in response to an external stimulus or environmental perturbation. This Account highlights recent advances in the development and application of scanning probe microscopy methods that can help address such questions while filling key gaps between the capabilities of conventional electron microscopy and newer super-resolution optical methods. Focusing on semiconductor materials for solar energy applications, we highlight a range of electrical and optoelectronic scanning probe microscopy methods that exploit the local dynamics of an atomic force microscope tip to probe key properties of the solar cell material or device structure. We discuss how it is possible to extract relevant device properties using noncontact scanning probe methods as well as how these properties guide materials development. Specifically, we discuss intensity-modulated scanning Kelvin probe microscopy (IM-SKPM), time-resolved electrostatic force microscopy (trEFM), frequency-modulated electrostatic force microscopy (FM-EFM), and cantilever ringdown imaging. We explain these developments in the context of classic atomic force microscopy (AFM) methods that exploit the physics of cantilever motion and photocarrier generation to provide robust, nanoscale measurements of materials physics that are correlated with device operation. We predict that the multidimensional data sets made possible by these types of methods will become increasingly important as advances in data science expand capabilities and opportunities for image correlation and discovery.« less

Predator Dispersal Determines the Effect of Connectivity on Prey Diversity

PubMed Central

Limberger, Romana; Wickham, Stephen A.

2011-01-01

Linking local communities to a metacommunity can positively affect diversity by enabling immigration of dispersal-limited species and maintenance of sink populations. However, connectivity can also negatively affect diversity by allowing the spread of strong competitors or predators. In a microcosm experiment with five ciliate species as prey and a copepod as an efficient generalist predator, we analysed the effect of connectivity on prey species richness in metacommunities that were either unconnected, connected for the prey, or connected for both prey and predator. Presence and absence of predator dispersal was cross-classified with low and high connectivity. The effect of connectivity on local and regional richness strongly depended on whether corridors were open for the predator. Local richness was initially positively affected by connectivity through rescue of species from stochastic extinctions. With predator dispersal, however, this positive effect soon turned negative as the predator spread over the metacommunity. Regional richness was unaffected by connectivity when local communities were connected only for the prey, while predator dispersal resulted in a pronounced decrease of regional richness. The level of connectivity influenced the speed of richness decline, with regional species extinctions being delayed for one week in weakly connected metacommunities. While connectivity enabled rescue of prey species from stochastic extinctions, deterministic extinctions due to predation were not overcome through reimmigration from predator-free refuges. Prey reimmigrating into these sink habitats appeared to be directly converted into increased predator abundance. Connectivity thus had a positive effect on the predator, even when the predator was not dispersing itself. Our study illustrates that dispersal of a species with strong negative effects on other community members shapes the dispersal-diversity relationship. When connections enable the spread of a generalist predator, positive effects of connectivity on prey species richness are outweighed by regional extinctions through predation. PMID:22194992