scholarly journals ESRF X-rays at the service of industry

2014 ◽  
Vol 70 (a1) ◽  
pp. C591-C591
Author(s):  
Stéphanie Monaco-Malbet ◽  
Emilie Poudevigne ◽  
Michael Sztucki ◽  
Elodie Boller ◽  
Tamzin Lafford ◽  
...  
Keyword(s):  
Smart Materials ◽  
Large Scale ◽  
Business Models ◽  
Critical Role ◽  
Academic Research ◽  
Atomic Scale ◽  
X Rays ◽  
New Materials ◽  
Wide Range ◽  
The Impact

The creation and tailoring of new materials are at the heart of current industry challenges. New materials must meet ever more stringent requirements of performance, whilst fitting into the modern cradle-to-grave cycle of material production, use, and recycling. The properties and function expected of materials depend heavily upon their composition and their micro- or even nano-structure. Their "ultimate" characterisation is possible down to the atomic scale using the tools and techniques of large-scale facilities such as synchrotron X-rays. The European Synchrotron Radiation Facility (ESRF) provides the ability to visualise the atomic, nano-, and macro-structure of a huge range of complex materials, often under processing or end-use conditions and in real time. This capability lends itself to an equally wide range of industrial R&D problems which, in particular, have been adopted by the healthcare industry. Beyond drug discovery and development, the ESRF is also very active in providing analysis for micro- and nano-electronics, energy and smart materials, transport, chemistry and catalysis, engineering materials, and home and body care amongst others. In Europe and worldwide, funding agencies are requesting and demanding a stronger economic return from the significant public investments made in central facilities and this is resulting a gradual but firm pressure for stronger interactions with industry. In this context, new business models are springing to life, with more partnerships, more services, and nimble small start-ups bridging the gap between the oft "ivory tower" nature of research infrastructure and the commercially driven industry world. This presentation will present and discuss the increasingly critical role of such large-scale facilities in delivering ultimate materials characterization for innovative industrial and applied R&D, looking to both the current developments and future possibilities as well as review several examples of partnerships between research and industry and the impact these partnerships have on academic research.

scholarly journals The cardiac nanoenvironment: form and function at the nanoscale

2021 ◽  
Author(s):  
Jashan P. Singh ◽  
Jennifer L. Young
Keyword(s):  
Large Scale ◽  
New Materials ◽  
Length Scales ◽  
Form And Function ◽  
Molecular Features ◽  
Wide Range ◽  
Physiological Homeostasis ◽  
Organ Level ◽  
And Function

AbstractMechanical forces in the cardiovascular system occur over a wide range of length scales. At the whole organ level, large scale forces drive the beating heart as a synergistic unit. On the microscale, individual cells and their surrounding extracellular matrix (ECM) exhibit dynamic reciprocity, with mechanical feedback moving bidirectionally. Finally, in the nanometer regime, molecular features of cells and the ECM show remarkable sensitivity to mechanical cues. While small, these nanoscale properties are in many cases directly responsible for the mechanosensitive signaling processes that elicit cellular outcomes. Given the inherent challenges in observing, quantifying, and reconstituting this nanoscale environment, it is not surprising that this landscape has been understudied compared to larger length scales. Here, we aim to shine light upon the cardiac nanoenvironment, which plays a crucial role in maintaining physiological homeostasis while also underlying pathological processes. Thus, we will highlight strategies aimed at (1) elucidating the nanoscale components of the cardiac matrix, and (2) designing new materials and biosystems capable of mimicking these features in vitro.

scholarly journals OncoThreads: Visualization of Large Scale Longitudinal Cancer Molecular Data

2021 ◽  
Author(s):  
Theresa A Harbig ◽  
Sabrina Nusrat ◽  
Tali Mazor ◽  
Qianwen Wang ◽  
Alexander Thomson ◽  
...  
Keyword(s):  
Longitudinal Data ◽  
Large Scale ◽  
Cancer Genomics ◽  
Temporal Patterns ◽  
Molecular Data ◽  
Liquid Biopsies ◽  
Sequencing Technologies ◽  
Molecular Features ◽  
Wide Range ◽  
The Impact

Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts. To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts. The tool visualizes patient cohorts as temporal heatmaps and Sankey diagrams that support the interactive exploration and ranking of a wide range of clinical and molecular features. This allows analysts to discover temporal patterns in longitudinal data, such as the impact of mutations on response to a treatment, e.g. emergence of resistant clones. We demonstrate the functionality of OncoThreads using a cohort of 23 glioma patients sampled at 2-4 timepoints. OncoThreads is freely available at http://oncothreads.gehlenborglab.org and implemented in Javascript using the cBioPortal web API as a backend.

Ivan Kavaleridze`s dramaturgy on the Sumy stage

2021 ◽  
Author(s):  
D.V. Budianskyi
Keyword(s):  
Large Scale ◽  
Musical Comedy ◽  
Historical Figures ◽  
Wide Range ◽  
Socialist Realist ◽  
History Of ◽  
Characteristic Features ◽  
Old Men ◽  
The Impact ◽  
First Time

The characteristic features of I. Kavaleridze’s drama is considered in the article. It is noted that there are signs of the artist’s individuality, attraction to expressionist forms, artistic techniques characteristic for the art of sculpture: symbolism, monumentality, hyperbole. I. Kavaleridze was well versed in the drama laws, understood the specifics of the stage events construction, had a large arsenal of literary means, thanks to which the characters’ monologues and dialogues were extremely expressive and colorful. In his work, he implemented original solutions that were ahead of time. Therefore, many of the artist’s ideas and achievements received due recognition only after his death. I. Kavaleridze’s creative heritage covers a wide range of both purely artistic and general philosophical problems. Among them the formation of the era of modernism and its features in the Ukrainian art of the early XX century, the impact of revolutionary ideas on the work of the 1920s, the role of spiritual leaders of the Ukrainian people T. Shevchenko and G. Skovoroda in the formation of national consciousness, political and ideological pressure on figurative art language and the formation of a socialist-realist canon, etc. The analysis of the productions of I. Kavalerizde’s plays “The First Furrow” and “Gregory and Paraskeva” on the stage of the Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy in 1970-1972. The article notes that these plays were staged in Sumy for the first time in the history of Ukrainian theater. The premiere of “The First Furrow” (the play was called “Old Men”) took place on March 19, 1970. The figure of the national genius Hryhoriy Skov oroda was als o embodied for the first time on t he stage in Sumy in th e play “Hryhoriy and Paraskeva”. It premiered on October 21, 1972. I. Rybchynsky, Honored Artist of the USSR, performed the production. Creating generalized historical outlines of people’s life, features of life at that time, depicting psychological portraits of people in various, sometimes-dramatic collisions, in the productions of I. Kavaleridze’s plays on the Sumy stage the emphasis was on universal values such as virtue, love. The main character was the Ukrainian people, who nurtured such large-scale historical figures, gave them strength and wisdom for great achievements. Based on publications in periodicals of that time, memoirs of Ukrainian directors, the peculiarities of the director’s interpretation, stenographic and musical design of these plays on the Sumy stage are considered. Considerable attention is paid to the analysis of acting works in I. Kavaleridze’s plays. In particular, the peculiarities of the actor’s embodiment of the image of the national genius Hryhoriy Skovoroda on the stage are presented. It is noted that I. Kavaleridze’s plays, created in a difficult political, social and ideological context, are rightly considered to be highly artistic works of Ukrainian drama. Their staging was carried out on various theatrical stages, including Mykhailo Shchepkin Sumy Theater of Drama and Musical Comedy is an important page of national theatrical art.

scholarly journals Economics of the disintegration of the Greenland ice sheet

2019 ◽  
Vol 116 (25) ◽  
pp. 12261-12269 ◽  
Author(s):  
William Nordhaus
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Social Cost ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Reduced Form ◽  
Small Contribution ◽  
Wide Range ◽  
The Impact

Concerns about the impact on large-scale earth systems have taken center stage in the scientific and economic analysis of climate change. The present study analyzes the economic impact of a potential disintegration of the Greenland ice sheet (GIS). The study introduces an approach that combines long-run economic growth models, climate models, and reduced-form GIS models. The study demonstrates that social cost–benefit analysis and damage-limiting strategies can be usefully extended to illuminate issues with major long-term consequences, as well as concerns such as potential tipping points, irreversibility, and hysteresis. A key finding is that, under a wide range of assumptions, the risk of GIS disintegration makes a small contribution to the optimal stringency of current policy or to the overall social cost of climate change. It finds that the cost of GIS disintegration adds less than 5% to the social cost of carbon (SCC) under alternative discount rates and estimates of the GIS dynamics.

scholarly journals InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3207
Author(s):  
Ioannis Papoutsis ◽  
Charalampos Kontoes ◽  
Stavroula Alatza ◽  
Alexis Apostolakis ◽  
Constantinos Loupasakis
Keyword(s):  
Time Series ◽  
Ground Motion ◽  
Large Scale ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Processing Chain ◽  
Persistent Scatterer ◽  
Basin Scale ◽  
Wide Range ◽  
The Impact

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community.

scholarly journals Activity-dependent myelination: A glial mechanism of oscillatory self-organization in large-scale brain networks

2020 ◽  
Vol 117 (24) ◽  
pp. 13227-13237 ◽  
Author(s):  
Rabiya Noori ◽  
Daniel Park ◽  
John D. Griffiths ◽  
Sonya Bells ◽  
Paul W. Frankland ◽  
...  
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Networks ◽  
Self Organization ◽  
Conduction Delay ◽  
Neural Communication ◽  
Wide Range ◽  
The Impact ◽  
Activity Dependent

Communication and oscillatory synchrony between distributed neural populations are believed to play a key role in multiple cognitive and neural functions. These interactions are mediated by long-range myelinated axonal fiber bundles, collectively termed as white matter. While traditionally considered to be static after development, white matter properties have been shown to change in an activity-dependent way through learning and behavior—a phenomenon known as white matter plasticity. In the central nervous system, this plasticity stems from oligodendroglia, which form myelin sheaths to regulate the conduction of nerve impulses across the brain, hence critically impacting neural communication. We here shift the focus from neural to glial contribution to brain synchronization and examine the impact of adaptive, activity-dependent changes in conduction velocity on the large-scale phase synchronization of neural oscillators. Using a network model based on primate large-scale white matter neuroanatomy, our computational and mathematical results show that such plasticity endows white matter with self-organizing properties, where conduction delay statistics are autonomously adjusted to ensure efficient neural communication. Our analysis shows that this mechanism stabilizes oscillatory neural activity across a wide range of connectivity gain and frequency bands, making phase-locked states more resilient to damage as reflected by diffuse decreases in connectivity. Critically, our work suggests that adaptive myelination may be a mechanism that enables brain networks with a means of temporal self-organization, resilience, and homeostasis.

Motion Simulation Experiments for Driver Behavior and Road Vehicle Dynamics

2011 ◽  
Vol 11 (4) ◽  
Author(s):  
Kemper Lewis ◽  
Kevin Hulme ◽  
Edward Kasprzak ◽  
Deborah Moore-Russo ◽  
Gregory Fabiano
Keyword(s):  
Vehicle Dynamics ◽  
Large Scale ◽  
Driving Simulation ◽  
Vehicle Design ◽  
Simulation Environment ◽  
Learning Mechanisms ◽  
Road Vehicle ◽  
Wide Range ◽  
Traffic Systems ◽  
The Impact

This paper discusses the design and development of a motion-based driving simulation and its integration into driving simulation research. The integration of the simulation environment into a road vehicle dynamics curriculum is also presented. The simulation environment provides an immersive experience to conduct a wide range of research on driving behavior, vehicle design and intelligent traffic systems. From an education perspective, the environment is designed to promote hands-on student participation in real-world engineering experiences that enhance conventional learning mechanisms for road vehicle dynamics and engineering systems analysis. The paper assesses the impact of the environment on student learning objectives in an upper level vehicle dynamics course and presents results from research involving teenage drivers. The paper presents an integrated framework for the use of real-time simulation and large-scale visualization to both study driving behaviors and to discover the impact that design decisions have on vehicle design using a realistic simulated driving interface.

Approximate weighted matching on emerging manycore and multithreaded architectures

2012 ◽  
Vol 26 (4) ◽  
pp. 413-430 ◽  
Author(s):  
Mahantesh Halappanavar ◽  
John Feo ◽  
Oreste Villa ◽  
Antonino Tumeo ◽  
Alex Pothen
Keyword(s):  
Approximation Algorithms ◽  
Large Scale ◽  
Scientific Computing ◽  
Graph Matching ◽  
Combinatorial Problem ◽  
Fine Tuning ◽  
Matching Problem ◽  
Weighted Matching ◽  
Wide Range ◽  
The Impact

Graph matching is a prototypical combinatorial problem with many applications in high-performance scientific computing. Optimal algorithms for computing matchings are challenging to parallelize. Approximation algorithms are amenable to parallelization and are therefore important to compute matchings for large-scale problems. Approximation algorithms also generate nearly optimal solutions that are sufficient for many applications. In this paper we present multithreaded algorithms for computing half-approximate weighted matching on state-of-the-art multicore (Intel Nehalem and AMD Magny-Cours), manycore (Nvidia Tesla and Nvidia Fermi), and massively multithreaded (Cray XMT) platforms. We provide two implementations: the first uses shared work queues and is suited for all platforms; and the second implementation, based on dataflow principles, exploits special features available on the Cray XMT. Using a carefully chosen dataset that exhibits characteristics from a wide range of applications, we show scalable performance across different platforms. In particular, for one instance of the input, an R-MAT graph (RMAT-G), we show speedups of about [Formula: see text] on [Formula: see text] cores of an AMD Magny-Cours, [Formula: see text] on [Formula: see text] cores of Intel Nehalem, [Formula: see text] on Nvidia Tesla and [Formula: see text] on Nvidia Fermi relative to one core of Intel Nehalem, and [Formula: see text] on [Formula: see text] processors of Cray XMT. We demonstrate strong as well as weak scaling for graphs with up to a billion edges using up to 12,800 threads. We avoid excessive fine-tuning for each platform and retain the basic structure of the algorithm uniformly across platforms. An exception is the dataflow algorithm designed specifically for the Cray XMT. To the best of the authors' knowledge, this is the first such large-scale study of the half-approximate weighted matching problem on multithreaded platforms. Driven by the critical enabling role of combinatorial algorithms such as matching in scientific computing and the emergence of informatics applications, there is a growing demand to support irregular computations on current and future computing platforms. In this context, we evaluate the capability of emerging multithreaded platforms to tolerate latency induced by irregular memory access patterns, and to support fine-grained parallelism via light-weight synchronization mechanisms. By contrasting the architectural features of these platforms against the Cray XMT, which is specifically designed to support irregular memory-intensive applications, we delineate the impact of these choices on performance.

scholarly journals Carbon / nitrogen interactions in European forests and semi-natural vegetation. Part I: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

2019 ◽  
Author(s):  
Chris R. Flechard ◽  
Andreas Ibrom ◽  
Ute M. Skiba ◽  
Wim de Vries ◽  
Marcel van Oijen ◽  
...  
Keyword(s):  
Large Scale ◽  
Ghg Emissions ◽  
C Sequestration ◽  
Natural Vegetation ◽  
N Saturation ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Ecosystem Monitoring ◽  
Wide Range ◽  
The Impact

Abstract. The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilised, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC / dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2019) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes, soil NO3− leaching sampling, as well as results of soil incubation experiments for N and greenhouse gas (GHG) emissions, surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g (C) m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g (N) m−2 yr−1; and from −4 to 361 g (C) m−2 yr−1 at Ndep rates of 0.1 to 3.1 g (N) m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilised extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Nitrogen losses in the form of NO, N2O and especially NO3− were of the order of 10–20 % of Ndep at sites with Ndep  3 g (N) m−2 yr−1, indicating that perhaps one third of the sites were in a state of early to advanced N saturation. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g (N) m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP / GPP ratio). At elevated Ndep levels (> 2.5 g (N) m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC / dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.

scholarly journals Numerical Performance of Different Formulations for Alternating Current Optimal Power Flow

2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
Kibaek Kim
Keyword(s):  
Nonlinear Optimization ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Optimization Problems ◽  
Alternating Current ◽  
Box Constraints ◽  
Optimal Power ◽  
Wide Range ◽  
The Impact

<div>Alternating current optimal power flow (ACOPF) problems are nonconvex and nonlinear optimization problems. Utilities and independent service operators (ISO) require ACOPF to be solved in almost real time. Interior point methods (IPMs) are one of the powerful methods for solving large-scale nonlinear optimization problems and are a suitable approach for solving ACOPF with large-scale real-world transmission networks. Moreover, the choice of the formulation is as important as choosing the algorithm for solving an ACOPF problem. In this paper, different ACOPF formulations with various linear solvers and the impact of employing box constraints are evaluated for computational viability and best performance when using IPMs. Different optimization structures are used in these formulations to model the ACOPF problem representing a range of sparsity. The numerical experiments suggest that the least sparse ACOPF formulations with polar voltages yield the best computational results. Additionally, nodal injected models and current-based branch flow models are improved by enforcing box constraints. A wide range of test cases, ranging from 500-bus systems to 9591-bus systems, are used to verify the test results.</div>

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