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This software represents a complete, unsupervised processing chain that generates a continuously updating global image of the Earth from the most recent available MODIS Level 1B scenes. The software constantly updates a global image of the Earth at 250 m per pixel.
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Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.
Purpose: We propose continuous dose delivery techniques for stereotactic treatments delivered by Gamma Knife Perfexion using inverse treatment planning system that can be applied to various tumour sites in the brain. We test the accuracy of the plans on Perfexion’s planning system (GammaPlan) to ensure the obtained plans are viable. This approach introduces continuous dose delivery for Perefxion, as opposed to the currently employed step-and-shoot approaches, for different tumour sites. Additionally, this is the first realization of automated inverse planning on GammaPlan. Methods: The inverse planning approach is divided into two steps of identifying a quality path inside the target, and finding the best collimator composition for the path. To find a path, we select strategic regions inside the target volume and find a path that visits each region exactly once. This path is then passed to a mathematical model which finds the best combination of collimators and their durations. The mathematical model minimizes the dose spillage to the surrounding tissues while ensuring the prescribed dose is delivered to the target(s). Organs-at-risk and their corresponding allowable doses can also be added to the model to protect adjacent organs. Results: We test this approach on various tumour sizes and sites. The quality of the obtained treatment plans are comparable or better than forward plans and inverse plans that use step- and-shoot technique. The conformity indices in the obtained continuous dose delivery plans are similar to those of forward plans while the beam-on time is improved on average (see Table 1 in supporting document). Conclusion: We employ inverse planning for continuous dose delivery in Perfexion for brain tumours. The quality of the obtained plans is similar to forward and inverse plans that use conventional step-and-shoot technique. We tested the inverse plans on GammaPlan to verify clinical relevance. This research was partially supported by Elekta, Sweden (vendor of Gamma Knife Perfexion)
Continuous integration, delivery, and deployment (CICD) is widely used in DevOps communities, as it allows for teams of all sizes to deploy rapidly-changing hardware and software resources quickly and confidently. In this paper, we will describe how University of Colorado Boulder Research Computing has adopted these practices on the RMACC Summit supercomputer to allow system engineers and researchers alike to capitalize on the benefits of CICD-centric development workflows. We will introduce the topic of CICD at a high level and describe how such practices can ease common software management challenges for High-Performance Computing (HPC) resources. We will then document the infrastructure deployed for Summit, and explain how software such as Jenkins and Singularity enabled adaptation for an HPC environment. We will conclude with two case studies discussing the use of our CICD infrastructure: one case study from the perspective of a system engineer maintaining user-facing resources, and the other case study from the perspective of a researcher developing, maintaining, and using the MFiX-Exa codebase.
Purpose: Linac commissioning is a time consuming and labor intensive process, the streamline of which is highly desirable. In particular, manual measurement of output factors for a variety of field sizes and energy greatly hinders the commissioning efficiency. In this study, automated measurement of output factors was demonstrated as ‘one-click’ using data logging of an electrometer. Methods: Beams to be measured were created in the recording and verifying (R&V) system and configured for continuous delivery. An electrometer with an automatic data logging feature enabled continuous data collection for all fields without human intervention. The electrometer saved data into a spreadsheet every 0.5 seconds. A Matlab program was developed to analyze the excel data to monitor and check the data quality. Results: For each photon energy, output factors were measured for five configurations, including open field and four wedges. Each configuration includes 72 fields sizes, ranging from 4×4 to 20×30 cm{sup 2}. Using automation, it took 50 minutes to complete the measurement of 72 field sizes, in contrast to 80 minutes when using the manual approach. The automation avoided the necessity of redundant Linac status checks between fields as in the manual approach. In fact, the only limiting factor in such automation is Linac overheating. The data collection beams in the R&V system are reusable, and the simplified process is less error-prone. In addition, our Matlab program extracted the output factors faithfully from data logging, and the discrepancy between the automatic and manual measurement is within ±0.3%. For two separate automated measurements 30 days apart, consistency check shows a discrepancy within ±1% for 6MV photon with a 60 degree wedge. Conclusion: Automated output factor measurements can save time by 40% when compared with conventional manual approach. This work laid ground for further improvement for the automation of Linac commissioning.
Purpose: A novel rotational IMRT (rIMRT) technique using burst delivery (continuous gantry rotation with beam off during MLC repositioning) is investigated. The authors evaluate the plan quality and delivery efficiency and accuracy of this dynamic technique with a conventional flat 6 MV photon beam. Methods: Burst-delivery rIMRT was implemented in a planning system and delivered with a 160-MLC linac. Ten rIMRT plans were generated for five anonymized patient cases encompassing head and neck, brain, prostate, and prone breast. All plans were analyzed retrospectively and not used for treatment. Among the varied plan parameters were the number of optimization points, number of arcs, gantry speed, and gantry angle range (alpha) over which the beam is turned on at each optimization point. Combined rotational/step-and-shoot rIMRT plans were also created by superimposing multiple-segment static fields at several optimization points. The rIMRT trial plans were compared with each other and with plans generated using helical tomotherapy and VMAT. Burst-mode rotational IMRT plans were delivered and verified using a diode array, ionization chambers, thermoluminescent dosimeters, and film. Results: Burst-mode rIMRT can achieve plan quality comparable to helical tomotherapy, while the former may lead to slightly better OAR sparing for certain cases and the latter generally achieves slightly lower hot spots. Few instances were found in which increasing the number of optimization points above 36, or superimposing step-and-shoot IMRT segments, led to statistically significant improvements in OAR sparing. Using an additional rIMRT partial arc yielded substantial OAR dose improvements for the brain case. Measured doses from the rIMRT plan delivery were within 4% of the plan calculation in low dose gradient regions. Delivery time range was 228-375 s for single-arc rIMRT 200-cGy prescription with a 300 MU/min dose rate, comparable to tomotherapy and VMAT. Conclusions: Rotational IMRT with burst delivery, whether combined with static fields or not, yields clinically acceptable and deliverable treatment plans.
Application packaging and distribution are the final steps for delivering software to end-users; both are frequently neglected when creating scientific software. Commercial businesses rely on electronic distribution systems that have rendered disk drives obsolete. Still, national laboratories continue to rely heavily on removable media to distribute and limit access to controlled applications. With increasing concerns of unauthorized copying of sensitive applications, a modern distribution system that utilizes cryptographically secure communication and authentication protocols has been developed. This new distribution system will secure the chain of custody for nuclear software while simultaneously simplifying access to these tools. This report summarizes four primary advancements made toward the secure distribution of Nuclear Energy Advanced Modeling and Simulation (NEAMS)-developed, Multiphysics Object Oriented Simulation Environment (MOOSE)-based applications: application installation, package distribution, automated package building, and distribution of documentation. NEAMS is currently developing more than ten separate applications based on the open-source MOOSE Framework. Distribution of these applications has primarily been accomplished by distributing source code, with end-users compiling the applications themselves. This work created a mechanism where MOOSE applications can be installed in a similar way to any other software. This allows both administrators and end-users simplified access to runnable executables. With this new installation capability, it was then possible to rethink distribution. A new, secure capability for delivering MOOSE-based applications over the internet has been created. This system requires unique cryptographic tokens for authentication, greatly securing the custody chain for software. Once granted access, installation of any NEAMS code can be accomplished with these terminal commands: "conda install ncrc" "ncrc install ncrc-bison." After these two commands (and authenticating) the BISON application will be securely down- loaded from Idaho National Laboratory (INL)’s servers, installed, and ready to use. To enable this new distribution capability to be successful, the open-source Continuous Integration, Verification, Enhancement, and Testing (CIVET) Continuous Integration (CI) capability was augmented to add Continuous Delivery (CD). CD enables the automated building and packaging of MOOSE-based applications as they are modified by development teams, ensuring that our customers can obtain up-to-date versions of the software at any time. The need for instruction on how to use these applications was addressed through modifications to the MOOSE documentation system. The MooseDocs capability, which enables robust documentation of MOOSE-based applications, has been extended to allow both for the installation of documentation and the packaging of documentation with installed applications. Together, these enhancements form the core of a new, secure distribution mechanism for nuclear simulation tools. In concert with the Nuclear Computational Resource Center (NCRC), NEAMS- developed applications will now be straightforward to obtain securely.
The exposure age histograms for H-, L-, and LL-chondrites are discussed. None of these histograms is consistent with a continuous delivery of asteroidal material to the earth, as the observed T(e) histograms clearly disagree with expected exponential distributions for a variety of orbital lifetimes. It is concluded that T(e) histograms are dominated by stochastic events and that the continuous supply of asteroidal material can account only for a minor background of the T(e) histograms. An attempt is made to identify major collisional levels among the major classes of ordinary chondrites in order to estimate the frequency of stochastic events. Orbital maturity in the inner solar system is documented by the p.m./total fall ratio among observed meteorite falls. All chondrite classes exhibit a uniform ratio of 2/3 except type H5 chondrites, which reveal a 0.5 or lower p.m./total fall ratio. This shift in the time of fall statistics suggests a strongly evolved orbit for the H5 parent at the time of collision about 7 Ma ago.
Purpose: VMAT involves two main sources of uncertainty: one related to the dose calculation accuracy, and the other linked to the continuous delivery of a discrete calculation. The purpose of this work is to present QuAArC, an alternative VMAT QA system to control and potentially reduce these uncertainties. Methods: An automated MC simulation of log files, recorded during VMAT treatment plans delivery, was implemented in order to simulate the actual treatment parameters. The linac head models and the phase-space data of each Control Point (CP) were simulated using the EGSnrc/BEAMnrc MC code, and the corresponding dose calculation was carried out by means of BEAMDOSE, a DOSXYZnrc code modification. A cylindrical phantom was specifically designed to host films rolled up at different radial distances from the isocenter, for a 3D and continuous dosimetric verification. It also allows axial and/or coronal films and point measurements with several types of ion chambers at different locations. Specific software was developed in MATLAB in order to process and evaluate the dosimetric measurements, which incorporates the analysis of dose distributions, profiles, dose difference maps, and 2D/3D gamma index. It is also possible to obtain the experimental DVH reconstructed on the patient CT, by an optimization method to find the individual contribution corresponding to each CP on the film, taking into account the total measured dose, and the corresponding CP dose calculated by MC. Results: The QuAArC system showed high reproducibility of measurements, and consistency with the results obtained with the commercial system implemented in the verification of the evaluated treatment plans. Conclusion: A VMAT QA system based on MC simulation and high resolution dosimetry with film has been developed for treatment verification. It shows to be useful for the study of the real VMAT capabilities, and also for linac commissioning and evaluation of other verification devices.
Infrastructure as Code (IaC) refers to managing infrastructure (networks, physical/virtual machines, storage, and connection topology) in a descriptive model/language, rather than configuring it manually or using interactive configuration tools. Just like source code can be compiled to generate the same binary code, IaC enables generating the same environment every time it is applied. IaC is a key DevOps practice and is generally used in conjunction with continuous integration (CI) and continuous delivery (CD). In CI, all code changes are merged into a mainline branch and validated multiple times a day as developers check in their changes to the source code. In CD on the other hand, code changes are automatically packaged for a new release-to-production on a regular basis. This typically enables teams to deliver software changes much more quickly and often. Developing and managing the ACES platform using (IaC) is vital for the robust deployment and continued sustainment of this foundational computing capability. IaC and DevOps practices will help us solve many of the common challenges often encountered in developing and maintaining compute infrastructure. First, it will make the provisioning, deployment, and maintenance of the compute infrastructure across multiple environments much more efficient. Second, these processes help make the overall system much more stable by continuously testing new changes as they are introduced to the system. Third, it allows us to be much more confident of the security controls in place since they can be tested as part of the CI process and all new changes can be audited and tracked. Finally, IaC enables the ACES Platform to be adaptable to the emerging technologies due to its ability to spin up different test beds to evaluate and incorporate these technologies. This document addresses common infrastructure-management challenges, describes what happens if they are not addressed, and highlights the value of utilizing IaC to tackle them. Finally, we will provide a high-level overview of the IaC and DevOps practices being utilized by the ACES Platform team.
Purpose: Conformal radiotherapy with forward planning has many practical advantages (e.g., more uniform target dose) and has been used routinely for stereotactic body radiation therapy (SBRT) and other conventional treatment. This study investigates a forward-planning approach for conformal arc therapy and a dedicated treatment planning system (TPS) for a newly designed cobalt 60 machine with a ring type gantry and a multileaf collimator (MLC). Methods: Conformal arcs were modeled with continuous delivery of treatment fields conformal to the target cross-section. Treatment plans were further optimized by weighting or offsetting beams based on the target-critical structure relationship. CT and structure data of seven previous SBRT patients treated at our center were used for plan evaluation. An in-house forward planning tool was developed to aid the forward planning process. A graphical user interface (GUI) was designed with interactive and automatic adjustment between beam gantry angle and the beam weight. Dose distributions were calculated using our in-house Monte Carlo based TPS. Dose contributions from individual beam angles were summed together with different weight factors, which were continuously optimized until the pre-set dose conformity goal was met. Results: We were able to achieve target coverage and critical structure sparing to meet the required clinical criteria in all studied cases. It should be mentioned that those cases were selected having critical structures not proximal to the target. However, this was usually the case in the majority of SBRT cases especially those involving lung targets. The developed GUI tool was very useful in the forward treatment planning process. Conclusion: Conformal arcs can be used successfully on the new Cobalt 60 modality for the treatment of a sizeable fraction of cancer patients, which can be efficiently planned with our simple forward planning approach.
The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.
Purpose: To investigate the accuracy and potential limitations of MV image-based dynamic multileaf collimator (DMLC) tracking in a porcine model on a linear accelerator. Methods and Materials: A thermo-expandable NiTi stent designed for kilovoltage (kV) X-ray visualization of lung lesions was inserted into the bronchia of three anaesthetized Goettingen minipigs. A four-dimensional computed tomography scan was used for planning a five-field conformal treatment with circular multileaf collimator (MLC) apertures. A 22.5 Gy single fraction treatment was delivered to the pigs. The peak-to-peak stent motion was 3 to 8 mm, with breathing periods of 1.2 to 4 s. Before treatment, X-ray images were used for image-guided setup based on the stent. During treatment delivery, continuous megavoltage (MV) portal images were acquired at 7.5 Hz. The stent was segmented in the images and used for continuous adaptation of the MLC aperture. Offline, the tracking error in beam's eye view of the treatment beam was calculated for each MV image as the difference between the MLC aperture center and the segmented stent position. The standard deviations of the systematic error {Sigma} and the random error {sigma} were determined and compared with the would-be errors for a nontracking treatment with pretreatment image-guided setup. Results: Reliable stent segmentation was obtained for 11 of 15 fields. Segmentation failures occurred when image contrast was dominated by overlapping anatomical structures (ribs, diaphragm) rather than by the stent, which was designed for kV rather than MV X-ray visibility. For the 11 fields with reliable segmentation, {Sigma} was 0.5 mm/0.4 mm in the two imager directions, whereas {sigma} was 0.5 mm/1.1 mm. Without tracking, {Sigma} and {sigma} would have been 1.7 mm/1.4 mm and 0.8 mm/1.4 mm, respectively. Conclusion: For the first time, in vivo DMLC tracking has been demonstrated on a linear accelerator showing the potential for improved targeting accuracy. The study mimicked the envisioned patient workflow of future patient treatments. Clinical implementation of MV image-based tracking would require markers designed for MV visibility.
The practice of serial X-ray crystallography (SX) depends on efficient, continuous delivery of hydrated protein crystals while minimizing background scattering. Of the two major types of sample delivery devices, fixed-target devices offer several advantages over widely adopted jet injectors, including: lower sample consumption, clog-free delivery, and the ability to control on-chip crystal density to improve hit rates. In this study we present our development of versatile, inexpensive, and robust polymer microfluidic chips for routine and reliable room temperature serial measurements at both synchrotrons and X-ray free electron lasers (XFELs). Our design includes highly X-ray-transparent enclosing thin film layers tuned to minimize scatter background, adaptable sample flow layers tuned to match crystal size, and a large sample area compatible with both raster scanning and rotation based serial data collection. The optically transparent chips can be used both for in situ protein crystallization (to eliminate crystal handling) or crystal slurry loading, with prepared samples stable for weeks in a humidified environment and for several hours in ambient conditions. Serial oscillation crystallography, using a multi-crystal rotational data collection approach, at a microfocus synchrotron beamline (SSRL, beamline 12-1) was used to benchmark the performance of the chips. Furthermore, high-resolution structures (1.3–2.7 Å) were collected from five different proteins – hen egg white lysozyme, thaumatin, bovine liver catalase, concanavalin-A (type VI), and SARS-CoV-2 nonstructural protein NSP5. Overall, our modular fabrication approach enables precise control over the cross-section of materials in the X-ray beam path and facilitates chip adaption to different sample and beamline requirements for user-friendly, straightforward diffraction measurements at room temperature.
The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).
During normal and pathological conditions, endothelial cells (ECs) are subjected to locally generated reactive oxygen species, produced by themselves or by other vessel wall cells. In excess these molecules cause oxidative injury to the cell but at moderate levels they might modulate intracellular signalling pathways. We have investigated the effect of oxidative stress on the palmitoylation and trafficking of caveolin-1 in bovine aortic ECs. Exogenous H2O2 did not alter the intracellular localization of caveolin-1 in ECs. However, metabolic labelling experiments showed that H2O2 inhibited the trafficking of newly synthesized caveolin-1 to membrane raft domains. Several mechanisms potentially responsible for this inhibition were examined. Impairment of caveolin-1 synthesis by H2O2 was not responsible for diminished trafficking. Similarly, the inhibition was independent of H2O2-induced caveolin-1 phosphorylation as shown by the markedly different concentration dependences. We tested the effect of H2O2 on palmitoylation of caveolin-1 by the incorporation of [3H]palmitic acid. Exposure of ECs to H2O2 markedly inhibited the palmitoylation of caveolin-1. Comparable inhibition was observed after treatment of cells with H2O2 delivered either as a bolus or by continuous delivery with glucose and glucose oxidase. Kinetic studies showed that H2O2 did not alter the rate of caveolin-1 depalmitoylation but instead decreased the 'on-rate' of palmitoylation. Together these results show for the first time the modulation of protein palmitoylation by oxidative stress, and suggest a cellular mechanism by which stress might influence caveolin-1-dependent cell activities such as the concentration of signalling proteins and cholesterol trafficking.
Obtaining accurate and timely satellite observations is of paramount importance in fields like disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing. Stored mission data (SMD), from low Earth orbiting (LEO) satellite sensors, provides important observations for these fields and applications, however data access to SMD can be delayed from one and half hours to three hours from the time the observations were made. This data latency poses a significant impact on data product optimal use. We developed a Ground Station Observation Network (GSON) that utilizes commercial ground station as a service (GSaaS) providers to acquire low latency direct broadcast (DB) data from AQUA, SNPP, and JPSS-1 satellites using antennas located in strategic locations around the world. We will discuss techniques to improve the deployment efficiency and code reliability and quality of the GSON framework. Topics include right-sizing and containerization of the code to facilitate integration and adaptation with continuous delivery (CD) pipeline, locating non-code assets in referenceable repositories separated from code, adaptation of pipelines as code and simplification of CD, intersecting with code quality tests and checks as part of the pipeline execution and deployment, and establishing distributed repositories, registries, and system identities in a way that mitigates compromise to the CD pipeline. These techniques enable deployment of processing systems that are both highly specific but also dynamically modifiable. This new class of system allows for a flexible and scalable deployment while avoiding the “black box” issues that can plague large system deployments.