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The objective of this presentation is to provide International Directory Network (IDN) updates on features and activities to the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS) and provider community.
We address the development of innovative algorithms designed to solve the strong-constraint Four Dimensional Variational Data Assimilation (4DVar DA) problems in large scale applications. We present a space-time decomposition approach which employs the whole domain decomposition, i.e. both along the spacial and temporal direction in the overlapping case, and the partitioning of both the solution and the operator. Starting from the global functional defined on the entire domain, we get to a sort of regularized local functionals on the set of sub domains providing the order reduction of both the predictive and the Data Assimilation models. The algorithm convergence is developed. Performance in terms of reduction of time complexity and algorithmic scalability is discussed on the Shallow Water Equations on the sphere. The number of state variables in the model, the number of observations in an assimilation cycle, as well as numerical parameters as the discretization step in time and in space domain are defined on the basis of discretization grid used by data available at repository Ocean Synthesis/Reanalysis Directory of Hamburg University.
Heat transfer through the building envelope and associated air leakage comprise the largest HVAC loads in most climates, and windows, which are known as the weakest link in the thermal envelope, are responsible for about 5 Quads, or approximately 10%, of building energy use. Therefore, windows offer a significant opportunity for building energy savings. High performance windows, such as triple glazing, though comprised of less than 2% of all US window sales in 2016 and has remained stagnant because they typically require a full and expensive redesign of the typical window sash and frame. One potential low incremental cost solution to kick start the market is upgrading the glazing with a thin-glass triple-pane design that does not require modifications to existing frame and sash. Here in this work, we first define the characteristics and performance of current “typical” residential windows through an examination of the National Fenestration Rating Council (NFRC) Certified Products Directory (CPD). With knowledge of the typical window, we determine the potential thermal performance impact of replacing typical glazing with thin-glass triple-pane glazing. Finally, with an understanding of the potential improvements to traditional performance metrics, such as U-factor, we show the energy savings potential of the thin-triple glazing in place of typical low-e windows in residential buildings is 16% in heating dominated climates such as Minneapolis, MN, 12% in mixed climates such as Washington DC, and 7% in cooling dominated climates such as Houston, TX.
Purpose: To conduct a nationwide survey to evaluate the current status of resident mentorship in radiation oncology. Methods and Materials: An anonymous electronic questionnaire was sent to all residents and recent graduates at US Accreditation Council for Graduate Medical Education–accredited radiation oncology residency programs, identified in the member directory of the Association of Residents in Radiation Oncology. Factors predictive of having a mentor and satisfaction with the mentorship experience were identified using univariate and multivariate analyses. Results: The survey response rate was 25%, with 85% of respondents reporting that mentorship plays a critical role in residency training, whereas only 53% had a current mentor. Larger programs (≥10 faculty, P=.004; and ≥10 residents, P<.001) were more likely to offer a formal mentorship program, which makes it more likely for residents to have an active mentor (88% vs 44%). Residents in a formal mentoring program reported being more satisfied with the overall mentorship experience (univariate odds ratio 8.77, P<.001; multivariate odds ratio 5, P<.001). On multivariate analysis, women were less likely to be satisfied with the mentorship experience. Conclusions: This is the first survey focusing on the status of residency mentorship in radiation oncology. Our survey highlights the unmet need for mentorship in residency programs.
Purpose: To test the hypothesis that recent resident research productivity might be different than a decade ago, and to provide contemporary information about resident scholarly activity. Methods and Materials: We compiled a list of radiation oncology residents from the 2 most recent graduating classes (June 2014 and 2015) using the Association of Residents in Radiation Oncology annual directories. We queried the PubMed database for each resident's first-authored publications from postgraduate years (PGY) 2 through 5, plus a 3-month period after residency completion. We abstracted corresponding historical data for 2002 to 2007 from the benchmark publication by Morgan and colleagues (Int J Radiat Oncol Biol Phys 2009;74:1567-1572). We tested the null hypothesis that these 2 samples had the same distribution for number of publications using the Wilcoxon rank-sum test. We explored the association of demographic factors and publication number using multivariable zero-inflated Poisson regression. Results: There were 334 residents publishing 659 eligible first-author publications during residency (range 0-17; interquartile range 0-3; mean 2.0; median 1). The contemporary and historical distributions were significantly different (P<.001); contemporary publication rates were higher. Publications accrued late in residency (27% in PGY-4, 59% in PGY-5), and most were original research (75%). In the historical cohort, half of all articles were published in 3 journals; in contrast, the top half of contemporary publications were spread over 10 journals—most commonly International Journal of Radiation Oncology • Biology • Physics (17%), Practical Radiation Oncology (7%), and Radiation Oncology (4%). Male gender, non-PhD status, and larger residency size were associated with higher number of publications in the multivariable analysis. Conclusion: We observed an increase in first-author publications during training compared with historical data from the mid-2000s. These contemporary figures may be useful to medical students considering radiation oncology, current residents, training programs, and prospective employers.
The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.
This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (H S ), mean wave period (T m ), and mean wave direction (θ m ) computed over time-slices 1979–2004 and 2081–2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.
The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.
Profiling the archival storage system in scientific computing environments has received much less attention compared to the parallel file system, but is equally important since it stores the final data products safely, for a long duration. In this paper, we analyze eight years worth of data transfer logs for accessing the archival file system (HPSS) in the Oak Ridge Leadership Computing Facility (OLCF), which has been hosting the world's largest supercomputers and file systems. Our analysis encompasses about 135 million data transfer activities to the 80 PB High Performance Storage System (HPSS), between 2010 and 2017. We analyze the logs from several dimensions, including studying the workload characteristics (e.g., access patterns, frequency of accesses and temporal behavior), file system characteristics (e.g., directory depth, file system scaling trends, file types), and scientific user behavior (e.g., domain-specific usage and organization). Based on the analysis, we derive insights into the future evolution of the archive in terms of provisioning, desired features and functionality from the archive software, role and right sizing of the archive tiers, quota management, and the importance of smart and efficient metadata and storage management. We believe our study will prove useful for both operating current archival storage and better provisioning future systems.
Data provenance provides a way for scientists to observe how experimental data originates, conveys process history, and explains influential factors such as experimental rationale and associated environmental factors from system metrics measured at runtime. The US Department of Energy Office of Science Integrated end-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) project has developed a provenance harvester that is capable of collecting observations from file based evidence typically produced by distributed applications. To achieve this, file based evidence is extracted and transformed into an intermediate data format inspired in part by W3C CSV on the Web recommendations, called the Harvester Provenance Application Interface (HAPI) syntax. This syntax provides a general means to pre-stage provenance into messages that are both human readable and capable of being written to a provenance store, Provenance Environment (ProvEn). HAPI is being applied to harvest provenance from climate ensemble runs for Accelerated Climate Modeling for Energy (ACME) project funded under the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) Earth System Modeling (ESM) program. ACME informally provides provenance in a native form through configuration files, directory structures, and log files that contain success/failure indicators, code traces, and performance measurements. Because of its generic format, HAPI is also being applied to harvest tabular job management provenance from Belle II DIRAC scheduler relational database tables as well as other scientific applications that log provenance related information.
An investigation of security resilience of the current Windows Active Directory (AD) environments to Pass-the-Hash and Pass-the-Ticket, two prominent post-exploitation, credential theft attacks.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.
Please check the README file inside the metadata directory for more information about the dataset.