Run Files Research Articles

Robust and Efficient Sorting with Offset-value Coding

Sorting and searching are large parts of database query processing, e.g., in the forms of index creation, index maintenance, and index lookup, and comparing pairs of keys is a substantial part of the effort in sorting and searching. We have worked on simple, efficient implementations of decades-old, neglected, effective techniques for fast comparisons and fast sorting, in particular offset-value coding. In the process, we happened upon its mutually beneficial relationship with prefix truncation in run files as well as the duality of compression techniques in row- and column-format storage structures, namely prefix truncation and run-length encoding of leading key columns. We also found a beneficial relationship with consumers of sorted streams, e.g., merging parallel streams, in-stream aggregation, and merge join. We report on our implementation in the context of Google’s Napa and F1 Query systems as well as an experimental evaluation of performance and scalability.

Implications of declining donor offers with increased risk of disease transmission on waiting list survival in lung transplantation.

Donors with characteristics that may increase the likelihood of disease transmission with transplantation are noted as increased risk via Public Health Service criteria. This study aimed to establish the implications of declining an increased-risk donor (IRD) organ offer in lung transplantation. Adult candidates waitlisted for isolated lung transplantation in the United States using the Organ Procurement and Transplantation Network /United Network of Organ Sharing registry from 2007 to 2017 were identified. Individual match run files identified candidate recipients who matched to an IRD offer. Competing-risks analysis ascertained the likelihood of survival to transplantation. A stratified Cox model and restricted mean survival times estimated the survival benefit associated with the acceptance of an IRD organ. A total of 6,963 candidates met inclusion criteria, and 1,473 (21.2%) accepted an IRD offer. Candidates who accepted an IRD offer were older, more likely to be male, and had a higher lung allocation score at the time of listing (all p < 0.05). At 1 year after an IRD offer decline, 70.5% of candidates underwent a lung transplant, 13.8% died or decompensated, and 14.9% were still awaiting transplant. Compared with those who declined, candidates who accepted the IRD offer had significantly improved cumulative mortality at 1 year (14.1% vs 23.9%, p < 0.001) and 5 years (48.4% vs 53.8%, p < 0.001). IRD organ declination is associated with a decreased rate of lung transplantation and worse survival. Overall post-transplant survival rates for those who survive to transplantation are equivalent.

HOW TO USE CROP GROWTH MODEL WOFOST FOR FORECASTING GROWTH AND YIELD OF A CROP

WOFOST version 7.1.3 is a computer model that simulates the growth and production of annual field crops. All the run options are operational through a graphical user interface named WOFOST Control Center version 1.8 (WCC). WCC facilitates selecting the production level, and input data sets on crop, soil, weather, crop calendar, hydrological field conditions, soil fertility parameters and the output options. The files with crop, soil and weather data are explained, as well as the run files and the output files. A general overview is given of the development and the applications of the model. Its underlying concepts are discussed briefly.

Pophelper: an R package and web app to analyse and visualizepopulation structure.

The pophelper r package and web app are software tools to aid in population structure analyses. They can be used for the analyses and visualization of output generated from population assignment programs such as admixture, structure and tess. Some of the functions include parsing output run files to tabulate data, estimating K using the Evanno method, generating files for clumpp and functionality to create barplots. These functions can be streamlined into standard r analysis workflows. The latest version of the package is available on github (https://github.com/royfrancis/pophelper). An interactive web version of the pophelper package is available which covers the same functionalities as the r package version with features such as interactive plots, cluster alignment during plotting, sorting individuals and ordering of population groups. The interactive version is available at http://pophelper.com/.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost.

Virtual Patient Case #4: Mrs. Violetta Mitsuko Tang - Chief Diagnosis: Osteoporosis/Incontinence

OPEN ACCESSJanuary 24, 2007Virtual Patient Case #4: Mrs. Violetta Mitsuko Tang - Chief Diagnosis: Osteoporosis/Incontinence Kathryn Denson Kathryn Denson Medical College of Wisconsin Google Scholar More articles by this author https://doi.org/10.15766/mep_2374-8265.136 SectionsAboutAbstract ToolsDownload Citations ShareFacebookTwitterEmail AbstractAbstractThis resource contains the virtual patient case of Mrs. Violetta Mitsuko Tang, a geriatric patient diagnosed with osteoporosis and incontinence. This case is part of a series of virtual patient cases designed to allow facilitators to demonstrate how to care for an aging population. This case contains screening/diagnostic test results, radiographic images, still pictures, genograms, and narrative case presentations. One- to three-minute long video clips depicting the patients as she ages over a 15-25 year span are also included, and these clips have been explicitly designed to limit references to specific treatments (e.g., medications) or other aspects of care that may be time-limited. A technical manual with instructions on how to administer the module is also provided. In this particular case, Mrs. Tang initially presents as a 65-year-old Japanese-American, with a history of hypertension, mild hyperthyroidism, and hip pain. Over time she develops chest pain, atrial fibrillation, degenerative joint disease, osteoporosis, and incontinence through age 80. Unique digital resources available on this resource include bone density studies, biofeedback for incontinence with computer display, interactions with array of health care professionals (e.g., physical therapist, social worker), audiogram, thyroid histology, compression fracture, and EKG. TThe flexibility and quality of virtual patient resources such as these has been attested to by both basic science and clinical faculty to enhance core curriculum lectures. This resource may also serve as problem-based core case (since facilitators access resources in response to learner questions/issues during the tutorial), an e-learning application, and, in aggregated form, a longitudinal presentation of a geriatric patient. Ultimately, the effectiveness of these resources is dependent on the creativity of faculty who determine what, how, and when the resources are incorporated into new and/or established curriculum. Educational Objectives By the end of this session, learners will be able to: Become consistent with the American Geriatrics Society's (AGS's) Basic Competencies for Care of Older Patients.Gain knowledge of common diseases/conditions of the elderly including degenerative joint disease, functional assessment, hearing and vision, incontinence, osteoporosis, thyroid disease, cardiac disease, and incontinence.Gain knowledge of multi-disciplinary team care in multiple care settings (e.g., hospital, nursing, rehabilitation, home care).Understand preventive care including screening.Understand cultural sensitivity and communication with a patient and their family. Sign up for the latest publications from MedEdPORTAL Add your email below FILES INCLUDEDReferencesRelatedDetails FILES INCLUDED Included in this publication: Run Files images pdf pictures To view all publication components, extract (i.e., unzip) them from the downloaded .zip file. This publication includes large downloadable files. If you experience difficulty downloading these files, please contact [email protected] to receive a free DVD version via mail. Download editor’s noteThis publication may contain technology or a display format that is no longer in use. Related Virtual Patient Case #1: Mr. Karl Andrews - Chief Diagnosis: Coronary Artery Disease, Diabetes and Stroke Virtual Patient Case #2: Mrs. Dubois - Chief Diagnosis: Breast Cancer Virtual Patient Case #3: Mr. Clarence Malone - Chief Diagnosis: Dementia/Depression Virtual Patient Case #4: Mrs. Violetta Mitsuko Tang - Chief Diagnosis: Osteoporosis/Incontinence Copyright & Permissions© 2007 Denson. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivatives license.KeywordsDegenerative Joint DiseaseThyroid DiseaseOsteoporosisNursing HomeUrinary IncontinenceMultidisciplinary Care Disclosures None to report. Funding/Support This research was supported by the Donald W. Reynolds Foundation, with secondary support from the Association of American Medical Colleges, John A. Hartford Foundation, Society of General Internal Medicine, and the Medical College of Wisconsin. Prior Presentations None to report. Loading ...

External sorting: Run formation revisited

External mergesort begins with a run formation phase creating the initial sorted runs. Run formation can be done by a load-sort-store algorithm or by replacement selection. A load-sort-store algorithm repeatedly fills available memory with input records, sorts them, and writes the result to a run file. Replacement selection produces longer runs than load-sort-store algorithms and completely overlaps sorting and I/O, but it has poor locality of reference resulting in frequent cache misses and the classical algorithm works only for fixed-length records. This paper introduces batched replacement selection: a cache-conscious version of replacement selection that works also for variable-length records. The new algorithm resembles AlphaSort in the sense that it creates small in-memory runs and merges them to form the output runs. Its performance is experimentally compared with three other run formation algorithms: classical replacement selection, Quicksort, and AlphaSort. The experiments show that batched replacement selection is considerably faster than classic replacement selection. For small records (average 100 bytes), CPU time was reduced by about 50 percent and elapsed time by 47-63 percent. It was also consistently faster than Quicksort, but it did not always outperform AlphaSort. Replacement selection produces fewer runs than Quicksort and AlphaSort. The experiments confirmed that this reduces the merge time whereas the effect on the overall sort time depends on the number of disks available.

A Second Generation Automated Powder Diffractometer Control System

AbstractThe real-time x-ray powder diffractometer control system AUTO incorporates several advances in data collection and analysis. Counting procedures for selected area data collection are optimized to achieve either a preselected statistical error in minimum time or a minimum error in fixed total time. Run files are employed to greatly simplify quantitative analysis procedures and for controlling repetitive runs. External calibration curves for 20 are used to eliminate all but sample dependent aberrations to peak positions. A generalized data file structure is used to document the instrumental variables and sample parameters.