Risa 3d Version
Catherin Bergan
Students and Professors can utilize a special version of RISA-2D which is aimed at teaching and understanding the basics of structural analysis. While this version has a limited number of features, it will prove to be a useful tool in expanding the students structural engineering knowledge.
Being the best version of yourself starts with your relationship with yourself. On this episode of Best Year Ever, Rob Cressy is joined by Risa Kostis as they share the mindset & process for how to build a loving relationship with yourself. One that is full of energy, positivity, and helping others. They also share lessons learned from their Driveway to Hell experience, plus the importance of lifestyle design & creating your future.
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Background: The ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment.
Results: The Risa package bridges the gap between the metadata collection and curation in an ISA-compliant way and the data analysis using the widely used statistical computing environment R. The package offers functionality for: i) parsing ISA-Tab datasets into R objects, ii) augmenting annotation with extra metadata not explicitly stated in the ISA syntax; iii) interfacing with domain specific R packages iv) suggesting potentially useful R packages available in Bioconductor for subsequent processing of the experimental data described in the ISA format; and finally v) saving back to ISA-Tab files augmented with analysis specific metadata from R. We demonstrate these features by presenting use cases for mass spectrometry data and DNA microarray data.
Conclusions: The Risa package is open source (with LGPL license) and freely available through Bioconductor. By making Risa available, we aim to facilitate the task of processing experimental data, encouraging a uniform representation of experimental information and results while delivering tools for ensuring traceability and provenance tracking.
Software availability: The Risa package is available since Bioconductor 2.11 (version 1.0.0) and version 1.2.1 appeared in Bioconductor 2.12, both along with documentation and examples. The latest version of the code is at the development branch in Bioconductor and can also be accessed from GitHub -tools/Risa, where the issue tracker allows users to report bugs or feature requests.
The Pacific RISA used qualitative input from stakeholders and available spatial data sources to build a series of maps depicting potential future land cover for the island of Maui, which can be modified as needed to suit the needs of different users and projects.
The Pacific RISA generated four future scenarios for this project, using many different datasets to represent future land cover classes for the island of Maui. This page is intended as in introduction to the scenarios and associated maps. Below are descriptions of each scenario narrative, and a summary of the steps that were taken to build them.
The current version of the data provided on this page (Version 1.1) was finalized in October 2018. A previous version (Version 1) was finalized in May 2015 and has been has been updated to reflect the cessation of sugarcane farming activities in central Maui, based on a new land cover map representing circa 2017 conditions. These data were used as the input land cover classes for the future climate/hydrological modeling component of this project. The data is available for download and modification to suit the needs of different users and projects. The Pacific RISA assumes no responsibility for any modifications to or products derived from the original datasets. To download the ArcGIS shapefile that contains the most recent Version 1.1 of the future scenario land cover classes and associated source information, please click here. For a more detailed description of how the scenario maps were created, please read the metadata, which is attached to the downloadable shapefile in xml format. The previous Version 1 and associated metadata can be found here. If you have any questions regarding the use of this data, please contact Laura Brewington, the Pacific RISA Program Manager, or check out the Frequently Asked Questions at the bottom of this page.
A set of 25 land cover classes was chosen to correspond to known parameter values for the hydrological model. Each future scenario narrative and key assumptions/components were translated into the 25 land cover classes. If participants did not agree with the spatial representation of a scenario assumption or component, the group identified potential alternative inputs and the maps were adjusted accordingly. Additionally, concepts evolved as each narrative component was depicted in a map. Four final scenario maps were produced.
This scenario reflected an interest to see how climate change could impact groundwater recharge in a future where more emphasis is placed on maintaining existing and actively restoring native forest, preventing spread of invasive species, and adding diversified agriculture and biofuels for food and energy self-sufficiency. Almost all of the current native forest cover is retained, and high investments in watershed protection facilitate the construction of additional ungulate fencing and active forest restoration within fence boundaries in the high elevations or east and west Maui. Alien forest expands in unprotected or unmanaged areas, particularly on southeast Maui, but not within ranch boundaries. Biofuel production replaces some sugarcane in central Maui as a renewable energy source, while land owned by the Department of Hawaiian Homelands (DHHL) in west Maui is also designated for future biofuel production. Remaining area that was formerly sugarcane is fallow or grassland.
Diversified agriculture as a sustainable local food source expands on new IALs, and assumes streamflow diversions or reservoir catchment for irrigation. Grasslands expand in ranching areas to promote mob grazing techniques, and some ranchland with suitable regions is converted to diversified agriculture. The Hawaiian cultural practice of taro cultivation is promoted, and assumes additional surface water use. Urban development proceeds at a slow pace, with around 60% of the projects in the 2013 Maui Island Plan database achieving completion.
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The assumption that a cyberattacker will potentially exploit all present vulnerabilities drives most modern cyber risk management practices and the corresponding security investments. We propose a new attacker model, based on dynamic optimization, where we demonstrate that large, initial, fixed costs of exploit development induce attackers to delay implementation and deployment of exploits of vulnerabilities. The theoretical model predicts that mass attackers will preferably (i) exploit only one vulnerability per software version, (ii) largely include only vulnerabilities requiring low attack complexity, and (iii) be slow at trying to weaponize new vulnerabilities. These predictions are empirically validated on a large data set of observed massed attacks launched against a large collection of information systems. Findings in this article allow cyber risk managers to better concentrate their efforts for vulnerability management, and set a new theoretical and empirical basis for further research defining attacker (offensive) processes.
N2 - The assumption that a cyberattacker will potentially exploit all present vulnerabilities drives most modern cyber risk management practices and the corresponding security investments. We propose a new attacker model, based on dynamic optimization, where we demonstrate that large, initial, fixed costs of exploit development induce attackers to delay implementation and deployment of exploits of vulnerabilities. The theoretical model predicts that mass attackers will preferably (i) exploit only one vulnerability per software version, (ii) largely include only vulnerabilities requiring low attack complexity, and (iii) be slow at trying to weaponize new vulnerabilities. These predictions are empirically validated on a large data set of observed massed attacks launched against a large collection of information systems. Findings in this article allow cyber risk managers to better concentrate their efforts for vulnerability management, and set a new theoretical and empirical basis for further research defining attacker (offensive) processes.
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