Search results

1,061 results

View results as:
Number of results to display per page
Collection
Software and data produced by Baker Research Group
This page provides data and code to document the referenced paper, which examines four methods by which ground motions can be selected for dynamic seismic response analyses of engineered systems when the underlying seismic hazard is quantified via ground motion simulation rather than empirical ground motion prediction equations. Even with simulation-based seismic hazard, a ground motion selection process is still required in order to extract a small number of time series from the much larger set developed as part of the hazard calculation. Four specific methods are presented for ground motion selection from simulation-based seismic hazard analyses. One of the four methods provides a ‘benchmark’ result (i.e. using all simulated ground motions), enabling the consistency of the other three more efficient selection methods to be addressed.
This page provides data and code to document the referenced paper, which examines four methods by which ground motions can be selected for dynamic seismic response analyses of engineered systems when the underlying seismic hazard is quantified via ground motion simulation rather than empirical ground motion prediction equations. Even with simulation-based seismic hazard, a ground motion selection process is still required in order to extract a small number of time series from the much larger set developed as part of the hazard calculation. Four specific methods are presented for ground motion selection from simulation-based seismic hazard analyses. One of the four methods provides a ‘benchmark’ result (i.e. using all simulated ground motions), enabling the consistency of the other three more efficient selection methods to be addressed.
Collection
Stanford Research Data
The data package contains 10 anonymized datasets of scalp-recorded EEG in MATLAB (.mat) format. Each .mat file contains EEG data from one experimental subject. Data matrices have been preprocessed and are in the form used as input for classification. Dimensionality reduction/PCA has not been performed.
The data package contains 10 anonymized datasets of scalp-recorded EEG in MATLAB (.mat) format. Each .mat file contains EEG data from one experimental subject. Data matrices have been preprocessed and are in the form used as input for classification. Dimensionality reduction/PCA has not been performed.
Collection
VISTA Lab
This site houses sample data and code for the publication, Takemura, H., Wandell, B. A., and Pestilli, F. Ensemble tractography (under review). All code in this repository is written in MATLAB (Mathworks) and, together with the included data, can be used to reproduce several of the figures from the publication. Code and data are provided as part of the goal of ensuring that computational methods are reproducible by other researchers.
This site houses sample data and code for the publication, Takemura, H., Wandell, B. A., and Pestilli, F. Ensemble tractography (under review). All code in this repository is written in MATLAB (Mathworks) and, together with the included data, can be used to reproduce several of the figures from the publication. Code and data are provided as part of the goal of ensuring that computational methods are reproducible by other researchers.
Collection
Stanford Research Data
Comparison of magnetic characteristics of three major active regions before and after major flare.
Comparison of magnetic characteristics of three major active regions before and after major flare.
Dataset
1 online resource (1 data file, 1 text file (46 pages)) : color illustrations. Digital: data file; Excel. text file; PDF.
The NewSpace Global 2015 Investor Report examines over $10B in across over 400 investments in NewSpace. Over 250 investors and 100 companies are covered in the Report, including case studies of investment in Skybox Imaging, The Climate Corporation, and SpaceX. The DataDive contains the data at the foundation of the report, and the Analysis Guide contains "key takeaways" and conclusions based on the DataDive. Macros must be enabled to view the DataDive.
The NewSpace Global 2015 Investor Report examines over $10B in across over 400 investments in NewSpace. Over 250 investors and 100 companies are covered in the Report, including case studies of investment in Skybox Imaging, The Climate Corporation, and SpaceX. The DataDive contains the data at the foundation of the report, and the Analysis Guide contains "key takeaways" and conclusions based on the DataDive. Macros must be enabled to view the DataDive.
Collection
Stanford Research Data
We develop comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) to reveal the composition and dynamics of specific long noncoding RNA- protein complexes (lncRNPs) in vivo. ChIRP-MS across four ncRNAs nominates protein interactors likely contributing to specific RNA functions. ChIRP-MS of snRNAs discovers an U1-specific link to 3’ RNA processing machinery. Xist, a key lncRNA for X- chromosome inactivation (XCI), interacts with 81 proteins in chromatin modification, nuclear matrix, and RNA remodeling pathways. Xist lncRNP is assembled in two steps coupled with transition from pluripotency to differentiation, and Xist lncRNP is nearly identical in random vs. imprinted XCI. HnrnpK participates in Xist-mediated gene silencing and histone modifications but not Xist localization. Drosophila Split ends homolog Spen interacts via the A-repeat domain of Xist and is further required for gene silencing. Thus, Xist lncRNA engages diverse protein complexes in a modular and developmentally controlled manner to coordinate chromatin spreading and silencing. The supplemental data contain the following: Table S1. Full list of enriched U1/U2 associated proteins and the peptide counts detected in each experiment. Table S2. Sequences of ChIRP probes for the indicated RNAs and Usp9x intron-smFISH probes used in this study. Table S3. Full list of enriched Xist RBPs and the peptide counts detected in each experiment (“-“ indicates respective negative controls). Table S4. Specific vs. non-specific components in Xist lncRNP. Columns C-F indicate the ranks of peptide abundances in each of the indicated ChIRP experiments. Xist-specific interactors (highlighted in yellow) are defined as proteins with Xist ChIRP-MS rank at least twice better than in ChIRP-MS of U1, U2, and 7SK. Known gene repressors are annotated in blue. Non-specific interactors (highlighted in red) are proteins that show rank ratio <2 in Xist ChIRP vs. U1, U2, or 7SK. Many in the latter set are retrieved by all four ncRNAs and should be interpreted with caution in future ChIRP-MS experiments. Table S5. Full list of siRNAs used in this study.
We develop comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) to reveal the composition and dynamics of specific long noncoding RNA- protein complexes (lncRNPs) in vivo. ChIRP-MS across four ncRNAs nominates protein interactors likely contributing to specific RNA functions. ChIRP-MS of snRNAs discovers an U1-specific link to 3’ RNA processing machinery. Xist, a key lncRNA for X- chromosome inactivation (XCI), interacts with 81 proteins in chromatin modification, nuclear matrix, and RNA remodeling pathways. Xist lncRNP is assembled in two steps coupled with transition from pluripotency to differentiation, and Xist lncRNP is nearly identical in random vs. imprinted XCI. HnrnpK participates in Xist-mediated gene silencing and histone modifications but not Xist localization. Drosophila Split ends homolog Spen interacts via the A-repeat domain of Xist and is further required for gene silencing. Thus, Xist lncRNA engages diverse protein complexes in a modular and developmentally controlled manner to coordinate chromatin spreading and silencing. The supplemental data contain the following: Table S1. Full list of enriched U1/U2 associated proteins and the peptide counts detected in each experiment. Table S2. Sequences of ChIRP probes for the indicated RNAs and Usp9x intron-smFISH probes used in this study. Table S3. Full list of enriched Xist RBPs and the peptide counts detected in each experiment (“-“ indicates respective negative controls). Table S4. Specific vs. non-specific components in Xist lncRNP. Columns C-F indicate the ranks of peptide abundances in each of the indicated ChIRP experiments. Xist-specific interactors (highlighted in yellow) are defined as proteins with Xist ChIRP-MS rank at least twice better than in ChIRP-MS of U1, U2, and 7SK. Known gene repressors are annotated in blue. Non-specific interactors (highlighted in red) are proteins that show rank ratio <2 in Xist ChIRP vs. U1, U2, or 7SK. Many in the latter set are retrieved by all four ncRNAs and should be interpreted with caution in future ChIRP-MS experiments. Table S5. Full list of siRNAs used in this study.
Collection
Stanford Research Data
Birds improve vision by stabilizing head position with respect to the body, which is forced up and down during flapping flight. Stabilization is facilitated by compensatory motion of the sophisticated avian head-neck system. While relative head motion has been studied in stationary and walking birds, little is known about how birds accomplish head stabilization during flapping flight. To unravel this, we approximate the avian neck with a linear mass-spring-damper system for vertical displacements, analogous to proven head stabilization models for walking humans. We corroborated the model’s dimensionless natural frequency and damping ratios from high-speed video recordings of Whooper Swans (Cygnus cygnus) flying over a lake. The data show that flap-induced body oscillations can be passively attenuated through the neck by tuning neck stiffness and damping at time scales much slower than the wingbeat. We found that the passive model robustly attenuates large body oscillations, even in response to head mass and gust perturbations. Our proof of principle demonstrates that bio-inspired drones with flapping wings will record better images with a swan-inspired passive camera suspension.
Birds improve vision by stabilizing head position with respect to the body, which is forced up and down during flapping flight. Stabilization is facilitated by compensatory motion of the sophisticated avian head-neck system. While relative head motion has been studied in stationary and walking birds, little is known about how birds accomplish head stabilization during flapping flight. To unravel this, we approximate the avian neck with a linear mass-spring-damper system for vertical displacements, analogous to proven head stabilization models for walking humans. We corroborated the model’s dimensionless natural frequency and damping ratios from high-speed video recordings of Whooper Swans (Cygnus cygnus) flying over a lake. The data show that flap-induced body oscillations can be passively attenuated through the neck by tuning neck stiffness and damping at time scales much slower than the wingbeat. We found that the passive model robustly attenuates large body oscillations, even in response to head mass and gust perturbations. Our proof of principle demonstrates that bio-inspired drones with flapping wings will record better images with a swan-inspired passive camera suspension.
Database topics
Uncategorized
Dataset
1 online resource.
Public datasets related to transportation, land use, the economy, and the environment for the Bay Area.
Public datasets related to transportation, land use, the economy, and the environment for the Bay Area.
Collection
VISTA Lab
This site houses sample data and code for the publication, Takemura, H., Rokem, A., Winawer, J., Yeatman, J.D., Wandell, B. A., and Pestilli, F. A major human white-matter pathway between dorsal and ventral visual cortex. All code in this repository is written in MATLAB (Mathworks) and, together with the included data, can be used to reproduce several of the figures from the publication. Code and data are provided as part of the goal of ensuring that computational methods are reproducible by other researchers.
This site houses sample data and code for the publication, Takemura, H., Rokem, A., Winawer, J., Yeatman, J.D., Wandell, B. A., and Pestilli, F. A major human white-matter pathway between dorsal and ventral visual cortex. All code in this repository is written in MATLAB (Mathworks) and, together with the included data, can be used to reproduce several of the figures from the publication. Code and data are provided as part of the goal of ensuring that computational methods are reproducible by other researchers.
Collection
Stanford Research Data
In this supplement we include the data and R code necessary to reproduce our model fit for the eucalypt data from the paper, in two steps: First, constructData.R, which converts raw data into the processed data frames contained in allData.RData. Second, modeling.R, which loads allData.RData and fits the model that we fit in our article. There is a "lightweight version," biasCorrectionNoGrids.zip, which does not include the raw environmental grid data required to execute constructData.R, but does include allData.RData and modeling.R, so modeling.R can still be executed. See the readme file for more details. The data provided in this archive are described in Online Appendix C of Fithian et al. (2014). The presence-only species data are sourced from Atlas of Living Australia and Atlas of NSW Wildlife, Office of Environment and Heritage (OEH), both publicly available. The presence-absence data were downloaded from the Flora Survey Module of the Atlas of NSW Wildlife, Office of Environment and Heritage (OEH), and we thank them for permission to archive the data here. Any further use of these data should cite Fithian et al. (2014) and acknowledge the data sources.
In this supplement we include the data and R code necessary to reproduce our model fit for the eucalypt data from the paper, in two steps: First, constructData.R, which converts raw data into the processed data frames contained in allData.RData. Second, modeling.R, which loads allData.RData and fits the model that we fit in our article. There is a "lightweight version," biasCorrectionNoGrids.zip, which does not include the raw environmental grid data required to execute constructData.R, but does include allData.RData and modeling.R, so modeling.R can still be executed. See the readme file for more details. The data provided in this archive are described in Online Appendix C of Fithian et al. (2014). The presence-only species data are sourced from Atlas of Living Australia and Atlas of NSW Wildlife, Office of Environment and Heritage (OEH), both publicly available. The presence-absence data were downloaded from the Flora Survey Module of the Atlas of NSW Wildlife, Office of Environment and Heritage (OEH), and we thank them for permission to archive the data here. Any further use of these data should cite Fithian et al. (2014) and acknowledge the data sources.
Collection
Stanford Research Data
In this code supplement we offer a Matlab software library that includes: - A function that calculates the optimal shrinkage coefficient in known or unknown noise level. - Scripts that generate each of the figures in this paper. - A script that generates figures similar to Figure 7, comparing AMSE to MSE in various situations.
In this code supplement we offer a Matlab software library that includes: - A function that calculates the optimal shrinkage coefficient in known or unknown noise level. - Scripts that generate each of the figures in this paper. - A script that generates figures similar to Figure 7, comparing AMSE to MSE in various situations.
Collection
Software and data produced by Baker Research Group
Example code and spreadsheets to illustrate the calculations from the paper "Efficient analytical fragility function fitting using dynamic structural analysis."
Example code and spreadsheets to illustrate the calculations from the paper "Efficient analytical fragility function fitting using dynamic structural analysis."
Collection
Software and data produced by Baker Research Group
Example code to illustrate the calculations from the paper "Ground-motion intensity and damage map selection for probabilistic infrastructure network risk assessment using optimization."
Example code to illustrate the calculations from the paper "Ground-motion intensity and damage map selection for probabilistic infrastructure network risk assessment using optimization."
Collection
Research Datasets for MPEG
Camera equipped mobile devices, such as mobile phones or tablets are becoming ubiquitous platforms for deployment of visual search and augmented reality applications. A visual database is typically stored on remote servers. Hence, for a visual search, information must be either uploaded from the mobile device to the server, or downloaded from the server to the mobile device. With relatively slow wireless links, the response time of the system critically depends on how much information must be transferred. MPEG is considering standardizing technologies that will enable efficient and interoperable design of visual search applications. In particular we are seeking technologies for visual content matching in images or video. Visual content matching includes matching of views of objects, landmarks, and printed documents that is robust to partial occlusions as well as changes in vantage point, camera parameters, and lighting conditions. There are a number of component technologies that are useful for visual search, including format of visual descriptors, descriptor extraction process, as well as indexing, and matching algorithms. As a minimum, the format of descriptors as well as parts of their extraction process should be defined to ensure interoperability. It is envisioned that a standard for compact descriptors will ensure interoperability of visual search applications and databases, enable high level of performance of implementations conformant to the standard, simplify design of visual search applications, enable hardware support for descriptor extraction and matching functionality in mobile devices, reduce load on wireless networks transmitting visual search-related information. It is envisioned that such standard will provide a complementary tool to the suite of existing MPEG standards, such as MPEG-7 visual descriptors. To build full visual search application this standard may be used jointly with other standards, such as MPEG Query Format, HTTP, XML, JPEG, JPSec, and JPSearch.
Camera equipped mobile devices, such as mobile phones or tablets are becoming ubiquitous platforms for deployment of visual search and augmented reality applications. A visual database is typically stored on remote servers. Hence, for a visual search, information must be either uploaded from the mobile device to the server, or downloaded from the server to the mobile device. With relatively slow wireless links, the response time of the system critically depends on how much information must be transferred. MPEG is considering standardizing technologies that will enable efficient and interoperable design of visual search applications. In particular we are seeking technologies for visual content matching in images or video. Visual content matching includes matching of views of objects, landmarks, and printed documents that is robust to partial occlusions as well as changes in vantage point, camera parameters, and lighting conditions. There are a number of component technologies that are useful for visual search, including format of visual descriptors, descriptor extraction process, as well as indexing, and matching algorithms. As a minimum, the format of descriptors as well as parts of their extraction process should be defined to ensure interoperability. It is envisioned that a standard for compact descriptors will ensure interoperability of visual search applications and databases, enable high level of performance of implementations conformant to the standard, simplify design of visual search applications, enable hardware support for descriptor extraction and matching functionality in mobile devices, reduce load on wireless networks transmitting visual search-related information. It is envisioned that such standard will provide a complementary tool to the suite of existing MPEG standards, such as MPEG-7 visual descriptors. To build full visual search application this standard may be used jointly with other standards, such as MPEG Query Format, HTTP, XML, JPEG, JPSec, and JPSearch.
Collection
Research Datasets for MPEG
MPEG is currently developing a standard titled Compact Descriptors for Visual Search (CDVS) for descriptor extraction and compression. In this work, we develop comprehensive patch-level experiments for a direct comparison of low bitrate descriptors for visual search. For evaluating different compression schemes, we propose a data set of matching pairs of image patches from the MPEG-CDVS image-level data sets.
MPEG is currently developing a standard titled Compact Descriptors for Visual Search (CDVS) for descriptor extraction and compression. In this work, we develop comprehensive patch-level experiments for a direct comparison of low bitrate descriptors for visual search. For evaluating different compression schemes, we propose a data set of matching pairs of image patches from the MPEG-CDVS image-level data sets.
Collection
Payne Paleobiology Lab Data Files
These data were used to produce the figures and analyses presented in the Science paper by Heim et al, published in 2015.
These data were used to produce the figures and analyses presented in the Science paper by Heim et al, published in 2015.
Collection
Payne Paleobiology Lab Data Files
These data were used to produce the figures and analyses presented in the Proceedings B paper by Payne et al, published in 2014.
These data were used to produce the figures and analyses presented in the Proceedings B paper by Payne et al, published in 2014.
Collection
Stanford Research Data
These are primary data for the paper: Waskom, M.L., Kumaran, D., Gordon, A.M., Rissman, J., Wagner, A.D. (2014) Frontoparietal representations of task context support the flexible control of goal-directed cognition. Journal of Neuroscience. 34(32): 10743-10755. When unpacked, the archive will contain a directory called `data/`, which has subdirectories for each of the subjects (`dk02` - `dk16`). Each subject's directory has four subdirectories: - `nifti/`: This directory contains the four functional timeseries images (stored as compressed 4D nifti files) from the main experiment and one timeseries image from a short practice scan that was not analyzed in the paper. - `anat/`: This directory contains the high-resolution T1-weighted anatomical image, which has been processed with the Freesurfer `mri_deface` to remove identifying information. - `behav/`: This directory contains a single csv file with all relevant information about paradigm presentation and subject performance. - `design/`: This directory contains paradigm files for the three main analyses reported in the paper. Each analysis file has columns that identify the scanner run, condition name, onset time (assuming 6 TRs of T1 stabilization), and the subject's reaction time. This information is redundant with the larger `behav/behav_data.csv` file, but may be easier to work with. The data are best accompanied by the analysis code, which is openly available at https://github.com/WagnerLabPapers/Waskom_JNeurosci_2014.
These are primary data for the paper: Waskom, M.L., Kumaran, D., Gordon, A.M., Rissman, J., Wagner, A.D. (2014) Frontoparietal representations of task context support the flexible control of goal-directed cognition. Journal of Neuroscience. 34(32): 10743-10755. When unpacked, the archive will contain a directory called `data/`, which has subdirectories for each of the subjects (`dk02` - `dk16`). Each subject's directory has four subdirectories: - `nifti/`: This directory contains the four functional timeseries images (stored as compressed 4D nifti files) from the main experiment and one timeseries image from a short practice scan that was not analyzed in the paper. - `anat/`: This directory contains the high-resolution T1-weighted anatomical image, which has been processed with the Freesurfer `mri_deface` to remove identifying information. - `behav/`: This directory contains a single csv file with all relevant information about paradigm presentation and subject performance. - `design/`: This directory contains paradigm files for the three main analyses reported in the paper. Each analysis file has columns that identify the scanner run, condition name, onset time (assuming 6 TRs of T1 stabilization), and the subject's reaction time. This information is redundant with the larger `behav/behav_data.csv` file, but may be easier to work with. The data are best accompanied by the analysis code, which is openly available at https://github.com/WagnerLabPapers/Waskom_JNeurosci_2014.
Collection
Pleistocene Lake Surprise
Data Repository Item #2014221 for the paper "Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California" by Daniel E. Ibarra, Anne E. Egger, Karrie L. Weaver, Caroline R. Harris and Kate Maher. Included in the document is analytical methods, discussion of the runoff coefficient, as well as supporting figures and tables.
Data Repository Item #2014221 for the paper "Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California" by Daniel E. Ibarra, Anne E. Egger, Karrie L. Weaver, Caroline R. Harris and Kate Maher. Included in the document is analytical methods, discussion of the runoff coefficient, as well as supporting figures and tables.
Collection
Pleistocene Lake Surprise
Data tables (main text and supplement for the paper "Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California" by Daniel E. Ibarra, Anne E. Egger, Karrie L. Weaver, Caroline R. Harris and Kate Maher. All tables are provided as an xlsx file.
Data tables (main text and supplement for the paper "Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California" by Daniel E. Ibarra, Anne E. Egger, Karrie L. Weaver, Caroline R. Harris and Kate Maher. All tables are provided as an xlsx file.