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1. CMOS Technology Scaling Trend[2017]Online

Collection
Stanford Research Data
This data set is a compilation of the historical CMOS technology scaling data presented in the ITRS, journals, and conferences including IEDM and VLSI Technology from 1988 and onward. Chi-Shuen Lee, Jieying Luo, and H.-S. Philip Wong at Stanford University compiled the data; Thomas N. Theis at Columbia University provided the data originally compiled by Robert W. Keyes at IBM T.J. Watson Research Center and published in Figure 1 of Rolf Landauer's 1988 paper. The historical scaling trend of logic switching energy and integration density were published in Figure 1 and 2, respectively in the paper, "The End of Moore’s Law: A New Beginning for Information Technology" by Theis and Wong (see Related Published Work below for the full citation.

2. Code and Data Supplement for "Near-optimal matrix recovery from random linear measurements"[2017]Online

Collection
Stanford Research Data
In matrix recovery from random linear measurements, one is interested in recovering an unknown $M$-by-$N$ matrix $X_0$ from \$n

3. Data and Source Code for Analyses of Longitudinal Cleanout Experiment, 2017[2017]Online

Collection
Reproducible Research Support for Statistics of the Microbiome
Complete ribosomal sequence variant abundance data and analysis files for paper entitled: Multidomain Analyses of a Longitudinal Human Microbiome Intestinal Cleanout Perturbation Experiment. This work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods. Funded by NIH TR01 grant AI112401.

4. Data for Heim et al. 2017 Proc B paper: Hierarchical complexity and the size limits of life[2017]Online

Collection
Payne Paleobiology Lab Data Files
Over the past 3.8 billion years, the maximum size of living organisms has increased by approximately 18 orders of magnitude. Much of this increase is associated with two major evolutionary innovations: the evolution of eukaryotes from prokaryotic cells ~ 1.9 billion years ago (Ga), and multicellular life diversifying from unicellular ancestors ~ 0.6 Ga. However, the quantitative relationship between organismal size and structural complexity remains poorly documented. We assessed this relationship using a comprehensive dataset that includes organismal size and level of biological complexity for 11,172 extant genera. We find that the distributions of sizes within complexity levels are unimodal whereas the aggregate distribution is multimodal. Moreover, both the mean size and the range of size occupied increases with each additional level of vertical complexity. Interestingly, the increase in size range is non-symmetric; the maximum organismal size increases more than the minimum. The majority of the observed increase in organismal size over the Geozoic is accounted for by two discrete jumps in complexity rather than evolutionary trends within levels of complexity. Our results provide quantitative support for an evolutionary expansion away from a minimal size constraint and suggest a fundamental rescaling of the constrains on maximal size as biological complexity increases.

5. Data repository for "Distributed representation of context by intrinsic subnetworks in prefrontal cortex"[2017]Online

Collection
Stanford Research Data
# Data for Waskom and Wagner (2017) PNAS This repository contains data related to the following paper: Waskom M.L., Wagner A.D. (2017). Distributed representation of context by intrinsic subnetworks in prefrontal cortex. Proceedings of the National Academy of the Sciences, USA. The paper is available on the PNAS website: http://www.pnas.org/cgi/doi/10.1073/pnas.1615269114 Code implementing the results in the paper is included here and is also available on github: https://github.com/WagnerLabPapers/Waskom_PNAS_2017 The datasets in this repository are organized in subdirectories as follows: ## Preprocessed data - roi_cache: Preprocessed/denoised time series data from the ROIs in the paper ## Analysis results - decoding_analysis: Decoding analyses and estimated context preferences - spatial_analysis: Spatial organization analyses - correlation_analysis: Spontaneous correlation analyses ## Supporting data - mesh: Computationally reconstructed cortex models - reg: Functional template and registration relating it to anatomical space ## Analysis code - code: A copy of the analysis code repository available on github ## License Copyright (c) 2017, Michael Waskom and Anthony Wagner Released under a CC-BY 4.0 License

6. NeuroVault.org snapshot (19th of February 2017)[2017]Online

Collection
Stanford Research Data
This a snapshot of the NeuroVault.org database. It include all public collections of statistical maps deposited in NeuroVault as long as they were linked to an external publication. This snapshot is an attempt to improve chances of long term persistance of data deposited in NeuroVault.org.

7. Palladio data model for British Architects on the Grand Tour[2017]Online

Collection
Mapping the Republic of Letters

8. Supplemental Information for Lopez, Dalton et al. "An information theoretic framework reveals a tunable allosteric network in the group II chaperonins"[2017]Online

Collection
Stanford Research Data
Group II chaperonins are ring-shaped chaperones. Their ATP-dependent allosteric regulation remains ill-defined. Given their complex oligomeric topology, structural techniques have had limited success in suggesting allosteric determinants. High sequence conservation among chaperonins has also hindered the prediction of allosteric networks, as many mathematical covariation approaches cannot be applied to conserved proteins. Here, we develop an information theoretic strategy robust to residue conservation and apply it to group II chaperonins. We identify a contiguous network of covarying residues that connects all nucleotide binding pockets within each chaperonin ring. An interfacial residue between the networks of neighboring subunits controls positive cooperativity by communicating nucleotide occupancy. Strikingly, chaperonin allostery is tunable through mutations at this position. Naturally occurring variants that double the extent of positive cooperativity are less prevalent in nature. We propose that being less cooperative that attainable allows the chaperonins to support robust folding over a wider range of metabolic conditions.

9. Supplementary data on macrophage cells for thesis entitled: "Advances on chip inside a cell for monitoring physiological cell parameters"[2017]Online

Collection
Stanford Research Data
Continuous monitoring of physiological parameters inside a living cell will lead to major advances in understanding of biology and complex diseases, such as cancer. It also enables us to develop new medical diagnostics and therapeutics. In addition, progress in nanofabrication and wireless communication has opened up the potential of making our wireless chip small enough that it can be wholly inserted into a cell. To investigate how the chip could be internalized into the cell and how the chip would affect cell physiology, we designed and fabricated a series of 3D multilayer structures with different sizes as a potential RFID (Radio Frequency IDentification) cell tracker. Our experiments show that the chips with smaller sizes than 21 micron x 9 micron x 1.5 micron can be easily internalized by various types of living cells, such as macrophages, cancer cells, and normal/healthy cells. The incubated cells with internalized chips stayed alive during the 5 days of monitoring. Also, we observed successful cell division from these incubated cells. These results are the first steps towards long-term, wireless, intracellular physiologic monitoring. This data set contains short and long videos of cell division or internalization (as indicated in the file names) of macrophages cells incubating microscale silicon chips of 4 different sizes -- 12 micron x 12 micron, 9 micron x 15 micron, 9 micron x 18 micron, and 9 micron x 21 micron.

10. Supplementary data on melanoma, breast, colon cancer, and healthy fibroblast skin cells for thesis entitled: "Advances on chip inside a cell for monitoring physiological cell parameters"[2017]Online

Collection
Stanford Research Data
Continuous monitoring of physiological parameters inside a living cell will lead to major advances in understanding of biology and complex diseases, such as cancer. It also enables us to develop new medical diagnostics and therapeutics. In addition, progress in nanofabrication and wireless communication has opened up the potential of making our wireless chip small enough that it can be wholly inserted into a cell. To investigate how the chip could be internalized into the cell and how the chip would affect cell physiology, we designed and fabricated a series of 3D multilayer structures with different sizes as a potential RFID (Radio Frequency IDentification) cell tracker. Our experiments show that the chips with smaller sizes than 21 micron x 9 micron x 1.5 micron can be easily internalized by various types of living cells, such as macrophages, cancer cells, and normal/healthy cells. The incubated cells with internalized chips stayed alive during the 5 days of monitoring. Also, we observed successful cell division from these incubated cells. These results are the first steps towards long-term, wireless, intracellular physiologic monitoring. This data set contains short and long videos of internalization or incubation of melanoma, breast, colon cancer or healthy fibroblast skin cells with microscale silicon tags of 4 different sizes -- 12 micron x 12 micron, 9 micron x 15 micron, 9 micron x 18 micron, and 9 micron x 21 micron.

11. Underwater Image Systems Simulation Sample Data[2017]Online

Collection
VISTA Lab
We use modern computer graphics tools such as ray-tracing, digital camera simulation tools, and a physically accurate model of seawater constituents to simulate how light is captured by the imaging sensor in a digital camera placed in underwater ocean environments. Our water model includes parameters for the type and amount of phytoplankton, the concentration of chlorophyll, the amount of dissolved organic matter (CDOM) and the concentration of detritus (non-algal particles, NAP). We show that by adjusting the model parameters, we can predict real sensor data captured by a digital camera at a fixed distance and depth from a reference target with known spectral reflectance. We also provide an open-source implementation of all our tools and simulations. This repository contains sample data (camera images and simulation results) that demonstrates how the simulation environment works and that allows to reproduce the analyses we present in publications.

12. A library of human electrocorticographic data and analyses[2016]Online

Collection
Stanford Research Data

13. A multimodal brain imaging dataset on sleep deprivation in young and old humans: The Sleepy Brain Project I[2016]Online

Collection
OpenfMRI Datasets
Dataset Information The Stockholm Sleepy Brain Study I is a functional brain imaging study where 48 younger (20-30 years) and 36 older (65-75 years) healthy participants underwent magnetic resonance imaging after normal sleep and partial sleep deprivation in a crossover design. We performed three experiments investigating emotional mimicry, empathy for pain, and cognitive reappraisal, as well as resting state functional magnetic resonance imaging (fMRI). We also acquired T1- and T2-weighted structural images and diffusion tensor images. On the night before imaging, participants were monitored with ambulatory polysomnography and were instructed to sleep either as usual or only three hours. Participants came to the scanner the following evening. Besides MRI scanning, participants underwent behavioral tests and contributed blood samples, which have been stored in a biobank and used for DNA analyses. Participants also completed a variety of self-report measures. The resulting multimodal dataset may be useful for hypothesis generation or independent validation of effects of sleep deprivation and aging, as well as investigation of cross-sectional associations between our different outcomes. Dataset Notes The faces, hands, and arrows task-based fMRI experiment data will be published at a later time. Update (2016/06/21): resting state fMRI will also be published at a later time. The currently published data set includes: Demographics, surveys, questionnaire data Eye tracking data High resolution T1-weighted and T2-weighted structural scans B0 field map data Diffusion-weighted imaging scans Polysomnography raw data DNA analysis results Data Descriptor Manuscript A preprint of the corresponding data descriptor manuscript (submitted) is available at the Karolinska Institutet open archive.

14. Benjamin Franklin's Correspondence (1757-1775) Palladio Data Models for Interactive Visualizations[2016]Online

Collection
Mapping the Republic of Letters
This json file that can be read with Palladio, a visualization platform developed at Stanford University for the Mapping the Republic of Letters project. The interactive visualizations include two maps with accompanying facet filters, timeline histograms, timespan charts and tables. Together, these correspondence and correspondents visualizations allow you to investigate and probe the changing nature and make-up of Franklin’s network during the London Decades (1757-1775) in your own way.

15. Bioconductor Microbiome Workflow Files[2016]Online

Collection
Reproducible Research Support for Statistics of the Microbiome
High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97\% similarity and normalize the data by subsampling to eqalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or non-parametric. We provide examples of using the R packages dada2, phyloseq, DESeq2 and vegan to filter, visualize and test microbiome data and community networks.

16. Block design food and nonfood picture viewing task[2016]Online

Collection
OpenfMRI Datasets
Thirty female subjects performed a passive viewing task with blocks of food and nonfood images. More procedures can be found in the publication" Allured or alarmed: counteractive control responses to food temptations in the brain.  "During scanning, subjects alternately viewed 24 s blocks of palatable food images (8 blocks) and non-food images (i.e., office utensils; 8 blocks), interspersed with 8–16 s rest blocks showing a crosshair (12 s on average). Halfway the task there was a 10 s break. In the image blocks, 8 images were presented for 2.5 s each with a 0.5 s inter-stimulus interval. All pictures were of equal size and displayed the (food) object on a white background. Food pictures were selected to represent foods that are both attractive and ‘forbidden’ (i.e., fattening), congruent with our definition of temptations." Dataset Contains: BOLD-contrast fMRI data and T1-weighted high resolution structural scans

17. Classification learning and reversal[2016]Online

Collection
OpenfMRI Datasets
Subjects performed two blocks of an event-related probabilistic classification learning task. They then performed two more blocks of the same task with the reward contingencies reversed.

18. Code and Data supplement to "Incoherence of Partial Component Sampling in multidimensional NMR"[2016]Online

Collection
Stanford Research Data
The data and code provided here are supplementary information for the paper “Incoherence of Partial Component Sampling in multidimensional NMR" by H. Monajemi, D.L. Donoho, J.C. Hoch, and A.D. Schuyler. Please read INSTRUCTION.TXT for reproducing the results of the article. Abstract of the article: In NMR spectroscopy, random undersampling in the indirect dimensions causes reconstruction artifacts whose size can be bounded using the so-called {\it coherence}. In experiments with multiple indirect dimensions, new undersampling approaches were recently proposed: random phase detection (RPD) \cite{Maciejewski11} and its generalization, partial component sampling (PCS) \cite{Schuyler13}. The new approaches are fully aware of the fact that high-dimensional experiments generate hypercomplex-valued free induction decays; they randomly acquire only certain low-dimensional components of each high-dimensional hypercomplex entry. We provide a classification of various hypercomplex-aware undersampling schemes, and define a hypercomplex-aware coherence appropriate for such undersampling schemes; we then use it to quantify undersampling artifacts of RPD and various PCS schemes.

19. Code supplement to "The Neogene De-greening of Central Asia" (Caves et al., 2016 Geology)[2016]Online

Collection
Stanford Research Data
This data repository contains the code used to calculate mean values of d13C and of soil respiration and to perform sensitivity tests on the analysis. To calculate soil respiration requires the installation of two packages ("soilresp" and "CRGfunc"), both of which are included in this data repository. Additionally included is the .csv file which contains the compilation of d13C data. The output of these R scripts are Figure 2 (main text) and DR Figures 3-9 (Data Repository).

20. Compilation of state data on the Affordable Care Act.[2016]Online

Dataset
1 online resource Digital: data file; text file.
Collection
Government Information United States Federal Collection
• December 2016 state-by-state data
• December 2016 state-by-state spreadsheet sources by column.
This excel table contains the most up to date state-level data available related to certain provisions of the Affordable Care Act. This table includes data on the uninsured, private market reforms, employer coverage, Medicaid, the individual market (including the Health Insurance Marketplace), and Medicare. These data are drawn from previously published sources and new analyses. Also includes a text document with sources and additional details.