Excel spreadsheet containing, in separate sheets, the underlying numerical values for generating Fig 2A, 2B, 2C, 3A, 3B, 3C, 3D, 4A, 4B, 4C, 4D, 5A, and 5B.

This study developed a framework for quantifying the amount of risk sharing among states in the United States, and constructed data that allowed researchers to decompose the cross-sectional variance in gross state product into levels of smoothing capital markets, federal government, and credit market smoothing. The collection contains 67 Excel data files, that were grouped into 17 datasets based on the organizational ordering schematic provided by the principal investigator, including: Dataset 1 - State Personal Income: n=1,938, 51 variables Dataset 2 - Federal Taxes and Contributions: n=17,948, 424 variables Dataset 3 - State Population: n=1,887, 51 variables Dataset 4 - State and Local Personal Taxes: n=11,526, 306 variables Dataset 5 - Interests on State and Local Funds: n=7,609, 205 variables Dataset 6 - Transfers: n=5,814, 153 variables Dataset 7 - Non Federal State Income: n=1,887, 51 variables Dataset 8 - Federal Grants: n=1,938, 51 variables Dataset 9 - Federal Transfers to Individuals: n=27,415, 766 variables Dataset 10 - Federal Personal Taxes: n=1,938, 51 variables Dataset 11 - State Government Expenditure: n=1,887, 51 variables Dataset 12 - Disposable State Income: n=1,836, 51 variables Dataset 13 - State Consumption: n=5,508, 153 variables Dataset 14 - State and Local Transfers: n=1,836, 51 variables Dataset 15 - Gross State Product: n=1,910, 52 variables Dataset 16 - Retail Sales: n=3,774, 102 variables Dataset 17 - Personal Consumption Expenditures: n=38, 2 variables

Information on the FF2.xlsm file (Jan Papuga, 2024-03-04) The data provided in this xlsm file are processed via scripts written in Visual Basic, the internal programming language for Microsoft Office programs. Due to security threads, the use of macros built in Visual Basic can be forbidden when such file is opened. The user can be warned the file contains potentially malicious code and he/she is warned not to allow the full functionality of the code part. The authors ensure that no harmful code is integrated into the file and the Visual Basic code can be accessed from within the Microsoft Excel environment to check this claim. The macros are used above all for regression analyses, and if the user is not interested in running them, he/she can simply disallow their execution – in such way, the buttons visible on individual sheets will be non-functional. Despite of that, the regression results, data and graphs will still stay visible and ready to be used. For more details if required, you can contact me on: papuga@pragtic.com

Information on the tensile_props&composition.xlsx file (Martin Nesládek, 2024-05-10) This file contains basic static tensile properties and chemical composition of the material.

Snakes can move through almost any terrain. Although their locomotion on flat surfaces using planar gaits is inherently stable, when snakes deform their body out of plane to traverse complex terrain, maintaining stability becomes a challenge. On trees and desert dunes, snakes grip branches or brace against depressed sand for stability. However, how they stably surmount obstacles like boulders too large and smooth to gain such ‘anchor points’ is less understood. Similarly, snake robots are challenged to stably traverse large, smooth obstacles for search and rescue and building inspection. Our recent study discovered that snakes combine body lateral undulation and cantilevering to stably traverse large steps. Here, we developed a snake robot with this gait and snake-like anisotropic friction and used it as a physical model to understand stability principles. The robot traversed steps as high as a third of its body length rapidly and stably. However, on higher steps, it was more likely to fail due to more frequent rolling and flipping over, which was absent in the snake with a compliant body. Adding body compliance reduced the robot's roll instability by statistically improving surface contact, without reducing speed. Besides advancing understanding of snake locomotion, our robot achieved high traversal speed surpassing most previous snake robots and approaching snakes, while maintaining high traversal probability.

Designed Microsoft Excel form which was used to develop the questionnaire on the ODK.