MAVEN Supra-Thermal And Thermal Ion Composition (STATIC) Particle Distributions. This collection contains files with time-ordered event rate data sorted into 12 rates x 64 energy bin arrays that are summed over multiple spins. Data are derived from APID d9. Description of the STATIC instrument can be found on the STATIC home page https://lasp.colorado.edu/maven/science/instrument-package/static/ and in the STATIC instrument publication https://doi.org/10.1007/s11214-015-0175-6.

Spin Distribution Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

MAVEN STATIC Event Rate: 12 Rate Channels Summed Over Multiple Spins Data Collection

This dataset provides endpoints for dockless mobility providers that are operating within the City of Tempe. The City of Tempe shares these data as provided and the quality of these data are the responsibility of the third-party vendor.For more information see the following Github repository.This endpoint is provided by Spin and lists the free scooters that are available within the City of Tempe.Additional InformationContact (author): Vanessa SpartanContact E-Mail (author): vanessa_spartan@tempe.gov

Deception in Roulette: A Look at Random Number Manipulation

Roulette has been a cornerstone in the study of randomness and statistics since its invention, influencing not only physical casinos but also online platforms. I have created a unique dataset that simulates a roulette wheel, not only to explore the random generation of numbers but also to illustrate how certain techniques can be easily employed by online casinos for fraudulent activities.

Dynamic Factors at Play:

-Temporal and Climatic Variables: Each spin is precisely recorded, integrating sports results and weather conditions that influence fraud techniques.

-Dynamic Fraud Techniques: I have created 53 different fraud techniques, including 5 advanced hybrid techniques that combine various manipulation methods. I select and change fraud techniques daily, adjusting them according to the 'peak hours' of casino traffic to reflect realistic manipulation methods.

-Influence of Historical Results: I use spin histories to determine 'hot' (more frequent) and 'cold' (less frequent) numbers, which are key to deciding the fraud techniques at any given moment.

-Distributions and Biases: The distributions of resulting numbers are adjusted based on these analyses, showing how historical information can be used to manipulate future results.

-Majority of Legitimate Spins: Almost 95% of the spins in this dataset are completely legitimate, without any manipulation, reflecting the normal operation of a roulette wheel.

-Fraud Concentrated During Peak Hours, Weeks, Months, and Days: The remaining 5% corresponds to fraudulent spins, strategically distributed during peak hours, weeks, months, and days, covering a period of one year. This proportion highlights the importance of thoroughly auditing these high-activity periods.

I would love to see more studies on this database, so I encourage everyone who reads this post to share the insights you discover.

Here is the list of strategies used in the dataset (some of them are not as intuitive as they might seem by their names):

0 == No Fraud 1. 'number_bias' 2. 'predictable_sequences' 3. 'color_omission' 4. 'low_range_bias' 5. 'sequence_repetition' 6. 'cyclic_alteration' 7. 'day_night_bias' 8. 'altered_zero_frequency' 9. 'random_alterations' 10. 'temporal_bias' 11. 'day_hour_bias' 12. 'day_of_week_bias' 13. 'day_of_month_bias' 14. 'bimodal_distribution' 15. 'fibonacci_bias' 16. 'parity_alteration' 17. 'prime_sequence' 18. 'double_sinusoidal_distribution' 19. 'normal_distribution' 20. 'time_series_patterns' 21. 'adaptive_variation' 22. 'wear_simulation' 23. 'advanced_hybrid_1' 24. 'advanced_hybrid_2' 25. 'advanced_hybrid_3' 26. 'advanced_hybrid_4' 27. 'advanced_hybrid_5' 28. 'previous_result_sum_bias' 29. 'special_dates_bias' 30. 'weighted_global_events_distribution' 31. 'previous_winning_combinations_bias' 32. 'sentiment_analysis_alteration' 33. 'weighted_day_of_month_bias' 34. 'weather_patterns_bias' 35. 'weighted_hour_of_day_distribution' 36. 'sports_events_bias' 37. 'lunar_cycles_modulation' 38. 'high_range_bias' 39. 'inverse_prime_sequence' 40. 'alternate_parity_bias' 41. 'zero_series_frequency' 42. 'game_history_bias' 43. 'gaussian_noise_modulation' 44. 'time_weighted_distribution_bias' 45. 'last_digit_bias' 46. 'cumulative_temporal_bias' 47. 'hidden_previous_results_patterns' 48. 'weighted_hot_cold_oscillation' 49. 'adaptive_hot_cold_sequence' 50. 'cold_number_mirage' 51. 'hot_number_evasion' 52. 'false_cold' 53. 'hot_deviation'

Attached is an example of analysis for a specific hour using a specific strategy, in this case, "double_sinusoidal_distribution":

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F9698182%2Ff536eaa650aeebb5737a9d9a2ec53665%2Foutputexample.png?generation=1720566276284440&alt=media" alt="">

Health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost, and durable products. In an effort to address technical issues concerning health monitoring, this article considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating turbine engine-like-disk to detect the disk faults and assess its structural integrity. The experimental results composed at a range of rotational speeds from tests conducted at the NASA Glenn Research Center’s Rotordynamics Laboratory are evaluated and integrated into multiple data-driven anomaly detection techniques to identify faults and anomalies in the disk. In summary, this study presents a select evaluation of online health monitoring of a rotating disk using high caliber capacitive sensors and demonstrates the capability of the in-house spin system.

Spins Sweet And Savory Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Supporting data for "Robust spin squeezing from the tower of states of U(1)-symmetric spin Hamiltonians" (https://link.aps.org/doi/10.1103/PhysRevA.105.022625, https://arxiv.org/abs/2103.07354), by Tommaso Comparin, Fabio Mezzacapo and Tommaso Roscilde. If you use these data in a scientific work, please cite the corresponding article. For additional details, please contact Tommaso Comparin (tommaso.comparin@ens-lyon.fr).

This dataset includes tVMC results for several values of the coupling exponent alpha and of the system size N (see file names). Each file includes a set of relevant observables (see file header).

These results are directly shown in Figures 1, 3, 7, 9. Further data processing leads to Fig. 4.

Details on the variational Ansatz for tVMC - We employ the pair-product Ansatz defined in the main text. In general, there are N*(N-1)/2 independent spin pairs with 4 possible states for each pair, leading to 4*N complex coefficients. - Thanks to translational invariance, we can use coefficients which only depend on the distance between the two spins, reducing the number of independent pairs to N/2 (for a one-dimensional chain with periodic boundary conditions). - We also impose the spin-inversion symmetry for each spin pair, so that configurations like {up,down} and {down,up} have the same coefficient. - Therefore the total number of variational coefficients in our tVMC simulations is equal to N.

NOTE: Data are provided without error bars. An analysis of the statistical/systematic errors is included in the folder Errors, for some representative cases.

The dataset contains pitching data from Joe Musgrove collected from the 2022 MLB Regular & Post season.
Allegations of a foreign substance to increase Spin Rate were brought up during the Playoffs vs NY Mets. I was curious to find out if the data would suggest this was the case.

I was interested in finding if there had been a significant increase in his Spin Rate in Regular Season vs Post season, and if so did it have an impact? Please use this dataset to investigate and draw your own conclusions.

All data was collected from MLB Baseball Savant and then cleaned for analysis in SQL. I have also converted the batter column from an MLB assigned ID number to batter 'Last name, First name' for ease of use.

This dataset contains the predicted prices of the asset Spins Club over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

'Laser-written waveguide-integrated coherent spins in diamond' dataThe dataset includes excel files with the raw data for each figure in the manuscript. The filename of the files points towards each labelled subplot in each figure and the necessary description.Figure 1 is photoluminescence (PL) studies of laser-written waveguide integrated nitrogen-vacancy centers (WGINVs). (a) PL map of WGINV A in type IIa diamond from the z-direction (overhead). It includes x-y and x-z planes with the resolution of 250 nm and PL rate unit of kHz, and x, y, z slices from PL maps. (b) The emission spectrum of single WGINV A and ensemble NVs. (c) The photon emission correlation of single WGINV A. (d) The power-dependent PL rate for single WGINV A. (e) PL map of WGINVs in type Ib diamond from the z-direction (overhead). It includes x-y and x-z planes with the resolution of 250 nm and PL rate unit of Hz, and x, y, z slices from PL maps. (f) PL map of the WGINVs in type Ib diamond mapped from the y-direction (along the waveguide). It includes x-y and x-z planes with the resolution of 250 nm and PL rate unit of kHz, and x, z slices from PL map. Figure 2 is optically detected magnetic resonance (ODMR) spectra of single WGINVs and ensemble WGINVs.(a) includes continuous wave (CW) and pulse zero-field ODMR for single WGINV A. (b) includes CW and pulse ODMR with applied magnetic field for single WGINV A. (c) includes CW and pulse zero-field ODMR for single WGINV B.(d) includes CW and pulse ODMR with applied magnetic field for single WGINV B. (e) is the zero-field ODMR for ensemble WGINVs(f) is CW ODMR with applied magnetic field for ensemble WGINVs.Figure 3 is the time domain ODMR spectrum of single WGINVs in type IIa diamond (from (a) to (h)) and ensemble WGINVs in type Ib diamond (from (i) to (l)). (a), (b), (c), and (d) are Rabi, free induced decay (FID), Hahn echo, and relaxometry measurements for single WGINV A. (e), (f), (g), and (h) are Rabi, FID, Hahn echo, and relaxometry measurements for single WGINV B. (i), (j), (k), and (l) are Rabi, free induced decay (FID), Hahn echo, and relaxometry measurements for ensemble WGINVs. Figure 4 is an illustration figure, and does not contain any raw data to be included as part of this data repository.Figure 5 is high-resolution confocal normalized PL image of single WGINVs A in type IIa diamond. It includes the PL maps from x-y plane and x-z plane with the resolution of 50 nm, and the x, y, z slices from PL maps.Figure 6 is Rabi oscillations for single WGINV A (a) and single WGINV B (b) at weak MW power.Reserach results based upon these data are published at https://doi.org/10.1063/5.0209294

This dataset provides endpoints for dockless mobility providers that are operating within the City of Tempe. The City of Tempe shares these data as provided and the quality of these data are the responsibility of the third-party vendor.For more information see the following Github repository.This endpoint is provided by Spin and makes available metadata information about its dockless mobility service.Additional InformationContact (author): Vanessa SpartanContact E-Mail (author): vanessa_spartan@tempe.gov

This data set contains the raw data files as well as the analysis code used to produce all the experimental plots in the PhD thesis 'Coherent dynamics of atomic spins on a surface' by Lukas M. Veldman under supervision of prof. Sander Otte at the TU Delft. It contains measurements done with a scanning tunneling microscope (STM) on individual titanium atoms adsorbed on MgO thin films on top of Ag(100). Using electron spin resonance (ESR) methods, transitions between different spin states of a single atoms can be driven, revealing their magnetic state space. By using DC pulses in a pump-probe scheme, we inject a single spin excitation into the atomic structures and observe the resulting dynamics. This way, we are able to study the propagation of a spin excitation between the electron spins of individual magnetic atoms as well as between the electron spin and the nuclear spin within a single atom. The dataset is ordered by chapter that contains experimental data.

This is a tabulation of determinations of asteroid pole orientations gathered from the literature from 1932 through 1995. It is an updated (Dec. 1995) version of the tabulation given in Magnusson (1989) [MAGNUSSON1989] in the Asteroids II book. For more information about the Uppsala Asteroid Database, of which this collection is a part, see Magnusson et al. 1993 [MAGNUSSONETAL1993].

Comprehensive financial and analytical metrics for Spin, including key performance indicators, market data, and ecosystem analytics.

Data repository for: Microwave spectroscopy of interacting Andreev spins

Andreev bound states are fermionic states localized in weak links between superconductors which can be occupied with spinful quasiparticles. Microwave experiments using superconducting circuits with InAs/Al nanowire Josephson junctions have recently enabled probing and coherent manipulation of Andreev states but have remained limited to zero or small magnetic fields. Here we use a flux-tunable superconducting circuit compatible in magnetic fields up to 1T to perform spectroscopy of spin-polarized Andreev states up to ∼ 250 mT, beyond which the spectrum becomes gapless. We identify singlet and triplet states of two quasiparticles occupying different Andreev states through their dispersion in magnetic field. These states are split by exchange interaction and couple via spinorbit coupling, analogously to two-electron states in quantum dots. We also show that the magnetic field allows to drive a direct spin-flip transition of a single quasiparticle trapped in the junction. Finally, we measure a gate- and field-dependent anomalous phase shift of the Andreev spectrum, of magnitude up to ∼ 0.7π. Our observations demonstrate new ways to manipulate Andreev states in a magnetic field and reveal spin-polarized triplet states that carry supercurrent.

README CONTENTS (also included in the .ZIP)

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# Data repository for: Microwave spectroscopy of interacting Andreev spins

Manuscript located at https://arxiv.org/abs/2208.11198

Authors: J. J. Wesdorp, F. J. Matute-Caňadas, A. Vaartjes, L. Grünhaupt, T. Laeven, S. Roelofs, L. J. Splitthoff, M. Pita-Vidal, A. Bargerbos, D. J. van Woerkom, P. Krogstrup, L. P. Kouwenhoven, C. K. Andersen, A. Levy Yeyati, B. van Heck, G. de Lange

This is a self-contained repository with the code that analyses the raw data (exported to .nc format).

Required packages are:

* matplotlib

* xarray

* h5py

* h5netcdf

* lmfit

* scipy

* numpy

* jupyter-notebook

* jupyter_contrib_nbextensions (recommended to see the table of content per notebook)

* imageio (for gif generation)

* qcodes (only for the notebook qcodes to xarray conversion, the rest of the code is qcodes independent).

An environment.yaml file is provided for conda based installations. The exact versions are denoted there.

Folder structure:

- ./ : The top level folder contains the analysis notebooks that were used to process the data and fit to the minimal theoretical model. The Figures.ipynb contains the figure generation code and can be run standalone.

- data : All data files used to generate the figures in the paper. The data is stored in netcdf format with h5netcdf as engine for loading with xarray.

- data/processing is where intermediate analysis results are stored

- data/processing/phi_0 analysis tool/verification_gifs : The GIF are stored here that show the phi_0 two tone data with traced minima/maxima for verification.

- img : The raw output (separate panels) of the figure generation code is stored in the img folder

- lib: custom code used for analysis and plotting of the data

- kwant_simulation : code used for simulating and generating the figures the non-interacting model used for figure S19-S22.

- kwant_simulation/data : simulation output of the kwant simulations.

One dataset (20201109_1372_parity_selection.nc) for figure S11 is added as a separate file and should be copied to the data folder because of its large file size. This allows for a direct preview of the rest of the repository in the 4TU repository.

This is a tabulation of 526 determinations of asteroid pole orientations, covering 104 numbered asteroids, gathered from the literature from 1932 through 1995.

This is the experimental data of tetris artificial spin ice. The islands are made of Permalloy materials with size of 170 nm by 470 nm by 2.5 nm. The systems are measured at a temperature where the islands are fluctuating around room temperature. The data is recorded as photoemission electron microscopy intensity. More details about the dataset can be found in the file Note.txt and Tetris_data_list.xlsx Note: 2 files name bl11_teris600_033 and bl11_tetris600_2_135 are not recorded in the excel sheet because they are corrupted during the measurement. Any data that is not recorded in the excel sheet is either corrupted or of low quality. From files *_028 to *_049, tetris is spelled with “t” while in the raw data folder without “t”. This is a typo. Throughout the dataset, tetris and teris are supposed to have the same meaning.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

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