This dataset contains raw ROOT formatted timestamped list-mode data obtained using an array of HPGe detectors for the purpose of testing coincidence spectrometry, in the context of measurements on air filter samples. The data can be read with ROOT version 6.32.08.

In addition, the dataset contains the same data converted to CSV format. The conversion was made by an example C++ code that is also provided in the dataset. The C++ code can be compiled by a compiler adhering to the standard ISO/IEC 14882:2017 (i.e, ”C++17”).

This dataset contains model output from the Navy Coastal Ocean Model (NCOM) run during the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) field campaign. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. NCOM model output consists of daily files during the deployment dates of the pilot campaign in Fall 2021, IOP1 in Fall 2022, and IOP2 in Spring 2023. Data consists of ocean variables such as salinity, sea water temperature, water depth, and surface wind stress, and are available in netCDF format.

This dataset contains concurrent airborne DopplerScatt radar retrievals of surface vector winds and ocean currents from the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) during a pilot campaign conducted approximately 300 km offshore of San Francisco over two weeks in October 2021. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. DopplerScatt is a Ka-band (35.75 GHz) scatterometer with a swath width of 24 km that records Doppler measurements of the relative velocity between the platform and the surface. It is mounted on a B200 aircraft which flies daily surveys of the field domain during deployments, and data is used to give larger scale context, and also to compare with in-situ measurements of velocities and divergence. Level 2 data includes estimates of surface winds and currents. The V1 data have been cross-calibrated against SIO-DopVis leading to the 'dopvis_2021' current geophysical model function. It is expected that additional DopVis data will lead to a reprocessing of this data set and it should be regarded as provisional, to be refined after future S-MODE deployments. Data are available in netCDF format.

Spreadsheet which provides estimates of reductions in Levelized Cost of Energy for a surge-mode wave energy converter (WEC). This is made available via adoption of the advanced control strategies developed during this research effort.

Matlab scripts, source C-code, mex compiled C-code, and figure data points for the paper entitled “Semi-Analytical Analytical Modelling of Linear Mode Coupling in Few -Mode Fibers”.

Folders: 0_differential_equations_solver Matlab scripts based on the Symbolic Math Toolbox for the derivation of a semi-analytical solution to the differential equations describing linear mode coupling in few-mode fibres. Scripts available for 3, 4, 5 and 6 modes.

1_C_code_for_high_precision_solution_of_polynomials C-code for the numerical evaluation of the 6-modes semi-analytical solutions obtained in 0_differential_equations_solver. Two versions: “highPrecRootFind_6M_doubleIO” uses always the same seed for the root finding section; “highPrecRootFind_6M_doubleIO_rand” uses a randomized seed for the root finding section.

2_crosstalk_vs_radial_displacement Script for plotting typical fibre coupling coefficients and plotting of the crosstalk introduced by a single fibre displacement as a function of the radial displacement and averaged in the azimuth coordinate.

3_solutions_precision Script for the evaluation of the precision of the semi-analytical solutions proposed against Runge-Kutta-Fehlberg Method (RKF45) numerical solutions.

98_poly_solvers_mex_files_compiled_for_R2014b_64bit Compiled mex C-code at 1_C_code_for_high_precision_solution_of_polynomials. Compiled for Mex Matlab R2014b 64bit.

99_fibre_parameters Typical fibre parameters used in this dataset.

100_figures_data_poins Excel files containing the data points in the figures presented in the paper.

This table shows passenger kilometres for modes of transport including passenger cars, buses, rail, air, and other. Bus and rail passenger kilometres values are trend estimates - subject to later revision when final data becomes available. BITRE modelling uses data from a range of sources to provide a consistent time series of Australian passenger travel (PKM). Vehicles not classified to passenger cars, buses, rail or air are included in ‘other transport mode’ (Table T 3.1). The other transport mode represents primarily non–freight use of light commercial vehicles (with contributions from motorcycles, non–business use of trucks and ferries).

No description found

Mode de cantonnement sur les lignes du Réseau Ferré National.Le mode de cantonnement indique le système de signalisation mis en place pour assurer l’espacement des trains circulant dans le même sens.Sur ligne, le mode de cantonnement correspond à celui décrit dans les renseignements techniques, au PK moyen si le changement ne se fait pas exactement au même endroit pour chaque voie, sans tenir compte des interruptions du cantonnement à la traversée de certaines gares, si ce cantonnement existe de par et d’autre de ces gares.Les différents types de mode de cantonnement sont :Les blocks automatiques (BAL et BAPR)Les blocks manuels (BM)Les cantonnements téléphoniques (CAPI et CT)Les transmissions voie-machine (TVM)Les ETCSautresDernière mise à jour 28/04/2023

This page includes R codes for all studies discussed in the manuscript Robustness of normality-based likelihood ratio tests for interaction in two-mode data and a permutation-based alternative.

The processed spectroscopic and experimental conditions (as applicable) data which are used to construct each figure is provided.

This tar.gz file contains the original Mathematica data files for the gravitational quasi-normal modes of the Kerr geometry. For n=0--15, all m values for the l=2--16 modes are present. For n=16--32, all m values for the l=2--4 modes are present. These data sets were constructed using the methods outlines in Cook & Zalutskiy, Phys. Rev. D 90 (2014) pp. 124021 (DOI: https://doi.org/10.1103/PhysRevD.90.124021).

Data Mode measured via Uncategorized in . Part of dataset Argo Float Core Profiles - June 2024

This dataset contains shipboard radiometer measurements taken during the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) pilot campaign conducted approximately 300 km offshore of San Francisco over two weeks in October 2021. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. Air-Sea Interaction METeorology (ASIMET) sensors mounted onboard the R/V Oceanus record shortwave and longwave radiation fluxes. These are used by S-MODE to compare with DopplerScatt retrievals. Data are available in netCDF format.

Latent space models have garnered significant attention in the analysis of two-mode networks. In numerous applications, auxiliary information in the form of a hierarchical tree structure, which elucidates the interrelationships between nodes and provides extensive insights into connectivity patterns, can be easily obtained. To harness the potential of such tree-structured information, we introduce an innovative tree-enhanced latent space model (TLSM) for two-mode networks. In this framework, each node is characterized by a latent embedding vector, reparameterized as the aggregate of intermediate vectors corresponding to nodes within the tree structure. By optimizing the log-likelihood function augmented with a tree-based regularization term, the proposed model facilitates the simultaneous estimation of embedding vectors and the derivation of interpretable community structures. We have developed an efficient Alternating Direction Method of Multipliers (ADMM) algorithm to solve the resulting optimization problem. Theoretical analysis establishes the consistency of the proposed estimator under some mild conditions. Furthermore, comprehensive simulation studies and empirical applications on the Amazon review dataset substantiate the efficacy and practical relevance of the proposed model. Supplementary materials for this article are available online.

These tar.gz files contain the original Mathematica data files for the gravitational total transmission modes of the Kerr geometry for n=0 (Normal) and n=1 & 2 (Asymptotic) sequences for l=2--8. These data sets were constructed using the methods outlines in Cook & Zalutskiy, Phys. Rev. D 90 (2014) pp. 124021 (DOI: https://doi.org/10.1103/PhysRevD.90.124021) and Cook & Lu, Phys. Rev. D 107 (2023) pp. 044043 (DOI: https://doi.org/10.1103/PhysRevD.107.044043).

This dataset provides information about the number of properties, residents, and average property values for 1959 East Road cross streets in Mode, IL.

This dataset contains the predicted prices of the asset FOUNDER MODE 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.

This dataset contains Saildrone in-situ measurements taken during the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) conducted approximately 300 km offshore of San Francisco during a pilot campaign over two weeks in October 2021, and an intensive operating period (IOP) in Fall 2022. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. Saildrones are wind-and-solar-powered unmanned surface vehicles rigged with atmospheric and oceanic sensors that measure upper ocean horizontal velocities, near-surface temperature and salinity, Chlorophyll-a fluorescence, dissolved oxygen concentration, 5-m winds, air temperature, and surface radiation. Acoustic Doppler Current Profiler (ADCP) data samples originally measured at 1 Hz frequency are averaged into 5 minute bins, along with navigation data. Non-ADCP data from IOP1 contain additional bio-optical measurements. All data are available in netCDF format.

This data set contains openly-documented, machine readable digital research data corresponding to figures published in K.E. Thome et al., 'High Confinement Mode and Edge Localized Mode Characteristics in a Near-Unity Aspect Ratio Tokamak,' Phys. Rev. Lett. 116, 175001 (2016).

This dataset contains the predicted prices of the asset "BASE MODE ON" 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.