Population connectivity research involves investigating the presence, strength and characteristics of spatial and temporal relationships between populations. These data can be used in many different ways: to identify source-sink relationships between populations; to detect critical pathways or keystone habitats; to find natural clusters or biogeographic regions; or to investigate the processes underlying population genetic structure, among others. This information can be of significant value for managers and decision-makers when designing reserve networks, evaluating the potential spread of invasive species. This database represents the first publicly-available collection of national/continental-scale marine connectivity data.

You can also purchase hard copies of Geoscience Australia data and other products at http://www.ga.gov.au/products-services/how-to-order-products/sales-centre.html

Field data used to support numerical simulations of variably-saturated flow focused on variability in soil-water retention properties for the U.S. Geological Survey Bay Area Landslide Type (BALT) Site #1 in the East Bay region of California, USA

No of Housing Unit: Georgia data was reported at 4,282,106.000 Unit in 2017. This records an increase from the previous number of 4,236,284.000 Unit for 2016. No of Housing Unit: Georgia data is updated yearly, averaging 4,049,890.000 Unit from Jun 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 4,282,106.000 Unit in 2017 and a record low of 3,305,925.000 Unit in 2000. No of Housing Unit: Georgia data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB012: Number of Housing Units: By States.

Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 3 / 6 (Continuation of https://doi.org/10.5281/zenodo.13902381 database)
Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior

The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. The pressure and temperature of the jet flow match those of the surrounding ambient conditions.

The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file.

For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file.
The database is divided into six parts. The present set of data is number one.

This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". The numerical data presented herein were previously published in the work entitled "Accuracy Assessment of Discontinuous Galerkin Spectral Element Method in Simulating Supersonic Free Jets" (https://doi.org/10.1007/s40430-024-04788-z) and the Ph.D. Thesis "Study of Turbulent Supersonic Jet Flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".

Hindicast database for Wind Characteristics Data for Point 29.60E, 31.4N (WGS 84) for 43 years, time step of 1 hours.

This database of selected borehole records from the Yamal Peninsula, Russia, contains environmental descriptions (textual and numerical) of the units on the index map, and relevant borehole data. The Index Map of Yamal Peninsula (VSEGINGEO-Earth Cryosphere Institute SB RAS; PI - Prof.E.S.Melnikov) was originally compiled at a scale of 1 to 1,000,000, as 'The Map of Natural Complexes of West Siberia for the Purpose of Geocryological Prediction and Planning of Nature-Protection Measures for the Mass Construction, 1 to 1 mln' (1991) by E.S.Melnikov and N.G.Moskalenko (eds.). It was taken as a base map for nature-protection regionalization. Environmental 'regions', 'sub-regions', 'landscapes' and localities' shown on a landscape map are merged into the nature-protection regions. The map was compiled by interpreting more than 1000 satellite images and aerial photos as well as from analysis of field data from several institutions. Dominating components of the landscape, composition of the surface deposits, geocryological conditions and natural protection of ground water were considered while distinguishing the Nature-Protection Regions within the limits of Environmental Regions (Melnikov, 1988). The map is supplied with relevant databases, containing the following information - number of regions and landscape type; category of resiliency; category of the ground water protection; vegetation type; geological and geocryological structure to the depth of 10-15 m; ice content (of lenses and of macro-inclusions separately); thickness of seasonally frozen and seasonally thawed layers; ground temperature; contemporary exogenic geological (periglacial) processes; and the area affected by these processes.The 55 nature-protection regions of Yamal Peninsula generalize information. To approve the ranges of geocryological and cryolithological characteristics, 160 boreholes were retrieved out of the database containing more than 4000 boreholes data obtained in 1977-1990 by Fundamentproekt Design Institute (Moscow, Russia; PI - Dr.sci.M.A.Minkin) at Kharasavey and Bovanenkovo gas fields and along the pipelines Yamal-Ukhta and Yamal-Uzhgorod. The boreholes have reference to geographical coordinates (latitude and longitude), as well as to the nature-protection region numbers shown on the Index Map. A total of 21 units are covered by borehole data, 5-8 boreholes in each unit, covering most typical conditionsThe original database consisted of 3 relational tables. The first table includes category of resiliency; locality type description; landscape type description; ground-ice content, water saturation, cryogenic structure, macro-ground-ice content; vegetation types; seasonally frozen and seasonally thawed layer depths; ground temperature at 10 m; exogenic geological processes an their paragenesis and combinations; and degree of the surface disturbance. The second relational table contains layer-by-layer description of the lithological section types. The third table for the boreholes includes the description of topography around the borehole; types of geological profiles through the active layer and depths down to the permafrost table; ground temperature at 10-m depth (close to the depth of zero annual amplitude in the area); macro-ice content; and salinity of permafrost. These data are presented on the CAPS Version 1.0 CD-ROM, June 1998.

Excel spreadsheet containing, in separate sheets, the underlying numerical data for figure panels.

An Excel file with separate sheets for each figure panel where numerical data were graphed. (XLSX)

Sign Up for a free trial: https://rampedup.io/sign-up-%2F-log-in - 7 Days and 50 Credits to test our quality and accuracy.

These are the fields available within the RampedUp Global dataset.

CONTACT DATA: Personal Email Address - We manage over 115 million personal email addresses Professional Email - We manage over 200 million professional email addresses Home Address - We manage over 20 million home addresses Mobile Phones - 65 million direct lines to decision makers Social Profiles - Individual Facebook, Twitter, and LinkedIn Local Address - We manage 65M locations for local office mailers, event-based marketing or face-to-face sales calls.

JOB DATA: Job Title - Standardized titles for ease of use and selection Company Name - The Contact's current employer Job Function - The Company Department associated with the job role Title Level - The Level in the Company associated with the job role Job Start Date - Identify people new to their role as a potential buyer

EMPLOYER DATA: Websites - Company Website, Root Domain, or Full Domain Addresses - Standardized Address, City, Region, Postal Code, and Country Phone - E164 phone with country code Social Profiles - LinkedIn, CrunchBase, Facebook, and Twitter

FIRMOGRAPHIC DATA: Industry - 420 classifications for categorizing the company’s main field of business Sector - 20 classifications for categorizing company industries 4 Digit SIC Code - 239 classifications and their definitions 6 Digit NAICS - 452 classifications and their definitions Revenue - Estimated revenue and bands from 1M to over 1B Employee Size - Exact employee count and bands Email Open Scores - Aggregated data at the domain level showing relationships between email opens and corporate domains. IP Address -Company level IP Addresses associated to Domains from a DNS lookup

CONSUMER DATA: Education - Alma Mater, Degree, Graduation Date Skills - Accumulated Skills associated with work experience
Interests - Known interests of contact Connections - Number of social connections. Followers - Number of social followers

Download our data dictionary: https://rampedup.io/our-data

The Wellbore Exploration and Location Logistic System (WELLS) is a living national wellbore database and tool created and maintained by the National Energy Technology Laboratory (NETL), providing access to over 6 million public wellbore records from state, federal, and tribal resources. Sourced from over 65 authoritative, but disparate resources, the WELLS products combine well data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater and other types of wells in a single, unified system. In addition to surface location of these wells, the underlying database combines select, key attributes for features such as, well age, depth, and operating status. The system also provides users with references back to the 65 disparate original sources used in this unified platform. Additional Information: The WELLS (formerly titled CO2-Locate) offers two related and published product collections for users: the WELLS Database and the WELLS Interactive Application. The WELLS Database contains the public wellbore data in both tabular and geospatial formats, and the WELLS Interactive Application enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. Together, the WELLS resource provides a centralized, geospatial-enabled wellbore repository to support Carbon Capture, Utilization, and Storage (CCUS) initiatives from site suitability to long-term storage integrity. The WELLS Database is an integrated national well dataset, representing open-source wellbore data from over 65 disparate state, tribal, and federal entities. The database provides publicly available well header data with key attributes such as well age, depth, and status. The database contains a fully integrated CSV file with all values in numerical columns, such as depth, converted into numbers. This version has a NETL produced API (American Petroleum Institute) number column and has been handled for redundancies, resulting in one record for every unique API number. The database also contains a fully integrated CSV file, where all original data are kept as text values. Additionally, the database includes a shapefile containing key attributes and coordinates from the integrated dataset, reformatted public wells CSV files, and a proprietary well density grid shapefile. Notes for consideration: The WELLS Database and Interactive Application will be updated periodically with new datasets and information. A field dictionary with field (i.e., attribute) coverage across acquired public well resources, and the resulting integrated public well datasets are available in the spreadsheet, WELLS_Field_Dictionary.xlsx. Summary layers provided in this database are derived from proprietary layers and do not always contain key features (status, type, true vertical depth, or spud year) and therefore might not be shown when data are queried for those features.

This interactive database, maintained by the NIST Atomic Spectroscopy Data Center, contains more than 8000 references, dating from 1914 through current year and is updated regularly in intervals between one and four weeks. These references pertain to publications that include numerical data, comments, and reviews on atomic transition probabilities, oscillator strengths, line strengths, and radiative lifetimes.

Macau Gaming: Number of Gaming Table data was reported at 6,598.000 Unit in Sep 2018. This records an increase from the previous number of 6,588.000 Unit for Jun 2018. Macau Gaming: Number of Gaming Table data is updated quarterly, averaging 5,302.000 Unit from Mar 2005 (Median) to Sep 2018, with 55 observations. The data reached an all-time high of 6,598.000 Unit in Sep 2018 and a record low of 1,226.000 Unit in Mar 2005. Macau Gaming: Number of Gaming Table data remains active status in CEIC and is reported by Gaming Inspection and Coordination Bureau. The data is categorized under Global Database’s Macau SAR – Table MO.Q019: Number of Casinos and Gaming Tables.

This data set consists of three-dimensional meteorological analyses for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser and Rabbit Ears) using high-resolution (500 m horizontal grid spacing).

Abstract: This code has been used for the numerical experiments in the thesis "Numerical homogenization of time-dependent Maxwell's equations with dispersion effects" by Jan Philip Freese, see https://www.doi.org/10.5445/IR/1000129214. TechnicalRemarks: # Readme This code was used for the numerical experiments of the PhD thesis "Numerical homogenization of time-dependent Maxwell's equations with dispersion effects" by P. Freese (cf. Section 7.2, Section 7.3) https://www.doi.org/10.5445/IR/1000129214. The computations are done in C++ using the Finite Element library deal.II. Requirements

Vietnam whatsapp number list has the potential that you have been seeking for a long time. We create the database by maintaining all the legal policies. Therefore, none of our databases will disappoint you and that’s our motive. We can guarantee almost 95% accuracy over our services. Not to mention we verify the data so many times before making it available on the sites. Again, we double-check the data. We go through several of our trusted sources for contacts and other information. In the end, help your business by purchasing Vietnam whatsapp number list. Vietnam whatsapp phone number data is one of the best directories which is essential to run a successful online marketing campaign. The contacts will help you to grow your marketing campaign all across the country. List to Data here can help you by providing an accurate and exact contact database. For a successful marketing campaign, you need the right data and authentic data that only a few can serve and we are one of them. So, trust us and see our database services to gain something extraordinary. Vietnam whatsapp phone number data will surely bring a good return on investment(ROI) for you.

This dataset features direct numerical simulations (DNS) of high-pressure, transcritical, homogeneous isotropic turbulence (HIT) for carbon dioxide (CO₂). Unlike their low-pressure counterparts, these flows exhibit fundamentally different behavior due to the strong nonlinearities in the equation of state (EoS) and the tight coupling between thermodynamic and transport properties. The simulations include variable-density flows with a Reynolds number based on the integral length scale of Re_L0 = 60 and a turbulent Mach number of Ma_t = 0.1. The dataset spans five distinct thermodynamic states: a gas-like state, a liquid-like state, and three pseudo-boiling conditions at different pressures. For comparison, an additional ideal-gas case at low pressure with variable transport properties is also included.The dataset is structured into folders, each corresponding to a specific simulation case. Within each folder, there are 30 snapshot files capturing the statistically stationary regime, sampled every three integral times. Each snapshot includes spatial coordinates (x, y, z) and instantaneous fields such as primitive variables (density, velocity components u, v, w, and total energy), transport properties (dynamic viscosity μ and thermal conductivity κ), and thermodynamic quantities (pressure, temperature, speed of sound, specific heat at constant volume c_v, and constant pressure c_p). Statistical data averaged over 100 t* is stored separately in an HDF5 file.

This replication package reproduces the results for the paper entitled "Adding measurement error to location data to protect subject confidentiality while allowing for consistent estimation of exposure effects," which is published in The Journal of the Royal Statistical Society: Series C (Applied Statistics), DOI: https://doi.org/10.1111/rssc.12439. This package contains 2 Stata Do-Files (.do) that produce the simulated dataset and run one replication of the simulation (the main paper runs 1,000 replications), and 2 Stata Data Files (.dta) that are used for the simulation in the main paper. (2020-02-29).

Description: This dataset contains historical economic data spanning from 1871 to 2024, used in Jaouad Karfali’s research on Economic Cycle Analysis with Numerical Time Cycles. The study aims to improve economic forecasting accuracy through the 9-year cycle model, which demonstrates superior predictive capabilities compared to traditional economic indicators.

Dataset Contents: The dataset includes a comprehensive range of economic indicators used in the research, such as:

USGDP_1871-2024.csv – U.S. Gross Domestic Product (GDP) data. USCPI_cleaned.csv – U.S. Consumer Price Index (CPI), cleaned and processed. USWAGE_1871-2024.csv – U.S. average wages data. EXCHANGEGLOBAL_cleaned.csv – Global exchange rates for the U.S. dollar. EXCHANGEPOUND_cleaned.csv – U.S. dollar to British pound exchange rates. INTERESTRATE_1871-2024.csv – U.S. interest rate data. UNRATE.csv – U.S. unemployment rate statistics. POPTOTUSA647NWDB.csv – U.S. total population data. Significance of the Data: This dataset serves as a foundation for a robust economic analysis of the U.S. economy over multiple decades. It was instrumental in testing the 9-year economic cycle model, which demonstrated an 85% accuracy rate in economic forecasting when compared to traditional models such as ARIMA and VAR.

Applications:

Economic Forecasting: Predicts a 1.5% decline in GDP in 2025, followed by a gradual recovery between 2026-2034. Economic Stability Analysis: Used for comparing forecasts with estimates from institutions like the IMF and World Bank. Academic and Institutional Research: Supports studies in economic cycles and long-term forecasting. Source & Further Information: For more details on the methodology and research findings, refer to the full paper published on SSRN:

https://ssrn.com/author=7429208 https://orcid.org/0009-0002-9626-7289

• Jaouad Karfali

A completely new, detailed three-dimensional numerical simulation model of the Cerro Prieto geothermal field has been developed to optimize field management and the plant capacity expansion. A conceptual model was developed from all available exploration data, drilling records, well logs, chemical and well test data. A three-dimensional simulation model was then constructed and calibrated against the initial state of the system, which confirmed the conceptual model and helped refine boundary conditions. The model was further calibrated by trial-and-error matching of the production history, which involved over 200 wells and a 26-year exploitation history. Observed and calculated production histories were matched satisfactorily. Using the calibrated reservoir model and wellbore simulation, well behavior was forecast under various possible production and injection scenarios and proposed capacity expansion schemes. These forecasts were the basis of optimization of field management and capacity expansion.

During the fourth quarter of 2024, data breaches exposed more than a million user data records in the United Kingdom (UK). The figure decreased significantly from nearly 41 million in the quarter prior. Overall, the time between the first quarter of 2022 and the fourth quarter of 2023, saw the lowest number of exposed user data accounts.