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This formatted dataset (AnalysisDatabaseGBD) originates from raw data files from the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD2017) affiliated with the University of Washington. We are volunteer collaborators with IHME and not employed by IHME or the University of Washington.

The population weighted GBD2017 data are on male and female cohorts ages 15-69 years including noncommunicable diseases (NCDs), body mass index (BMI), cardiovascular disease (CVD), and other health outcomes and associated dietary, metabolic, and other risk factors. The purpose of creating this population-weighted, formatted database is to explore the univariate and multiple regression correlations of health outcomes with risk factors. Our research hypothesis is that we can successfully model NCDs, BMI, CVD, and other health outcomes with their attributable risks.

These Global Burden of disease data relate to the preprint: The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis. The data include the following: 1. Analysis database of population weighted GBD2017 data that includes over 40 health risk factors, noncommunicable disease deaths/100k/year of male and female cohorts ages 15-69 years from 195 countries (the primary outcome variable that includes over 100 types of noncommunicable diseases) and over 20 individual noncommunicable diseases (e.g., ischemic heart disease, colon cancer, etc). 2. A text file to import the analysis database into SAS 3. The SAS code to format the analysis database to be used for analytics 4. SAS code for deriving Tables 1, 2, 3 and Supplementary Tables 5 and 6 5. SAS code for deriving the multiple regression formula in Table 4. 6. SAS code for deriving the multiple regression formula in Table 5 7. SAS code for deriving the multiple regression formula in Supplementary Table 7
8. SAS code for deriving the multiple regression formula in Supplementary Table 8 9. The Excel files that accompanied the above SAS code to produce the tables

For questions, please email davidkcundiff@gmail.com. Thanks.

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Formula Steel Colombia Sas Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

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(SAS7BDAT)

This layer contains census tract level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, BLOCK, BLKGRP, and TBLKGRP.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.**To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the tract itself.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

Title of program: EQSYSTM Catalogue Id: AAQX_v1_0

Nature of problem This program is designed to operate on a system of equations, making user-specified substitutions and returning for each expression its partial derivatives with respect to a list of specified variables. The output expressions for the derivatives of each input expression, in the form of statements directly usable in other programs, are organized into an array with subscripts corresponding to the variables by which it was differentiated. Output in either PL/1, Fortran, or SAS syntax is available a ...

Versions of this program held in the CPC repository in Mendeley Data AAQX_v1_0; EQSYSTM; 10.1016/0010-4655(81)90085-0

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA S.A.S DI GIULIO OREGLIA & C. S.A.S. in GENOVA (GE)

This paper introduces new and old features of the SAS System for the estimation and simulation of systems of first-order differential equations with emphasis on examples in kinetics.

Results of One-way ANOVA analysis of the relationships between drivers’ SAS and drivers’ driving characteristics.

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per AUTOLAVAGGIO FORMULA UNO S.A.S. DI GIUSEPPE PAGANO & C. in LETOJANNI (ME)

Fit indices of the Smartphone Addiction Scale—Chinese Short Version (SAS-CSV)’s structural equation model (n = 278).

ABSTRACT: The least limiting water range is a soil physical quality indicator, which is useful to predict the optimum water range for plant growth in a given soil and to study the effects of soil use and management over this optimum water range by integrating the effects of available water, penetration resistance and air filled porosity. This study tested six equations to fit water retention and penetration resistance surface responses used to determine the least limiting water range and present a simple algorithm written in the open source software R for fitting, calculation and visualization of the least limiting water range. Five soils from Brazil and Canada, under different use and management conditions were used to test the functions. The results show that the three water retention surface responses had good statistical properties for fitting water retention and that two of the penetration resistance surface responses were adequate to fit the data, while one failed to achieve convergence in two instances. The open source code performed as well as the commercial statistical package SAS for fitting the penetration resistance and water retention equations.

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA BUSINESS S.A.S. DI MATTEO BARONTI in FIRENZE (FI)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA 2000 S.A.S. DI MACCORIN NICOLA & C. in PRAMAGGIORE (VE)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA SOCIETA' IN ACCOMANDITA SEMPLICE DI CARELLA MAURO & C. SIGLABILE FORMULA S.A.S. DI CARELLA MAURO & C. in TORINO (TO)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA UNO S.A.S. DI LA ROSA STEFANO E C. in ISOLA D'ASTI (AT)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA ONE S.A.S. DI CAVIGLIA EMANUELLE & C. in COLLEGNO (TO)

Fatturato per gli ultimi anni, elenco utili/perdita, costo dipendenti, soci esponenti e contatti per FORMULA ABITARE S.A.S. DI SCAVETTA EMILIA E C. in SESTO SAN GIOVANNI (MI)