About this dataset

Context

The dataset tabulates the Soldiers Grove population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Soldiers Grove. The dataset can be utilized to understand the population distribution of Soldiers Grove by age. For example, using this dataset, we can identify the largest age group in Soldiers Grove.

Key observations

The largest age group in Soldiers Grove, WI was for the group of age 10 to 14 years years with a population of 80 (13.51%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Soldiers Grove, WI was the 5 to 9 years years with a population of 7 (1.18%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Soldiers Grove is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Soldiers Grove total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Soldiers Grove Population by Age. You can refer the same here

This dataset investigates the Instagram engagement metrics (likes and comments) of the U.S. and British Armies to understand their strengths and weaknesses in their marketing. For the quantitative data collection, a random number generator was used to compile a 20% data sample (73 posts) from a total of 365 posts from each account. For instance, a number 1 in the random generator corresponded to the most recent post from the start date of data collection (May 23rd, 2024). By picking from 365 posts, the data collection was meant to represent roughly a year of Instagram content, assuming their Instagram accounts posted every day. This method ensured an unbiased representation of which content was included in the 20% data sample.However, the U.S Army posted almost once a day while the British Army posted only a few days a week. In the end, data was collected across 365 U.S. Army posts from May 23rd, 2024, to October 28th, 2023. For the British Army’s Instagram, the data collection span from May 23rd, 2024, to November 25th, 2021. By engaging with recent posts, the purpose was to understand how effectively these Armies responded to their recruitment crisis (which started in 2022).For the data collection, variables for each post included the following:Date of postNumber of likesPercentage of likes by follower populationNumber of commentsPercentage of comments by follower populationTo understand which Instagram posts were successful, the content with the highest number of likes and comments were defined as the most engaged. But, to accurately compare the British Army’s Instagram engagement to the U.S., the number of likes/comments was divided by the number of their followers. As of May 23, 2024, the U.S. Army had 2.9 million followers on Instagram whereas the British Army had 594,000 followers. While social media users outside of the Armies’ followers engaged with the posts, these ratios provided a basis to fairly compare their engagement metrics.

About this dataset

Context

The dataset tabulates the data for the Soldiers Grove, WI population pyramid, which represents the Soldiers Grove population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Soldiers Grove, WI, is 35.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Soldiers Grove, WI, is 45.0.
• Total dependency ratio for Soldiers Grove, WI is 79.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Soldiers Grove, WI is 2.2.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Soldiers Grove population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Soldiers Grove for the selected age group is shown in the following column.
• Population (Female): The female population in the Soldiers Grove for the selected age group is shown in the following column.
• Total Population: The total population of the Soldiers Grove for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Soldiers Grove Population by Age. You can refer the same here

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and recreation access across the nation. The PAD-US 3.0 Combined Fee, Designation, Easement feature class (with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class) was modified to remove overlaps, avoiding overestimation in protected area statistics and to support user needs. A Python scripted process ("PADUS3_0_CreateVectorAnalysisFileScript.zip") associated with this data release prioritized overlapping designations (e.g. Wilderness within a National Forest) based upon their relative biodiversity conservation status (e.g. GAP Status Code 1 over 2), public access values (in the order of Closed, Restricted, Open, Unknown), and geodatabase load order (records are deliberately organized in the PAD-US full inventory with fee owned lands loaded before overlapping management designations, and easements). The Vector Analysis File ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") associated item of PAD-US 3.0 Spatial Analysis and Statistics ( https://doi.org/10.5066/P9KLBB5D ) was clipped to the Census state boundary file to define the extent and serve as a common denominator for statistical summaries. Boundaries of interest to stakeholders (State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative) were incorporated into separate geodatabase feature classes to support various data summaries ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip") and Comma-separated Value (CSV) tables ("PADUS3_0SummaryStatistics_TabularData_CSV.zip") summarizing "PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip" are provided as an alternative format and enable users to explore and download summary statistics of interest (Comma-separated Table [CSV], Microsoft Excel Workbook [.XLSX], Portable Document Format [.PDF] Report) from the PAD-US Lands and Inland Water Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). In addition, a "flattened" version of the PAD-US 3.0 combined file without other extent boundaries ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") allow for other applications that require a representation of overall protection status without overlapping designation boundaries. The "PADUS3_0VectorAnalysis_State_Clip_CENSUS2020" feature class ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.gdb") is the source of the PAD-US 3.0 raster files (associated item of PAD-US 3.0 Spatial Analysis and Statistics, https://doi.org/10.5066/P9KLBB5D ). Note, the PAD-US inventory is now considered functionally complete with the vast majority of land protection types represented in some manner, while work continues to maintain updates and improve data quality (see inventory completeness estimates at: http://www.protectedlands.net/data-stewards/ ). In addition, changes in protected area status between versions of the PAD-US may be attributed to improving the completeness and accuracy of the spatial data more than actual management actions or new acquisitions. USGS provides no legal warranty for the use of this data. While PAD-US is the official aggregation of protected areas ( https://www.fgdc.gov/ngda-reports/NGDA_Datasets.html ), agencies are the best source of their lands data.

The 2012 US Army Anthropometric Survey (ANSUR II) was executed by the Natick Soldier Research, Development and Engineering Center (NSRDEC) from October 2010 to April 2012 and is comprised of personnel representing the total US Army force to include the US Army Active Duty, Reserves, and National Guard. The data was made publicly available in 2017. In addition to the anthropometric and demographic data described below, the ANSUR II database also consists of 3D whole body, foot, and head scans of Soldier participants. These 3D data are not publicly available out of respect for the privacy of ANSUR II participants. The data from this survey are used for a wide range of equipment design, sizing, and tariffing applications within the military and has many potential commercial, industrial, and academic applications.These data have replaced ANSUR I as the most comprehensive publicly accessible dataset on body size and shape. The ANSUR II dataset includes 93 measurements from over 6,000 adult US military personnel, comprising 4,082 men (ANSUR_II_MALE_Public.csv) and 1,986 women (ANSUR_II_FEMALE_Public.csv).

The ANSUR II working databases contain 93 anthropometric measurements which were directly measured, and 15 demographic/administrative variables.

Much more information about the data collection methodology and content of the ANSUR II Working Databases may be found in the following Technical Reports, available from theDefense Technical Information Center (www.dtic.mil) through:

a. 2010-2012 Anthropometric Survey of U.S. Army Personnel: Methods and Summary
Statistics. (NATICK/TR-15/007)
b. Measurer’s Handbook: US Army and Marine Corps Anthropometric Surveys,
2010-2011 (NATICK/TR-11/017)

United States US: Military Expenditure: % of GDP data was reported at 3.149 % in 2017. This records a decrease from the previous number of 3.222 % for 2016. United States US: Military Expenditure: % of GDP data is updated yearly, averaging 4.864 % from Sep 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.063 % in 1967 and a record low of 2.908 % in 1999. United States US: Military Expenditure: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Defense and Official Development Assistance. Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, conversion, and destruction of weapons. This definition cannot be applied for all countries, however, since that would require much more detailed information than is available about what is included in military budgets and off-budget military expenditure items. (For example, military budgets might or might not cover civil defense, reserves and auxiliary forces, police and paramilitary forces, dual-purpose forces such as military and civilian police, military grants in kind, pensions for military personnel, and social security contributions paid by one part of government to another.); ; Stockholm International Peace Research Institute (SIPRI), Yearbook: Armaments, Disarmament and International Security.; Weighted average; Data for some countries are based on partial or uncertain data or rough estimates.

The ERS Food Expenditure Series annually measures total U.S. food expenditures, including purchases by consumers, governments, businesses, and nonprofit organizations. The ERS Food Expenditure Series contributes to the analysis of U.S. food production and consumption by constructing a comprehensive measure of the total value of all food expenditures by final purchasers. This series annually measures total U.S. food expenditures, including purchases by consumers, governments, businesses, and nonprofit organizations. Because the term expenditure is often associated with household decisionmaking, it is important to recognize that ERS's series also includes nonhousehold purchases. For example, the series includes the dollar value of domestic food purchases by military personnel and their dependents at military commissary stores and exchanges, the value of commodities and food dollars donated by the Federal government to schools, and the value of food purchased by airlines for serving during flights.

Fire Stations in the United States Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included. TGS has made a concerted effort to include all fire stations in the United States and its territories. This dataset is comprised completely of license free data. The HSIP Freedom Fire Station dataset and the HSIP Freedom EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 01/03/2005 and the newest record dates from 01/11/2010.Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total fire fighting capability in a given area is adequate. 2. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest. 3. A resource for Emergency Management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for Federal Government events.

About this dataset

Context

The dataset tabulates the population of Soldiers Grove by race. It includes the population of Soldiers Grove across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Soldiers Grove across relevant racial categories.

Key observations

The percent distribution of Soldiers Grove population by race (across all racial categories recognized by the U.S. Census Bureau): 89.53% are white, 1.01% are Black or African American, 2.03% are Asian, 2.70% are some other race and 4.73% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Soldiers Grove
• Population: The population of the racial category (excluding ethnicity) in the Soldiers Grove is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Soldiers Grove total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Soldiers Grove Population by Race & Ethnicity. You can refer the same here

• Context I am greatly inspired with this dataset containing geo spatial details for each zip code and contains the total wages for each area.This gave me opportunity to create a data visualisation in Tableau using HexBin chart which is added as a Kernel to this dataset.

• Content

  • About the data: 81,831 rows of data. All 41,891 active zipcodes + 634 decommisioned zipcodes from the recent past. All 80673 active Primary(41885), Acceptable(13988), and Not Acceptable(24800) placenames. Some additonal placenames for decommisioned codes. 29,971 Standard, 9465 PO BOX, 2437 Unique, and 649 Military codes.

• 50 States + 361 AA Military

• Americas 38 AE Military

• Europe 164 AP Military

• Pacific 1 AS American Samoa 290 DC Washinton DC 4 FM Federated States Micronesia 13 GU Guam 2 MH Marshall Islands 3 MP Northern Mariana Islands 176 PR Puerto Rico 2 PW Palau 16 VI Virgin Islands

• Name Type Description

• Zipcode Text 5 digit Zipcode or military postal code(FPO/APO)

• ZipCodeType Text Standard, PO BOX Only, Unique, Military(implies APO or FPO)

• City Text USPS offical city name(s)

• State Text USPS offical state, territory, or quasi-state (AA, AE, AP) abbreviation code

• LocationType Text Primary, Acceptable,Not Acceptable

• Lat Double Decimal Latitude, if available

• Long Double Decimal Longitude, if available

• Location Text Standard Display (eg Phoenix, AZ ; Pago Pago, AS ; Melbourne, AU )

• Decommissioned Text If Primary location, Yes implies historical Zipcode, No Implies current Zipcode; If not Primary, Yes implies Historical Placename

• TaxReturnsFiled Long Integer Number of Individual Tax Returns Filed in 2008

• EstimatedPopulation Long Integer Tax returns filed + Married filing jointly + Dependents

• TotalWages Long Integer Total of Wages Salaries and Tips

  • Source: http://federalgovernmentzipcodes.us/

  • Current zipcodes, placenames, zipcode type(Standard, PO, Unique, Military), placename type (Primary, Acceptable, Not Acceptable)

• : USPS Military place names (base or ship name)

• : MPSA 2008 Election Ballot information Tax returns filed, estimated population, total wages: IRS 2008 Latitude and Longitude; National Weather Service supplemented by Google Earth and Maps and occasionally other sources Decommissioned zip codes, Our old database--usually quality sources, but not verifiable.

• Acknowledgements

  Other Sources of zipcode information:

• Placenames (Cities, towns, geographic features) can be found at US Geological Survey GNIS Dataset The IRS has additional data fields for 2008 and is reviewing their publication procedures for later years.

  see http://www.irs.gov/taxstats/indtaxstats/article/0,,id=96947,00.html

• The Census publishes data, but they use Zipcode Tabulation Areas (ZCTAs) which

• 1) have changed areas between the 2000 census and the 2010 census

• 2) do not map well to USPS zipcodes well. If needed http://www.census.gov/geo/ZCTA/zcta.html Social Security recipients by zipcode http://www.ssa.gov/policy/docs/statcomps/oasdi_zip/ For economic researchers and those who want tons of background on data sources by zipcode, University of Missouri OSEDA project

  • Free Zipcode Database (8.7 MB) Updated 1/22/2012 All Locations (Multiple locations for some zipcodes)

  Inspiration I am hoping that people in the right government agencies/authorities would be able to utilize this data to focus on

  community developments where it needs immediate attention.

Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce.While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document which of these skills are being developed in higher education at a similar granularity.Here, we fill this gap by presenting Course-Skill Atlas -- a longitudinal dataset of skills inferred from over three million course syllabi taught at nearly three thousand U.S. higher education institutions. To construct Course-Skill Atlas, we apply natural language processing to quantify the alignment between course syllabi and detailed workplace activities (DWAs) used by the DOL to describe occupations. We then aggregate these alignment scores to create skill profiles for institutions and academic majors. Our dataset offers a large-scale representation of college education's role in preparing students for the labor market.Overall, Course-Skill Atlas can enable new research on the source of skills in the context of workforce development and provide actionable insights for shaping the future of higher education to meet evolving labor demands, especially in the face of new technologies.

Judgement on American and Soviet foreign policy. Attitude to selected countries and NATO. Topics: Most important problems of the country; attitude to France, Germany, Great Britain, the USSR and the USA as well as perceived changes in the last few years; assumed reputation of one´s own country abroad; trust in the USA and the USSR to solve world problems; judgement on the agreement of words and deeds in foreign policy as well as the seriousness of the peace efforts of the two great powers; the USSR or the USA as current and as future world power in the military and scientific area as well as in space research; benefit of space travel; attitude to a strengthening of space flight efforts; knowledge about the landing on the moon; necessity of NATO; trust in NATO; judgement on the contribution of one´s own country to NATO; preference for acceptance of political functions by NATO; attitude to a reduction in US soldiers stationed in Western Europe; expected reductions of American obligations in Europe; probability of European unification; desired activities of government in the direction of European unification; preference for a European nuclear force; judgement on the disarmament negotiations between the USA and the USSR; expected benefit of such negotiations for one´s own country and expected consideration of European interests; increased danger of war from the new missile defense systems; prospects of the so-called Budapest recommendation; attitude to the American Vietnam policy; negotiating party that can be held responsible for the failure of the Paris talks; sympathy for Arabs or Israelis in the Middle East Conflict; preference for withdrawal of the Israelis from the occupied territories; attitude to an increase in the total population in one´s country and in the whole world; attitude to birth control in one´s country; attitude to economic aid for lesser developed countries; judgement on the influence and advantageousness of American investments as well as American way of life for one´s own country; autostereotype and description of the American character by means of the same list of characteristics (stereotype); general attitude to American culture; perceived increase in American prosperity; trust in the ability of American politics to solve their own economic and social problems; judgement on the treatment of blacks in the USA and determined changes; proportion of poor in the USA; comparison of proportion of violence or crime in the USA with one´s own country; general judgement on the youth in one´s country in comparison to the USA; assessment of the persuasiveness of the American or Soviet view; religiousness; city size. Also encoded was: length of interview; number of contact attempts; presence of other persons during the interview; willingness of respondent to cooperate; understanding difficulties of respondent. Beurteilung der amerikanischen und sowjetischen Außenpolitik. Einstellung zu ausgewählten Ländern und zur Nato. Themen: Wichtigste Probleme des Landes; Einstellung zu Frankreich, Deutschland, Großbritannien, UdSSR und USA sowie wahrgenommene Veränderungen in den letzten Jahren; vermutetes Ansehen des eigenen Landes im Ausland; Vertrauen in die USA und die UdSSR zur Lösung der Weltprobleme; Beurteilung der Übereinstimmung von Worten und Taten in der Außenpolitik sowie der Ernsthaftigkeit der Friedensbemühungen der beiden Großmächte; UdSSR oder USA als derzeitige und als künftige Weltmacht im militärischen, wissenschaftlichen Bereich sowie in der Weltraumforschung; Nutzen der Weltraumfahrt; Einstellung zu einer Verstärkung von Raumfahrtanstrengungen; Kenntnisse über die Mondlandung; Notwendigkeit der Nato; Vertrauen in die Nato; Beurteilung des Beitrags des eigenen Landes zur Nato; Präferenz für die Übernahme politischer Funktionen durch die Nato; Einstellung zu einer Verringerung der stationierten US-Soldaten in Westeuropa; erwartete Einschränkungen der amerikanischen Verpflichtungen in Europa; Wahrscheinlichkeit einer europäischen Vereinigung; gewünschte Aktivitäten der Regierung in Richtung europäische Einigung; Präferenz für eine europäische Atomstreitmacht; Beurteilung der Abrüstungsverhandlungen zwischen den USA und der UdSSR; erwarteter Nutzen solcher Verhandlungen für das eigene Land und erwartete Berücksichtigung der europäischen Interessen; erhöhte Kriegsgefahr durch die neuen Raketenabwehrsysteme; Aussichten des sogenannten Budapest-Vorschlags; Einstellung zur amerikanischen Vietnam-Politik; Verhandlungspartei, der die Mißerfolge der Pariser Gespräche zugeschrieben werden; Sympathie für die Araber oder Israelis im Nahost-Konflikt; Präferenz für einen Abzug der Israelis aus den besetzten Gebieten; Einstellung zu einer Erhöhung der Bevölkerungszahl im eigenen Land und auf der ganzen Welt; Einstellung zu einer Geburtenkontrolle im eigenen Land; Einstellung zur Wirtschaftshilfe an weniger entwickelte Länder; Beurteilung des Einflusses und der Vorteilhaftigkeit amerikanischer Investitionen sowie amerikanischer Lebensart für das eigene Land; Autostereotyp und Beschreibung des amerikanischen Charakters anhand der gleichen Eigenschaftsliste (Stereotyp); allgemeine Einstellung zur amerikanischen Kultur; wahrgenommene Steigerung des amerikanischen Wohlstands; Vertrauen in die Kompetenz amerikanischer Politik zur Lösung ihrer eigenen wirtschaftlichen und sozialen Probleme; Beurteilung der Behandlung von Schwarzen in den USA und festgestellte Veränderungen; Armenanteil in den USA; Vergleich des Gewaltanteils bzw. der Kriminalität in den USA mit dem eigenen Land; allgemeine Beurteilung der Jugend im eigenen Land im Vergleich zu den USA; Einschätzung der Überzeugungskraft amerikanischer bzw. sowjetischer Anschauung; Religiosität; Ortsgröße. Zusätzlich verkodet wurde: Interviewdauer; Anzahl der Kontaktversuche; Anwesenheit anderer Personen beim Interview; Kooperationsbereitschaft des Befragten; Verständnisschwierigkeiten des Befragten.

To evaluate the incidence, refractive error (RE) association, and distribution of atraumatic rhegmatogenous retinal detachment (RRD) in U.S. military service members (SMs). This study used data from the Military Health System (MHS) M2 database to identify active U.S. military and National Guard SMs diagnosed with RRD from 2017 to 2022. The RE in diopters (D) was manually extracted from available medical charts for 518 eyes. The annual incidence rate of RRD was calculated overall and evaluated in terms of age, gender, and RE. A multivariate Poisson regression model was used to estimate the relative risk (RR) for RRD with RE. From 2017 to 2022, 1,537 SMs were diagnosed with RRD and 1,243,189 were diagnosed with RE. One thousand two hundred seventy-five SMs had both diagnoses: RRD and RE. The overall incidence rate of RRD over the 6-year study was 16.3 per 100,000 people (16.4 and 15.9 for males and females, respectively). In all study groups, the incidence of RRD increased with age. SMs with RE had an overall 25-fold increased risk for RRD compared to SMs without RE. RE was present in 83.0% of cases of RRD. Myopia accounted for 93.3% of cases for eyes with detailed refractive data. The incidence of RRD in U.S. SMs is comparable to other studies and is similar among male and female SMs. RE is present in most cases of RRD in SMs, with the most common type being low to moderate amounts of myopia.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Soldiers Grove, WI, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Soldiers Grove, WI reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Soldiers Grove households based on income levels.

Key observations

• For Family Households: In Soldiers Grove, the majority of family households, representing 20.16%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.78%, have incomes falling $75,000 to $99,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Soldiers Grove, the majority of non-family households, accounting for 21.51%, have income $50,000 to $59,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $75,000 to $99,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Soldiers Grove, WI (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Soldiers Grove, WI
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Soldiers Grove, WI
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Soldiers Grove, WI

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Soldiers Grove median household income. You can refer the same here

Microalgae are integral primary producers for global ecosystems whose genomes can be mined for ecological insights, but representative genome sequences are lacking for many phyla. We cultured and sequenced 107 microalgae species from 11 different phyla indigenous to varied geographies and climates. This genome collection was used to resolve genomic differences between saltwater and freshwater microalgae. Freshwater species showed domain-centric ontology enrichment for nuclear and nuclear membrane functions, while saltwater species were enriched in organellar and cellular membrane functions. Marine species contained significantly more viral families in their genomes (p-value = 8 x 10(-4)). Viral sequences were identified from Chlorovirus, Coccolithovirus, Pandoravirus, Marseillevirus, Tupanvirus, and others integrated into algal genomes. Algal, viral-origin sequences were found to be expressed and to code for a wide variety of functions. Our results clarify the poorly characterized occurrences of viral elements in algal genomes and define a unified adaptive strategy for algal halotolerance.

Methods METHODS DETAILS

Microalgal strain selection and cultivation

Cultivation, DNA extraction, and sequencing of isogenic microalgae was done in several international culture collections and sequencing centers; UTEX (Austin, TX, USA), Bigelow laboratories (NMCA culture collection center, East Boothbay, ME, USA), New York University Abu Dhabi Center for Genomics and Systems Biology (Abu Dhabi, UAE), Admera Health LCC (South Plainfield, NJ, USA), and Novogene (HK).

The UTEX strains were grown on slants using one of the following media as appropriate: BG11 Medium, Bristol Medium, Cyandidium Medium, f/2 Medium, Modified Artificial Seawater Medium, Modified Bold's 3N Medium, Porphyridium Medium, Proteose Medium, Soil Extract Medium, Trebouxia Medium, or Volvox Medium with 1.5% agar as described on the UTEX website (https://utex.org/pages/algal-culture-media-recipes); grown under cool white fluorescent lights at 20⁰C on a 12 hour light cycle. For species isolated and cultured at NYUAD, f/2 medium (Lananan et al., 2013), or Tris-minimal medium (https://chlamycollection.org/), was used (https://utex.org/pages/algal-culture-media-recipes).

The species chosen for sequencing were intended to represent as many microalgae phyla and as many different environments as possible. We sequenced representatives from 11 phyla (see Table S1). Most of the species were from the Chlorophyta or the Ochrophyta phyla. The project designations were algallCODE phase II (n=107, this manuscript), algallCODE phase I (n=22), NCBI-hosted (n=43), and Phytozome-hosted (n=2). Individual strain cultures were selected as representative species for their lineages or as standards to confirm workflow reproducibility (see Table S1; Dataset S1).

We emphasized maximizing the sample size of each saltwater and freshwater species (Fig. 1; Table S1). Of our initial effort to culture >150 species, 24 failed to produce sufficient biomass, six were contaminated, and 3 yielded reads inadequate for an assembly matching the expected size (Dataset S1). The de novo assemblies from the final batch of 107 sequenced species were combined with publicly-available algal genomes for downstream analyses, including coding sequence (CDS) predictions (Dataset S2), hidden Markov model (HMM)-based functional predictions, including viral and protein family domain identification, hierarchical bi-clustering (Fig. 1), enrichment analyses (Fig. 5), principal component analyses (Fig. 5), and ternary graph-based analyses (Fig. S10, Dataset S12).

The natural habitats of these microalgae include a range of diverse geographic locations and all climatic zones, with various temperatures, wind speeds, precipitation, and solar radiation. To allow the study of their evolution, we included species from different types of environments (from the arctic to the tropics) and both salt- and fresh-water habitats (Fig. 1A; Table S1). The freshwater species sequenced in this project included members of the Chlorophyta and Ochrophyta; most of the Haptophytes, Rhodophytes, and Myzozoa we sequenced were saltwater species. Most of the UTEX accessions were freshwater species (28/40); most of the NCMA accessions were saltwater species (50/57). Alexandrium andersonii, a mixotrophic dinoflagellate (1.7Gb), Heterocapsa arctica, an arctic dinoflagellate (1.3 Gb), Lingulodinium polyedra, a red-tide dinoflagellate (1.2 Gb), Amphidinium gibbosum (1.1Gb), and Karena brevis (1.0 Gb) were the largest de novo-assembled genomes in this work (Table S2).

Long-read assemblies, including those from other studies (i.e., Chromochloris zofingiensis (Roth et al., 2017), Thalassiosira pseudonana (Armbrust et al., 2004), and Chlamydomonas reinhardtii (Merchant et al., 2007)), were used to validate our high-throughput short-read assembly process. Four subtropical axenic isolates (from the United Arab Emirates) were sequenced for this study using long-read technologies, including 10x Genomics (Pleasanton, CA, USA) linked-reads, and Pacific Biosciences (Menlo Park, CA, USA) Sequel long reads. Long reads were used to validate assemblies, viral element insertions, and to resolve repeat-containing regions (Ummat and Bashir, 2014; Vondrak et al., 2019). Our results indicated that the CDSs that provided the foundational information for the comparative analyses in this manuscript were reliably determined using short reads (Illumina HiSeq X or Novoseq6000). For example, the Chromochloris zofingiensis genome is the highest quality algal genome published to date (Roth et al., 2017) and has 33,513 exons; our short-read assembly for Chromochloris zofingiensis had 33,910 exons. Other reference microalgae used in this study as resequencing standards included Thalassiosira psuedonana (Armbrust et al., 2004), Chlamydomonas reinhardtii (Merchant et al., 2007), Scenedesmus sp., Guillardia theta (Curtis et al., 2012), Fragilariopsis cylindricus (Mock et al., 2017), Coccomyxa subellipsoidea (Blanc et al., 2012), and Bigelowiella natans (Curtis et al., 2012). A comparison of the assemblies generated from the monoculture and sequencing performed in this study and previous whole-genome sequencing projects is presented in Fig. S3, and QUAST and BUSCO assembly metrics are in Table S2. Hidden Markov models were used to predict structure and function from the whole-genome sequences (Fig. 1, B–D; Tables S3,5; Datasets S6, S7). The results for functional characterization using Enzyme Commission (EC) codes (Alborzi et al., 2017; Ryu et al., 2019), Kyoto Encyclopedia of Genes and Genomes (KEGG) designations (Porollo, 2014), and Gene Ontology (GO) terms (Hayes and Mamano, 2018; Teng et al., 2017) are in Tables S6,8.

DNA extraction

DNA was extracted from mature cultures with QIAGEN DNeasy Plant Maxi kits for HiSeqX 150x2 paired-end (short read) sequencing or QIAGEN MagAttract High Molecular Weight DNA Kits (48) for long-read sequencing. DNA was quantified and assayed for integrity as per the kit manufacturer's protocol. For HMW DNA extraction, briefly, DNA concentration was measured using a Qubit Fluorometer and checked for size by pulsed-field electrophoresis. A length-weighted mean of 50-70 kb was obtained, or the sample was rejected for sequencing. See Dataset S2 for FastQC reports and Fig. S1 for the gel images showing DNA integrity. Extracted DNA with low integrity was not included in library preparations. More than 30 cultures were grown whose DNA did not meet the quality threshold; in these instances, substitute strains were chosen. The final, sequenced strains are listed in Table S1.

Sequencing

Genomic DNA sequencing was performed with Illumina paired-end (Illumina, San Diego, CA, USA), PacBio Sequel (Pacific Biosciences, Menlo Park, CA, USA), and 10x Genomics linked-reads, where indicated, (10x Genomics, Pleasanton, CA, USA) to enable reliable coverage, contig assembly, and de novo genomic sequence assembly. For Illumina paired-end sequencing, Nextera 2x150 bp libraries (Illumina, San Diego, CA, USA) with approximately 72 million reads per sample passing quality filters (Dataset S2) were used for sequencing with a HiSeqX (https://emea.illumina.com/systems/sequencing-platforms/hiseq-x.html). All reads are uploaded to the National Center for Biotechnology Information (NCBI) under the Bioproject accession PRJNA517804). The target coverage was 100x on a 100 Mbp genome. Quality control for library preparation for Illumina sequencing was done with Qubit, Tapestation (Fig. S1), and qPCR. Combining these technologies assisted the validation of VFAM placement within selected genomes and ensured reliable assembly.

De novo genome assembly

De novo assembly can produce variable output depending on the source species and software used; we used both ABySS 2.0 (Jackman et al., 2017) and the Platanus (Kajitani et al., 2019) pipelines for each species sequenced with short-reads (Illumina HiSeqX (Illumina, San Diego, CA, USA)). The ABySS 2.0 command was: 'unset SLURM_NTASKS && mkdir -p $READFILE && TMPDIR=/tmp ABySS-pe -j 18 lib=pe1 k=64 name=$READFILE pe1='$READFILE R1_001.fastq.gz $READFILE R2_001.fastq.gz' --directory=/ data/analysis/ABySS_pe/$READFILE'. The Platanus commands were: '/platanus assemble -o $READ.OUT -f $READ-1.trimmed $READ-2.trimmed -t 4 -m 72 2>assemble.$READ.log'. Details of all YML workflows used are in Dataset S3 and the Key Resources Table lists all essential software used in the creation and analysis of these genomes.

The output with the most single-copy, universally-conserved orthologs, according to “Based on evolutionary-informed expectations of the gene content of near-universal single-copy orthologs,” BUSCO, was chosen for subsequent analyses (Table S2, Dataset S2). This step produces some bias, as ABySS produced assemblies that were much closer in size to the estimated genome sizes from close relatives.

About this dataset

Context

The dataset tabulates the Soldiers Grove population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Soldiers Grove across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Soldiers Grove was 561, a 0.36% decrease year-by-year from 2022. Previously, in 2022, Soldiers Grove population was 563, a decline of 0.88% compared to a population of 568 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Soldiers Grove decreased by 88. In this period, the peak population was 649 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Soldiers Grove is shown in this column.
• Year on Year Change: This column displays the change in Soldiers Grove population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Soldiers Grove Population by Year. You can refer the same here

The U.S. Army Corps of Engineers Fish Passage Facility, located on the White River, Washington State, collects upstream-migrating fish and transfers them to trucks, allowing the fish to access the watershed upstream of Mud Mountain Dam. The structure, constructed in 2019, includes an impoundment held by gates that can be raised or lowered remotely. Those gates are typically lowered during higher flows to allow sediment trapped in the impoundment to flush downstream. Starting in 2020, the USGS collected repeat bathymetric surveys of the White River in the immediate vicinity of the facility to help document how the local channel bed responded to various gate operation strategies. Surveys were generally conducted as soon as possible after high flows that exceeded 4,000 ft3/s. Surveys were conducted using acoustic doppler current profilers (ADCPs) mounted on a remote-control boat, providing XY-depth data, combined with global navigation satellite system (GNSS) surveys used to measure water surface elevations and the location of waters edge. The data were used to construct continuous one-meter digital elevation models (DEMs) of the channel bed. The extent covered in a given survey varied between survey dates, primarily as a function of where water depths were sufficient to operate the ADCP, though all surveys covered the forebay just upstream of the impoundment. A total of ten surveys were conducted between December 15, 2020 and September 30, 2022. Each survey is packaged into a zip file containing: the final one-meter DEM; a csv of all GNSS data; a csv of all xy-depth data from ADCPs; a geopackage, containing the full set of final XYZ points used to construct the DEM, a polygon defining the extents of the DEM, lines defining the waters edge, where depth was enforced to be zero, and lines defining the linear referencing used to link ADCP and GNSS data; a folder containing the original ADCP output in proprietary and ASCII formats; an R script containing all processing steps used to construct the final DEM; and metadata specific to that survey date. An additional folder ('white_fpf_supporting_scripts_data.zip') contains two R scripts, each containing custom functions used in processing the data, and a CSV of coordinates for the four control points used to validate survey datum in the latter surveys.