All-time high price data for Origin Ether, including the peak value, date achieved, and current comparison metrics.

This dataset is linked with the following publication: Lancaster, LT and Kay, KM. 2012. Origin and diversification of the California flora: re-examining classic hypotheses with molecular phylogenies. Evolution. doi: 10.1111/evo.12016. The study found that California's current biodiversity is primarily a result of low extinction rates, as opposed to elevated speciation or immigration rates. Five datasets are presented here. 1. "Genbank accession numbers.csv" provides the Genbank accession numbers of published ITS loci and Jepson II name changes for species used in the study. 2. "Nucleotide substitution models.csv" provides the nucleotide substitution models and calibration dates for each of the 16 clades under consideration. 3. "MCMC analyses.csv" provides a comparison of 1000 versus 10,000 generation MCMC analyses of BiSSE rates for the posterior set of 1000 trees per clade. A burnin of 1% was discarded from each run. 4. "Comparison of diversification models.csv" provides data from the comparison of diversification models for the CA native subclades, using the method of (Morlon et al. 2011). 5. "Comparison of rates within and beyond California.csv" provides data that compares speciation, extinction, net diversification, and migration rates within California versus those beyond California within each of the selected clades.

We provide new evidence of one channel through which circular labor migration has long-run effects on origin communities: by raising completed human capital of the next generation. We estimate the net effects of migration from Malawi to South African mines using newly digitized census and administrative data on access to mine jobs, a difference-in-differences strategy, and two opposite-signed and plausibly exogenous shocks to the option to migrate. Twenty years after these shocks, human capital is 4.8-6.9 percent higher among cohorts who were eligible for schooling in communities with the easiest access to migrant jobs.

Aralia elata buds contain many nutrients and have a pleasant taste with unique flavor. Previous studies mainly focused on triterpene saponins in the root bark of this species, but little information existed concerning other chemical components, especially in the buds. To better understand the nutritional value of Aralia elata, we compared total flavonoids, total saponins, phenolic compounds and mineral elements contents in the buds of Aralia elata collected from eight different geographical regions (S1: Benxi; S2: Linjiang; S3: Pingwu; S4: Enshi; S5: Changbaishan; S6: Shangzhi; S7: Xiaoxinganling and S8: Harbin) in China. The results showed that the basic composition in the buds presented a wide variation noticed by ash (8.76 to 10.35%), crude fiber (5.38 to 11.07%), polysaccharides (33.85 to 46.79 mg/g), total flavonoid content (4.06 to 48.63 mg/g) and total saponins (13.62 to 27.85 mg/g). UPLC combined with LC-MS/MS method was used for the phenolic compounds analysis, and eleven phenolic compounds were identified and quantified in the 8 samples. The total phenolic content in Enshi (S4) was significantly higher than others, and quercetin was the predominant phenolic compound in this sample. We used ICP-OES to identify and quantify nine mineral elements in the buds. The Fe and Cu contents in S5 were much higher than that of others. We got maximum Mg, Mn, Co and Ni contents in S4, and found rich Zn content in S7. Moreover, the maximum estimated quantity of Ca and Sr contents were found in S8. This study indicated that the chemical composition in the buds of Aralia elata was obviously affected by geographical origin. Our results provided an essential theoretical basis on quality evaluation of Aralia elata buds in food production field.

The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Much of the ACS data provided on the Census Bureau's Web site are available separately by age group, race, Hispanic origin, and sex. Summary files, Subject tables, Data profiles, and Comparison profiles are available for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Comparison profiles are similar to data profiles but also include comparisons with past-year data. The current year data are compared with each of the last four years of data and include statistical significance testing. There are over 1,000 variables in this dataset.

Life Stage, chorion, and hatchery origin differences in the toxicity of 6PPDQ to coho salmon

Dataset DOI: 10.5061/dryad.j6q573nsk

Description of the data and file structure

Files and variables

File: Acute_Exposure.csv

Description: rows describe the conditions and outcomes of each acute exposure aquarium.

Variables

• Measured_6PPDQ_ng_L: the concentration of 6PPDQ, measured by LC-MS/MS, in nanograms per liter from 200 milliliter water samples taken from the replicate at the beginning of the experiment.
• Number_Dead: the number of individual coho salmon in the replicate that were determined to be dead after 24 hours of exposure.
• Number_Total: the total number of individual coho salmon included in the replicate.
• MortalityRate: Number_Dead/Number_Total
• Group: the life stage or creek of origin of the individuals in the replicates.
• Days_Post_Fertilization: the age in days since fertilization of the individuals in the replic...

This dataset includes teen birth rates for females by age group, race, and Hispanic origin in the United States since 1960. Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison. National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf). SOURCES NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES 1. National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf. 2. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf. 3. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf. 4. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf. 5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf. 6. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Data were collected from recordings of lab-raised male and female bay wrens individiually raised in acoustic isolation and tutored with duets from wild-caught birds. Duets were presented to one tretament group from a single monoaural speaker, and stereophincally to another group, with male and female contributions to the duet coming from separate speakers. Spectrograms of songs produced during and after song development were sorted into types and scored by independent observers to sdtermine repertoire size and,for sero-tutored birds, quality of song performance during song development.

State comparisons data for population,age, race, Hispanic Origin, and housing information for all states. Data include a national ranking.

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

This dataset includes live births, birth rates, and fertility rates by race of mother in the United States since 1960.

Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.

SOURCES

NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).

REFERENCES

1. National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.

2. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.

3. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.

4. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.

6. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

The vegetation of the montane and subalpine zones of the Rocky Mountains is a mosaic of conifer forests and large (1 ha to several square kilometers) treeless “parks” dominated by sagebrush (Artemisia spp.), grasses, and forbs. Three hypotheses for the origin of parks are proposed. The “permanent site hypothesis” states that the park–forest vegetation mosaic is a result of differences in physical characteristics of sites. In the “remnant hypothesis” parks are thought to be remnants of vegetation that was widespread under previous climate conditions. The “replacement hypothesis” states that parks replace forest vegetation in response to disturbance, climate change, or a combination of these two factors. Patterns in the past distribution of park and forest vegetation in the vicinity of Fish Creek Park (elevation 2750 m) were used to test these hypotheses. Fossil pollen extracted from the sediments of five small ponds in and around Fish Creek Park was used to reconstruct Holocene vegetation changes. Changes in vegetation were reconstructed through the use of multivariate analyses and pollen ratios derived from modern surface samples and by comparison with pollen data from other studies. The pollen record indicates that shortly after deglaciation (∼11000 yr BP) the area supported alpine tundra, followed by whitebark pine–spruce–fir parkland at ∼9500 yr BP. From ∼8500 to 6000 yr BP, a pine parkland occupied the area, perhaps in response to climate conditions warmer than today. By 5000 yr BP a mixed pine–spruce–fir forest resembling the modern subalpine forest near Fish Creek Park probably replaced the pine parkland at all five sites. The modern park vegetation originated only within the last ∼2500 yr. The conversion to park vegetation may not have been synchronous at all three sites, and the replacement of forest by park did not always result in a long-term conversion to park vegetation. The timing and pattern of changes in the vegetation mosaic eliminate the permanent site and remnant hypotheses and suggest instead that climatic cooling over the last several thousand years, possibly combined with removal of forest cover by fire or some other disturbance, could explain the origin of Fish Creek Park.

Lynch, E.A. 1998. Origin of a park-forest vegetation mosaic in the Wind River Range, Wyoming. Ecology 79, 1320-1338.

The origin band in the b̃1B1−ã1A1 transition of CH2 near 1.2 μm has been recorded at Doppler-limited resolution using diode laser transient absorption spectroscopy. The assignments of rotational transitions terminating in upper state levels with Ka = 0 and 1, were confirmed by ground state combination differences and extensive optical−optical double resonance experiments. The assigned lines are embedded in a surprisingly dense spectral region, which includes a strong hot band, b̃(0,1,0) Ka = 0  ã(0,1,0) Ka = 1 sub-band lines, with combination or overtone transitions in the ã1A1 state likely responsible for the majority of unassigned transitions in this region. From measured line intensities and an estimate of the concentration of CH2 in the sample, we find the transition moment square for the 000 ← 110 transition in the b̃1B1(0,0,0)0−ã1A1(0,0,0)1 sub-band is 0.005(1) D2. Prominent b̃1B1(0,1,0)0−ã1A1(0,1,0)1 hot band lines were observed in the same spectral region. Comparison of the intensities of corresponding rotational transitions in the two bands suggests the hot band has an intrinsic strength approximately 28 times larger than the origin band. Perturbations of the excited state Ka = 0 and 1 levels are observed and discussed. The new measurements will lead to improved future theoretical modeling and calculations of the Renner−Teller effect between the ã and b̃ states in CH2.

The OCTO-Twin Study aims to investigate the etiology of individual differences among twin-pairs age 80 and older, on a range of domains including health and functional capacity, cognitive functioning, psychological well-being, personality and personal control. In the study, twin pairs were withdrawn from the Swedish Twin Registry. At the first wave, the twins had to be born 1913 or earlier and both partners in the pair had to accept participation. At baseline in 1991-94, 351 twin pairs (149 monozygotic and 202 like-sex dizygotic pairs) were investigated (mean age: 83.6 years and 67% were female). The two-year longitudinal follow-ups were conducted on all twins who were alive and agreed to participate. Data have been collected at five waves over a total of eight years.

In wave 4, 84 twin pairs participated, with a total of 315 individuals. Refer to the description of wave 1/the base line and the individual datasets in the NEAR portal for more details on variable groups and individual variables.

In this study, we investigated the relative contribution of geographic barriers and Pleistocene refuges in the diversification of the Rhinella crucifer species complex, a group of endemic toads with a widespread distribution in the Brazilian Atlantic Forest (AF). We used intensive sampling and multilocus DNA sequence data to compare nucleotide diversity between refuge and nonrefuge areas, investigate regional demographic patterns, estimate demographic parameters related to genetic breaks and test refuge versus barrier scenarios of diversification using approximate Bayesian computation. We did not find higher levels of genetic diversity in putative refuge areas, either at regional or biome scale. Rather, the demographic history of the species complex supports regional differences with moderate population growth in the north and central regions and stability in southern AF. Genetic breaks were dated to the Plio–Pleistocene; however, our analyses rejected the role of refuges in creating a northern and central divergence, supporting a recent colonization scenario at a smaller scale within the central AF. Overall, our data rule out massive climatically driven fragmentation and large-scale recolonization events for populations across the biome. We confirmed the importance of geographic barriers in creating main divergences and underscored the importance of searching for cryptic discontinuities in the landscape. Comparison of our results with those of other AF taxa indicates organismal specific responses to moderate shifts in habitat and that multiple refuges may constitute a more realistic model for diversification of Atlantic Forest biota.

The origin of flowers has puzzled plant biologists ever since Darwin referred to their sudden appearance in the fossil record as an abominable mystery. Flowers are considered to be an assembly of protective, attractive and reproductive male and female leaf-like organs. Their origin cannot be understood by a morphological comparison to gymnosperms, their closest relatives, which develop separate male or female cones. Despite these morphological differences, gymnosperms and angiosperms possess a similar genetic toolbox consisting of phylogenetically related MADS-domain proteins. Using ancestral MADS-domain protein reconstruction, we trace the evolution of organ identity quartets along the stem lineage of crown angiosperms. We provide evidence that current floral quartets specifying male organ identity, which consist of four types of subunits, evolved from ancestral complexes of two types of subunits through gene duplication and integration of SEPALLATA proteins just before the origin of flowering plants. Our results suggest that protein interaction changes underlying this compositional shift were the result of a gradual and reversible evolutionary trajectory. Modelling shows that such compositional changes may have facilitated the evolution of the perfect, bisexual flower.

Context:

This dataset provides data on death rates for suicide categorized by selected population characteristics including sex, race, Hispanic origin, and age in the United States. It includes critical information about measures, definitions, and changes over time.

Source: - NCHS, National Vital Statistics System (NVSS) - Grove RD, Hetzel AM. Vital statistics rates in the United States, 1940–1960. National Center for Health Statistics. 1968 - Numerator data from NVSS annual public-use Mortality Files - Denominator data from U.S. Census Bureau national population estimates - Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics. 2021

Source URLs:

Death rates for suicide by sex, race, Hispanic origin, and age: United States - HUS 2019 Data Finder - National Vital Statistics Reports - NVSS Appendix Entry

Dataset Details and Key Features

The dataset consists of data collected from the National Vital Statistics System (NVSS) and the U.S. Census Bureau, providing a comprehensive overview of suicide death rates across different demographics in the United States from 1950 to 2001.

Key Features:

• Historical Coverage: Data spans from 1950 to 2001, providing long-term trends.
• Demographic Breakdown: Includes data by sex, race, Hispanic origin, and age, facilitating targeted analysis.
• Yearly Data: Provides annual death rate estimates, enabling year-over-year comparison.
• Reliable Sources: Data collected from NVSS and U.S. Census Bureau, ensuring accuracy and reliability.

Usage:

Research and Analysis:

• Trend Analysis: Study long-term trends in suicide rates across different demographic groups.
• Impact Assessment: Analyze the impact of socio-economic factors on suicide rates over time.
• Health Disparities: Identify disparities in suicide rates among different demographic segments.

Policy Making:

• Intervention Development: Inform the creation of targeted interventions for high-risk groups.
• Resource Allocation: Aid in the effective allocation of resources to areas with higher suicide rates.
• Policy Evaluation: Evaluate the effectiveness of past policies and programs aimed at reducing suicide rates.

Public Health Initiatives:

• Awareness Campaigns: Develop awareness campaigns tailored to specific demographic groups.
• Prevention Programs: Design and implement suicide prevention programs based on demographic data.
• Community Outreach: Facilitate community outreach efforts by identifying high-risk areas.

Data Maintenance:

Updates:

• Periodic Updates: The dataset is periodically updated to incorporate the latest available data.
• Version Control: Maintains previous versions for reference and longitudinal studies.

Quality Assurance:

• Data Validation: Ensures data accuracy through rigorous validation processes.
• Consistency Checks: Regular consistency checks to maintain data integrity.

Additional Notes:

• For detailed definitions and explanations of measures, refer to the PDF or Excel version of this table in the HUS 2019 Data Finder.
• Numerator data is derived from NVSS annual public-use Mortality Files, while denominator data comes from U.S. Census Bureau national population estimates.
• The dataset also includes historical data, providing context and continuity for contemporary analysis.

Columns:

An efficient and general entry to unsaturated cyclopropane- and lactone-containing oxylipins of marine origin has been designed and applied to the first enantioselective total synthesis of solandelactone E. The synthesis, which proceeds in a total of 23 steps from commercially available materials, features a diastereoselective acetal-directed cyclopropanation of an electron-deficient diene, a regioselective Sharpless enantioselective dihydroxylation, and a stereoselective [2,3]-sigmatropic rearrangement of a selenoxide to effect a 1,3-transposition of an allylic alcohol. Comparison of spectral data for the synthetic solandelactone, thus prepared, with data in the literature led to a revision of the original structural assignments of the C(11)-epimeric solandelactones.