Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Men (LEU0254638300A) from 2000 to 2024 about mathematicians, science, second quartile, miscellaneous, occupation, full-time, males, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

Modeling the relationship between pupil features and IQR indicates that baseline and peak latency are associated with the distribution of response time between sessions in this longitudinal study.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Women was 1640.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Women reached a record high of 1640.00000 in January of 2024 and a record low of 867.00000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Women - last updated from the United States Federal Reserve on July of 2025.

The interquartile range (IQR) for the total number of contacts is also indicated. Group Contacts represent the number of people met in group settings, Total contacts represents the sum of individual and group contacts.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Men was 2043.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Men reached a record high of 2043.00000 in January of 2024 and a record low of 977.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Computer and mathematical occupations: 16 years and over: Men - last updated from the United States Federal Reserve on August of 2025.

Our work aims to substantiate and extend earlier findings on the effects of student-teacher race matching on academic achievement using longitudinal data for students in Grades 3 through 8 in Tennessee. We examine heterogenous effects not only by racial subgroup and student preparedness, as explored in prior literature, but also by levels of teacher effectiveness, drawing on data from the state’s teacher evaluation system. We find that student-teacher race congruence does not have a significant overall effect on test scores. However, subgroup analyses reveal a positive, significant race-match effect in elementary school math. We observe meaningful effects for Black students in both reading and math, race-matched students in the bottom-most preparedness quartile in math, and race-matched students assigned to teachers in the middle two teacher performance quartiles in math. Our results align with prior findings, emphasizing that race-match effects transcend state borders. Findings support policy efforts to diversify the educator labor force.

Background: Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019 and quickly spread throughout China and the rest of the world. Many mathematical models have been developed to understand and predict the infectiousness of COVID-19. We aim to summarize these models to inform efforts to manage the current outbreak.Methods: We searched PubMed, Web of science, EMBASE, bioRxiv, medRxiv, arXiv, Preprints, and National Knowledge Infrastructure (Chinese database) for relevant studies published between 1 December 2019 and 21 February 2020. References were screened for additional publications. Crucial indicators were extracted and analysed. We also built a mathematical model for the evolution of the epidemic in Wuhan that synthesised extracted indicators.Results: Fifty-two articles involving 75 mathematical or statistical models were included in our systematic review. The overall median basic reproduction number (R0) was 3.77 [interquartile range (IQR) 2.78–5.13], which dropped to a controlled reproduction number (Rc) of 1.88 (IQR 1.41–2.24) after city lockdown. The median incubation and infectious periods were 5.90 (IQR 4.78–6.25) and 9.94 (IQR 3.93–13.50) days, respectively. The median case-fatality rate (CFR) was 2.9% (IQR 2.3–5.4%). Our mathematical model showed that, in Wuhan, the peak time of infection is likely to be March 2020 with a median size of 98,333 infected cases (range 55,225–188,284). The earliest elimination of ongoing transmission is likely to be achieved around 7 May 2020.Conclusions: Our analysis found a sustained Rc and prolonged incubation/ infectious periods, suggesting COVID-19 is highly infectious. Although interventions in China have been effective in controlling secondary transmission, sustained global efforts are needed to contain an emerging pandemic. Alternative interventions can be explored using modelling studies to better inform policymaking as the outbreak continues.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Men was 1907.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Men reached a record high of 3859.00000 in January of 2005 and a record low of 0.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Men - last updated from the United States Federal Reserve on July of 2025.

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This dataset have been constructed and used for scientific purpose, available in the paper "Detecting the effects of inter-annual and seasonal changes of environmental factors on the the striped red mullet population in the Bay of Biscay" authored by Kermorvant C., Caill-Milly N., Sous D., Paradinas I., Lissardy M. and Liquet B. and published in Journal of Sea Research. This file is an extraction from the SACROIS fisheries database created by Ifremer (for more information see https://sextant.ifremer.fr/record/3e177f76-96b0-42e2-8007-62210767dc07/) and from the Copernicus database. Biochemestry comes from the product GLOBAL_ANALYSIS_FORECAST_BIO_001_028 (https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=GLOBAL_ANALYSIS_FORECAST_BIO_001_028). Temperature and salinity comes from GLOBAL_ANALYSIS_FORECAST_PHY_001_024 product (https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=GLOBAL_ANALYSIS_FORECAST_PHY_001_024). As fisheries landing per unit of effort is only available per ICES rectangle and by month, environmental data have been aggregated accordingly.

######### # Colomns description # ############### rectangle - The 6 ICES statistical rectangles used in the study. time_m - Time in months, from the beginning to the end of the study. annee = year mois = month (from 1 to 12) Poids = Weight of red mullet landed valeur = Temps_peche = fishing time Nb_sequence = number of fishing sequences Moy / Med / Var / StD Quartil_1 / Quartil_3 / min / max / CV / IQR = statistical descriptors of landing by rectangle and by month log_cpue = log of Med colomn mean_surface_s = mean of surface salinity by month and by rectangle median_surface_s = median of surface salinity by month and by rectangle mean_surface_t = mean of surface temperature by month and by rectangle median_surface_t = median of surface temperature by month and by rectangle si / zeu /po4 / pyc / o2/ nppv / no3 and nh4 mean and median concentration by rectangle and by month pc3 / pc2 / pc1 - projections of previous biochemestry variables on the three first axes of a PCA

Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Women was 1564.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Women reached a record high of 1800.00000 in January of 2007 and a record low of 0.00000 in January of 2003. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Miscellaneous mathematical science occupations: 16 years and over: Women - last updated from the United States Federal Reserve on July of 2025.

BackgroundTo date, there is a lack of sufficient evidence on the type of clusters in which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is most likely to spread. Notably, the differences between cluster-level and population-level outbreaks in epidemiological characteristics and transmissibility remain unclear. Identifying the characteristics of these two levels, including epidemiology and transmission dynamics, allows us to develop better surveillance and control strategies following the current removal of suppression measures in China.MethodsWe described the epidemiological characteristics of SARS-CoV-2 and calculated its transmissibility by taking a Chinese city as an example. We used descriptive analysis to characterize epidemiological features for coronavirus disease 2019 (COVID-19) incidence database from 1 Jan 2020 to 2 March 2020 in Chaoyang District, Beijing City, China. The susceptible-exposed-infected-asymptomatic-recovered (SEIAR) model was fitted with the dataset, and the effective reproduction number (Reff) was calculated as the transmissibility of a single population. Also, the basic reproduction number (R0) was calculated by definition for three clusters, such as household, factory and community, as the transmissibility of subgroups.ResultsThe epidemic curve in Chaoyang District was divided into three stages. We included nine clusters (subgroups), which comprised of seven household-level and one factory-level and one community-level cluster, with sizes ranging from 2 to 17 cases. For the nine clusters, the median incubation period was 17.0 days [Interquartile range (IQR): 8.4–24.0 days (d)], and the average interval between date of onset (report date) and diagnosis date was 1.9 d (IQR: 1.7 to 6.4 d). At the population level, the transmissibility of the virus was high in the early stage of the epidemic (Reff = 4.81). The transmissibility was higher in factory-level clusters (R0 = 16) than in community-level clusters (R0 = 3), and household-level clusters (R0 = 1).ConclusionsIn Chaoyang District, the epidemiological features of SARS-CoV-2 showed multi-stage pattern. Many clusters were reported to occur indoors, mostly from households and factories, and few from the community. The risk of transmission varies by setting, with indoor settings being more severe than outdoor settings. Reported household clusters were the predominant type, but the population size of the different types of clusters limited transmission. The transmissibility of SARS-CoV-2 was different between a single population and its subgroups, with cluster-level transmissibility higher than population-level transmissibility.

Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study.

Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study.

All ranges are uniformly distributedTwo AIDS stages were included because during the final months before death, patients have limited sexual activity** Due to window phase of p24 antigen testing† Includes cost of false positives that require additional testing (0·7% false positivity rate)‡ Four times the length of a normal outpatient clinic appointment§ The average cost per person per stage of infection/treatment. Includes diagnosis, treatment, personnel costs. Averaged per patient per year.Key model parameters and costs.

Mathematical models have suggested that spatially-targeted screening interventions for tuberculosis may efficiently accelerate disease control, but empirical data supporting these findings are limited. Previous models demonstrating substantial impacts of these interventions have typically simulated large-scale screening efforts and have not attempted to capture the spatial distribution of tuberculosis in households and communities at a high resolution. Here, we calibrate an individual-based model to the locations of case notifications in one district of Lima, Peru. We estimate the incremental efficiency and impact of a spatially-targeted interventions used in combination with household contact tracing (HHCT). Our analysis reveals that HHCT is relatively efficient with a median of 40 (Interquartile Range: 31.7 to 49.9) household contacts required to be screened to detect a single case of active tuberculosis. However, HHCT has limited population impact, producing a median incidence reduction of only 3.7% (Interquartile Range: 5.8% to 1.9%) over 5 years. In comparison, spatially targeted screening (which we modeled as active case finding within high tuberculosis prevalence areas 100 m2 grid cell) is far less efficient, requiring evaluation of ≈12 times the number of individuals as HHCT to find a single individual with active tuberculosis. Furthermore, the addition of the spatially targeted screening effort produced only modest additional reductions in tuberculosis incidence over the 5 year period (≈1.3%) in tuberculosis incidence. In summary, we found that HHCT is an efficient approach for tuberculosis case finding, but has limited population impact. Other screening approaches which target areas of high tuberculosis prevalence are less efficient, and may have limited impact unless very large numbers of individuals can be screened.

Global model inputs.

MSE of all the estimators based on simulation studies under SRS.

Some combinations of proposed class of ratio estimators of .

Average feature values at the starting moment of the cut marks according to quartile groups.