Data from simulations of COVID-19 spread in Sweden under different public-health measures. Results from individual-based models.

In this work we present results of all the major global models and normalise the model results by looking at changes over time relative to a common base year value. We give an analysis of the variability across the models, both before and after normalisation in order to give insights into variance at national and regional level. A dataset of harmonised results (based on means) and measures of dispersion is presented, providing a baseline dataset for CBCA validation and analysis. The dataset is intended as a goto dataset for country and regional results of consumption and production based accounts. The normalised mean for each country/region is the principle result that can be used to assess the magnitude and trend in the emission accounts. However, an additional key element of the dataset are the measures of robustness and spread of the results across the source models. These metrics give insight into the amount of trust should be placed in the individual country/region results. Code at https://doi.org/10.5281/zenodo.3181930

Multiple populations are ubiquitous in the old massive globular clusters (GCs) of the Milky Way. It is still unclear how they arose during the formation of a GC. The topic of iron and metallicity variations has recently attracted attention with the measurement of iron variations among the primordial population (P1) stars of Galactic GCs. We use the spectra of more than 8000 RGB stars in 21 Galactic GCs observed with MUSE to derive individual stellar metallicities [M/H]. For each cluster, we use the HST photometric catalogs to separate the stars into two main populations (P1 and P2). We measure the metallicity spread within the primordial population of each cluster by combining our metallicity measurements with the stars {Delta}F275W,F814W pseudo-color. We also derive metallicity dispersions ({sigma}[M/H]) for the P1 and P2 stars of each GC. In all but three GCs, we measure a significant correlation between the metallicity and the {Delta}F275W,F814W pseudo-color of the P1 stars such that stars with larger {Delta_F275W,F814W_ have higher metallicities. We measure metallicity spreads that range from 0.03 to 0.24dex and correlate with the GC masses. As for the intrinsic metallicity dispersions, when combining the P1 and P2 stars, we measure values ranging from 0.02 dex to 0.08dex that correlate very well with the GC masses. We compared the metallicity dispersion among the P1 and P2 stars and found that the P2 stars have metallicity dispersions that are smaller or equal to that of the P1 stars. We find that both the metallicity spreads of the P1 stars (from the {Delta_F275W,F814W_ spread in the chromosome maps) and the metallicity dispersions ({sigma_[M/H]_) correlate with the GC masses, as predicted by some theoretical self-enrichment models presented in the literature.

This​ law​ sets​ out​ the health​ and​ administrative​ measures,​ and​ other​ measures​ to​ be​ taken​ to​ combat​ and​ prevent​ the​ spread​ of​ COVID-19​ and​ other​ deadly​ communicable​ diseases​ now​ and​ in​ the​ future​ to​ protect​ the​ people's​ life,​ public​ health​ and​ public​ order,​ as​ well​ as​ to​ minimize​ the​ impact​ of​ the​ disease​ on​ Cambodia's​ social​ and​ economic​ sectors.

This is a spectral dataset of natural objects and daylights collected in Japan.

We collected 359 natural objects and measured the reflectance of all objects and the transmittance of 75 leaves. We also measured daylights from dawn till dusk on four different days using a white plate placed (i) under the direct sun and (ii) under the casted shadow (in total 359 measurements). We also separately measured daylights at five different locations (including a sports ground, a space between tall buildings and a forest) with minimum time intervals to reveal the influence of surrounding environments on the spectral composition of daylights reaching the ground (in total 118 measurements).

Dataset contains following Excel spread sheets and csv files:

(A) Surface properties of natural objects

(A-1) Reflectance_ver1-2.xlsx and .csv

(A-2) Transmittance_FrontSideUp_ver1-2.xlsx and .csv

(A-2) Transmittance_BackSideUp_ver1-2.xlsx and .csv

(B) Daylight measurements

(B-1) Daylight_TimeLapse_v1-2.xlsx and .csv

(B-2) Daylight_DifferentLocations_v1-2.xlsx and .csv

Data description

(A) Surface properties

(A-1) Reflectance_ver1-2.xlsx and .csv

This file contains surface spectral reflectance data (380 - 780 nm, 5 nm step) of 359 natural objects, including 200 flowers, 113 leaves, 23 fruits, 6 vegetables, 8 barks, and 9 stones measured by a spectrophotometer (SR-2A, Topcon, Tokyo, Japan). Photos of all samples are included in the .xlsx file.

For the analysis presented in the paper, we identified reflectance pairs that have a Pearson’s correlation coefficient across 401 spectral channels of more than 0.999 and removed one of reflectances from each pair. The column 'Used in analysis' indicates whether or not each sample is used for the analysis (TRUE indicates used and FALSE indicate not used).

At the time of collection, we noted the scientific names of flowers, leaves and barks from a name board provided by the Tokyo Institute of Technology in which samples are collected. If not available, we used a smartphone software which automatically identifies the scientific name from an input image (PictureThis - Plant Identifier developed by Glority Global Group Ltd.). The names of 2 flowers and 9 stones whose name could not be identified through either method were left blank.

(A-2) Transmittance_FrontSideUp_v1-2.xlsx and .csv

This file contains surface spectral transmittance data (380 - 780 nm, 5 nm step) for 75 leaves measured by a spectrophotometer (SR-2A, Topcon, Tokyo, Japan). Photos of all samples are included in the .xlsx file.

For this data, the transmittance was measured with the front-side of leaves up (the light was transmitted from the back side of the leaves). This is the data presented in the associated article.

(A-3) Transmittance_BackSideUp_v1-2.xlsx and .csv

Spectral transmittance data of the same leaves presented in (A-2).

For this data, the transmittance was measured with the back-side of leaves up (the light was transmitted from the front side of the leaves).

(B) Daylight measurements

(B-1) Daylight_TimeLapse_ver1-2.xlsx and .csv

This file contains daylight spectra from sunrise to sunset on four different days (2013/11/20, 2013/12/24, 2014/07/03 and 2014/10/27) measured by a spectrophotometer (SR-LEDW, Topcon, Tokyo, Japan) with a wavelength range from 380 nm to 780 nm with 1 nm step. We measured the reflected light from the white calibration plate placed either under a direct sunlight or under a casted shadow.

The column 'Cloud cover' provides visual estimate of percentage of cloud cover across the sky at the time of each measurement. The column 'Red lamp' indicates whether an aircraft warning lamp at the measurement site was on (circle) or off (blank).

(B-2) Daylight_DifferentLocations_ver1-2.xlsx and .csv

This file includes daylight spectra measured at five different sites within the Suzukakedai Campus of Tokyo Institute of Technology with minimum time gap on 2014/07/08, using a spectroradiometer (IM-1000, Topcon) from 380 nm to 780 nm with 1 nm step. The instrument was oriented either towards the sun or towards the zenith sky. When the instrument was oriented to the sun, we measured spectra in two ways: (i) one using a black cylinder covering the photodetector and (ii) the other without using a cylinder.

The column 'Cylinder' indicates whether the black cylinder was used (circle) or not (cross). The column 'Cloud cover' shows the visual estimate of percentage of cloud cover at the time of each measurement. The column 'Sun hidden in clouds' denotes whether the measurement was taken when the sun was covered by clouds (circle) or not (blank).

The TROPESS Chemical Reanalysis O3 Spread 6-Hourly 3-dimensional Product contains the ozone ensemble spread, a measure of data assimilation analysis uncertainty. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.The data files are written in the netCDF version 4 file format, and each file contains a year of data at 6-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees at 27 pressure levels between 1000 and 60 hPa. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The infections caused by various bacterial pathogens both in clinical and community settings represent a significant threat to public healthcare worldwide. The growing resistance to antimicrobial drugs acquired by bacterial species causing healthcare-associated infections has already become a life-threatening danger noticed by the World Health Organization. Several groups or lineages of bacterial isolates usually called 'the clones of high risk' often drive the spread of resistance within particular species.

Thus, it is vitally important to reveal and track the spread of such clones and the mechanisms by which they acquire antibiotic resistance and enhance their survival skills. Currently, the analysis of whole genome sequences for bacterial isolates of interest is increasingly used for these purposes, including epidemiological surveillance and developing of spread prevention measures. However, the availability and uniformity of the data derived from the genomic sequences often represents a bottleneck for such investigations.

In this dataset, we present the results of a genomic epidemiology analysis of 61,857 genomes of a dangerous bacterial pathogen Klebsiella pneumoniae obtained from NCBI Genbank database. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), capsular (KL) and oligosaccharide (OL) types, CRISPR-Cas systems, and cgMLST profiles are presented, as well as the assignment of particular isolates to clonal groups (CG). The presence of antimicrobial resistance and virulence genes, as well as plasmid replicons, within the genomes is also reported.

These data will be useful for researchers in the field of K. pneumoniae genomic epidemiology, resistance analysis and prevention measure development.

The TROPESS Chemical Reanalysis O3 Spread 6-Hourly 3-dimensional Product contains the ozone ensemble spread, a measure of data assimilation analysis uncertainty. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.The data files are written in the netCDF version 4 file format, and each file contains a year of data at 6-hourly resolution, and a spatial resolution of 1.125 x 1.125 degrees at 27 pressure levels between 1000 and 60 hPa. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

The TROPESS Chemical Reanalysis CO Spread Monthly 3-dimensional Product contains the carbon monoxide ensemble spread, a measure of data assimilation analysis uncertainty. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.The data files are written in the netCDF version 4 file format, and each file contains a year of data at monthly resolution, and a spatial resolution of 1.125 x 1.125 degrees at 27 pressure levels between 1000 and 60 hPa. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

Statistical measures extracted from the simulation results.

The guidance identifies core personal and community-based public health measures to mitigate the transmission of coronavirus disease (COVID-19).

Mean FWHM of PSFs on the coverslip and on top of live myocytes with oil and water immersion objectives (one S.E.M. shown). The focal plane is described by x and y, while the optical axis is described by z.

Full edition for scientific use. This dataset consists of five separate datafiles representing three measurement points and two types of methods (cross-sectional and longitudinal) for the project "Lernen unter COVID-19-Bedingungen Studierende" [Learning conditions during COVID-19 Students] of the University of Vienna. Measurement point 1 (cross-sectional and longitudinal) contains 6074 data records of students in Austria attending higher education and was surveyed in March/April 2020. Measurement point 2 (cross-sectional) contains 3732 data records of the same target group and Measurement point 2 (longitudinal) contains 1819 data records, both were surveyed in April/May 2020. Measurement point 3 (cross-sectional) contains 661 data records and Measurement point 3 (longitudinal) contains 1386 data records, both were surveyed in June 2020. The dataset contains sociodemographic variables as well as items that can be used to operationalize positive emotion, intrinsic learning motivation, competence, autonomy, social relatedness, engagement, perseverance, gender role self-concept, procrastination and self-regulated learning (SRL) in terms of goal setting and planning, time management and metacognition. Furthermore, the dataset contains information on changes in these variables over time, variables measuring the degree to which students are informed on COVID-19 measures as well as items that explore perception of measures implemented to contain the spread of corona virus.

We present an up-to-date catalog of intrinsic iron abundance spreads in the 55 Milky Way globular clusters (GCs) for which sufficiently precise spectroscopic measurements are available. Our method combines multiple data sets when possible to improve the statistics, taking into account the fact that different methods and instruments can lead to systematically offset metallicities. Only high spectral resolution (R>14000) studies that measure the equivalent widths of individual iron lines are found to have uncertainties on the metallicities of the individual stars that can be calibrated sufficiently well for the intrinsic dispersion to be separated cleanly from a random measurement error. The median intrinsic iron spread is found to be 0.045dex, which is small but unambiguously measured to be nonzero in most cases. There is large variation between clusters, but more luminous GCs, above 10^5^L_{sun}_, have increasingly large iron spreads on average; no trend between the iron spread and metallicity is found. Cone search capability for table J/ApJS/245/5/table1 (Derived dispersions {sigma}0 and average metallicity [Fe/H] for each cluster)

Measures taken in relation to the cat to prevent the spread of COVID-19.

Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the system’s functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns. Here we explore to what extent it is possible to use past temporal data of a system’s pattern of contacts to predict the risk of infection of its elements during an emerging outbreak, in absence of updated data. We focus on two real-world temporal systems; a livestock displacements trade network among animal holdings, and a network of sexual encounters in high-end prostitution. We define the node’s loyalty as a local measure of its tendency to maintain contacts with the same elements over time, and uncover important non-trivial correlations with the node’s epidemic risk. We show that a risk assessment analysis incorporating this knowledge and based on past structural and temporal pattern properties provides accurate predictions for both systems. Its generalizability is tested by introducing a theoretical model for generating synthetic temporal networks. High accuracy of our predictions is recovered across different settings, while the amount of possible predictions is system-specific. The proposed method can provide crucial information for the setup of targeted intervention strategies.

We employ a cellular-automata to reconstruct the land use patterns of cities that we characterize by two measures of spatial heterogeneity: (a) a variant of spatial entropy, which measures the spread of residential, business, and industrial activity sectors, and (b) an index of dissimilarity, which quantifies the degree of spatial mixing of these land use activity parcels. A minimalist and bottom-up approach is adopted that utilizes a limited set of three parameters which represent the forces which determine the extent to which each of these sectors spatially aggregate into clusters. The dispersion degrees of the land uses are governed by a fixed pre-specified power-law distribution based on empirical observations in other cities. Our method is then used to reconstruct land use patterns for the city state of Singapore and a selection of North American cities. We demonstrate the emergence of land use patterns that exhibit comparable visual features to the actual city maps defining our case studies whilst sharing similar spatial characteristics. Our work provides a complementary approach to other measures of urban spatial structure that differentiate cities by their land use patterns resulting from bottom-up dispersion and aggregation processes.

In these measurements considered in this dataset, 15 measurement points are deployed in the scenario. They are sorted in two groups. Among line 1, all measurement points are LoS scenarios. Among line 2, measurement points 1, 2, 3, 4, 5,and 7 are LoS scenarios, and measurement points 6, 8, 9 are NLoS scenarios. Due to the limitation of the cable length, measurement data of line 2 locations 1-6 is collected at mmwave band. The heights of the Tx antenna and the Rx antenna are 2.05 m and 1.45 m, respectively.  The bandwidth of the intermediate frequency filter of the adopted VNA is 2 kHz. Both the Tx and the Rx antennas are omnidirectional antennas. 200 snapshots are collect at each Rx location. In terms of the 3-4 GHz  data, the bandwidth is 1 GHz. The number of frequency points swept in each snapshot is 501. In the aspect of 38-39 GHz and 39-40 GHz data, the center frequencies are 38.5 GHz and 39.5 GHz with 1 GHz bandwidth, respectively. The number of frequency points swept in each snapsh...

The Fire Weather Index (FWI) is a numeric rating of fire intensity, dependent on weather conditions. This is a good indicator of fire danger because it contains both a component of fuel availability (drought conditions) and a measure of ease of spread.

This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5 reanalysis dataset (Hersbach et al., 2019), and replaces the homonymous indices based on ERA-Interim (Vitolo et al., 2019). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs.

The dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately on Zenodo.

Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). The caliver R package (Vitolo et al. 2017, 2018) contains useful functions to process this dataset.

Details:

File format: netcdf4

Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326)

Longitude range: [-180, +180]

Latitude range: [-90, +90]

Temporal resolution: 1 day (at 12 local noon)

Spatial resolution: 0.28 degrees (~31 Km)

Spatial coverage: Global

Time span: from 1980-01-01 to 2019-06-30

Stream: Deterministic forecasts

The Hypatia Catalog is a compilation of abundance measurements from 84 literature sources for FGK stars within 150pc of the Sun. The full, raw, un-reduced catalog contains +3000 stars and can be found with the online journal paper. Provided here is the reduced catalog where stars are excluded if 1) they are probable thick-disk stars per Bensby et al. (2003A&A...410..527B, Cat. J/A+A/410/527) and 2) the spread in the compiled measurements for a star in either [X/Fe] or [Fe/H] is larger than the respective error in cases where multiple groups measured the same element in the same star. When abundance determinations were well agreed upon by multiple sources (or when the spread was less than the respective error), the median value of those measurements is found in the machine readable table here. In addition, all abundances here were re-normalized to the Lodders et al. (2009, Landolt-Bornstein-Group VI Astronomy and Astrophysics Numerical Data and Functional Relationships in Science and Technology Volume 4B: Solar System, ed. J. E. Trumper (Berlin: Springer), 44) solar abundance scale. Please see the main paper for more details. To facilitate use of the Hypatia Catalog, the reduced abundance determinations have been provided in this machine-readable format. However, there are two caveats which must be addressed. To begin, Hypatia is a three-dimensional catalog and placing it in two-dimensions created limitations, specifically for [Fe/H]. As an example, if five literature sources measured abundances in a star, then there are five [Fe/H] values. However, if only two of those five measured [X/Fe] within the star, then only the median of the two corresponding [Fe/H] values were used to produce the [X/Fe] Figs. 5-30 in the paper. Rather than give unique [Fe/H] determinations for each element with only the corresponding [Fe/H] values, the median of all [Fe/H] measurements are given in the FeH column. Per the example, we used the median of all five [Fe/H] measurements. Since elements with spreads larger than respective error are not included, we found that using all of the well agreed upon [Fe/H] measurements to be a conservative choice. Second, Hypatia is an ever-growing database where new measurements will be incorporated as they are released. We have made some small but important updates to the machine readable table. These two caveats only slightly affected the abundance results as compared to the figures in the paper and did not alter the main results and discussion of the paper. Inclusions of more recent surveys and major changes to trends will be addressed in subsequent publications and will be made available online. It is our hope to put all of the abundance data in a flexible database format in the near future.