After experiencing a ransomware attack, roughly ** percent of organizations worldwide paid up to get their encrypted data back. Survey data from January and March 2023 found that *** percent of the affected companies used other means, while ** percent used backups to regain access to their data. Overall, ** percent of companies got their data back after a ransomware attack.

This dataset was created to investigate research trends in each of the 11 digital health technology categories identified by previous studies. The dataset was created using the number of articles, such as books, conference papers, journal papers, and magazines published in the IEEE (Institute of Electrical and Electronics Engineers) Xplore between 2003 and 2022. The dataset consists of a sheet with the number of articles for each of the 11 digital health technology categories and a sheet summarizing them (i.e., the raw data in Figure 2). Each sheet of the xlsx file shows the following data. - The sheet named "Figure 2" is the raw data from Figure 2 of our published article. - Other sheets: Number of articles comprising the data in Figure 2, aggregated by year.

The objective of this study was to evaluate the effect of a back-support exoskeleton (Laevo V2.5) on the trunk and hip angles, low back muscle activity, and heart rate during in-bed patient handling tasks. Eight participants (5 males and 3 females) performed four different in-bed patient handling tasks, including sitting to lying, repositioning toward the caregiver, turning toward the caregiver, and turning away from the caregiver.

The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and beaches, contains a number of coastal communities, and supports a local fishing industry, all of which are impacted by coastal change. Knowledge derived from this research program can be used to mitigate hazards and facilitate effective management of this dynamic coastal system. This regional mapping project produced spatial datasets of high-resolution geophysical (bathymetry, backscatter intensity, and seismic reflection) and sedimentary (core and grab-sample) data. The high-resolution geophysical data were collected during numerous surveys within the back-barrier estuarine system, along the barrier island complex, in the nearshore, and along the inner continental shelf. Sediment cores were taken on the mainland and along the barrier islands, and both cores and grab samples were taken on the inner shelf. Data collection was a collaborative effort between the U.S. Geological Survey (USGS) and several other institutions including East Carolina University (ECU), the North Carolina Geological Survey, and the Virginia Institute of Marine Science (VIMS). The high-resolution geophysical data of the inner continental shelf were collected during six separate surveys conducted between 1999 and 2004 (four USGS surveys north of Cape Hatteras: 1999-045-FA, 2001-005-FA, 2002-012-FA, 2002-013-FA, and two USGS surveys south of Cape Hatteras: 2003-003-FA and 2004-003-FA) and cover more than 2600 square kilometers of the inner shelf. Single-beam bathymetry data were collected north of Cape Hatteras in 1999 using a Furuno fathometer. Swath bathymetry data were collected on all other inner shelf surveys using a SEA, Ltd. SwathPLUS 234-kHz bathymetric sonar. Chirp seismic data as well as sidescan-sonar data were collected with a Teledyne Benthos (Datasonics) SIS-1000 north of Cape Hatteras along with boomer seismic reflection data (cruises 1999-045-FA, 2001-005-FA, 2002-012-FA and 2002-013-FA). An Edgetech 512i was used to collect chirp seismic data south of Cape Hatteras (cruises 2003-003-FA and 2004-003-FA) along with a Klein 3000 sidescan-sonar system. Sediment samples were collected with a Van Veen grab sampler during four of the USGS surveys (1999-045-FA, 2001-005-FA, 2002-013-FA, and 2004-003-FA). Additional sediment core data along the inner shelf are provided from previously published studies. A cooperative study, between the North Carolina Geological Survey and the Minerals Management Service (MMS cores), collected vibracores along the inner continental shelf offshore of Nags Head, Kill Devils Hills and Kitty Hawk, North Carolina in 1996. The U.S. Army Corps of Engineers collected vibracores along the inner shelf offshore of Dare County in August 1995 (NDC cores) and July-August 1995 (SNL cores). These cores are curated by the North Carolina Geological Survey and were used as part of the ground validation process in this study. Nearshore geophysical and core data were collected by the Virginia Institute of Marine Science. The nearshore is defined here as the region between the 10-m isobath and the shoreline. High-resolution bathymetry, backscatter intensity, and chirp seismic data were collected between June 2002 and May 2004. Vibracore samples were collected in May and July 2005. Shallow subsurface geophysical data were acquired along the Outer Banks barrier islands using a ground-penetrating radar (GPR) system. Data were collected by East Carolina University from 2002 to 2005. Rotasonic cores (OBX cores) from five drilling operations were collected from 2002 to 2006 by the North Carolina Geological Survey as part of the cooperative study with the USGS. These cores are distributed throughout the Outer Banks as well as the mainland. The USGS collected seismic data for the Quaternary section within the Albemarle-Pamlico estuarine system between 2001 and 2004 during six surveys (2001-013-FA, 2002-015-FA, 2003-005-FA, 2003-042-FA, 2004-005-FA, and 2004-006-FA). These surveys used Geopulse Boomer and Knudsen Engineering Limited (KEL) 320BR Chirp systems, except cruise 2003-042-FA, which used an Edgetech 424 Chirp and a boomer system. The study area includes Albemarle Sound and selected tributary estuaries such as the South, Pungo, Alligator, and Pasquotank Rivers; Pamlico Sound and trunk estuaries including the Neuse and Pamlico Rivers; and back-barrier sounds including Currituck, Croatan, Roanoke, Core, and Bogue.

Cloud data back-up & recovery market size was valued at USD 10.9 Billion in 2024 and is anticipated to reach USD 35.2 Billion by 2034 at a CAGR of 10.5%. Data Backup and Recovery report classifies global market by share, software, deployment model, organization, end-use, and region | Data Backup and...

According to a survey conducted on cyber security in South Korea in August 2023, around ** percent of respondents utilized separate storage devices liked to use USB sticks or external hard drives for back-ups. Almost ** percent stated they used operating separate back-up servers.

According to a survey conducted on cyber security in South Korea in February 2024, around **** percent of respondents answered that they used some sort of data back up at their institution. The other approximately *** percent in the survey stated they did not use data back ups.

Our study aimed at assessing back pain impact over health-related quality of life (HRQoL). This is a cross-sectional population-based study that analyzed 1,192 adults. The dependent variables were the SF-36 scales and the main independent variables was back pain characterized by location, number of back pain region, intensity, frequency and limitations. Simple and multiple linear regression models were performed to estimate the crude and adjusted beta-coefficients (gender, age, schooling and co-morbidity conditions). Back pain prevalence were 35.4%. For HRQoL, comparing people with/without back pain, we found weak associations for the physical component (β = -3.6). However, strong associations were found for physical component (β = -12.4) when there were concomitant pain in cervical, dorsal and lumbar sites and also associations with mental health scales. Daily pain was associated with physical (β = -6.8) and mental (β = -2.7) components. Important impact on physical componente summary was found for intense/very intense pain (β = -7.9) and pain with severe limitation (β = -11.5). The impacts over HRQoL were strong when back pain was followed by (1) multiple back sites, (2) with pain in mental componente summary, (3) daily complaints, (4) very intense pain and (5) severe limitations; these results have revealed the importance to measure specific factors related to back pain.

Permits issued by the Department of Buildings in the City of Chicago from 2006 to the present. The dataset for each year contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. Data fields requiring description are detailed below. PERMIT TYPE: "New Construction and Renovation" includes new projects or rehabilitations of existing buildings; "Other Construction" includes items that require plans such as cell towers and cranes; "Easy Permit" includes minor repairs that require no plans; "Wrecking/Demolition" includes private demolition of buildings and other structures; "Electrical Wiring" includes major and minor electrical work both permanent and temporary; "Sign Permit" includes signs, canopies and awnings both on private property and over the public way; "Porch Permit" includes new porch construction and renovation (defunct permit type porches are now issued under "New Construction and Renovation" directly); "Reinstate Permit" includes original permit reinstatements; "Extension Permits" includes extension of original permit when construction has not started within six months of original permit issuance. WORK DESCRIPTION: The description of work being done on the issued permit, which is printed on the permit. PIN1 – PIN10: A maximum of ten assessor parcel index numbers belonging to the permitted property. PINs are provided by the customer seeking the permit since mid-2008 where required by the Cook County Assessor’s Office. CONTRACTOR INFORMATION: The contractor type, name, and contact information. Data includes up to 15 different contractors per permit if applicable.

Data Owner: Buildings.

Time Period: January 1, 2006 to present.

Frequency: Data is updated daily.

Related Applications: Building Data Warehouse (https://webapps.cityofchicago.org/buildingviolations/violations/searchaddresspage.html).

28341 Global import shipment records of Back Support with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

83056 Global export shipment records of Back Support with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

310 Observations, 13 Attributes (12 Numeric Predictors, 1 Binary Class Attribute - No Demographics)

Lower back pain can be caused by a variety of problems with any parts of the complex, interconnected network of spinal muscles, nerves, bones, discs or tendons in the lumbar spine. Typical sources of low back pain include:

The large nerve roots in the low back that go to the legs may be irritated The smaller nerves that supply the low back may be irritated The large paired lower back muscles (erector spinae) may be strained The bones, ligaments or joints may be damaged An intervertebral disc may be degenerating An irritation or problem with any of these structures can cause lower back pain and/or pain that radiates or is referred to other parts of the body. Many lower back problems also cause back muscle spasms, which don't sound like much but can cause severe pain and disability.

While lower back pain is extremely common, the symptoms and severity of lower back pain vary greatly. A simple lower back muscle strain might be excruciating enough to necessitate an emergency room visit, while a degenerating disc might cause only mild, intermittent discomfort.

This data set is about to identify a person is abnormal or normal using collected physical spine details/data.

WNA-FLEXPART-BackTraj-1994-2021-Merge is the combined 1994-2021 Western North America Back Trajectory data using the FLEXible PARTicle (FLEXPART) dispersion model. Data collection for this product is complete.Backward simulations of airmass transport using a Lagrangian Particle Dispersion Model (LPDM) framework can establish source-receptor relationships (SRRs), supporting analysis of source contributions from various geospatial regions and atmospheric layers to downwind observations. In this study, we selected receptor locations to match gridded ozone observations over Western North America (WNA) from ozonesonde, lidar, commercial aircraft sampling, and aircraft campaigns (1994-2021). For each receptor, we used the FLEXible PARTicle (FLEXPART) dispersion model, driven by ERA5 reanalysis data, to achieve 15-day backwards SRR calculations, providing global simulations at high temporal (hourly) and spatial (1° x 1°) resolution, from the surface up to 20 km above ground level. This product retains detailed information for each receptor, including the gridded ozone value product, allowing the user to illustrate and identify source contributions to various subsets of ozone observations in the troposphere above WNA over nearly 3 decades at different vertical layers and temporal scales, such as diurnal, daily, seasonal, intra-annual, and decadal. This model product can also support source contribution analyses for other atmospheric components observed over WNA, if other co-located observations have been made at the spatial and temporal scales defined for some or all of the gridded ozone receptors used here.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.

30-lt_input.csv

Life table input data.

id: unique row identifier

region_iso: iso3166-2 region codes

sex: Male, Female, Total

year: iso year

age_start: start of age group

age_width: width of age group, Inf for age_start 100, otherwise 1

nweeks_year: number of weeks in that year, 52 or 53

death_total: number of deaths by any cause

population_py: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)

death_total_nweeksmiss: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)

death_total_minnageraw: the minimum number of age-groups in the raw input data within this region-sex-year stratum

death_total_maxnageraw: the maximum number of age-groups in the raw input data within this region-sex-year stratum

death_total_minopenageraw: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_maxopenageraw: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_source: source of the all-cause death data

death_total_prop_q1: observed proportion of deaths in first quarter of year

death_total_prop_q2: observed proportion of deaths in second quarter of year

death_total_prop_q3: observed proportion of deaths in third quarter of year

death_total_prop_q4: observed proportion of deaths in fourth quarter of year

death_expected_prop_q1: expected proportion of deaths in first quarter of year

death_expected_prop_q2: expected proportion of deaths in second quarter of year

death_expected_prop_q3: expected proportion of deaths in third quarter of year

death_expected_prop_q4: expected proportion of deaths in fourth quarter of year

population_midyear: midyear population (July 1st)

population_source: source of the population count/exposure data

death_covid: number of deaths due to covid

death_covid_date: number of deaths due to covid as of

death_covid_nageraw: the number of age groups in the covid input data

ex_wpp_estimate: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year

ex_hmd_estimate: life expectancy estimates from the Human Mortality Database

nmx_hmd_estimate: death rate estimates from the Human Mortality Database

nmx_cntfc: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

source:

STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)

ONS for GB-EAW pre 2020

CDC for US pre 2020

STMF:

harmonized to single ages via pclm

pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110

smoothing parameters estimated via BIC grid search seperately for every pclm iteration

last age group set to [110,111)

ages 100:110+ are then summed into 100+ to be consistent with mid-year population information

deaths in unknown weeks are considered; deaths in unknown ages are not considered

ONS:

data already in single ages

ages 100:105+ are summed into 100+ to be consistent with mid-year population information

PCLM smoothing applied to for consistency reasons

CDC:

The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

source:

for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019

for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100

mid-year population

mid-year population translated into exposures:

if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates

if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

source: COVerAGE-DB (https://osf.io/mpwjq/)

the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

source:

World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019

Human Mortality Database (https://mortality.org/), single year and age tables

2880 Global import shipment records of Back After with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

657 Global export shipment records of Back Up Pads with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

WNA-FLEXPART-BackTraj-2018 is the 2018 Western North America Back Trajectory data using the FLEXible PARTicle (FLEXPART) dispersion model. Data collection for this product is complete.Backward simulations of airmass transport using a Lagrangian Particle Dispersion Model (LPDM) framework can establish source-receptor relationships (SRRs), supporting analysis of source contributions from various geospatial regions and atmospheric layers to downwind observations. In this study, we selected receptor locations to match gridded ozone observations over Western North America (WNA) from ozonesonde, lidar, commercial aircraft sampling, and aircraft campaigns (1994-2021). For each receptor, we used the FLEXible PARTicle (FLEXPART) dispersion model, driven by ERA5 reanalysis data, to achieve 15-day backwards SRR calculations, providing global simulations at high temporal (hourly) and spatial (1° x 1°) resolution, from the surface up to 20 km above ground level. This product retains detailed information for each receptor, including the gridded ozone value product, allowing the user to illustrate and identify source contributions to various subsets of ozone observations in the troposphere above WNA over nearly 3 decades at different vertical layers and temporal scales, such as diurnal, daily, seasonal, intra-annual, and decadal. This model product can also support source contribution analyses for other atmospheric components observed over WNA, if other co-located observations have been made at the spatial and temporal scales defined for some or all of the gridded ozone receptors used here.

A 2023 survey among cybersecurity leaders of worldwide organizations revealed that ** percent of organizations in Brazil paid the ransom and got data back. France ranked second by the share of organizations that restored the data by running backups, as ** percent reported doing so. However, the country also ranked first by the percentage of companies that paid the ransom but didn't get the data back.

WNA-FLEXPART-BackTraj-2020 is the 2020 Western North America Back Trajectory data using the FLEXible PARTicle (FLEXPART) dispersion model. Data collection for this product is complete.Backward simulations of airmass transport using a Lagrangian Particle Dispersion Model (LPDM) framework can establish source-receptor relationships (SRRs), supporting analysis of source contributions from various geospatial regions and atmospheric layers to downwind observations. In this study, we selected receptor locations to match gridded ozone observations over Western North America (WNA) from ozonesonde, lidar, commercial aircraft sampling, and aircraft campaigns (1994-2021). For each receptor, we used the FLEXible PARTicle (FLEXPART) dispersion model, driven by ERA5 reanalysis data, to achieve 15-day backwards SRR calculations, providing global simulations at high temporal (hourly) and spatial (1° x 1°) resolution, from the surface up to 20 km above ground level. This product retains detailed information for each receptor, including the gridded ozone value product, allowing the user to illustrate and identify source contributions to various subsets of ozone observations in the troposphere above WNA over nearly 3 decades at different vertical layers and temporal scales, such as diurnal, daily, seasonal, intra-annual, and decadal. This model product can also support source contribution analyses for other atmospheric components observed over WNA, if other co-located observations have been made at the spatial and temporal scales defined for some or all of the gridded ozone receptors used here.

WNA-FLEXPART-BackTraj-1999 is the 1999 Western North America Back Trajectory data using the FLEXible PARTicle (FLEXPART) dispersion model. Data collection for this product is complete.Backward simulations of airmass transport using a Lagrangian Particle Dispersion Model (LPDM) framework can establish source-receptor relationships (SRRs), supporting analysis of source contributions from various geospatial regions and atmospheric layers to downwind observations. In this study, we selected receptor locations to match gridded ozone observations over Western North America (WNA) from ozonesonde, lidar, commercial aircraft sampling, and aircraft campaigns (1994-2021). For each receptor, we used the FLEXible PARTicle (FLEXPART) dispersion model, driven by ERA5 reanalysis data, to achieve 15-day backwards SRR calculations, providing global simulations at high temporal (hourly) and spatial (1° x 1°) resolution, from the surface up to 20 km above ground level. This product retains detailed information for each receptor, including the gridded ozone value product, allowing the user to illustrate and identify source contributions to various subsets of ozone observations in the troposphere above WNA over nearly 3 decades at different vertical layers and temporal scales, such as diurnal, daily, seasonal, intra-annual, and decadal. This model product can also support source contribution analyses for other atmospheric components observed over WNA, if other co-located observations have been made at the spatial and temporal scales defined for some or all of the gridded ozone receptors used here.