Find research datasets worth reusing

opencc-by-4.0Mar 2022View details →

Raw Data for the article: Efficacy of Three Commercial Disinfectants in Reducing Microbial Surfaces' Contaminations of Pharmaceuticals Hospital Facilities

To evaluate and validate the efficacy of disinfectants used in our cleaning procedure, in order to reduce pharmaceutical hospital surfaces' contaminations, we tested the action of three commercial disinfectants on small representative samples of the surfaces present in our hospital cleanrooms. These samples (or coupons) were contaminated with selected microorganisms for the validation of the disinfectants. The coupons were sampled before and after disinfection and the microbial load was assessed to calculate the Log10 reduction index. Subsequently, we developed and validated a disinfection procedure on real surfaces inside the cleanrooms intentionally contaminated with microorganisms, using approximately 107-108 total colony forming units per coupon. Our results showed a bactericidal, fungicidal, and sporicidal efficacy coherent to the acceptance criteria suggested by United States Pharmacopeia 35 <1072>. The correct implementation of our cleaning and disinfection procedure, respecting stipulated concentrations and contact times, led to a reduction of at least 6 Log10 for all microorganisms used. The proposed disinfection procedure reduced the pharmaceutical hospital surfaces' contaminations, limited the propagation of microorganisms in points adjacent to the disinfected area, and ensured high disinfection and safety levels for operators, patients, and treated surfaces.

opencc-zeroJul 2022View details →

Availability and functionality of neontal care units in health facilities

Background Evidence shows that delivery of prompt and appropriate in-patient newborn care (IPNC) through health facility (HF)-based neonatal care and stabilization units (NCU/NSUs) reduce preventable newborn mortalities (NMs). This study investigated the HFs for the availability and performance of NCU/NSUs in providing quality IPNC, as well as an investigation of influencing factors in Mtwara region, Tanzania. Results About 70.6% (12/17) of surveyed HFs had at least one NCU/NSU room dedicated for delivery of IPNC, and 74.7% (3,600/4,819) of needy newborns were admitted/transferred in for management. Essential medicines such as tetracycline eye ointment was unavailable in 75% (3/4) of the district hospitals (DHs). A disparity existed between the availability and functioning of equipment including infant radiant warmers (92% vs 73%). Governance, support from implementing patterns (IPs), and access to healthcare commodities were identified from qualitative inquiries as factors influencing the establishment and running of NCUs/NSUs at the HFs in Mtwara region, Tanzania. Conclusion Despite the positive progress, the establishment and performance of NCUs/NSUs in providing quality IPNC in HFs in Mtwara has lagged behind the Tanzania neonatal care guideline standards, particularly after the IPs of newborn health interventions completed their terms in 2016. This study suggests additional improvement plans for Mtwara region and other comparable settings to optimize the provision of quality IPNC and lower avoidable NMs.

opencc-by-4.0Aug 2022View details →

Dataset - Performance of a compost aeration and heat recovery system at a commercial composting facility

Dataset for "Performance of a compost aeration and heat recovery system at a commercial composting facility"

opencc-by-4.0Sep 2022View details →

Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.

Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees  among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.

opencc-by-4.0Oct 2022View details →

Available Wireless Sensor Network and Internet of Things testbed facilities: dataset

In this data set, we present data collected for the purpose of carrying out a systematic review of the available Wireless Sensor Network and Internet of Things testbed facilities. The data was collected through multiple stages and in each stage the pre-defined criteria were applied. We provide a dataset describing the hardware and software aspects of Wireless Sensor Network and Internet of Things testbed facilities available in the market and scientific community. The data were gathered through an extensive systematic review process of scientific articles published between the years 2011 and 2021. The review aims to obtain good quality data for people who are actively researching the Internet of Things facilities or anyone who is interested in that field.

Radiographic data of a wooden block with metal markers at the J. Paul Getty Museum X-ray facility

Summary This submission contains radiographic data containing metal markers of a small wooden block.   The data is made available as part of [Bossema et al., 2024].   Apparatus The dataset is acquired using the X-ray facility located at the J. Paul Getty Museum, Los Angeles. Full details can be found in [Bossema et al., 2024].   List of Contents The content of the submission is given below. All raw data (i.e. no corrections) is made available in .tif format. The folder contains: <ul> <li>darks: folder containing darkfield images, IMG*.dicom</li> <li>flats: folder containing flatfield images, IMG*.dicom</li> <li>data1: raw (unprocessed or uncorrected) projection data, IMG*.dicom</li> <li>data2: raw (unprocessed or uncorrected) projection data, IMG*.dicom</li> </ul>   Additional Links Accompanying code can be found here.   Contact Details For more information or guidance in using these datasets, please get in touch with  <ul> <li>bossema [at] cwi.nl</li> </ul> References <a href="https://www.nature.com/articles/s41467-024-48102-w">Bossema, F.G., Palenstijn, W.J., Heginbotham, A. et al. Enabling 3D CT-scanning of cultural heritage objects using only in-house 2D X-ray equipment in museums. Nat Commun 15, 3939 (2024). https://doi.org/10.1038/s41467-024-48102-w</a>

Radiographic data of a wooden block with metal markers at the Rijksmuseum X-ray facility

Summary This submission contains radiographic data containing metal markers of a small wooden block.   The data is made available as part of [Bossema et al., 2024].   Apparatus The dataset is acquired using the X-ray facility located at the Rijksmuseum, Amsterdam. Full details can be found in [Bossema et al., 2024].   List of Contents The content of the submission is given below. All raw data (i.e. no corrections) is made available in .tif format. The folder contains: <ul> <li>darks_flats: folder containing darkfield and flatfield images, frame*.tif</li> <li>data: raw (unprocessed or uncorrected) projection data, frame*.tif</li> </ul>   Additional Links These datasets are produced by the <a>Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). Accompanying code can be found here.   Contact Details For more information or guidance in using these datasets, please get in touch with  <ul> <li>bossema [at] cwi.nl</li> </ul> References <a href="https://www.nature.com/articles/s41467-024-48102-w">Bossema, F.G., Palenstijn, W.J., Heginbotham, A. et al. Enabling 3D CT-scanning of cultural heritage objects using only in-house 2D X-ray equipment in museums. Nat Commun 15, 3939 (2024). https://doi.org/10.1038/s41467-024-48102-w</a>

opencc-zeroMay 2024View details →

Research data on health facility-level factors that contribute to delayed diagnosis of cervical cancer

In Kenya, cervical cancer is the 2nd commonly diagnosed type of cancer and the top cause of cancer-related deaths among women. Globally, over 50% of cervical cancer diagnoses are made late, with this proportion rising to 80% in developing countries. Poor Health systems can cause delays in diagnosis, thus, this study focused on determining the health facility-level factors that contribute to delayed diagnosis among cervical cancer patients at the Kenyatta National Hospital (KNH). An analytical cross-sectional mixed method study was adopted to collect data on hospital and referral experiences from 139 cervical cancer patients systematically sampled at KNH, using a semi-structured questionnaire. Associations between the stage at diagnosis and hospital and referral experiences were tested using a logistic regression model at 95% Confidence Interval. 86 (61.9%) were diagnosed at advanced stages III and IV. The potential predictors for delayed diagnosis were; More number of hospital referral times (p-value=0.000), Facing referral challenges (p-value=0.041), Longer time taken for diagnosis appointment (p-value=0.059), and Longer time taken for diagnostic results (p-value=0.007) in the bivariate analysis. More number of hospital referral times (p-value=0.001) and longer time taken for diagnostic results (p-value=0.025), were significantly associated with delayed diagnosis of cervical cancer in the multivariate logistic regression test model. Referral challenges included misdiagnosis, cost of diagnosis, and prolonged diagnosis appointments. The study concluded that the cause of delays in diagnosis for most patients is due to poor health and referral systems and inadequate medical personnel and diagnosis equipment. This study recommends improving referral systems and encouraging partnerships to decentralize diagnostic centers and equipment and train more expertise on cervical cancer.

opencc-zeroJun 2024View details →

Financial, supplies, and human resource preparedness in management of COVID-19 pandemic among dental facilities in Nairobi County, Kenya

The COVID-19 pandemic put a strain on healthcare facilities across the globe. Dental facilities pose the highest COVID-19 transmission risk categories due to the aerosol-generating procedures involved in dental practice. This study aimed to determine financial, supplies, and human resource preparedness in managing the COVID-19 pandemic among Nairobi County, Kenya dental facilities. A cross-sectional study was conducted using a mixed-methods approach among 183 dental facilities in Nairobi County. Data was collected using a KoboCollect questionnaire and analyzed using MS Excel and SPSS version 26. Dental facilities' readiness was assessed using the ReadyScore Criteria. Qualitative data was collected through one-on-one interviews with key informants and analyzed thematically. Readyscore Criteria analysis showed that 39 (21.3%) of the evaluated dental facilities were considered "ready," while 133 (72.7%) and 11 (6%) were considered to have "work to do" and "not ready" for the pandemic. Bivariate analysis showed that the level of facility (p<0.001), presence of other departments (p<0.001), funds sufficiency for COVID-19 emergency response (p=0.001), and clients attended per month (p=0.017) were statistically significant factors associated with pandemic preparedness scores. Regression analysis revealed that the presence of other departments among the dental facilities was a significant predictor of readiness, with a 4.5 times higher likelihood of being ready for a pandemic (aOR 4.591; 1.471–14.327, p=0.009) compared to other facilities. Support from healthcare authorities and capacity-building initiatives are recommended to enhance preparedness and resilience among dental facilities in the face of the COVID-19 pandemic.

opencc-zeroJul 2024View details →

Data for: Facile Preparation of Tunable Polyborosiloxane Networks via Hydrosilylation

Polyborosiloxanes are used in a variety of fields due to their unique and useful dynamic properties. Traditionally, crosslinked polyborosiloxanes are prepared by incorporating boric acid into siloxane pre-polymers, a process that is time consuming, energy intensive, and challenging due to the immiscibility of the reagents. Here, we report a versatile synthetic method to rapidly cure polyborosiloxane networks via hydrosilylation of chain-end or backbone functionalized polydimethylsiloxane (PDMS) derivatives with an inexpensive trivinylboronate. Networks synthesized from these readily available building blocks cure in ~2 minutes at convenient temperatures (e.g., 90 °C) and exhibit enhanced viscoelastic behavior when compared to traditional polyborosiloxane networks fabricated via the conventional condensation route. By virtue of using efficient hydrosilylation chemistry, another key advantage of this synthetic platform is the ability to synthesize dynamic polyborosiloxanes with different network connectivity by simply using silicones with Si–H moieties placed at the chain ends (telechelic) or distributed throughout the repeat-unit structure (copolymers). The availability of other alkenes amenable to hydrosilylation provides an additional formulation handle to synthesize mixed dynamic–static networks with tunable control over stress relaxation and solvent resistance. In summary, the synthetic approach disclosed herein is a simple and accessible platform for preparing dynamic polyborosiloxanes with tunable material properties.

opencc-by-4.0Jan 2019View details →

How does the proximity to restaurants and sports facilities influence the Body Mass Index in Geneva?

Sport facilities and restaurants of the canton of Geneva, located by means of adresses, are published. They were obtained from the Geographic Information System of Geneva (Système d'Information du Territoire à Genève, SITG). The BMI dataset is strictly confidential and could not be published.

opencc-by-4.0Nov 2018View details →

Facility ownership and mortality among older adults residing in care homes

Dataset, STATA do-file, and R script to replicate the findings of the following article: Damián J, Pastor-Barriuso R, García-López FJ, Ruigómez A, Martínez-Martín P, de Pedro-Cuesta J. Facility ownership and mortality among older adults residing in care homes. PLoS One 2019

opencc-by-4.0Jun 2019View details →

Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"

# README These files contain r data objects and R files that represent the key details of the paper, "Evaluating health facility access using Bayesian spatial models and location analysis methods". The following datasources are available for simulation of some of the ideas in the paper. - dat_grid_sim: simulated data of the grid and grid cells - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data - dat_ohca_sim: simulated OHCA event data - dat_aed_sim: simulated AED location data - dat_bldg_sim: simulated building location data - dat_municipality_sim: simulated municipality information - table_1: Table 1 information containing key demographic data These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R In terms of the paper itself, the functions and code used in the manuscript are located in: * 01_tidy.Rmd - analysis code used to tidy up the data * 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs * 02_model.Rmd - analysis code used to fit the model in INLA * 03_manuscript.Rmd - Full code and text used to create the paper * 04_supp_materials.Rmd - full code and text used to create the supplementary materials The following files are a part of an R package "swatial" that was developed along with the paper. These files are: * DESCRIPTION * NAMESPACE * LICENSE * LICENSE.md * decay.R * spherical-distance.R * test-figure-data-matches.R * test-table-data-matches.R * testthat.R * tidy-inla.R * tidy-posterior-coefs.R * tidy-predictions.R * utils-pipe.R * All files that end in .Rd are documentation files for the functions. ## Regarding data sources Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: "swiss_census_popn_2010_2015.xlsx". These data are put into analysis ready format in the file “01_tidy.Rmd” Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&bgLayer=ch.swisstopo.pixelkarte-grau&lang=en&topic=ech&layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&E=2717616.28&N=1096597.25&catalogNodes=687,696&layers_timestamp=,,2016,2016,,&layers_visibility=true,false,false,false,false,false&layers_opacity=1,1,1,1,1,0.75 For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1 Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&tema=33&id2=61&id3=65&c1=01&c2=02&c3=02 ## Future work In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Oulu facility

This data set covers core network and end-to-end measurements at the Oulu facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Malaga facility

This data set covers core network and end-to-end measurements at the Malaga facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Berlin facility

This data set covers core network and end-to-end measurements at the Berlin facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Athens facility

This data set covers core network and end-to-end measurements at the Athens facility, part of the 6G-SANDBOX infrastructure.

opencc-by-4.0May 2019View details →

Table 1 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations

Table 1. Mean and median life expectancies (in years, with 95% confidence intervals) for bottlenose dolphins in zoological care as calculated by Kaplan-Meier analyses.<table><tbody><tr><th>Time period</th><th>Median LE (CI)</th><th>Mean LE (CI)</th></tr></tbody><tbody><tr><th>1974–1982</th><td>9.0 (5.9–11.4)</td><td>10.6 (8.8–12.5)</td></tr><tr><th>1983–1992</th><td>15.3 (12.5–17.1)</td><td>17.3 (15.2–19.4)</td></tr><tr><th>1993–2002</th><td>18.2 (14.1–20.3)</td><td>20.3 (18.0–22.5)</td></tr><tr><th>2003–2012</th><td>29.2 (25.0–32.9)</td><td>28.2 (25.3–31.0)</td></tr></tbody></table>

opencc-zeroAug 2021View details →

Temporal and regional trends of antibiotic use in long-term aged care facilities across 39 countries, 1985-2019: systematic review and meta-analysis

Background Antibiotic misuse is a key contributor to antimicrobial resistance and a concern in long-term aged care facilities (LTCFs). Our objectives were to: i) summarise key indicators of systemic antibiotic use and appropriateness of use, and ii) examine temporal and regional variations in antibiotic use, in LTCFs (PROSPERO registration CRD42018107125). Methods & Findings Medline and EMBASE were searched for studies published between 1990-2021 reporting antibiotic use rates in LTCFs. Random effects meta-analysis provided pooled estimates of antibiotic use rates (percentage of residents on an antibiotic on a single day [point prevalence] and over 12 months [period prevalence]; percentage of appropriate prescriptions). Meta-regression examined associations between antibiotic use, year of measurement and region. A total of 90 articles representing 78 studies from 39 countries with data between 1985-2019 were included. Pooled estimates of point prevalence and 12-month period prevalence were 5.2% (95% CI: 3.3-7.9; n=523,171) and 62.0% (95% CI: 54.0-69.3; n=946,127), respectively. Point prevalence varied significantly between regions (Q=224.1, df=7, p<0.001), and ranged from 2.4% (95% CI: 1.7-2.7) in Eastern Europe to 9.0% in the British Isles (95% CI: 7.6-10.5) and Northern Europe (95% CI: 7.7-10.5). Twelve-month period prevalence varied significantly between region (Q=15.1, df-3, p=0.002) and ranged from 53.9% (95% CI: 48.3-59.4) in the British Isles to 68.3% (95% CI: 63.6-72.7) in Australia. Meta-regression found no association between year of measurement and antibiotic use prevalence. The pooled estimate of the percentage of appropriate antibiotic prescriptions was 28.5% (95% CI: 10.3-58.0; n=17,245) as assessed by the McGeer criteria. Year of measurement was associated with decreasing appropriateness of antibiotic use over time (OR: 0.78, 95% CI: 0.67-0.91). The most frequently used antibiotic classes were penicillins (n=44 studies), cephalosporins (n=36), sulphonamides/trimethoprim (n=31), and quinolones (n=28). Conclusions Coordinated efforts focusing on LTCFs are required to address antibiotic misuse in LTCFs. Our analysis provides overall baseline and regional estimates for future monitoring of antibiotic use in LTCFs.