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433 results for “Cost-effectiveness”

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zenodo40/100

Identifying cost-effective decarbonisation pathways for South Africa's power sector (EMP-A 2023) - Dataset

<p>Dataset of the project &quot;Identifying cost-effective decarbonisation pathways for South Africa&#39;s power sector (EMP-A&nbsp;2023)&quot;.</p>

opencc-by-4.0Apr 2023View details →
dryad40/100

Data and code from: Cost-effectiveness Analysis of Alternative Infant and Neonatal Rotavirus Vaccination Schedules in Malawi

Open the record for dataset details and reuse information.

publicJan 2025View details →
dryad40/100

Data from: A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus), and Panthera species, using targeted bisulfite sequencing and machine learning models

Open the record for dataset details and reuse information.

publicJan 2024View details →
dryad40/100

Data from: harnessing the power of regional baselines for broad-scale genetic stock identification: a multistage, integrated, and cost-effective approach

Open the record for dataset details and reuse information.

publicDec 2023View details →
zenodo36/100

An Empirical Analysis of Amazon EC2 Spot Instance Features Affecting Cost-effective Resource Procurement

<p>This repository contains code and data for the paper "An Empirical Analysis of Amazon EC2 Spot Instance Features Affecting Cost-effective Resource Procurement", by Cheng Wang, Qianlin Liang and Bhuvan Urgaonkar.</p>

opencc-by-4.0Jan 2017View details →
zenodo36/100

Performance Measurement Dataset of the HPC Benchmarks FASTEST, Kripke, and RELeARN for Cost-Effective Modeling Analysis with Extra-P

<p>Performance Measurement Dataset of the HPC Benchmarks FASTEST, Kripke, RELeARN for Scalability Studies with Extra-P. This data was used to analyze cost-effective modeling approaches presented in the IPDPS 2020 paper "Learning Cost-Effective Sampling Strategies for Empirical Performance Modeling".</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Self-synchronized cost-effective time-resolved measurements at x-ray free-electron lasers with femtosecond resolution

<p>In compliance with guidelines from SNSF (Swiss National Science Foundation), we upload the raw data that belongs to a publication we submitted to <em>Physical Review Research</em>.<br> The dataset also contains the analysis scripts used to produce the plots we show in the publication.</p> <p>Our software is attached to the dataset. An installation of the well known ELEGANT code is required to run it.</p> <p>Shortly after upload of the first version of this dataset, a bug was found in the analysis software.<br> The second version contains the corrected software.</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Evaluation Dataset: SemOI2 – Building Adaptive And Cost-Effective Recognition Applications With Semantic Augmentation

<p>Evaluation dataset for the paper &quot;SemOI2 &ndash; Building Adaptive And Cost-Effective Recognition Applications With Semantic Augmentation&quot;, presented at the AAAI-Make conference 2022, to be published in: <em>A. Martin, K. Hinkelmann, H.-G. Fill, A. Gerber, D. Lenat, R. Stolle, F. van Harmelen (Eds.), Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022), Stanford University, Palo Alto, California, USA, March 21&ndash;23, 2022.</em></p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Dataset for Cost-effective Simulation-based Test Selection in Self-driving Cars Software with SDC-Scissor

<p><strong>SDC-Scissor tool for Cost-effective Simulation-based Test Selection in Self-driving Cars Software</strong></p> <p>This dataset provides test cases for self-driving cars with the BeamNG simulator. Check out the repository and demo video to get started.</p> <p><strong>GitHub:</strong>&nbsp;<a href="https://github.com/ChristianBirchler/sdc-scissor">github.com/ChristianBirchler/sdc-scissor</a></p> <p>This project extends the tool competition platform from the&nbsp;<a href="https://github.com/se2p/tool-competition-av">Cyber-Phisical Systems Testing Competition</a>&nbsp;which was part of the&nbsp;<a href="https://sbst21.github.io/">SBST Workshop in 2021</a>.</p> <p><strong>Usage</strong></p> <p><strong>Demo</strong></p> <p>&nbsp;<a href="https://youtu.be/Cn8p648KnfQ">YouTube Link</a></p> <p><strong>Installation</strong></p> <p>The tool can either be run with&nbsp;<a href="https://docs.docker.com/get-docker/">Docker</a>&nbsp;or locally using&nbsp;<a href="https://python-poetry.org/docs/">Poetry</a>.</p> <p>When running the simulations a working installation of&nbsp;<a href="https://beamng.gmbh/research/">BeamNG.research</a>&nbsp;is required. Additionally, this simulation cannot be run in a Docker container but must run locally.</p> <p>To install the application use one of the following approaches:</p> <ul> <li>Docker:&nbsp;<code>docker build --tag sdc-scissor .</code></li> <li>Poetry:&nbsp;<code>poetry install</code></li> </ul> <p><strong>Using the Tool</strong></p> <p>The tool can be used with the following two commands:</p> <ul> <li>Docker:&nbsp;<code>docker run --volume &quot;$(pwd)/results:/out&quot; --rm sdc-scissor [COMMAND] [OPTIONS]</code>&nbsp;(this will write all files written to&nbsp;<code>/out</code>&nbsp;to the local folder&nbsp;<code>results</code>)</li> <li>Poetry:&nbsp;<code>poetry run python sdc-scissor.py [COMMAND] [OPTIONS]</code></li> </ul> <p>There are multiple commands to use. For simplifying the documentation only the command and their options are described.</p> <ul> <li>Generation of tests: <ul> <li><code>generate-tests --out-path /path/to/store/tests</code></li> </ul> </li> <li>Automated labeling of Tests: <ul> <li><code>label-tests --road-scenarios /path/to/tests --result-folder /path/to/store/labeled/tests</code></li> <li><em>Note:</em>&nbsp;This only works locally with BeamNG.research installed</li> </ul> </li> <li>Model evaluation: <ul> <li><code>evaluate-models --dataset /path/to/train/set --save</code></li> </ul> </li> <li>Split train and test data: <ul> <li><code>split-train-test-data --scenarios /path/to/scenarios --train-dir /path/for/train/data --test-dir /path/for/test/data --train-ratio 0.8</code></li> </ul> </li> <li>Test outcome prediction: <ul> <li><code>predict-tests --scenarios /path/to/scenarios --classifier /path/to/model.joblib</code></li> </ul> </li> <li>Evaluation based on random strategy: <ul> <li><code>evaluate --scenarios /path/to/test/scenarios --classifier /path/to/model.joblib</code></li> </ul> </li> </ul> <p>The possible parameters are always documented with&nbsp;<code>--help</code>.</p> <p><strong>Linting</strong></p> <p>The tool is verified the linters&nbsp;<a href="https://flake8.pycqa.org/en/latest/">flake8</a>&nbsp;and&nbsp;<a href="https://pylint.org/">pylint</a>. These are automatically enabled in&nbsp;<a href="https://code.visualstudio.com/">Visual Studio Code</a>&nbsp;and can be run manually with the following commands:</p> <pre>poetry run flake8 . poetry run pylint **/*.py</pre> <p><strong>License</strong></p> <p>The software we developed is distributed under GNU GPL license. See the&nbsp;<a href="https://github.com/ChristianBirchler/sdc-scissor/blob/main/LICENSE.md">LICENSE.md</a>&nbsp;file.</p> <p><strong>Contacts</strong></p> <p>Christian Birchler - Zurich University of Applied Science (ZHAW), Switzerland -&nbsp;<a href="mailto:birc@zhaw.ch">birc@zhaw.ch</a></p> <p>Nicolas Ganz - Zurich University of Applied Science (ZHAW), Switzerland -&nbsp;<a href="mailto:gann@zhaw.ch">gann@zhaw.ch</a></p> <p>Sajad Khatiri - Zurich University of Applied Science (ZHAW), Switzerland -&nbsp;<a href="mailto:mazr@zhaw.ch">mazr@zhaw.ch</a></p> <p>Dr. Alessio Gambi - Passau University, Germany -&nbsp;<a href="mailto:alessio.gambi@uni-passau.de">alessio.gambi@uni-passau.de</a></p> <p>Dr. Sebastiano Panichella - Zurich University of Applied Science (ZHAW), Switzerland -&nbsp;<a href="mailto:panc@zhaw.ch">panc@zhaw.ch</a></p> <p><strong>References</strong></p> <ul> <li>Christian Birchler, Nicolas Ganz, Sajad Khatiri, Alessio Gambi, and Sebastiano Panichella. 2022. Cost-effective Simulation-based Test Selection in Self-driving Cars Software with SDC-Scissor. In 2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER), IEEE.</li> </ul> <p><strong>If you use this tool in your research, please cite the following papers:</strong></p> <pre><code>@INPROCEEDINGS{Birchler2022, author={Birchler, Christian and Ganz, Nicolas and Khatiri, Sajad and Gambi, Alessio, and Panichella, Sebastiano}, booktitle={2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER), title={Cost-effective Simulationbased Test Selection in Self-driving Cars Software with SDC-Scissor}, year={2022}, }</code></pre>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Development of Cost-Effective High-Modulus Asphalt 5. Report Date Aug. 2021 Concrete (HMAC) Mixtures Using Crumb Rubber and Local Construction Materials in Louisiana

<p>One of the emerging solutions to enhance the durability of asphalt pavements is the use of a French asphalt mix<br> known as &ldquo;High-Modulus Asphalt Concrete (HMAC).&rdquo; This mix uses a hard asphalt binder, high binder content<br> (about 6%), and low air voids content as compared to Superpave mixtures. The key objective of this study was<br> to develop a cost-effective HMAC mixture using crumb rubber and local materials in Louisiana. To achieve this<br> objective, four HMAC mixtures were prepared using two asphalt binders (PG 82-22 and PG 76-22 plus 10%<br> crumb rubber) and two Reclaimed Asphalt Pavement (RAP) contents (20% and 40%); additionally, a<br> conventional Superpave mixture in Louisiana was prepared as a control mixture. The laboratory performance<br> of these five mixtures was evaluated in terms of workability, dynamic modulus, rutting resistance, and cracking<br> resistance. The AASHTOWare Pavement ME Design software was also used to estimate the long-term field<br> performance of these mixtures. Results indicated that the HMAC mixture prepared with 10% crumb rubber and<br> 20% RAP successfully met the French mix design specifications for HMAC and LaDOTD specifications. This<br> HMAC mix outperformed the control Superpave mix in terms of dynamic modulus, rutting resistance, and<br> cracking resistance. Additionally, this HMAC mixture can reduce the required asphalt thickness by 1.5 or 2<br> inches based on traffic level. The cost-effectiveness analysis indicated that this HMAC mixture was more costeffective<br> than conventional Superpave mixtures in Louisiana. In addition, this mixture is environmentallyfriendly<br> since it can reduce the disposal of scrap tires in landfills.</p>

opencc-by-4.0Jul 2021View details →
zenodo36/100

Fig. 2 in It is recreational but profitability also matters: A cost-effective economic approach to marine recreational fishing in Spain Abstract

Fig. 2: Summary diagram of the cost-effectiveness indicator calculation process.

opencc-by-4.0Dec 2022View details →
zenodo36/100

Code and data for "Comparing cost-effectiveness of radio and drone telemetry with playback surveys for assessing translocation outcomes"

<p><strong>Overview</strong></p> <p>Code and data used for the analyses of Stone et al., 2024 "Comparing cost-effectiveness of radio and drone telemetry with playback surveys for assessing translocation outcomes". Forthcoming in Journal of Applied Ecology</p> <p><strong>Abstract</strong></p> <p>1. Post-release monitoring is critical for assessing translocation outcomes. Yet the quality of information gained from monitoring can vary greatly, and perceived monitoring costs often results in reduced monitoring effort. &nbsp;Selecting cost-effective monitoring strategies that provide high quality data is therefore important for assessing translocation outcomes and making informed management decisions.&nbsp;<br>2. To compare how monitoring strategy affects information gained, we monitored a toutouwai/North Island robin (Petroica longipes) reintroduction in Aotearoa New Zealand, based on monitoring objectives of determining survival, site fidelity and whether the extent of management was large enough to protect dispersing individuals. We compared how these objectives were met through four monitoring strategies: 1) comprehensive surveys with ground radio telemetry and playback; 2) aerial drone telemetry; 3) dedicated playback by trained surveyors and 4) opportunistic playback by predator control contractors. We undertook a viewshed analysis to determine search coverage of each strategy and compared detection rates, efficiency, and cost.&nbsp;<br>3. Comprehensive ground telemetry and playback, while costly, covered the largest area and provided the most accurate data on dispersal, survival and the translocation outcome. &nbsp;In comparison, opportunistic playback monitoring detected substantially fewer individuals, giving a false impression of low site fidelity and survival and a failed translocation. Although drone telemetry had considerable site-specific limitations, which limited its effectiveness during our study, it was the most cost-effective with a high detection rate and low search effort.&nbsp;<br>4. Synthesis and applications: Our study shows the value of intensive monitoring in facilitating management decisions for wildlife translocations. Comprehensive telemetry and playback, while costly, were invaluable for gaining high quality information on the translocation outcome. Without suitable monitoring, reintroduction outcomes can be difficult to assess and potentially result in unnecessary, ineffective, or overly expensive management actions. We recommend that monitoring intensity and methodology should reflect the site, species and level of uncertainty regarding the translocation outcome. Prioritising monitoring can help reduce long-term costs, increase quality of information gained and allow for more informed management decisions that can improve subsequent translocation outcomes.</p>

opencc-by-4.0Jul 2024View details →
zenodo36/100

Data from: A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration

<p>This is a complete dataset for achieving results of the manuscript &quot;<strong>A landscape approach for optimizing the cost-effectiveness of large-scale forest restoration</strong>&quot;.&nbsp;</p> <p>&nbsp;</p> <p><strong>Abstract: </strong></p> <ol> <li>Achieving global targets for forest restoration will require cost-effective strategies to return agricultural land to forest, while minimizing implementation costs and negative outcomes for agricultural production.</li> <li>We present a landscape approach for optimizing the cost-effectiveness of large-scale forest restoration. Across three different landscapes within Brazil&#39;s Atlantic Forest biodiversity hotspot, we modelled landscape scenarios based on spatially-explicit data on the probability of natural regeneration, restoration costs, land opportunity costs, and forest restoration outcomes for increasing carbon stocking and landscape connectivity<em>.</em> We compare benefits of our cost-reduction approach to the legally mandated riparian restoration and randomly distributed approaches.</li> <li>Compared with riparian prioritization and considering both implementation and opportunity costs, our cost-reduction scenario produced the greatest savings (20.9%) in mechanized agricultural landscapes.</li> <li>When only considering implementation costs, our cost-reduction scenario led to the highest savings (38.4%) in the landscape with highest forest cover where natural regeneration potential is highest and enables cost-effective carbon stocking and connectivity.</li> </ol> <p><em>Synthesis and applications.</em> We present a guide for forest restoration planning that maximizes specific outcomes with minimal costs and reduction of agricultural production. Furthermore, we show how policies could encourage prioritization of low-cost restoration via natural regeneration, increasing cost-effectiveness. While our study focuses on Brazil&rsquo;s Atlantic Forest, the approach can be parameterized for other regions.</p> <p><strong>Resumo:</strong></p> <ol> <li>Atingir metas globais para a restaura&ccedil;&atilde;o florestal exigir&aacute; estrat&eacute;gias economicamente vi&aacute;veis para transformar terras agr&iacute;colas em floresta, minimizando custos de implementa&ccedil;&atilde;o e os resultados negativos para a produ&ccedil;&atilde;o agr&iacute;cola.</li> <li>Apresentamos uma abordagem de paisagem para otimizar a rela&ccedil;&atilde;o custo-efic&aacute;cia da restaura&ccedil;&atilde;o florestal em larga escala. Em tr&ecirc;s diferentes paisagens, no Bioma da Mata Atl&acirc;ntica, modelamos cen&aacute;rios baseados em dados espacialmente expl&iacute;citos sobre a probabilidade de regenera&ccedil;&atilde;o natural, custos de restaura&ccedil;&atilde;o, custos de oportunidade da terra e resultados de restaura&ccedil;&atilde;o florestal com o objetivo de aumentar o estoque de carbono e a conectividade da paisagem. Por fim, comparamos os benef&iacute;cios da nossa abordagem de redu&ccedil;&atilde;o de custos com a tradicional abordagem de restaura&ccedil;&atilde;o da paisagem em zonas rip&aacute;rias (&aacute;reas de preserva&ccedil;&atilde;o permanente) e abordagens de espacialidade aleatoriamente distribu&iacute;das.</li> <li>Comparado com a prioriza&ccedil;&atilde;o rip&aacute;ria e considerando os custos de implementa&ccedil;&atilde;o e de oportunidade, nosso cen&aacute;rio de redu&ccedil;&atilde;o de custos produziu as maiores economias (20,9%) em paisagens agr&iacute;colas mecanizadas.</li> <li>Ao considerar apenas os custos de implementa&ccedil;&atilde;o, nosso cen&aacute;rio de redu&ccedil;&atilde;o de custos levou &agrave; maior economia (38,4%) na paisagem com maior cobertura florestal, onde o potencial de regenera&ccedil;&atilde;o natural &eacute; maior e permite uma melhor rela&ccedil;&atilde;o de custo-oportunidade no estoque de carbono e na conectividade da paisagem.</li> </ol> <p><em>S&iacute;ntese e aplica&ccedil;&otilde;es.</em> Apresentamos aqui um guia para o planejamento de restaura&ccedil;&atilde;o florestal que maximiza resultados espec&iacute;ficos com redu&ccedil;&atilde;o de custos e m&iacute;nima influ&ecirc;ncia na produ&ccedil;&atilde;o agr&iacute;cola. Al&eacute;m disso, mostramos como pol&iacute;ticas p&uacute;blicas poderiam incentivar a prioriza&ccedil;&atilde;o da restaura&ccedil;&atilde;o de baixo custo via regenera&ccedil;&atilde;o natural, aumentando a rela&ccedil;&atilde;o custo-benef&iacute;cio. Enquanto nosso estudo se concentra na Mata Atl&acirc;ntica do Brasil, a abordagem pode ser parametrizada para outras regi&otilde;es.</p>

opencc-by-nc-nd-4.0May 2018View details →
zenodo36/100

Evaluation of the Performance and Cost-Effectiveness of Engineered Cementitious Composites (ECC) Produced from Region 6 Local Materials

<p>Corresponding data set for Tran-SET Project No. 17CLSU05. Abstract of the final report is stated below for reference:</p> <p>&quot;The project objective is to develop cost-effective Engineered Cementitious Composites (ECC) with locally available ingredients in Region 6 to address the deficiencies observed in ordinary concrete materials. The study explored the utilization of two types of river sands (coarse and fine), two types of PVA fibers (long and short), four levels of cement replacement with Class F fly ash, and the implementation of recycled crumb rubber in the performance of ECC materials. A total of 24 mix designs were prepared and evaluated in compression, tension, and bending to assess its mechanical properties. Furthermore, the cracking characteristics of the materials produced were evaluated to assess the durability potential of these composites. Lastly, the cost of each mix design and the feasibility of ECC implementation in transportation infrastructure were assessed. The experimental results showed that implementing crumb rubber and/or increasing contents of fly ash in the mixtures produced a positive impact in the ductility of the materials. However, a tradeoff between ductility and strength was observed. Furthermore, the utilization of the different types of sand evaluated in this study produced minor effects in the mechanical properties of ECCs evaluated. The properties of the materials developed in this study were exceedingly superior than that of regular concrete. It was concluded that ECC materials are promising for the future of transportation infrastructure.&quot;</p>

opencc-by-4.0Nov 2018View details →
zenodo36/100

Phytoplankton Dataset: Supporting HAB monitoring based on cost-effective open-hardware solutions

<p>ASTRAL Phytoplankton monitoring dataset which has supported technology validation based on images from single-specie phytoplankton sample and prototype deployment within IMTA labs</p>

opencc-by-4.0Sep 2024View details →
zenodo36/100

Microplastic Dataset: Supporting microplastic monitoring based on cost-effective open-hardware solutions

<p>ASTRAL Dataset related to microplastic monitoring based on the open-hardware initiative PlanktoScope</p>

opencc-by-4.0Sep 2024View details →
zenodo36/100

Data and codes for "The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"

<p>Data and codes for the manuscript entitled:</p> <p>"<strong>The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"</strong></p> <p>&nbsp;</p> <p><strong>Please see Readme.txt for details</strong></p>

opencc-by-4.0Sep 2024View details →
zenodo36/100

Simulation results for "COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness"

<p>The high-performance computing results for raw epidemiological simulations and quantiled scenarios associated with https://doi.org/10.1101/2021.02.24.21252338.</p> <p>All results stored as compressed rds files of data.table objects (use-able as data.frame objects)&nbsp;for use with R programming language.</p>

opencc-by-4.0Jul 2021View details →
zenodo36/100

Data and Results for: Cost-effective, high-throughput fruit phenotyping system for three-dimensional reconstruction of fruit form

<p>The dataset contains the raw data used for generating the results in the paper, and the reconstructed results at 1mm and 2mm voxel resolution.</p> <p><strong>Raw data</strong>: Samples are gathered into groups of five, DataObjects1-5.zip, ... , DataObjects56-59.zip.</p> <p>Once uncompressed, each directory holds the images and configuration information used for each sample. For instance, &#39;1_obj&#39; is for the first sample, and the &#39;data&#39; folder has the image files by camera.&nbsp; In this case one camera was used, &#39;cam2&#39;, and there are 62 images.&nbsp; &#39;pattern_square_mm_external.txt&#39;, &#39;pattern_square_mm_internal.txt&#39;, and &#39;rotate_specification_file.txt&#39; are all configuration files needed for the calibration step.</p> <p>&nbsp;</p> <p><strong>Results</strong>: Reconstructions results are in compressed folders &#39;reconstruction-results-1mm.zip&#39; and &#39;reconstruction-results-2mm.zip&#39; for 1 mm and 2 mm voxel resolutions, respectively.&nbsp; These results are three-dimensional model files than can be viewed with a variety of software, we have used the free MeshLab: https://www.meshlab.net/ .</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2021View details →
dryad36/100

Data from: Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): a randomized trial and cost-effectiveness analysis

<p>Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD). Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD).</p> <p>In this open, three-arm randomised trial, adults (≥18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard-of-care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically-confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention to treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15/11/2018-27/11/2019, 8236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV-screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5-38), 6 (1-22) and 1 (0-3) days (hazard ratio for HIV-TB vs. SOC: 2.86, 1.04-7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p=0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically-confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV-screening arm (risk ratio [RR]: 0.18, 0.04-0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01-0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1200/quality-adjusted life-year (QALY) threshold were 83.9% and 0%. Main limitations were the lower than anticipated prevalence of tuberculosis and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon.</p> <p>DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment.</p>

opencc-zeroAug 2021View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record