100+ datasets found
  1. f

    Descriptive statistics for those providing self-report data and those...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Oct 19, 2017
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    Webb, Thomas L.; Rowse, Georgina; Scott, Alexander J. (2017). Descriptive statistics for those providing self-report data and those providing objective sleep data. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001796611
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    Dataset updated
    Oct 19, 2017
    Authors
    Webb, Thomas L.; Rowse, Georgina; Scott, Alexander J.
    Description

    Descriptive statistics for those providing self-report data and those providing objective sleep data.

  2. objective-quest-2025

    • kaggle.com
    zip
    Updated Sep 6, 2025
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    Muhammad Naufal Muzaki (2025). objective-quest-2025 [Dataset]. https://www.kaggle.com/datasets/muhammadnaufalmuzaki/objective-quest-2025
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    zip(342889420 bytes)Available download formats
    Dataset updated
    Sep 6, 2025
    Authors
    Muhammad Naufal Muzaki
    Description

    Dataset

    This dataset was created by Muhammad Naufal Muzaki

    Contents

  3. d

    National Objectives for Digital Assets Research and Development

    • catalog.data.gov
    • s.cnmilf.com
    Updated May 14, 2025
    + more versions
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    NCO NITRD (2025). National Objectives for Digital Assets Research and Development [Dataset]. https://catalog.data.gov/dataset/national-objectives-for-digital-assets-research-and-development
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    Dataset updated
    May 14, 2025
    Dataset provided by
    NCO NITRD
    Description

    This document lays out national objectives for R&D related to digital assets, as defined in Executive Order 14067. This includes R&D on technology that underpins digital assets, such as blockchain and other distributed ledger technology (DLT), as well as applied R&D for digital assets both inside and outside of the financial ecosystem.

  4. Unadjusted and adjusted regression analyses for objective und subjective...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Markus Koch; Lars-Kristian Lunde; Tonje Gjulem; Stein Knardahl; Kaj Bo Veiersted (2023). Unadjusted and adjusted regression analyses for objective und subjective measures. [Dataset]. http://doi.org/10.1371/journal.pone.0162881.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Markus Koch; Lars-Kristian Lunde; Tonje Gjulem; Stein Knardahl; Kaj Bo Veiersted
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Unadjusted and adjusted regression analyses for objective und subjective measures.

  5. T

    Objective Corporation | OCL - Equity Capital And Reserves

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 15, 2024
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    TRADING ECONOMICS (2024). Objective Corporation | OCL - Equity Capital And Reserves [Dataset]. https://tradingeconomics.com/ocl:au:equity-capital-and-reserves
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Dec 15, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Dec 2, 2025
    Area covered
    Australia
    Description

    Objective Corporation reported AUD95.93M in Equity Capital and Reserves for its fiscal semester ending in December of 2024. Data for Objective Corporation | OCL - Equity Capital And Reserves including historical, tables and charts were last updated by Trading Economics this last December in 2025.

  6. e

    Water Body Status Objectives South West TraC

    • data.europa.eu
    • data.wu.ac.at
    unknown
    Updated Oct 11, 2021
    + more versions
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    Environment Agency (2021). Water Body Status Objectives South West TraC [Dataset]. https://data.europa.eu/88u/dataset/water-body-status-objectives-south-west-trac
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    unknownAvailable download formats
    Dataset updated
    Oct 11, 2021
    Dataset authored and provided by
    Environment Agency
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    Water body status objectives describe the long term aim for specific parts of the water environment. This dataset includes the latest objectives of all water bodies in the South West TraC catchment. Water body objectives consist of two pieces of information: the status and the date by which that status is planned to be achieved. The status part of an objective is based on a prediction of the future status classification that would be achieved if technically feasible measures are implemented and, when implemented, would give rise to more benefits than they cost. The objective also takes into account the requirement to prevent deterioration and, as far as practicable, the requirements of protected areas. The date part of an objective is determined by considering whether the measures needed to achieve the planned status are currently affordable and, once implemented, the time taken for ecology or the groundwater to recover. This data supports the Water Framework Directive river basin management plans that can be found here: https://www.gov.uk/government/collections/river-basin-management-plans-2015 and is available to view interactively here: http://environment.data.gov.uk/catchment-planning/ManagementCatchment/3086 Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved.

  7. R

    Ball And Goal Dataset

    • universe.roboflow.com
    zip
    Updated May 30, 2025
    + more versions
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    doughnuts4days20 (2025). Ball And Goal Dataset [Dataset]. https://universe.roboflow.com/doughnuts4days20/ball-and-goal-zovxw
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    zipAvailable download formats
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    doughnuts4days20
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Objects Bounding Boxes
    Description

    Ball And Goal

    ## Overview
    
    Ball And Goal is a dataset for object detection tasks - it contains Objects annotations for 768 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  8. i

    Sweden's Mounted Objective Lens Market Report 2025 - Prices, Size, Forecast,...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Nov 1, 2025
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    IndexBox Inc. (2025). Sweden's Mounted Objective Lens Market Report 2025 - Prices, Size, Forecast, and Companies [Dataset]. https://www.indexbox.io/store/sweden-mounted-objective-lenses-market-analysis-forecast-size-trends-and-insights/
    Explore at:
    doc, xls, xlsx, pdf, docxAvailable download formats
    Dataset updated
    Nov 1, 2025
    Dataset authored and provided by
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Nov 20, 2025
    Area covered
    Sweden
    Variables measured
    Demand, Supply, Price CIF, Price FOB, Market size, Export price, Export value, Import price, Import value, Export volume, and 8 more
    Description

    In 2024, after four years of growth, there was significant decline in the Swedish mounted objective lens market, when its value decreased by -84.1% to $56M. Overall, consumption, however, saw a measured increase. As a result, consumption attained the peak level of $352M, and then dropped sharply in the following year.

  9. H

    MULTI-OBJECTIVE OPTIMIZATION ANALYSIS OF WATER STORAGE AND FISH HABITAT IN...

    • hydroshare.org
    • beta.hydroshare.org
    • +1more
    zip
    Updated Feb 22, 2019
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    Ali Farshid (2019). MULTI-OBJECTIVE OPTIMIZATION ANALYSIS OF WATER STORAGE AND FISH HABITAT IN THE BEAR RIVER WATERSHED [Dataset]. https://www.hydroshare.org/resource/426793d465ef42bbb4991e7dc32ae8ba
    Explore at:
    zip(1.2 MB)Available download formats
    Dataset updated
    Feb 22, 2019
    Dataset provided by
    HydroShare
    Authors
    Ali Farshid
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    In this report, I used a multi-objective optimization modeling for analyzing the trade-offs between the benefits of the recently proposed dams in the Bear River watershed in northern Utah and their effects on aquatic habitat.

  10. g

    Urban Water Use Objectives – Compiled Report Data | gimi9.com

    • gimi9.com
    Updated Oct 3, 2025
    + more versions
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    (2025). Urban Water Use Objectives – Compiled Report Data | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_urban-water-use-objectives-compiled-report-data/
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    Dataset updated
    Oct 3, 2025
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    The Making Conservation a California Way of Life regulation requires urban retail water suppliers to annually calculate their Urban Water Use Objective (UWUO), which is the sum of efficiency budgets for a subset of urban water uses: residential indoor water use, residential outdoor water use, real water loss and commercial, industrial and institutional landscapes with dedicated irrigation meters. Each efficiency budget will be calculated using a statewide efficiency standard and local service area characteristics such as population, climate, and landscape area. Where relevant, suppliers may also include in their objective “variances” for unique uses, or a bonus incentive for potable recycled water use. This dataset contains the information submitted to the State Water Resources Control Board and the Department of Water Resources on the required reporting form. The values have been aggregated into individual tables that roughly correspond to the sections within the reporting form. The original submitted files can be found at the WUE Data Portal To view the source data that pre-filled many of the fields within the reporting form, please visit this page.

  11. T

    Objective Corporation | OCL - Operating Expenses

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 15, 2024
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    TRADING ECONOMICS (2024). Objective Corporation | OCL - Operating Expenses [Dataset]. https://tradingeconomics.com/ocl:au:operating-expenses
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Dec 15, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Dec 2, 2025
    Area covered
    Australia
    Description

    Objective Corporation reported AUD41.73M in Operating Expenses for its fiscal semester ending in December of 2024. Data for Objective Corporation | OCL - Operating Expenses including historical, tables and charts were last updated by Trading Economics this last December in 2025.

  12. C

    Replication data for: Multi-objective application placement in fog computing...

    • dataverse.csuc.cat
    Updated Nov 11, 2025
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    Isaac Lera; Isaac Lera; Carlos Guerrero; Carlos Guerrero (2025). Replication data for: Multi-objective application placement in fog computing using graph neural network-based reinforcement learning [Dataset]. http://doi.org/10.34810/data2671
    Explore at:
    application/x-ipynb+json(345220), text/x-python(1235), pdf(16710), sh(670), application/x-ipynb+json(654411), text/x-python(11735), text/x-python(4879), text/x-python(6066), sh(179), sh(1801), text/x-python(4053), text/x-python(2257), text/x-python(5115), application/x-ipynb+json(190630), text/x-python(5942), txt(8239), txt(3009), text/x-python(3101), sh(882), text/x-python(4410), sh(1343), pdf(27511), application/x-ipynb+json(310656), json(495), text/x-python(5379), text/x-python(15025), sh(3232), text/x-python(7782), text/x-python(5359), text/x-python(3464), application/x-ipynb+json(219261), text/x-python(5244), text/x-python(638), bin(204), text/x-python(6638), text/x-python(5081), pdf(16052), text/x-python(15199), pdf(14545), pdf(101252), text/x-python(2013), text/x-python(1478), pdf(18767), text/x-python(2621), text/x-python(9197), text/x-python(807), sh(660), application/x-ipynb+json(106068), application/x-ipynb+json(122058), text/x-python(3311), text/x-python(1214), pdf(20067), sh(1278), text/x-python(10742), text/x-python(7986), pdf(18310), text/markdown(3504), sh(2131), text/x-python(4099)Available download formats
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    CORA.Repositori de Dades de Recerca
    Authors
    Isaac Lera; Isaac Lera; Carlos Guerrero; Carlos Guerrero
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset comprises a collection of synthetic application‐placement instance sets for heterogeneous cloud–edge/fog infrastructures, designed for the evaluation of single‐ and multi‐objective optimization strategies. Each instance describes: - a directed acyclic graph (DAG) of interdependent services forming an application, - a set of compute nodes (cloud, edge, fog) with resource capacities and connectivity latencies, - resource demands of each service (e.g., CPU, memory), service‐to‐service dependency weights or communication cost, - one or more placement solutions together with objective values (such as latency, energy consumption, deployment cost) generated by algorithms including the DRL model, a genetic algorithm (GA) and an NSGA-II multi‐objective heuristic. The dataset is split into training and test sets and is generated via the provided instance_generator.py and generate_dataset.py scripts. It allows researchers to benchmark and compare placement algorithms in terms of Pareto-front coverage, convergence speed, and trade-offs between objectives. Potential uses: Investigating learning‐based or heuristic algorithms for application placement, multi‐objective optimisation in the cloud/fog continuum, dependency‐aware placement of microservices, as well as enabling reproducibility and comparison across approaches.

  13. The Influence of Subjective and Objective Rural School Security on Law...

    • icpsr.umich.edu
    • s.cnmilf.com
    • +1more
    ascii, delimited, r +3
    Updated Jul 28, 2021
    + more versions
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    Scalora, Mario (2021). The Influence of Subjective and Objective Rural School Security on Law Enforcement Engagement, Nebraska, 2017-2018 [Dataset]. http://doi.org/10.3886/ICPSR37915.v1
    Explore at:
    delimited, spss, r, sas, stata, asciiAvailable download formats
    Dataset updated
    Jul 28, 2021
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Scalora, Mario
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37915/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37915/terms

    Time period covered
    Jan 1, 2017 - Dec 31, 2018
    Area covered
    Nebraska, United States
    Description

    This study is to understand how perceptions and the organization of school safety and security are associated with the level and type of law enforcement engagement in rural schools. A triangulation mixed methods design was used to collect and examine individual, school, and community level quantitative and qualitative data. The social-ecological theory of violence prevention guides the research by predicting that an interplay of factors at multiple levels influences the type and level of law enforcement engagement in rural schools. Specifically, it was predicted that the more organized and coordinated a school is in the area of safety and security, the more likely it is to be formally engaged with law enforcement. Formal engagement is defined as use of some version of the school resource officer (SRO) model or defined roles and responsibilities for law enforcement in schools that are articulated in documents such as a memorandum of agreement or understanding.

  14. T

    Objective Corporation | OCL - Ebit

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 15, 2024
    + more versions
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    TRADING ECONOMICS (2024). Objective Corporation | OCL - Ebit [Dataset]. https://tradingeconomics.com/ocl:au:ebit
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Dec 15, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Dec 2, 2025
    Area covered
    Australia
    Description

    Objective Corporation reported AUD19.02M in EBIT for its fiscal semester ending in December of 2024. Data for Objective Corporation | OCL - Ebit including historical, tables and charts were last updated by Trading Economics this last December in 2025.

  15. Water Body Status Objectives Humber River Basin District - Dataset -...

    • ckan.publishing.service.gov.uk
    Updated Mar 23, 2016
    + more versions
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    ckan.publishing.service.gov.uk (2016). Water Body Status Objectives Humber River Basin District - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/water-body-status-objectives-humber-river-basin-district
    Explore at:
    Dataset updated
    Mar 23, 2016
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Humber
    Description

    Water body status objectives describe the long term aim for specific parts of the water environment. This dataset includes the latest objectives of all water bodies in the Humber River Basin District. Water body objectives consist of two pieces of information: the status and the date by which that status is planned to be achieved. The status part of an objective is based on a prediction of the future status classification that would be achieved if technically feasible measures are implemented and, when implemented, would give rise to more benefits than they cost. The objective also takes into account the requirement to prevent deterioration and, as far as practicable, the requirements of protected areas. The date part of an objective is determined by considering whether the measures needed to achieve the planned status are currently affordable and, once implemented, the time taken for ecology or the groundwater to recover. This data supports the Water Framework Directive river basin management plans that can be found here: https://www.gov.uk/government/collections/river-basin-management-plans-2015 and is available to view interactively here: http://environment.data.gov.uk/catchment-planning/RiverBasinDistrict/4 Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved.

  16. Comparison of single objective, multi-objective and improved...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 28, 2023
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    Xiaohua Zeng; Jieping Cai; Changzhou Liang; Chiping Yuan (2023). Comparison of single objective, multi-objective and improved multi-objective. [Dataset]. http://doi.org/10.1371/journal.pone.0287754.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 28, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Xiaohua Zeng; Jieping Cai; Changzhou Liang; Chiping Yuan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Comparison of single objective, multi-objective and improved multi-objective.

  17. Top objectives in the next five years at GBS organizations worldwide 2023

    • statista.com
    Updated Nov 24, 2025
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    Statista (2025). Top objectives in the next five years at GBS organizations worldwide 2023 [Dataset]. https://www.statista.com/statistics/1416277/gbs-organizations-top-objectives/
    Explore at:
    Dataset updated
    Nov 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    In 2023, the top objective in the next five years for GBS organizations was improving the customer experience. Second in the list was improving the employee experience, with ** percent of respondents reporting this as a priority.

  18. D

    Microscope Objective Lenses Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
    + more versions
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    Dataintelo (2025). Microscope Objective Lenses Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/microscope-objective-lenses-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Microscope Objective Lenses Market Outlook



    The global microscope objective lenses market size was valued at approximately USD 1.2 billion in 2023 and is expected to grow to around USD 2.3 billion by 2032, reflecting a robust CAGR of 7.5% during the forecast period. This growth is predominantly driven by the increasing demand for advanced imaging solutions in various scientific and industrial applications.



    A significant growth factor for the microscope objective lenses market is the ongoing advancements in optical technology. Modern research and industrial applications demand high-resolution imaging, and the development of advanced coatings and materials for lenses has significantly enhanced the performance of microscope objectives. This has led to an increased adoption of high-quality lenses in various sectors, including life sciences, material sciences, and forensics. Furthermore, the miniaturization of electronic components and the growing need for precise imaging in nanotechnology also contribute to the market's expansion.



    The rising investment in research and development activities across the globe is another critical driver for market growth. Governments and private organizations are increasingly funding scientific research to foster innovation and technological advancements. This surge in research activities necessitates high-performance microscopy equipment, thereby driving the demand for superior objective lenses. Additionally, the integration of digital technology with microscopy, such as digital imaging and automated microscopy systems, has further bolstered the market, providing researchers with enhanced capabilities to conduct detailed analyses.



    The expanding healthcare and pharmaceutical sectors are also key contributors to the growth of the microscope objective lenses market. With the rise in global health concerns and the increasing focus on personalized medicine and regenerative therapies, there is a heightened need for advanced diagnostic tools. Microscope objective lenses play a crucial role in clinical diagnostics, pathology, and drug development, facilitating accurate and detailed imaging of biological specimens. This has led to a substantial increase in their adoption in hospitals, clinics, and pharmaceutical and biotechnology companies.



    The integration of a Microscope Adaptor is becoming increasingly significant in the realm of modern microscopy. These adaptors serve as a crucial interface, allowing researchers to connect various imaging devices to their microscopes seamlessly. By facilitating the attachment of cameras or other imaging systems, microscope adaptors enhance the versatility and functionality of microscopes, enabling users to capture high-resolution images and videos for detailed analysis. This capability is particularly beneficial in fields such as life sciences and material sciences, where precise documentation and analysis are essential. As the demand for advanced imaging solutions grows, the role of microscope adaptors in enhancing research capabilities cannot be overstated.



    Regionally, the Asia Pacific is expected to witness significant growth in the microscope objective lenses market. The region's rapid industrialization, burgeoning healthcare infrastructure, and growing emphasis on scientific research have created a conducive environment for market expansion. Countries like China, Japan, and India are investing heavily in research and healthcare, further propelling the demand for high-quality microscope objective lenses. In contrast, established markets in North America and Europe continue to drive innovation and maintain steady growth, while Latin America and the Middle East & Africa are emerging as potential markets due to improving economic conditions and increasing focus on scientific advancements.



    Product Type Analysis



    The microscope objective lenses market is segmented by product type into achromatic, apochromatic, plan, semi-plan, and others. Achromatic lenses are designed to reduce chromatic aberration, which is the failure of a lens to focus all colors to the same point. These lenses are widely used in educational and routine laboratory applications due to their cost-effectiveness and adequate performance. The demand for achromatic lenses remains steady, driven by the need for basic yet reliable imaging solutions in various research and educational settings.



    Apochromatic lenses, on the other hand, offer superior correction of chromatic

  19. f

    Comparison of the objective quality for phantom and Mayo Clinic datasets.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Sep 9, 2022
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    Lee, Jaayeon; Kim, Wonjin; Kang, Mihyun; Choi, Jang-Hwan; Kim, Jin Sung (2022). Comparison of the objective quality for phantom and Mayo Clinic datasets. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000267479
    Explore at:
    Dataset updated
    Sep 9, 2022
    Authors
    Lee, Jaayeon; Kim, Wonjin; Kang, Mihyun; Choi, Jang-Hwan; Kim, Jin Sung
    Description

    Comparison of the objective quality for phantom and Mayo Clinic datasets.

  20. s

    Development Plan 2023 2029 Specific Objective Zoning FCC

    • data.smartdublin.ie
    • data.fingal.ie
    • +1more
    Updated Sep 19, 2023
    + more versions
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    (2023). Development Plan 2023 2029 Specific Objective Zoning FCC [Dataset]. https://data.smartdublin.ie/dataset/development-plan-2023-2029-specific-objective-zoning-fcc2
    Explore at:
    Dataset updated
    Sep 19, 2023
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Detail of Specific Objective Zoning as per the adopted Development plan of Fingal County Council 2023-2029

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Webb, Thomas L.; Rowse, Georgina; Scott, Alexander J. (2017). Descriptive statistics for those providing self-report data and those providing objective sleep data. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001796611

Descriptive statistics for those providing self-report data and those providing objective sleep data.

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Dataset updated
Oct 19, 2017
Authors
Webb, Thomas L.; Rowse, Georgina; Scott, Alexander J.
Description

Descriptive statistics for those providing self-report data and those providing objective sleep data.

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