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arXiv is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

arXiv is a free distribution service and an open-access archive for scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

Stay up to date with what is happening at arXiv on our blog.

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• Astrophysics ( astro-ph new , recent , search ) Astrophysics of Galaxies ; Cosmology and Nongalactic Astrophysics ; Earth and Planetary Astrophysics ; High Energy Astrophysical Phenomena ; Instrumentation and Methods for Astrophysics ; Solar and Stellar Astrophysics
• Condensed Matter ( cond-mat new , recent , search ) Disordered Systems and Neural Networks ; Materials Science ; Mesoscale and Nanoscale Physics ; Other Condensed Matter ; Quantum Gases ; Soft Condensed Matter ; Statistical Mechanics ; Strongly Correlated Electrons ; Superconductivity
• General Relativity and Quantum Cosmology ( gr-qc new , recent , search )
• High Energy Physics - Experiment ( hep-ex new , recent , search )
• High Energy Physics - Lattice ( hep-lat new , recent , search )
• High Energy Physics - Phenomenology ( hep-ph new , recent , search )
• High Energy Physics - Theory ( hep-th new , recent , search )
• Mathematical Physics ( math-ph new , recent , search )
• Nonlinear Sciences ( nlin new , recent , search ) includes: Adaptation and Self-Organizing Systems ; Cellular Automata and Lattice Gases ; Chaotic Dynamics ; Exactly Solvable and Integrable Systems ; Pattern Formation and Solitons
• Nuclear Experiment ( nucl-ex new , recent , search )
• Nuclear Theory ( nucl-th new , recent , search )
• Physics ( physics new , recent , search ) includes: Accelerator Physics ; Applied Physics ; Atmospheric and Oceanic Physics ; Atomic and Molecular Clusters ; Atomic Physics ; Biological Physics ; Chemical Physics ; Classical Physics ; Computational Physics ; Data Analysis, Statistics and Probability ; Fluid Dynamics ; General Physics ; Geophysics ; History and Philosophy of Physics ; Instrumentation and Detectors ; Medical Physics ; Optics ; Physics and Society ; Physics Education ; Plasma Physics ; Popular Physics ; Space Physics
• Quantum Physics ( quant-ph new , recent , search )

Mathematics

• Mathematics ( math new , recent , search ) includes: (see detailed description ): Algebraic Geometry ; Algebraic Topology ; Analysis of PDEs ; Category Theory ; Classical Analysis and ODEs ; Combinatorics ; Commutative Algebra ; Complex Variables ; Differential Geometry ; Dynamical Systems ; Functional Analysis ; General Mathematics ; General Topology ; Geometric Topology ; Group Theory ; History and Overview ; Information Theory ; K-Theory and Homology ; Logic ; Mathematical Physics ; Metric Geometry ; Number Theory ; Numerical Analysis ; Operator Algebras ; Optimization and Control ; Probability ; Quantum Algebra ; Representation Theory ; Rings and Algebras ; Spectral Theory ; Statistics Theory ; Symplectic Geometry

Computer Science

• Computing Research Repository ( CoRR new , recent , search ) includes: (see detailed description ): Artificial Intelligence ; Computation and Language ; Computational Complexity ; Computational Engineering, Finance, and Science ; Computational Geometry ; Computer Science and Game Theory ; Computer Vision and Pattern Recognition ; Computers and Society ; Cryptography and Security ; Data Structures and Algorithms ; Databases ; Digital Libraries ; Discrete Mathematics ; Distributed, Parallel, and Cluster Computing ; Emerging Technologies ; Formal Languages and Automata Theory ; General Literature ; Graphics ; Hardware Architecture ; Human-Computer Interaction ; Information Retrieval ; Information Theory ; Logic in Computer Science ; Machine Learning ; Mathematical Software ; Multiagent Systems ; Multimedia ; Networking and Internet Architecture ; Neural and Evolutionary Computing ; Numerical Analysis ; Operating Systems ; Other Computer Science ; Performance ; Programming Languages ; Robotics ; Social and Information Networks ; Software Engineering ; Sound ; Symbolic Computation ; Systems and Control

Quantitative Biology

• Quantitative Biology ( q-bio new , recent , search ) includes: (see detailed description ): Biomolecules ; Cell Behavior ; Genomics ; Molecular Networks ; Neurons and Cognition ; Other Quantitative Biology ; Populations and Evolution ; Quantitative Methods ; Subcellular Processes ; Tissues and Organs

Quantitative Finance

• Quantitative Finance ( q-fin new , recent , search ) includes: (see detailed description ): Computational Finance ; Economics ; General Finance ; Mathematical Finance ; Portfolio Management ; Pricing of Securities ; Risk Management ; Statistical Finance ; Trading and Market Microstructure
• Statistics ( stat new , recent , search ) includes: (see detailed description ): Applications ; Computation ; Machine Learning ; Methodology ; Other Statistics ; Statistics Theory

Electrical Engineering and Systems Science

• Electrical Engineering and Systems Science ( eess new , recent , search ) includes: (see detailed description ): Audio and Speech Processing ; Image and Video Processing ; Signal Processing ; Systems and Control
• Economics ( econ new , recent , search ) includes: (see detailed description ): Econometrics ; General Economics ; Theoretical Economics

About arXiv

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MIT Libraries home DSpace@MIT

• DSpace@MIT Home

DSpace@MIT is a digital repository for MIT's research, including peer-reviewed articles, technical reports, working papers, theses, and more.

• Communities & collections
• MIT Open Access Articles
• Sloan School of Management
• MIT OpenCourseWare
• Computer Science and Artificial Intelligence Laboratory
• Research Laboratory for Electronics
• Laboratory for Information and Decision Systems
• Deposit to an existing collection
• Deposit to the MIT Open Access Collection
• Learn more about depositing work at DSpace@MIT
• Get help with DSpace@MIT

MIT's DSpace and Open Access in the News

View news archive

Learn more about how DSpace@MIT is used

DSpace@MIT is used by researchers around the world. You can view the stats for the top papers by download, or view, as well as the top countries from which people access DSpace.

Harvard Dataverse

Harvard Dataverse is an online data repository where you can share, preserve, cite, explore, and analyze research data. It is open to all researchers, both inside and out of the Harvard community.

Harvard Dataverse provides access to a rich array of datasets to support your research. It offers advanced searching and text mining in over 2,000 dataverses, 75,000 datasets, and 350,000+ files, representing institutions, groups, and individuals at Harvard and beyond.

Explore Harvard Dataverse

The Harvard Dataverse repository runs on the open-source web application Dataverse , developed at the Institute for Quantitative Social Science . Dataverse helps make your data available to others, and allows you to replicate others' work more easily.   Researchers, journals, data authors, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility.

Why Create a Personal Dataverse?

• Easy set up
• Display your data on your personal website
• Brand it uniquely as your research program
• Makes your data more discoverable to the research community
• Satisfies data management plans

Terms to know

• A Dataverse repository is the software installation, which then hosts multiple virtual archives called dataverses .
• Each dataverse contains datasets, and each dataset contains descriptive metadata and data files (including documentation and code that accompany the data).
• As an organizing method, dataverses may also contain other dataverses.

Related Services and Tools

Research data services, qualitative research support.

• Researchers
• Librarians & Administrators
• ACS Journal Finder
• ACS Open Access Journals
• Hybrid and Transformative Journals
• Special Country Pricing
• Zero-Embargo Green Open Access
• Open Access Articles in ACS Journals
• List of Agreements
• Supporting Resources for Institutions
• What is Open Science?
• Our Open Science Story
• Open Science Resources

Open Access

Make your research freely available to readers around the world

What is open access?

Open access is one of the core elements of open science , making research articles openly and freely available to anyone who seeks to access, read, and build upon them. This is typically facilitated by article publishing fees, which in most cases are paid for by an author’s research grant, a research funder, or through an ACS read and publish agreement .

Open access research articles published in ACS journals are subject to the same rigorous peer review and high publishing standards as all our content.

There are two common paths to make your articles available in open access: the ‘gold’ and ‘green’ routes .

How can I publish open access with ACS?

ACS publishes a family of fully open access journals containing 100% free-to-read articles, and more than 60 hybrid / transformative journals which offer authors the choice to publish open access.

We provide multiple ways you can make your research articles available via open access:

• With support from your institution or research funder through a read and publish agreement ;
• CC BY and CC BY-NC-ND open access options for authors who are not currently covered by an ACS read and publish agreement, including those publishing using grant or personal funds ;
• A zero-embargo green open access option for authors without access to a read and publish agreement or grant / personal funds for gold open access publication, and who are required to make their accepted manuscript available in a repository immediately upon acceptance;
• Deposition of the version of record in selected national and funder open access repositories after a 12-month embargo period.

Selected articles may also be made free to read for a limited time underneath the ACS Editors’ Choice program .

You can find out more about our open access policies here .

What’s the difference between Gold and Green open access?

Gold open access involves making the final published article (the ‘version of record’) immediately available online, with no charges for readers, upon payment of an article publishing charge (APC).

Green open access involves archiving a version of the manuscript (usually the version prior to any peer review or typesetting) in an institutional or subject repository. This often happens after a set amount of time from when the article is published in a journal (an ‘embargo period’), though ACS also offers an option for immediate self-archiving (‘ zero-embargo green open access ‘).

Authors who publish a Gold open access article can also choose to archive the version of record in a repository immediately upon publication.

There are other differences between Green and Gold OA:

How can I make an existing ACS article open access?

Whether you need to meet a funder mandate or you want to make your previously published research articles more widely available, ACS gives you the option to apply an open access license to your research article. Find out more .

What open access content is available in ACS journals?

Thousands of new original research articles are made available as open access in ACS journals each year. These are published under a Creative Commons BY or CC BY-NC-ND license and are completely free to access and share.

Visit the Open Access Articles page on the ACS Publications website for a full list of open access research published across our full portfolio of journals.

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Redirect Notice

Repositories for Sharing Scientific Data

In general, NIH does not endorse or require sharing data in any particular repository, although some initiatives and funding opportunities will have individual requirements.  Overall, NIH encourages researchers to select the repository that is most appropriate for their data type and discipline. See  Selecting a Data Repository .

Browse through this listing of NIH-supported repositories to learn more about some places to share scientific data. Note that this list is not exhaustive. Select the link provided in the “Data Submission Policy” column to find data submission instructions for each repository. 

In addition, NIH provides a listing of generalist repositories that accept all data types .

NIH-supported Scientific Data Repositories*

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Data Repository Guidance

Scientific Data  mandates the release of datasets accompanying our Data Descriptors, but we do not ourselves host data. Instead, we ask authors to submit datasets to an appropriate public data repository. Data should be submitted to discipline-specific, community-recognized repositories where possible. Where a suitable discipline-specific resource does not exist, data should be submitted to a  generalist repository .

Authors must deposit their data to a data repository as part of the manuscript submission process; manuscripts will not otherwise be sent for review. If data have not been deposited to a repository prior to manuscript submission we offer a service to deposit them at figshare or dryad during the submission process via our article submission platform. Data may also be deposited to these resources temporarily, if the main host repository does not support confidential peer review (see below).

Repositories need to meet our requirements for anonymous peer-review, data access, preservation, resource stability, licences and suitability for use by all researchers with the appropriate types of data:

• Use open licences (CC0 and CC-BY, or their equivalents, are required in most cases learn more ). Exceptions will only be permitted for human derived data that is considered sensitive (e.g. risk of participant identification, controls on specific uses, etc), where we suggest data are shared under Data Usage Agreements (DUAs). We do not typically support the use of more restrictive CC licences - containing SA, NC or ND clauses - for either sensitive or non-sensitive datasets, other than where applied to third party data that has been re-used and the original licence needs to be retained. 
• Allow public access to data without barriers, such as formal application processes, unless required for sensitive human datasets requiring controlled access and Data Usage Agreements. Note that basic login functionalities, where data are captured for analytics purposes only, are accepted for non-sensitive datasets as long as immediate access is granted to the holder of the email address without manual checks, however we encourage login-free https access without registration in most cases. 
• All data need to be available for peer review. Where logins or other barriers are required or temporarily applied, routes for confidential peer review of submitted datasets need to be provided that do not reveal the identity of the reviewer to the data owner/author of the associated article. Please consult with the repository to arrange this, or provide the data in a temporary location for peer review. 
• Ensure long-term persistence and preservation of datasets in their published form. All Data Descriptors need to be associated with live data, so long term preservation and persistence is required to avoid future correction or other action to ensure the integrity of the paper. 
• Provide stable persistent identifiers for submitted datasets. DOIs are the default for most non-omics datasets described in the journal. 
• Subject specific repositories that are supported and recognized within their scientific community are strongly encouraged - general repositories should be used where no suitable subject repository is available, or the repository does not meet the requirements above. 

The list below is intended as a guide for those who are unsure where to deposit their data, and provides examples of repositories from a number of disciplines. Please note this list does not constitute a formal or exclusive list of repositories accepted by the journal and there are many more repositories that meet our criteria than we are able to track. The list is no longer updated (since 2021), but is retained as a useful list of suggestions. 

Authors may also wish to use external resources such as DataCite’s Repository Finder and the FAIRsharing registry to find an appropriate repository for their data. Please note that certain data types (e.g. most omics and cystallographic data) are subject to mandates on which repository should be used. Please see our policy on  mandated data types  for further informaton.

View data repositories

• Biological sciences: Nucleic acid sequence ; Protein sequence ; Molecular & supramolecular structure ; Neuroscience ; Omics ; Taxonomy & species diversity ; Mathematical & modelling resources ; Cytometry and Immunology ; Imaging ; Organism-focused resources
• Health sciences
• Chemistry and Chemical biology
• Earth, Environmental and Space sciences: Broad scope Earth & environmental sciences; Astronomy & planetary sciences; Biogeochemistry and Geochemistry; Climate sciences; Ecology; Geomagnetism & Palaeomagnetism; Ocean sciences; Solid Earth sciences
• Materials science
• Social sciences
• Generalist repositories

Biological sciences  ⤴

Nucleic acid sequence  ⤴.

Novel DNA sequence, novel RNA sequence, and novel genome assembly data must be deposited to repositories that are part of the International Nucleotide Sequence Collaboration (INSDC) or to those which are working towards INSDC inclusion (as listed below), unless there are privacy or ethics restrictions that prevent open sharing of such data. These data may in addition be deposited to regional and national repositories as required. For human data that requires special controls, please see our recommended health sciences repositories.

Protein sequence  ⤴

Molecular & supramolecular structure  ⤴.

These repositories accept structural data for small molecules; peptides and proteins (all); and larger assemblies (EMDB).

Small molecule crystallographic data should be uploaded to Dryad or figshare before manuscript submission, and should include a .cif file, and structure factors for each structure. Both the structure factors and the structural output must have been checked using the IUCR's CheckCIF routine , and a copy of the output must be included at submission, together with a justification for any alerts reported.

Neuroscience  ⤴

These data repositories all accept human-derived data (NeuroMorpho.org and G-Node also accept data from other organisms). Please note that human-subject data submitted to OpenfMRI must be de-identified.

Functional genomics

Functional genomics is a broad experimental category, and Scientific Data 's recommendations in this discipline likewise bridge disparate research disciplines. Data should be deposited following the relevant community requirements where possible.

Please refer to the MIAME standard for microarray data. Molecular interaction data should be deposited with a member of the International Molecular Exchange Consortium (IMEx), following the MIMIx recommendations .

For data linking genotyping and phenotyping information in human subjects, we strongly recommend submission to dbGAP, EGA or JGA, which have mechanisms in place to handle sensitive data.

Metabolomics & Proteomics

We ask authors to submit proteomics data to members of the ProteomeXchange consortium (listed below), following the MIAPE recommendations .

Taxonomy & species diversity  ⤴

Mathematical & modelling resources  ⤴, cytometry and immunology  ⤴, organism-focused resources  ⤴.

These resources provide information specific to a particular organism or disease pathogen. They may accept phenotype information, sequences, genome annotations and gene expression patterns, among other types of data. Incorporating data into these resources can be very valuable for promoting reuse within these specific communities; however, where applicable, we ask that data records be submitted both to a community repository and to one suitable for the type of data (e.g. transcriptome profiling; please see above).

Health sciences  ⤴

Some of the repositories in this section are suitable for datasets requiring restricted data access, which may be required for the preservation of study participant anonymity in clinical datasets. We suggest contacting repositories directly to determine those with data access controls best suited to the specific requirements of your study.

Chemistry and Chemical biology  ⤴

Earth, Environmental and Space sciences  ⤴

Broad scope Earth & environmental sciences  ⤴

Astronomy & planetary sciences  ⤴, biogeochemistry and geochemistry  ⤴, climate sciences  ⤴, geomagnetism & palaeomagnetism  ⤴, ocean sciences  ⤴, solid earth sciences  ⤴, materials science  ⤴, social sciences  ⤴, generalist repositories  ⤴.

Scientific Data  encourages authors to archive data to one of the above data-type specific repositories where possible. Where a data-type specific repository is not available, the following generalist repositories might be suitable. Generalist repositories may also be appropriate for archiving associated analyses, or experimental-control data, supplementing the primary data in a discipline-specific repository.

The generalist repositories listed below are able to accept data from all researchers, regardless of location or funding source. If your institution has its own generalist data repository this can be used to host your data as long as the repository is able to mint DataCite DOIs , and allows data to be shared under open terms of use (for example the CC0 waiver ). Please note that if your chosen repository is unable to support confidential peer-review, you will be asked to temporarily deposit a copy of the dataset to one of our  integrated generalist repositories  to facilitate review of your article. Upon completion of peer review, the temporary copy will be erased. To use a repository which does not appear in the manuscript submission system, select 'DataCite DOI' as the repository name during the submission process.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

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Featured communities

Open repository for EU-funded research outputs from Horizon Europe, Euratom and earlier Framework Programmes.

Collection of items related to the Generic Mapping Tools software [www.generic-mapping-tools.org].

A community to share publications related to bio-systematics.

Generalist Repository Ecosystem Initiative (GREI) aims to develop collaborative approaches for data management and sharing through inclusion of the generalist repositories in the NIH data ecosystem.

Aurora is a University network platform for European university leaders, administrators, academics, and students to learn from and with each other. The projects we do and the results that can be shared publically will be put in this community page.

ECEMF is a Horizon 2020-funded project aiming to establish a European forum for energy and climate researchers and policy makers to achieve climate neutrality.

Recent uploads

Uploaded on May 19, 2024

Part of USP3D@UGent

Comprehensive denormalized occurrence table built with the API of the Paleobiology Database (http://paleobiodb.org/). Archived for the Chronosphere project by Ádám T. Kocsis. Downloaded on 2024-05-18 with the API...

Part of chronosphere: Evolving Earth System Variables

741 more versions exist for this record

Das Intensivregister (www.intensivregister.de) ist eine digitale Plattform zur Echtzeiterfassung von intensivmedizinischen Behandlungs- und Bettenkapazitäten sowie den Fallzahlen intensivmedizinisch behandelter COVID-19-Patient:innen der etwa 1.300 Akut-Krankenhäuser Deutschlands. Bis 12 Uhr ist die tägliche Meldung laut Verordnung für die...

Part of Robert Koch Institute

556 more versions exist for this record

Der Datensatz 'Notaufnahmesurveillance' enthält aggregierte Daten der Routinedokumentation aus einer Auswahl deutscher Notaufnahmen aus dem AKTIN-Notaufnahmeregister und bildet die Grundlage für die Notaufnahmesurveillance am RKI.

158 more versions exist for this record

Leptogenys of Hong Kong measurements

Part of Biodiversity Literature Repository

Number of individuals per invertebrate family and month

Complete list of families/species found associated with ornamental palm trees in Spain

Example photographs of some of the methods

Description of Study Sites

El trabajo que aquí se presenta nace de la necesidad de acometer una serie de intervenciones de campo previas a la inminente transformación de una gran área situada en la Ribera de Cabanes (Castellón). Las prospecciones iniciales del sector ante la planificación de su desarrollo urbanístico y la ejecución de un primer PAI en el área de la...

Part of 3D Digitisation of Cultural Heritage

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Federal open science repository of canada.

The Federal Open Science Repository of Canada is the Government of Canada’s open access portal for its scientific articles and publications. This web-based repository makes federally authored Canadian research open and freely available to all.

The repository lets users explore scientific research produced by federal scientists and researchers from participating Government of Canada departments and agencies, creating opportunities to further collaborate and accelerate discoveries.

Preserving and growing scientific knowledge

The portal enables a sustainable approach to open science by ensuring permanent preservation of scientific work.

Researchers benefit from posting scientific publications to the repository through increased usage, citations and credit for their work.

Promoting efficiency and collaboration

Bringing federal scientific research output together in a central repository creates opportunities for the scientific community and science-driven individuals to collaborate, share knowledge, reduce duplication and promote a culture of openness.

Setting the direction for Canada’s scientific research landscape

The repository will shape Canada’s scientific research landscape by connecting researchers across the country and abroad with the latest discoveries, leading to greater impact and reach of federally authored research.

Simplifying the search for federal research

Users can search for scientific publications and articles from participating departments and agencies by community, collection, title, author, date, or subject.

Making federal science open to all

The Government of Canada is committed to making federal science open to all. This is emphasized in the National Action Plan on Open Government and the Roadmap for Open Science , created to support and deliver solutions for the open science commitment.

We believe that federal research should be available to everyone. This is why we developed the Federal Open Science Repository of Canada and made it easy to access for all Canadians, at any time and from anywhere.

To contact participating departments and agencies directly about specific publications, please visit the Contact us page. For general enquiries, please email [email protected] .

🇺🇦    make metadata, not war

A comprehensive bibliographic database of the world’s scholarly literature

The world’s largest collection of open access research papers, machine access to our vast unique full text corpus, core features, indexing the world’s repositories.

We serve the global network of repositories and journals

Comprehensive data coverage

We provide both metadata and full text access to our comprehensive collection through our APIs and Datasets

Powerful services

We create powerful services for researchers, universities, and industry

Cutting-edge solutions

We research and develop innovative data-driven and AI solutions

Committed to the POSI

Cost-free PIDs for your repository

OAI identifiers are unique identifiers minted cost-free by repositories. Ensure that your repository is correctly configured, enabling the CORE OAI Resolver to redirect your identifiers to your repository landing pages.

OAI IDs provide a cost-free option for assigning Persistent Identifiers (PIDs) to your repository records. Learn more.

Who we serve?

Enabling others to create new tools and innovate using a global comprehensive collection of research papers.

“ Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can ... ” Show more

Gareth Malcolm, Content Partner Manager at Turnitin

Academic institutions.

Making research more discoverable, improving metadata quality, helping to meet and monitor open access compliance.

“ CORE’s role in providing a unified search of repository content is a great tool for the researcher and ex... ” Show more

Nicola Dowson, Library Services Manager at Open University

Researchers & general public.

Tools to find, discover and explore the wealth of open access research. Free for everyone, forever.

“ With millions of research papers available across thousands of different systems, CORE provides an invalu... ” Show more

Jon Tennant, Rogue Paleontologist and Founder of the Open Science MOOC

Helping funders to analyse, audit and monitor open research and accelerate towards open science.

“ Aggregation plays an increasingly essential role in maximising the long-term benefits of open access, hel... ” Show more

Ben Johnson, Research Policy Adviser at Research England

Our services, access to raw data.

Create new and innovative solutions.

Content discovery

Find relevant research and make your research more visible.

Managing content

Manage how your research content is exposed to the world.

Companies using CORE

Gareth Malcolm

Content Partner Manager at Turnitin

Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can utilise in our plagiarism detection software.

Academic institution using CORE

Kathleen Shearer

Executive Director of the Confederation of Open Access Repositories (COAR)

CORE has significantly assisted the academic institutions participating in our global network with their key mission, which is their scientific content exposure. In addition, CORE has helped our content administrators to showcase the real benefits of repositories via its added value services.

Partner projects

Ben Johnson

Research Policy Adviser

Aggregation plays an increasingly essential role in maximising the long-term benefits of open access, helping to turn the promise of a 'research commons' into a reality. The aggregation services that CORE provides therefore make a very valuable contribution to the evolving open access environment in the UK.

Open Access Theses and Dissertations

Thursday, April 18, 8:20am (EDT): Searching is temporarily offline. We apologize for the inconvenience and are working to bring searching back up as quickly as possible.

Advanced research and scholarship. Theses and dissertations, free to find, free to use.

Advanced search options

Browse by author name (“Author name starts with…”).

Find ETDs with:

Written in any language English Portuguese French German Spanish Swedish Lithuanian Dutch Italian Chinese Finnish Greek Published in any country US or Canada Argentina Australia Austria Belgium Bolivia Brazil Canada Chile China Colombia Czech Republic Denmark Estonia Finland France Germany Greece Hong Kong Hungary Iceland India Indonesia Ireland Italy Japan Latvia Lithuania Malaysia Mexico Netherlands New Zealand Norway Peru Portugal Russia Singapore South Africa South Korea Spain Sweden Switzerland Taiwan Thailand UK US Earliest date Latest date

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October 3, 2022. OATD is dealing with a number of misbehaved crawlers and robots, and is currently taking some steps to minimize their impact on the system. This may require you to click through some security screen. Our apologies for any inconvenience.

Recent Additions

See all of this week’s new additions.

About OATD.org

OATD.org aims to be the best possible resource for finding open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions . OATD currently indexes 7,241,108 theses and dissertations.

About OATD (our FAQ) .

Visual OATD.org

We’re happy to present several data visualizations to give an overall sense of the OATD.org collection by county of publication, language, and field of study.

You may also want to consult these sites to search for other theses:

• Google Scholar
• NDLTD , the Networked Digital Library of Theses and Dissertations. NDLTD provides information and a search engine for electronic theses and dissertations (ETDs), whether they are open access or not.
• Proquest Theses and Dissertations (PQDT), a database of dissertations and theses, whether they were published electronically or in print, and mostly available for purchase. Access to PQDT may be limited; consult your local library for access information.

Repository Selection Process

Repository evaluation, selection, and coverage policies for the Data Citation Index within Web of Science.

With the ever-increasing amount of digital data being produced and made available, either voluntarily or through policy requirements from grant funding agencies, the need to discover and provide credit for the creation of scholarly research data has never been greater. Launched in 2012, the Data Citation Index is now included within Web of Science, allowing for search and discovery of the scientific research data and links to the published literature with appropriate citation metrics. Clarivate must balance the selection of material for inclusion in Data Citation Index with the ever-increasing abundance of digital web based resources. This essay sets forth the criteria and procedures for inclusion in the new Index.

As always, Clarivate remains responsive to new, innovative developments in data publication which share our mission to bring the existence of the data to the attention of the scholarly community.

Research data considered for inclusion include data studies, data sets, and software deposited in a recognized repository.

Definitions:

• Data repository: a database or collection comprising data studies, and data sets which stores and provides access to the raw data. Constituent data studies, and sometimes individual data sets, are marked up with metadata providing a context for the available raw data.
• Data study: description of studies or experiments held in repositories with the associated data or software which have been used in the data study. (Includes serial or longitudinal studies over time). Data studies can be a citable object in the literature and may have cited references attached in their metadata, together with information on such aspects as the principal investigators, funding information, subject terms, geographic coverage etc. The level of metadata provided varies between repositories.
• Data set: a single or coherent set of data, data file, or software object provided by the repository, as part of a collection, data study or experiment. Data sets may exist in a number of file formats and media types: they may be number based files such as spreadsheets, images, video, audio, databases etc. Data sets can be a citable object in the literature and may include cited references attached in their metadata, but more commonly they inherit the metadata of the overall study in which they are used.

The evaluation process

Repository identification and selection are continuous and ongoing at Clarivate, with repositories added as frequently as weekly. Moreover, existing coverage is constantly under review. Repositories now covered are monitored to ensure that they remain available and are maintaining high standards and a clear relevance to the Data Citation Index product. The repository selection process described here is applied to all resources covered in the Data Citation Index.

Many factors are taken into account when evaluating repositories for coverage, both qualitative and quantitative. The repository’s basic publishing standards, its editorial content, the international diversity of its authorship, and the citation data associated with it are all considered. No one factor is considered in isolation, but by combining and interrelating the data, the editor is able to determine the repository’s overall strengths and weaknesses. Clarivate editors who perform the evaluation have educational backgrounds relevant to their areas of responsibility, and understand the data held by the repositories they review. Primary selection is at the level of the repository where evaluation includes:

• Editorial content and repository attributes
• Geographic origin and scope

Once a repository is accepted for inclusion, further evaluation determines the appropriate metadata elements which will be captured to allow discovery and citation.

Basic repository publishing standards

Persistence and stability.

Persistence of a repository and the data deposited within it is a basic criterion in the evaluation process. A repository must demonstrate longevity to be considered for initial inclusion in Data Citation Index. Clarivate also reviews whether new data are currently deposited; a steady flow of newly deposited data is taken as an indicator that the resource is currently active. Generally, the data should be deposited with the repository, rather than the repository simply holding metadata and providing a web link to a remote/external source for the data. This ensures robust citation to the data to enable citation metrics and data re-use. A clear definition of the data-publication process with an indication of the data provider/creator’s affiliation should, ideally, be indicated. When a repository is selected for coverage, all deposited data are included in Data Citation Index; there is no sub-repository level selection other than to exclude data that is referenced rather than deposited.

Funding statements

The Data Citation Index aims to promote citation of data and link data to the research literature. To this end, particular consideration is given to repositories that show literature provenance and are accompanied by grant funding information. English is the universal language of science at this time in history. It is for this reason that Clarivate focuses on repositories that publish metadata in English or, at the very least, allow provision of sufficient descriptive (metadata) information in English. Some repositories covered in Data Citation Index publish only metadata descriptions in English with the actual data in another language. However, going forward, it is clear that the repositories most important to the international research community will publish data in English. This is especially true in the natural sciences. In addition, all repositories must have metadata and citations in the Roman alphabet.

Peer review

While peer review of deposited data is by no means universal, application of the peer-review process is another indication of repository standards and signifies overall quality of the data presented and the completeness of any cited references. It is also recommended that whenever possible, each repository, data study or data set is published with information on the funding source supporting the research presented.

Age of material

In addition, Clarivate must form a judgement on the long-term preservation and sustainability of the repository and research data. There are no restrictions on the age of the deposited data. As a multidisciplinary service, the disparate attitudes and requirements of researchers across the various disciplines with regard to “older” data are acknowledged. Timeliness is also no restriction. As grant-funded projects draw to a close, it is accepted that the valued research output presented will not necessarily be updated in future, yet it will continue to be cited and may be reused in current research; there may also be delays in data publication compared to the corresponding research article due to embargos defined by authors and/or funding bodies.

Links to the research literature

To promote standards for data citation, and, subsequently, measure the impact of this growing body of scholarship, priority will be given to data repositories that show the provenance relating the data set to the research literature that either produced or re-used the data. Again, no one factor is considered in isolation, but by combining and interrelating the data, the repository’s overall strengths and weaknesses can be evaluated. The Clarivate staff performing these repository evaluations have advanced-degree-level educational backgrounds relevant to their areas of responsibility.

Editorial content

Clarivate includes research data from three major subject areas: Science & Technology, Social Sciences, and Arts & Humanities. Individual repositories may be multidisciplinary, inter-disciplinary or may have a narrow focus in order to qualify for inclusion. With an enormous amount of data readily available to them, and their daily observation of the international data landscape, Clarivate editors are well positioned to spot emerging topics and active fields.

International diversity

While Clarivate looks for international diversity among the repository’s contributing authors, editors, data producers, and deposited data, with the aim of providing information for an international audience, the importance of local and regional cyber scholarship is also given due consideration. Selection criteria are applied consistently across all repositories, irrespective of geographic coverage (international, national, regional or institutional), or whether the repository is multidisciplinary or has a narrow subject focus.

Data citation & standards

While the research community has a strong desire to see data citation and attribution, there are no consistent standards and the occurrence of data in cited reference bibliographies of research articles is rare. To this end, Clarivate encourages data citation by providing a standardized citation format for each record. In determining the citation format a number of proposed standards were evaluated. The DataCite citation standard has been adopted by Clarivate due to its general acceptance and its ability to be applied to a wide range of data types and disciplines.

As data citation and the ability to link data repository content to the literature remains of high importance to Clarivate and the research community, repositories are given priority if they provide references which either cite the deposited data, or which are cited by the deposited data record.

Recommending a repository for coverage

To recommend a particular data repository for coverage, please send details to [email protected] , and include details such as the URL which provides electronic access.

References:

Ball, A. & Duke, M. (2011). How to Cite Datasets and Link to Publications. DCC How-to Guides. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/how-guides/cite-datasets

Borgman, C. L. (2008). Data, disciplines and scholarly publishing. Learned publishing 21 (1): 29-38 doi: 10.1087/095315108X254476 DataCite. Why Cite Data? http://www.datacite.org/whycitedata

Reilly, S., Schallier, W., Schrimpf, S., Smit, E., Wilkinson, M. (2011). Opportunities for Data Exchange Report on Integration of Data and Publications. Available online: http://www.alliancepermanentaccess.org/wp-content/uploads/downloads/2011/11/ODE-ReportOnIntegrationOfDataAndPublications-1_1.pdf

Recommended Repositories

All data, software and code underlying reported findings should be deposited in appropriate public repositories, unless already provided as part of the article. Repositories may be either subject-specific repositories that accept specific types of structured data and/or software, or cross-disciplinary generalist repositories that accept multiple data and/or software types.

If field-specific standards for data or software deposition exist, PLOS requires authors to comply with these standards. Authors should select repositories appropriate to their field of study (for example, ArrayExpress or GEO for microarray data; GenBank, EMBL, or DDBJ for gene sequences). PLOS has identified a set of established repositories, listed below, that are recognized and trusted within their respective communities. PLOS does not dictate repository selection for the data availability policy.

For further information on environmental and biomedical science repositories and field standards, we suggest utilizing FAIRsharing . Additionally, the Registry of Research Data Repositories ( Re3Data ) is a full scale resource of registered data repositories across subject areas. Both FAIRsharing and Re3Data provide information on an array of criteria to help researchers identify the repositories most suitable for their needs (e.g., licensing, certificates and standards, policy, etc.).

If no specialized community-endorsed public repository exists, institutional repositories that use open licenses permitting free and unrestricted use or public domain, and that adhere to best practices pertaining to responsible sharing, sustainable digital preservation, proper citation, and openness are also suitable for deposition.

If authors use repositories with stated licensing policies, the policies should not be more restrictive than the Creative Commons Attribution (CC BY) license .

Cross-disciplinary repositories

• Dryad Digital Repository
• Harvard Dataverse Network
• Network Data Exchange (NDEx)
• Open Science Framework

Repositories by type

Biochemistry.

*Data entered in the STRENDA DB submission form are automatically checked for compliance and receive a fact sheet PDF with warnings for any missing information.

Biomedical Sciences

Marine sciences.

• SEA scieNtific Open data Edition (SEANOE)

Model Organisms

Neuroscience.

• Functional Connectomes Project International Neuroimaging Data-Sharing Initiative (FCP/INDI)
• German Neuroinformatics Node/G-Node (GIN)
• NeuroMorpho.org

Physical Sciences

Social sciences.

• Inter-university Consortium for Political and Social Research (ICPSR)
• Qualitative Data Repository
• UK Data Service

Structural Databases

Taxonomic & species diversity, unstructured and/or large data.

PLOS would like to thank the Open Access Nature Publishing Group journal,  Scientific Data , for their own  list of recommended repositories .

Repository Criteria

The list of repositories above is not exhaustive and PLOS encourages the use of any repository that meet the following criteria:

Dataset submissions should be open to all researchers whose research fits the scientific scope of the repository. PLOS’ list does not include repositories that place geographical or affiliation restrictions on submission of datasets.

Repositories must assign a stable persistent identifier (PID) for each dataset at publication, such as a digital object identifier (DOI) or an accession number.

• Repositories must provide the option for data to be available under  CC0  or  CC BY  licenses (or equivalents that are no less restrictive). Specifically, there must be no restrictions on derivative works or commercial use.
• Repositories should make datasets available to any interested readers at no cost, and with no registration requirements that unnecessarily restrict access to data. PLOS will not recommend repositories that charge readers access fees or subscription fees.
• Repositories must have a long-term data management plan (including funding) to ensure that datasets are maintained for the foreseeable future.
• Repositories should demonstrate acceptance and usage within the relevant research community, for example, via use of the repository for data deposition for multiple published articles.
• Repositories should have an entry in  FAIRsharing.org  to allow it to be linked to the  PLOS entry .

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An open-source framework for machine learning and other computations on decentralized data.

google-parfait/tensorflow-federated

Folders and files, repository files navigation, tensorflow federated.

TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with Federated Learning (FL) , an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally. For example, FL has been used to train prediction models for mobile keyboards without uploading sensitive typing data to servers.

TFF enables developers to use the included federated learning algorithms with their models and data, as well as to experiment with novel algorithms. The building blocks provided by TFF can also be used to implement non-learning computations, such as aggregated analytics over decentralized data.

TFF's interfaces are organized in two layers:

Federated Learning (FL) API The tff.learning layer offers a set of high-level interfaces that allow developers to apply the included implementations of federated training and evaluation to their existing TensorFlow models.

Federated Core (FC) API At the core of the system is a set of lower-level interfaces for concisely expressing novel federated algorithms by combining TensorFlow with distributed communication operators within a strongly-typed functional programming environment. This layer also serves as the foundation upon which we've built tff.learning .

TFF enables developers to declaratively express federated computations, so they could be deployed to diverse runtime environments. Included with TFF is a single-machine simulation runtime for experiments. Please visit the tutorials and try it out yourself!

Installation

See the install documentation for instructions on how to install TensorFlow Federated as a package or build TensorFlow Federated from source.

Getting Started

See the get started documentation for instructions on how to use TensorFlow Federated.

Contributing

There are a number of ways to contribute depending on what you're interested in:

If you are interested in developing new federated learning algorithms, the best way to start would be to study the implementations of federated averaging and evaluation in tff.learning , and to think of extensions to the existing implementation (or alternative approaches). If you have a proposal for a new algorithm, we recommend starting by staging your project in the research directory and including a colab notebook to showcase the new features.

You may want to also develop new algorithms in your own repository. We are happy to feature pointers to academic publications and/or repos using TFF on tensorflow.org/federated .

If you are interested in applying federated learning, consider contributing a tutorial, a new federated dataset, or an example model that others could use for experiments and testing, or writing helper classes that others can use in setting up simulations.

If you are interested in helping us improve the developer experience, the best way to start would be to study the implementations behind the tff.learning API, and to reflect on how we could make the code more streamlined. You could contribute helper classes that build upon the FC API or suggest extensions to the FC API itself.

If you are interested in helping us develop runtime infrastructure for simulations and beyond, please wait for a future release in which we will introduce interfaces and guidelines for contributing to a simulation infrastructure.

Please be sure to review the contribution guidelines on how to contribute.

Use GitHub issues for tracking requests and bugs.

Please direct questions to Stack Overflow using the tensorflow-federated tag.

Contributors 107

• Python 72.7%
• Starlark 4.7%

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Celebrating Open Science trailblazers at The Neuro

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In an era where scientific collaboration and transparency are paramount, the Tanenbaum Open Science Institute (TOSI) proudly acknowledges those who lead the charge in embracing Open Science principles and practices.

The Neuro Open Science Internal Awards recognize the outstanding contributions of researchers, staff, and trainees at The Neuro who champion Open Science, as well as undergraduate students at the start of their research careers who are eager to engage and contribute to the movement. This initiative, spearheaded by TOSI, underscores our commitment to recognizing and promoting excellence in Open Science practices.

Through their leadership and enthusiasm, these awardees inspire their peers and foster a community where openness and collaboration are key drivers to great science.

Open Science Leadership Awards for Principal Investigators

This award recognizes principal investigators (PIs) at The Neuro who are dedicated to advancing Open Science. It aims to encourage sustained Open Science practices within research laboratories, spotlighting PIs actively working to drive progress in the field of neuroscience through transparent and collaborative approaches. Each winner is awarded CAD $9,000 in unrestricted funds and a CAD $1,000 cash award.

Udunna Anazodo William Dawson Scholar and Assistant Professor, Department of Neurology and Neurosurgery

Anazodo's commitment to Open Science principles and practices is evident in her leadership across initiatives aimed at reducing disparities in neuroscience. As chair of the Consortium for Advancement of MRI Education and Research in Africa (CAMERA), she has played a vital role in tackling imaging challenges in Africa and devising practical solutions. This award celebrates her efforts to extend access to underrepresented communities, alongside her steadfast dedication to diversity, equity, and inclusion principles, and her pivotal role in mentoring the next generation of practitioners.

Sylvain Baillet Professor, Department of Neurology and Neurosurgery

This award recognizes Baillet’s exceptional dedication to Open Science, not only within The Neuro but also extending beyond McGill, Quebec, and internationally. His contributions range from the creation of the Open MEG Archives (OMEGA) to the integration of Brainstorm software, which has cultivated a thriving community of over 43,000 users worldwide. His efforts have transcended mere practice to include fostering and advocating for Open Science principles, evident in his many leadership roles at McGill and beyond. His commitment to inclusivity and collaboration truly embodies the spirit of Open Science and makes him a deserving recipient of this award.

Open Science Champion Awards for Research Staff

This award celebrates research personnel such as research associates, research assistants, lab managers, and technicians at The Neuro who demonstrate leadership in Open Science activities. It aims to promote the lasting integration of Open Science practices within each laboratory, clinic, and unit, fostering a culture of transparency and collaboration. Winners receive a CAD $2,000 cash award.

Irina Shlaifer Early Drug Discovery Unit

Shlaifer's commitment to Open Science shines through her work in the Early Drug Discovery Unit. From generating and openly disseminating CRISPR cell lines to creating and sharing laboratory protocols and best practices, her contributions demonstrate her dedication to making Open Science practices the norm, fostering a culture of collaboration within the lab and beyond.

Taylor Goldsmith Early Drug Discovery Unit

Goldsmith receives this award in recognition of her work in the Early Drug Discovery Unit as well as her commitment to science communication and knowledge dissemination through initiatives that extend beyond the scope of her work. Besides being responsible for the generation and distribution of iPSC lines via an open biobank, Goldsmith hosts tours of the EDDU to a variety of audiences and actively participates in multiple other outreach activities.

Sarah Bogard Quebec Parkinson Network

Bogard’s dedication to Open Science shines through her work in recruiting participants for the Quebec Parkinson Network. Her efforts to ensure that patients residing in remote regions of Quebec can engage in research, alongside her fervent advocacy for patient outreach and facilitation of data sharing practices distinguishes her as a worthy recipient of this award.

Nicolas Ferry Neuro Open Biobank (C-BIG repository)

Ferry has been instrumental in integrating the work of the Neuro Open Biobank (C-BIG repository) with other key Open Science platforms. He receives this award for his dedication to protecting patient privacy, facilitating global data access, and going above and beyond to ensure that valuable patient samples and data can contribute to further the understanding of neurological disorders.

Hatrock Awards for Graduate Students and Postdoctoral Fellows

This award recognizes trainees with a proven track record of developing and contributing to Open Science initiatives, and/or in integrating Open Science best practices into their research, within their labs and beyond. Named in memory of Dale Hatrock, a passionate advocate for rigorous and transparent scientific communication, recipients of this award receive recognition for their dedication to fostering openness and collaboration in neuroscience research. The recipient of the Hatrock Award receives a CAD $1,000 cash award, while two runners-up are awarded CAD $500 each.

Allison Dilliott Postdoctoral fellow, Farhan lab, Rouleau lab

Dilliott's dedication to advancing Open Science is evident through her proactive engagement in a variety of clinical Open Science efforts. She receives this award for her commitment to open publishing, knowledge transfer, and open data sharing, with the ultimate goal of improving the lives of those living with amyotrophic lateral sclerosis (ALS).

Ruwan Bedeir MSc student, La Piana lab

This runner-up award is given in recognition of Bedeir's commitment to placing open science at the heart of her scientific activities, evident through her efforts in training, knowledge transfer, and outreach regarding white matter disorders.

Jordan DeKraker Postdoctoral fellow, Bernhardt lab, Evans lab

DeKraker receives this runner-up award in recognition especially of his efforts in leading the development and maintenance of the open access toolbox, HippoMaps, and supporting and encouraging the sustained Open Science practices within the research community.

Open Science Launchpad Awards for Undergraduate Internships

This award supports the scientific careers of McGill undergraduate researchers aiming to work at The Neuro by offering internship funding for research projects aligned with Open Science principles. With four awards of CAD $5,000 each, these awards not only facilitate hands-on training in Open Science practices but also inspire the next generation of changemakers to drive cultural change towards Open Science within our community.

Joshua Gertsvolf Stratton lab

Gertsvolf’s project involves the development of openly available tutorials to help onboard new users of the SingloCell website, which allows users to explore single cell data in an interactive and accessible format. The project exhibits a strong commitment to accessibility and improvement of the user experience, indicating a clear commitment to Open Science practices.

Doris Hua Early Drug Discovery Unit

Hua’s project represents an important contribution to the ongoing outreach and training efforts of the Early Drug Discovery Unit. Her work actively promotes Open Science practices through video production, social media management, and organizing seminars to facilitate the dissemination of research findings and advance accessibility to scientific knowledge.

Matthew Loukine Trenholm lab

Loukine has developed MousePi, an ultra-low-cost behavioral rig for training head-fixed mice, leveraging open hardware and software to democratize access to neuroscience research tools. This project builds on this work and aims to finalize documentation, provide openly available training materials, and release the system for broader use within the scientific community.

Emma Lacoume Baillet lab

Lacoume’s project aims to significantly expand the volume, diversity, and quality of the Open MEG Archive (OMEGA) by curating new data from over 390 participants. By adhering to best practices in data organization and curation, this work will enhance the repository's capacity and help facilitate access to relevant research data to scientists around the world.

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Facility for Rare Isotope Beams

At michigan state university, international research team uses wavefunction matching to solve quantum many-body problems, new approach makes calculations with realistic interactions possible.

FRIB researchers are part of an international research team solving challenging computational problems in quantum physics using a new method called wavefunction matching. The new approach has applications to fields such as nuclear physics, where it is enabling theoretical calculations of atomic nuclei that were previously not possible. The details are published in Nature (“Wavefunction matching for solving quantum many-body problems”) .

Ab initio methods and their computational challenges

An ab initio method describes a complex system by starting from a description of its elementary components and their interactions. For the case of nuclear physics, the elementary components are protons and neutrons. Some key questions that ab initio calculations can help address are the binding energies and properties of atomic nuclei not yet observed and linking nuclear structure to the underlying interactions among protons and neutrons.

Yet, some ab initio methods struggle to produce reliable calculations for systems with complex interactions. One such method is quantum Monte Carlo simulations. In quantum Monte Carlo simulations, quantities are computed using random or stochastic processes. While quantum Monte Carlo simulations can be efficient and powerful, they have a significant weakness: the sign problem. The sign problem develops when positive and negative weight contributions cancel each other out. This cancellation results in inaccurate final predictions. It is often the case that quantum Monte Carlo simulations can be performed for an approximate or simplified interaction, but the corresponding simulations for realistic interactions produce severe sign problems and are therefore not possible.

Using ‘plastic surgery’ to make calculations possible

The new wavefunction-matching approach is designed to solve such computational problems. The research team—from Gaziantep Islam Science and Technology University in Turkey; University of Bonn, Ruhr University Bochum, and Forschungszentrum Jülich in Germany; Institute for Basic Science in South Korea; South China Normal University, Sun Yat-Sen University, and Graduate School of China Academy of Engineering Physics in China; Tbilisi State University in Georgia; CEA Paris-Saclay and Université Paris-Saclay in France; and Mississippi State University and the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU)—includes  Dean Lee , professor of physics at FRIB and in MSU’s Department of Physics and Astronomy and head of the Theoretical Nuclear Science department at FRIB, and  Yuan-Zhuo Ma , postdoctoral research associate at FRIB.

“We are often faced with the situation that we can perform calculations using a simple approximate interaction, but realistic high-fidelity interactions cause severe computational problems,” said Lee. “Wavefunction matching solves this problem by doing plastic surgery. It removes the short-distance part of the high-fidelity interaction, and replaces it with the short-distance part of an easily computable interaction.”

This transformation is done in a way that preserves all of the important properties of the original realistic interaction. Since the new wavefunctions look similar to that of the easily computable interaction, researchers can now perform calculations using the easily computable interaction and apply a standard procedure for handling small corrections called perturbation theory.  A team effort

The research team applied this new method to lattice quantum Monte Carlo simulations for light nuclei, medium-mass nuclei, neutron matter, and nuclear matter. Using precise ab initio calculations, the results closely matched real-world data on nuclear properties such as size, structure, and binding energies. Calculations that were once impossible due to the sign problem can now be performed using wavefunction matching.

“It is a fantastic project and an excellent opportunity to work with the brightest nuclear scientist s in FRIB and around the globe,” said Ma. “As a theorist , I'm also very excited about programming and conducting research on the world's most powerful exascale supercomputers, such as Frontier , which allows us to implement wavefunction matching to explore the mysteries of nuclear physics.”

While the research team focused solely on quantum Monte Carlo simulations, wavefunction matching should be useful for many different ab initio approaches, including both classical and  quantum computing calculations. The researchers at FRIB worked with collaborators at institutions in China, France, Germany, South Korea, Turkey, and United States.

“The work is the culmination of effort over many years to handle the computational problems associated with realistic high-fidelity nuclear interactions,” said Lee. “It is very satisfying to see that the computational problems are cleanly resolved with this new approach. We are grateful to all of the collaboration members who contributed to this project, in particular, the lead author, Serdar Elhatisari.”

This material is based upon work supported by the U.S. Department of Energy, the U.S. National Science Foundation, the German Research Foundation, the National Natural Science Foundation of China, the Chinese Academy of Sciences President’s International Fellowship Initiative, Volkswagen Stiftung, the European Research Council, the Scientific and Technological Research Council of Turkey, the National Natural Science Foundation of China, the National Security Academic Fund, the Rare Isotope Science Project of the Institute for Basic Science, the National Research Foundation of Korea, the Institute for Basic Science, and the Espace de Structure et de réactions Nucléaires Théorique.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

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Science is making anti-aging progress. But do we want to live forever?

Nobel laureate details new book, which surveys research, touches on larger philosophical questions

Anne J. Manning

Harvard Staff Writer

Mayflies live for only a day. Galapagos tortoises can reach up to age 170. The Greenland shark holds the world record at over 400 years of life. 

Venki Ramakrishnan, Nobel laureate and author of the newly released “ Why We Die: The New Science of Aging and the Quest for Immortality ,” opened his packed Harvard Science Book Talk last week by noting the vast variabilities of lifespans across the natural world. Death is certain, so far as we know. But there’s no physical or chemical law that says it must happen at a fixed time, which raises other, more philosophical issues.

The “why” behind these enormous swings, and the quest to harness longevity for humans, have driven fevered attempts (and billions of dollars in research spending) to slow or stop aging. Ramakrishnan’s book is a dispassionate journey through current scientific understanding of aging and death, which basically comes down to an accumulation of chemical damage to molecules and cells.

“The question is whether we can tackle aging processes, while still keeping us who we are as humans,” said Ramakrishnan during his conversation with Antonio Regalado, a writer for the MIT Technology Review. “And whether we can do that in a safe and effective way.”

Even if immortality — or just living for a very, very long time — were theoretically possible through science, should we pursue it? Ramakrishnan likened the question to other moral ponderings.

“There’s no physical or chemical law that says we can’t colonize other galaxies, or outer space, or even Mars,” he said. “I would put it in that same category. And it would require huge breakthroughs, which we haven’t made yet.”

In fact, we’re a lot closer to big breakthroughs when it comes to chasing immortality. Ramakrishnan noted the field is moving so fast that a book like his can capture but a snippet. He then took the audience on a brief tour of some of the major directions of aging research. And much of it, he said, started in unexpected places.

Take rapamycin, a drug first isolated in the 1960s from a bacterium on Easter Island found to have antifungal, immunosuppressant, and anticancer properties. Rapamycin targets the TOR pathway, a large molecular signaling cascade within cells that regulates many functions fundamental to life. Rapamycin has garnered renewed attention for its potential to reverse the aging process by targeting cellular signaling associated with physiological changes and diseases in older adults.

Other directions include mimicking the anti-aging effects of caloric restriction shown in mice, as well as one particularly exciting area called cellular reprogramming. That means taking fully developed cells and essentially turning back the clock on their development.

The most famous foundational experiment in this area was by Kyoto University scientist and Nobel laureate Shinya Yamanaka, who showed that just four transcription factors could revert an adult cell all the way back to a pluripotent stem cell, creating what are now known as induced pluripotent stem cells.

Ramakrishnan , a scientist at England’s MRC Laboratory of Molecular Biology, won the 2009 Nobel Prize in chemistry for uncovering the structure of the ribosome. He said he felt qualified to write the book because he has “no skin in the game” of aging research. As a molecular biologist who has studied fundamental processes of how cells make proteins, he had connections in the field but wasn’t too close to any of it.

While researching the book, he took pains to avoid interviewing scientists with commercial ventures tied to aging.

The potential for conflicts of interest abound.

The world has seen an explosion in aging research in recent decades, with billions of dollars spent by government agencies and private companies . And the consumer market for products is forecast to hit $93 billion by 2027 .

As a result, false or exaggerated claims by companies promising longer life are currently on the rise, Ramakrishnan noted. He shared one example: Supplements designed to lengthen a person’s telomeres, or genetic segments that shrink with age, are available on Amazon.

“Of course, these are not FDA approved. There are no clinical trials, and it’s not clear what their basis is,” he said.

But still there appears to be some demand.

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Resultados científicos revolucionarios en la estación espacial de 2023

Melissa L. Gaskill

Microgravity, a unique orbit, crewed laboratory, twenty years and counting, adding subjects adds time.

The International Space Station provides unique features that enable innovative research, including microgravity, exposure to space, a unique orbit, and hands-on operation by crew members.

The space station provides consistent, long-term access to microgravity. Eliminating the effects of Earth’s gravity on experiments is a game-changer across many disciplines, including research on living things and physical and chemical processes. For example, without gravity hot air does not rise, so flames become spherical and behave differently. Removing the forces of surface tension and capillary movement allows scientists to examine fluid behavior more closely.

The speed, pattern, and altitude of the space station’s orbit provide unique advantages. Traveling at 17,500 miles per hour, it circles the planet every 90 minutes, passing over a majority of Earth’s landmass and population centers in daylight and darkness. Its 250-mile-high altitude is low enough for detailed observation of features, atmospheric phenomena, and natural disasters from different angles and with varying lighting conditions. At the same time, the station is high enough to study how space radiation affects material durability and how organisms adapt and examine phenomena such as neutron stars and blackholes. The spacecraft also places observing instruments outside Earth’s atmosphere and magnetic field, which can interfere with observations from the ground.

Other satellites in orbit contain scientific experiments and conduct Earth observations, but the space station also has crew members aboard to manage and maintain scientific activities. Human operators can respond to and assess events in real time, swap out experiment samples, troubleshoot, and observe results first-hand. Crew members also pack experiment samples and send them back to the ground for detailed analysis.

Thanks to the space station’s longevity, experiments can continue for months or even years. Scientists can design follow-up studies based on previous results, and every expedition offers the chance to expand the number of subjects for human research.

One area of long-term human research is on changes in vision, first observed when astronauts began spending months at a time in space. Scientists wondered whether fluids shifting from the lower to the upper body in microgravity caused increased pressure inside the head that changed eye shape. The Fluid Shifts investigation began in 2015 and continued to measure the extent of fluid shifts in multiple astronauts through 2020. 1

Whether the original study is long or short, it can take years for research to go from the lab into practical applications. Many steps are involved, some of them lengthy. First, researchers must come up with a question and a possible answer, or hypothesis. For example, Fluid Shifts questioned what was causing vision changes and a possible answer was increased fluid pressure in the head. Scientists must then design an experiment to test the hypothesis, determining what data to collect and how to do so.

Getting research onto the space station in the first place takes time, too. NASA reviews proposals for scientific merit and relevance to the agency’s goals. Selected investigations are assigned to a mission, typically months in the future. NASA works with investigators to meet their science requirements, obtain approvals, schedule crew training, develop flight procedures, launch hardware and supplies, and collect any preflight data needed. Once the study launches, in-flight data collection begins. When scientists complete their data collection, they need time to analyze the data and determine what it means. This may take a year or more.

Scientists then write a paper about the results – which can take many months – and submit it to a scientific journal. Journals send the paper to other experts in the same field, a process known as peer review. According to one analysis, this review takes an average of 100 days. 2 The editors may request additional analysis and revisions based on this review before publishing.

Aspects of research on the space station can add more time to the process. Generally, the more test subjects, the better – from 100 to 1,000 subjects for statistically significant results for clinical research. But the space station typically only houses about six people at a time.

Lighting Effects shows how the need for more subjects adds time to a study. This investigation examined whether adjusting the intensity and color of lighting inside the station could help improve crew circadian rhythms, sleep, and cognitive performance. To collect data from enough crew members, the study ran from 2016 until 2020.

Other lengthy studies about how humans adapt to life in space include research on loss of heart muscle and a suite of long-term studies on nutrition, including producing fresh food in space.

For physical science studies, investigators can send batches of samples to the space station and collect data more quickly, but results can create a need for additional research. Burning and Suppression of Solids ( BASS ) examined the characteristics of a wide variety of fuel samples from 2011 to 2013, and BASS-II continued that work through 2017. The Saffire series of fire safety demonstrations began in 2016 and wrapped up in 2024. Researchers have answered many burning (pun intended) questions, but still have much to learn about preventing, detecting, and extinguishing fires in space.

The timeline for scientific results can run long, especially in microgravity. But those results can be well worth the wait.

Melissa Gaskill International Space Station Research Communications Team Johnson Space Center

Search this database of scientific experiments to learn more about those mentioned above.

1 Macias BR, Liu JHK, Grande-Gutierrez N, Hargens AR. Intraocular and intracranial pressures during head-down tilt with lower body negative pressure. Aerosp Med Hum Perform. 2015; 86(1):3–7.  https://www.ingentaconnect.com/content/asma/amhp/2015/00000086/00000001/art00004;jsessionid=31bonpcj2e8tj.x-ic-live-01

2 Powell K. Does it take too long to publish research? Nature 530, pages148–151 (2016). https://www.nature.com/articles/530148a

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• Q&A: Exploring ethnic dynamics and climate change in Africa

Q&A: Exploring ethnic dynamics and climate change in Africa

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Evan Lieberman is the Total Professor of Political Science and Contemporary Africa at MIT, and is also director of the Center for International Studies. During a semester-long sabbatical, he’s currently based at the African Climate and Development Initiative at the University of Cape Town .

In this Q&A, Lieberman discusses several climate-related research projects he’s pursuing in South Africa and surrounding countries. This is part of an ongoing series exploring how the School of Humanities, Arts, and Social Sciences is addressing the climate crisis.

Q: South Africa is a nation whose political and economic development you have long studied and written about. Do you see this visit as an extension of the kind of research you have been pursuing, or a departure from it?

A: Much of my previous work has been animated by the question of understanding the causes and consequences of group-based disparities, whether due to AIDS or Covid. These are problems that know no geographic boundaries, and where ethnic and racial minorities are often hardest hit. Climate change is an analogous problem, with these minority populations living in places where they are most vulnerable, in heat islands in cities, and in coastal areas where they are not protected. The reality is they might get hit much harder by longer-term trends and immediate shocks.

In one line of research, I seek to understand how people in different African countries, in different ethnic groups, perceive the problems of climate change and their governments’ response to it. There are ethnic divisions of labor in terms of what people do — whether they are farmers or pastoralists, or live in cities. So some ethnic groups are simply more affected by drought or extreme weather than others, and this can be a basis for conflict, especially when competing for often limited government resources.

In this area, just like in my previous research, learning what shapes ordinary citizen perspectives is really important, because these views affect people’s everyday practices, and the extent to which they support certain kinds of policies and investments their government makes in response to climate-related challenges. But I will also try to learn more about the perspectives of policymakers and various development partners who seek to balance climate-related challenges against a host of other problems and priorities.

Q: You recently published “ Until We Have Won Our Liberty ," which examines the difficult transition of South Africa from apartheid to a democratic government, scrutinizing in particular whether the quality of life for citizens has improved in terms of housing, employment, discrimination, and ethnic conflicts. How do climate change-linked issues fit into your scholarship?

A: I never saw myself as a climate researcher, but a number of years ago, heavily influenced by what I was learning at MIT, I began to recognize more and more how important the issue of climate change is. And I realized there were lots of ways in which the climate problem resonated with other kinds of problems I had tackled in earlier parts of my work.

There was once a time when climate and the environment was the purview primarily of white progressives: the “tree huggers.” And that’s really changed in recent decades as it has become evident that the people who've been most affected by the climate emergency are ethnic and racial minorities. We saw with Hurricane Katrina and other places [that] if you are Black, you’re more likely to live in a vulnerable area and to just generally experience more environmental harms, from pollution and emissions, leaving these communities much less resilient than white communities. Government has largely not addressed this inequity. When you look at American survey data in terms of who’s concerned about climate change, Black Americans, Hispanic Americans, and Asian Americans are more unified in their worries than are white Americans.

There are analogous problems in Africa, my career research focus. Governments there have long responded in different ways to different ethnic groups. The research I am starting looks at the extent to which there are disparities in how governments try to solve climate-related challenges.

Q: It’s difficult enough in the United States taking the measure of different groups’ perceptions of the impact of climate change and government’s effectiveness in contending with it. How do you go about this in Africa?

A: Surprisingly, there’s only been a little bit of work done so far on how ordinary African citizens, who are ostensibly being hit the hardest in the world by the climate emergency, are thinking about this problem. Climate change has not been politicized there in a very big way. In fact, only 50 percent of Africans in one poll had heard of the term.

In one of my new projects, with political science faculty colleague Devin Caughey and political science doctoral student Preston Johnston, we are analyzing social and climate survey data [generated by the Afrobarometer research network] from over 30 African countries to understand within and across countries the ways in which ethnic identities structure people’s perception of the climate crisis, and their beliefs in what government ought to be doing. In largely agricultural African societies, people routinely experience drought, extreme rain, and heat. They also lack the infrastructure that can shield them from the intense variability of weather patterns. But we’re adding a lens, which is looking at sources of inequality, especially ethnic differences.

I will also be investigating specific sectors. Africa is a continent where in most places people cannot take for granted universal, piped access to clean water. In Cape Town, several years ago, the combination of failure to replace infrastructure and lack of rain caused such extreme conditions that one of the world’s most important cities almost ran out of water.

While these studies are in progress, it is clear that in many countries, there are substantively large differences in perceptions of the severity of climate change, and attitudes about who should be doing what, and who’s capable of doing what. In several countries, both perceptions and policy preferences are differentiated along ethnic lines, more so than with respect to generational or class differences within societies.

This is interesting as a phenomenon, but substantively, I think it’s important in that it may provide the basis for how politicians and government actors decide to move on allocating resources and implementing climate-protection policies. We see this kind of political calculation in the U.S. and we shouldn’t be surprised that it happens in Africa as well.

That’s ultimately one of the challenges from the perch of MIT, where we’re really interested in understanding climate change, and creating technological tools and policies for mitigating the problem or adapting to it. The reality is frustrating. The political world — those who make decisions about whether to acknowledge the problem and whether to implement resources in the best technical way — are playing a whole other game. That game is about rewarding key supporters and being reelected.

Q: So how do you go from measuring perceptions and beliefs among citizens about climate change and government responsiveness to those problems, to policies and actions that might actually reduce disparities in the way climate-vulnerable African groups receive support?

A: Some of the work I have been doing involves understanding what local and national governments across Africa are actually doing to address these problems. We will have to drill down into government budgets to determine the actual resources devoted to addressing a challenge, what sorts of practices the government follows, and the political ramifications for governments that act aggressively versus those that don’t. With the Cape Town water crisis, for example, the government dramatically changed residents’ water usage through naming and shaming, and transformed institutional practices of water collection. They made it through a major drought by using much less water, and doing it with greater energy efficiency. Through the government’s strong policy and implementation, and citizens’ active responses, an entire city, with all its disparate groups, gained resilience. Maybe we can highlight creative solutions to major climate-related problems and use them as prods to push more effective policies and solutions in other places.

In the MIT Global Diversity Lab , along with political science faculty colleague Volha Charnysh, political science doctoral student Jared Kalow, and Institute for Data, Systems and Society doctoral student Erin Walk, we are exploring American perspectives on climate-related foreign aid, asking survey respondents whether the U.S. should be giving more to people in the global South who didn’t cause the problems of climate change but have to suffer the externalities. We are particularly interested in whether people’s desire to help vulnerable communities rests on the racial or national identity of those communities.

From my new seat as director of the Center for International Studies (CIS), I hope to do more and more to connect social science findings to relevant policymakers, whether in the U.S. or in other places. CIS is making climate one of our thematic priority areas, directing hundreds of thousands of dollars for MIT faculty to spark climate collaborations with researchers worldwide through the Global Seed Fund program. 

COP 28 (the U.N. Climate Change Conference), which I attended in December in Dubai, really drove home the importance of people coming together from around the world to exchange ideas and form networks. It was unbelievably large, with 85,000 people. But so many of us shared the belief that we are not doing enough. We need enforceable global solutions and innovation. We need ways of financing. We need to provide opportunities for journalists to broadcast the importance of this problem. And we need to understand the incentives that different actors have and what sorts of messages and strategies will resonate with them, and inspire those who have resources to be more generous.

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