Digital Science partners with HERSA to build security, integrity and trust in UK research

Digital Science, a leading technology company serving stakeholders across the research ecosystem, is embarking on a multi-year partnership with the Higher Education Research Security Association (HERSA) to support universities across the UK in boosting research security and integrity, and building trust in science.

As part of the collaboration, Digital Science will support the development of a new Trusted Research, Education and Innovation Security Hub for UK institutions.

The company behind Dimensions Research Security, Digital Science will also host a dedicated Dimensions Research Security Community Forum, creating spaces where export control and research security practitioners can come together, share experiences and feel supported by a wider community.

HERSA Co-Chair Chris Buckland said: “Together, Digital Science and HERSA want to make it easier and more accessible for universities to look after both their people and their research.

“By combining HERSA’s sector-led network with Digital Science’s tools and expertise, our partnership will help institutions talk openly about challenges, learn from one another, and access practical guidance, events and training in a trusted and secure environment.”

Digital Science’s Executive Vice President of Academic, Jonathan Breeze, said: “Our collaboration with HERSA aims to give universities confidence that they can meet their responsibilities around export controls and research security, while still supporting open, international collaboration and the free exchange of ideas.

“Over time, we hope our collaboration with HERSA will help facilitate a national model of higher education collaboration across the research security landscape in the UK, enabling the sharing of best practice and lessons learned, within a peer-led community.”

About HERSA

HERSA is a sector-led, institutionally agnostic association led by research security professionals from some of the UK’s leading research-intensive universities. Formerly known as the Higher Education Export Control Association (HEECA) until early 2026, we were initially established to develop and promote best practice in Export Control compliance across the UK HE sector. Today, our work spans the broader research and economic security agenda, reflecting the dynamic, complex and ever-changing landscape of UK national security.  We serve as a conduit for technical exchange between practitioners, Government, industry and other national and international stakeholders – including through our participation in the Higher Education Security Forum (HESF). We enable collaboration across the UK HE sector to foster a consistent approach to security compliance at a national level, facilitating both in-person and online events that promote key discussions and best practices

Visit the HERSA website and follow HERSA on LinkedIn to learn more.

About Dimensions

Part of Digital Science, Dimensions hosts the largest collection of interconnected global research data, re-imagining research discovery with access to grants, publications, clinical trials, patents and policy documents all in one place. Follow Dimensions on Bluesky, X and LinkedIn.

About Digital Science

Digital Science is an AI-focused technology company providing innovative solutions to complex challenges faced by researchers, universities, governments, funders, industry, and publishers. We work in partnership to advance global research for the benefit of society. Through our brands – Altmetric, Dimensions, Figshare, IFI CLAIMS Patent Services, metaphacts, Overleaf, ReadCube, Symplectic, and Writefull – we believe when we solve problems together, we drive progress for all. Visit digital-science.com and follow Digital Science on Bluesky, on X or on LinkedIn.

Media Contacts

David Ellis, Press, PR & Social Manager, Digital Science: Mobile +61 447 783 023, d.ellis@digital-science.com

enquiries@hersa.co.uk 

The post Digital Science partners with HERSA to build security, integrity and trust in UK research appeared first on Digital Science.



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๐Ÿ”ฌ Analytical Modeling of Fully Coupled Photo-Thermoelastic Interactions in Semiconductor Media with Cylindrical Cavities ๐ŸŒก️

 ๐Ÿ”ฌ Photo-thermoelastic interactions in semiconductor media describe the complex coupling between optical excitation, temperature variation, and mechanical deformation. When light energy is absorbed, it generates heat and induces thermal stresses, which in turn affect the material’s structural and electronic properties. ๐ŸŒก️ Developing an analytical solution for this fully coupled behavior helps researchers understand how semiconductors respond under intense optical and thermal conditions.

⚙️ The presence of cylindrical cavities adds another layer of complexity. These geometric features influence stress concentration, heat distribution, and wave propagation within the material. ๐Ÿงฎ By solving the governing equations analytically, scientists can predict displacement fields, temperature changes, and stress patterns around cavities with high precision, without relying solely on numerical simulations.

๐Ÿš€ Such analytical models are crucial for designing advanced semiconductor devices used in lasers, sensors, and microelectronic systems. ๐ŸŒ Understanding coupled photo-thermoelastic effects improves structural reliability, enhances performance, and supports innovation in optoelectronics and nanotechnology, where thermal and mechanical stability are critical for long-term functionality.

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⚙️ Advanced Heat Sink Engineering for Improved Thermal Gradients๐ŸŒฌ️

 

๐Ÿ”ฅ Power semiconductor modules generate significant heat during operation, and efficient thermal management is critical for reliability and performance. An air-forced heat sink is a widely used cooling solution, where airflow enhances heat dissipation from the module surface. ๐ŸŒฌ️ Optimizing the design of these heat sinks helps reduce hotspots and improve the overall temperature gradient across the device.

๐Ÿ”ฌ Design optimization focuses on parameters such as fin geometry, spacing, height, base thickness, and airflow velocity. ⚙️ By refining these structural features, engineers can maximize surface area and promote uniform heat distribution. Computational fluid dynamics (CFD) simulations and thermal modeling play a key role in predicting airflow patterns and identifying areas where cooling efficiency can be enhanced.

๐Ÿš€ Improving the temperature gradient not only increases power efficiency but also extends the lifespan of semiconductor components. ๐ŸŒก️ Lower thermal stress reduces the risk of failure and enhances system stability in applications like electric vehicles, renewable energy converters, and industrial drives. Advanced heat sink optimization is therefore essential for next-generation high-power electronics.

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⚡ Robust Online Climate Prediction with Recursive Mixed-Norm Methods๐ŸŒ

๐ŸŒ Climate monitoring increasingly relies on interconnected sensor networks that generate massive streams of environmental data. Graph Signal Processing (GSP) provides a powerful framework to model these spatially distributed signals, capturing relationships between locations such as temperature stations or air-quality sensors. ๐Ÿ“Š A generalized recursive mixed-norm algorithm enhances this framework by enabling adaptive, real-time processing of graph-structured climate data.

๐Ÿ”ฌ The “mixed-norm” approach improves robustness by balancing sensitivity to small fluctuations while resisting large outliers or noise. ⚙️ Through recursive updating, the algorithm continuously refines its estimates as new data arrive, making it ideal for online climate estimation. This adaptability ensures stable performance even in dynamic and uncertain environmental conditions.

๐Ÿš€ By integrating advanced optimization techniques with graph-based modeling, this method supports accurate forecasting and anomaly detection in climate systems. ๐ŸŒ Such innovations strengthen early warning systems, improve environmental policy planning, and enable smarter responses to climate variability—demonstrating how intelligent signal processing can advance sustainable development.

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๐Ÿ”️ Mechanical Reinforcement of Soil by Olive Tree Root Systems Safety๐ŸŒ


 ๐ŸŒณ Olive trees are more than a source of fruit and oil—they also play a vital role in soil stabilization. Their root systems penetrate and bind soil layers, providing natural mechanical reinforcement. ๐Ÿ”️ Quantifying the tensile strength and distribution of olive roots helps researchers understand how they contribute to shallow slope stability and reduce the risk of surface landslides.

๐Ÿ”ฌ By measuring root density, diameter, and pull-out resistance, scientists can estimate how much additional shear strength roots add to the soil. ๐ŸŒฑ This root–soil interaction improves slope resistance against rainfall-induced erosion and gravitational forces. Such data are essential for developing predictive models that assess slope safety in agricultural and hilly terrains.

๐ŸŒ Integrating biological solutions like olive tree cultivation into slope management strategies supports sustainable land use. ๐Ÿšœ Farmers and land planners can use this knowledge to prevent soil degradation while maintaining productivity. Ultimately, olive roots act as a natural engineering system, strengthening slopes and promoting long-term environmental resilience.


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2025 Research Recap: The Top 10 Publications of the Year

With thousands of papers and studies being published daily, how do you know whether your research has made any waves in the field?

How is actual “impact” or “influence” measured, and what metrics matter? 

By number of citations or Altmetric score? Virality on social media? Longest title of 2025? And finally, are these measurements good, bad or simply delightful? 

All of these questions (and more) are ones that data and research experts, Mike Taylor (Head of Data Insights, Digital Science), Carrie Brubaker (Medical Affairs Consultant), and Carlos Areia (Senior Data Scientist, Altmetric, part of Digital Science) began to explore as part of a Medical Affairs Professional Society (MAPS) podcast a couple of years ago. Now, they’re back and have the additional expert insight of James Dathan (Associate Director, BBU Publication, AstraZeneca) to reflect on and discuss their take on the Top 10 Most Interesting Publications of 2025 using Altmetric data. Each deliberates on why they made these lists and what made these particular publications stand out above the rest.

This year’s roundup includes curated sub-lists such as Top Altmetric Score – Clinical Trial Publication, Top All-round Highest Score, and even Top U.S. Congress Attention.

Below, we cover some selected highlights from the podcast. Did you come across any of these publications? Is yours on the list? 

For the full list and insights, head over to the Top 10 Most “Interesting” Publications of 2025 on the MAPS website.

Top Altmetric Score – Clinical Trial Publication

Title: Tirzepatide as Compared with Semaglutide for the Treatment of Obesity
By: Atonne et al
Published in: The New England Journal of Medicine, 393(1), 26-36 – May 2025
DOI: https://doi.org/10.1056/nejmoa2416394

For a detailed breakdown of the Altmetric attention, click here.

This paper contrasts the two best-known GLP-1 drugs for obesity (in the absence of diabetes), finding that injectable tirzepatide was more effective in weight loss and waist reduction (although both work well).

“Twenty years ago, this therapeutic area (drug treatments for obesity) essentially didn’t exist. The introduction of GLP-1 drugs has been the key driver, and amongst them, semaglutide and tirzepatide have had a dramatic effect on the TA and publication space… These are two big beasts being compared in this paper: given the prevalence of obesity, we shouldn’t be surprised by these numbers – in fact, we should also take a moment to reflect on how many millions of people have read about GLP1-drugs in the mainstream media, heard podcasts, read blog posts, and shared about it on social media. It’s a very real example of the power that our publications have, and how our research can change attitudes and conversations around the world.” —Mike Taylor

Top All-round Highest Score and Top Social Media Sentiment – Clinicians

Title: Patient-Specific In Vivo Gene Editing to Treat a Rare Genetic Disease
By: Musunuru et al
Published in: The New England Journal of Medicine, 392(22), 2235-2243 – May 2025
DOI: https://doi.org/10.1056/nejmoa2504747

For a detailed breakdown of the Altmetric attention, click here.

In this paper, the authors describe how a newborn child, who’d been diagnosed with a rare genetic disorder with an estimated 50% mortality in early childhood is treated with a custom base-editing therapy. The treatment appears to have been successful with no significant adverse effects.

Altmetric attention score graphic
A graphic visualizing the Altmetric Attention Score and media mentions for an article. The Attention Score is 4667. Media mentions are broken down as follows: 507 mentions in news outlets, 24 in blogs, 1097 by X (formerly Twitter) users, 3 on Facebook pages, 6 on Wikipedia pages, 5 by YouTube creators, 382 by Bluesky users, and 15 mentions in podcasts.

Top U.S. Congress Attention

Title: Structured Exercise after Adjuvant Chemotherapy for Colon Cancer
By: Courneya et al
Published in: The New England Journal of Medicine, 393(1), 13-25 – June 2025
DOI: https://doi.org/10.1056/nejmoa2502760

For a detailed breakdown of the Altmetric attention, click here.

A phase 3 randomized trial found that a three-year structured exercise program after adjuvant chemotherapy for colon cancer significantly improved disease-free survival and suggested longer overall survival compared to a health-education group. At a median follow-up of eight years, the exercise group had an 80.3% five-year disease-free survival rate, compared to 73.9% in the health-education group.

“Despite not being a commercial trial, this was the most famous viral study in our congress data, particularly at the American Society of Clinical Oncology Annual Meeting (ASCO 2025), receiving exceptional positive sentiment and attention in social media, news, blogs and many other attention sources. I must disclose that I am a bit biased due to my Physio background, but I could not have this trial pass without a mention and strong congratulatory message to all involved in this brilliant and really impactful piece of work.” —Carlos Areia

Top Discussed on Podcasts

Title: Finerenone with Empagliflozin in Chronic Kidney Disease and Type 2 Diabetes
By: Agarwal et al
Published in: The New England Journal of Medicine, 393(6), 533-543 – June 2025
DOI: https://doi.org/10.1056/nejmoa2410659

For a detailed breakdown of the Altmetric attention, click here.

The study investigates the effects of combining finerenone and empagliflozin in patients with CKD and type 2 diabetes. Results show that this combination therapy significantly reduces the urinary albumin-to-creatinine ratio more than either drug alone, with no unexpected adverse events reported.

Screenshot of podcast mentions – in German and English. Source: Altmetric.

“Podcasts are a new source for me, and this one is fascinating – it’s been discussed by the diabetes and renal communities, as well as amongst cardiologists. To me, seeing the enormous growth of the podcast as a means of communication and the diversity is extraordinary! This particular paper was mentioned on eight podcasts. Seeing how different therapeutic communities all engaged with this publication is fascinating – in the wild world of scientometrics, the expectation is usually that papers that cross subjects often get lower levels of activity: this paper defies those expectations. Oh, and it’s been discussed in German as well as English.” —Mike Taylor

This recap was previously published on the Altmetric blog as A Year in Discovery: The Top 10 Standout Publications of 2025.

The post 2025 Research Recap: The Top 10 Publications of the Year appeared first on Digital Science.



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๐Ÿง  Intelligent Model Selection for Signal Processing Using Neural Networks๐Ÿ“ก

 

๐Ÿ“ก Signal processing plays a vital role in communications, healthcare, radar, audio analysis, and many other fields. Selecting the right model for analyzing signals can significantly impact accuracy and performance. ๐Ÿง  A neural network–based model selection method leverages deep learning to automatically evaluate patterns, noise characteristics, and signal features, helping researchers choose the most suitable processing architecture.

๐Ÿ” Instead of relying solely on manual tuning or traditional statistical criteria, neural networks can learn from large datasets to compare models dynamically. ⚙️ They assess performance metrics such as prediction error, robustness, and computational efficiency. By using validation strategies and adaptive learning, these intelligent systems optimize model complexity while preventing overfitting, ensuring reliable signal interpretation.

๐Ÿš€ As signal environments become more complex—especially with IoT, 5G, and biomedical applications—AI-driven model selection offers scalability and precision. ๐ŸŒ Integrating neural networks into signal processing workflows enhances automation, accelerates research, and improves real-time decision-making, paving the way for smarter and more efficient analytical systems.

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Digital Science partners with HERSA to build security, integrity and trust in UK research

Digital Science, a leading technology company serving stakeholders across the research ecosystem, is embarking on a multi-year partnership w...

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