Science

Agrivoltaics – combining land for solar and agriculture – is a genuine win-win. It allows a single piece of land to produce both food and clean energy at the same time. Around the world, farmers are finding that solar infrastructure creates microhabitats that boost resilience, improve yields and reduce water stress. For the agriculture: ✅ Shade from the panels lower ground temperatures and reduces evaporation. In arid areas, this has doubled or even tripled crop yields while cutting irrigation needs by half. ✅ Shade-tolerant crops like lettuce, kale, berries and broccoli thrive under reduced heat stress, especially during extreme weather. ✅ Higher soil moisture also promotes healthier pasture, leading to more nutritious forage for grazing animals. For solar operators: ✅ Sheep naturally keep vegetation under control, reducing mowing and maintenance costs and lowering fire risk. They also prevent plants from shading the panels. ✅ Crops underneath the panels help to cool the modules, improving performance on hot days. And the animals benefit too. A 3-year study of 1,700 sheep at the Wellington Solar Farm in NSW found the sheep produced higher quality wool and more of it. The arrays offer shade in summer, shelter during storms and cooler microclimates throughout the day. Economically it's a strong proposition: - Landowners gain a stable income stream while keeping land productive. - Developers access more viable sites with fewer permitting hurdles. - Communities retain agricultural land and benefit from local investment and tax revenue. And in the US, a significant "solar grazing" industry is emerging, where farmers become vegetation managers. They rent out flocks of sheep to solar farm owners and the sheep trim the vegetation. Agrivoltaics is showing that solar and agriculture don’t have to compete for land. They can thrive together – and create more value in the process. Image credit: Enel Green Power #energy #renewables #energytransition

Canadian Solar Inc. leads standard for UV induced #degradation Some PV cell technologies, especially those with an inappropriate front-side film stack are prone to UV-induced degradation (#UVID). We have been studying this for a long time and found that UVID test results vary greatly between labs. Sometimes wrong test conditions are used, which produce false degradation that does not occur in actual application environments. As a result, Canadian Solar recently proposed a new #IEC standard for UV induced degradation. This is the sixth IEC standard proposal Canadian Solar has led, and the first five proposals have been successfully completed and published. Experts from 10 countries agreed on the test conditions after 12 meetings, and a ‘committee draft’ has been finished. In the meantime, we conducted round-robin tests in different labs with different cell technologies and manufacturers. The results show that Canadian Solar’s #TOPCon and #HJT, which are designed with appropriate film stack and manufacturing process parameters, demonstrated outstanding UV resistance. Alarmingly back-contact (#BC) solar cells exhibit significantly higher UVID than TOPCon. We think it is because these BC products were released too fast to the marketplace and the film stack has not been well designed. I suppose that given time BC will eventually improve.  Canadian Solar always put quality at first and invests a lot of resources during the product development stage, so that problems can be discovered and solved in time. We will continue posting the progress in standard development and round-robin results. Stay tuned and welcome to join us as we dive deeper into the UVID mechanisms.  #SolarTechnology #IECstandard #SolarResearch

🌍 NASA - National Aeronautics and Space Administration, in collaboration with data from the World Meteorological Organization, merges satellite observations, advanced models, and immense computing power to monitor aerosols in our atmosphere. These tiny, invisible solid or liquid particles — including black carbon (orange/red), sea salt (cyan), dust (magenta), and sulfates (green) — travel vast distances, affecting air quality, human health, climate, and visibility far from their source. 🔹 In South America, black carbon from wildfires burning in the Amazon rainforest drifts across the continent. 🔹 Over the Atlantic, massive plumes of dust from Northern Africa journey westward toward the Americas, influencing ecosystems, weather, and even hurricane formation. This striking visualization, powered by NASA’s Goddard Earth Observing System (GEOS) model and informed by WMO’s authoritative climate data, delivers realistic, high-resolution weather and aerosol insights. These data streams fuel #AI innovation and help provide customized environmental predictions — critical tools for #climateresilience and disaster preparedness #EW4ALL. ➡ A reminder: Every particle tells a story about the planet’s interconnected systems — and our shared responsibility to protect them

Learning must come before deciding. Your brain stores different types of learning in your subconscious, your rote memory bank, and your habits. But no matter how you acquire your knowledge or where you store it, what’s most important is that what you know paints a true and rich picture of the realities that will affect your decision. That’s why it always pays to be radically open- minded and seek out believable others as you do your learning. Many people have emotional trouble doing this and block the learning that could help them make better decisions. Remind yourself that it’s never harmful to at least hear an opposing point of view. Deciding is the process of choosing which knowledge should be drawn upon—both the facts of this particular “what is” and your broader understanding of the cause-effect machinery that underlies it—and then weighing them to determine a course of action, the “what to do about it.” This involves playing different scenarios through time to visualize how to get an outcome consistent with what you want. To do this well, you need to weigh first-order consequences against second- and third-order consequences, and base your decisions not just on near-term results but on results over time. #principleoftheday

🌍 We Can’t Afford to Get Climate Policy Wrong—A Look at the Data Behind What Really Works 🌍 In the race against time to combat climate change, bold promises are everywhere. But here’s the critical question: Are the policies being implemented actually reducing emissions at the scale we need? A groundbreaking study published in Science, cuts through the noise and delivers the insights we desperately need. Evaluating 1,500 climate policies from around the world, the research identifies the 63 most effective ones—policies that have delivered tangible, significant reductions in emissions. What’s striking is that the most successful strategies often involve combinations of policies, rather than single initiatives. Think of it as the ultimate teamwork: when policies like carbon pricing, renewable energy mandates, and efficiency standards are combined thoughtfully, the impact is far greater than any one policy could achieve on its own. It’s a powerful reminder that for climate solutions the whole is indeed greater than the sum of its parts. Moreover, the study’s use of counterfactual emissions pathways is a game changer. By showing what would have happened without these policies, it provides a clear, quantifiable measure of their effectiveness. This is exactly the kind of rigorous evaluation we need to ensure that every policy counts, especially when we’re working against the clock. If we’re serious about meeting the Paris Agreement’s targets, we need to focus on what works—and this research offers a clear roadmap. Let’s champion policies that have proven to make a difference, because we don’t have time to waste on anything less. 🔗 Full study in the comments #ClimateAction #Sustainability #PolicyEffectiveness #ParisAgreement #NetZero #ClimateScience

🍱 How To Design Complex Data Tables (+ Figma Kits). Practical techniques and useful tools to design better data tables on mobile and desktop (scroll down for the newsletter) ↓ ✅ Start with observing, collecting and prioritizing user needs. ✅ Define complex functionality (drag-n-drop, resizing, reshuffling). ✅ Define logic and permissions (read-only, comment-only, editable). ✅ Decide on truncation, wrapping, stretching and resizing rules. ✅ Draw a table tree diagram that covers all needed features. 🤔 Users don’t expect tables to be the same on mobile/desktop. 🤔 But they do expect features that they rely on to exist in both. 🚫 Row-column-data-tables are terribly inefficient on mobile. ✅ Think about the data alone, rather than its tabular structure. ✅ See how to aggregate data and span it across fewer columns. 🤔 Users rarely navigate through all columns in the table. ✅ Let them show and hide columns (“Columns” button). ✅ There, let them also re-arrange, lock and reset columns. ✅ Abbreviate dates, long labels, units of measure, currency. 🚫 But: don’t rely on tooltips or hover to show critical details. Show only what users really need. Think “card”, not “row” to present a single record of data. Aggregate and re-group data across the table. You might not always need labels, but keep them available to screen reader users. And most importantly: re-organize, rethink and redesign data, rather than squeezing a multi-column table layout in a narrow mobile space. Useful resources: Data Grids and Tables Figma Kits, by Goldman Sachs https://www.figma.com/@gs How To Design Data Tables (+ Figma Kits), by Jordan Hughes https://lnkd.in/eAVuzbfw Designing A Complex Table For Mobile, by Joe Winter 🏳️🌈 https://lnkd.in/eeKVfKR5 How Screen Readers Navigate Data Tables, by Léonie Watson https://lnkd.in/eCQRrz6c Enterprise UX: Data Tables, by Stéphanie Walter https://lnkd.in/eCQRrz6c Architecting A Complex Data Table (+ Features Tree), by Slava Shestopalov https://lnkd.in/eWSZqHWt --- 👋🏼 I'm Vitaly Friedman, and you can find useful UX resources on my profile. I’m also running “Smart Interface Design Patterns” 🍣 (https://lnkd.in/epY4RmXR) with a friendly video library and live UX training. 😊 #ux #design

A couple of news items have me thinking. And frankly, getting a bit agitated. The first was the news that the Kiwisaver gender gap has got worse in the past year. New research from Te Ara Ahunga Ora The Retirement Commission shows a 36 percent gap between the amount men and women are putting into KiwiSaver each year, far outpacing the actual gender pay gap. Men and women are contributing the same percentage of their salaries, but women are disadvantaged by working part-time and taking greater (unpaid) care responsibilities. The other bit of not-unrelated news, is the NZ Herald’s list of top-earning CEOs. Of the top 10 - just one woman. In the 54 CEOs surveyed: seven women. In the immortal words of Carrie Bradshaw: I couldn’t help but wonder… WTF is going on here? How have we not come further? Of those top 10 CEO’s companies, how many are reporting on their gender pay gaps? (The answer, according to the Mind the Gap registry: 4) Is there a relationship between perimenopause/menopause support (or lack of it) and the lack of women in CEO roles in our top organisations? AND between perimenopause/menopause and the Kiwisaver gender gap? I think there might be. We know, for example, from the work of Sarah Hogan who found in her NZIER research that 14% of women said they had to reduce their working hours to manage their menopause symptoms, and 6% had changed roles. Twenty percent of women who experienced symptoms said it would have been helpful to be able to make adjustments, but they never requested any, mostly because of menopause and gendered ageism stigma. All of us who are working in menopause education have heard stories from women who - at a critical stage in their careers in midlife - have made the call to step back rather than step up into senior roles, because of the challenges of menopause and the lack of support for them in their organisations. We have to talk more about this. In fifty years we’ve made so little progress… we REALLY don’t want our granddaughters to be still facing these kinds of shocking statistics in fifty years’ time. 

Google DeepMind’s AI Co-Scientist paper was just released, and you should check it out! It represents a paradigm shift in scientific discovery, leveraging a multi-agent system built on Gemini 2.0 to autonomously generate, refine, and validate new research hypotheses. 🔹How does it work? Well the system uses a generate, debate, and evolve framework, where distinct agents called Generation, Reflection, Ranking, Evolution, Proximity, and Meta-Review, collaborate in an iterative hypothesis refinement loop. 🔹Some key innovations that pop out include an asynchronous task execution framework, which enables dynamic allocation of computational resources, and a tournament-based Elo ranking system that continuously optimizes hypothesis quality through simulated scientific debates. 🔹The agentic orchestration accelerates hypothesis validation for processes that take humans decades in some instance. For example empirical validation in biomedical applications, such as drug repurposing for acute myeloid leukemia (AML) and epigenetic target discovery for liver fibrosis, quickly helped researchers generate clinically relevant insights. What should we all get from this? 🔸Unlike traditional AI-assisted research tools, AI Co-Scientist doesn’t summarize existing knowledge but instead proposes experimentally testable, original hypotheses, fundamentally reshaping the research paradigm by acting as an intelligent collaborator that augments human scientific inquiry. Do take some time this Sunday to read! #genai #technology #artificialintelligence

My colleague Prof. Eleanor Maguire passed away this weekend after a long battle with cancer. Her contributions to #neuroscience have shaped how we understand memory and navigation, leaving a lasting legacy. One of Eleanor’s groundbreaking discoveries was that when a London taxi driver learns the 25,000 windy streets of London together with thousands of landmarks (collectively called “the Knowledge”), it physically changes their #brain. A part of the brain called the #hippocampus is important both for making new memories and for navigating one’s environment. For aspiring black cab drivers, learning the Knowledge pushes the hippocampus to adapt in remarkable ways. Eleanor and her colleagues used #MRI to measure the hippocampus in taxi drivers compared to a control group and discovered it was larger in the taxi drivers. In other words, London cabbies have special brains that are particularly well suited for their work. This raises a really interesting question: Are they born with a larger hippocampus and therefore better able to become taxi drivers or does learning the Knowledge change their brains? To answer this, Eleanor and her team ran a follow-up study where they followed 39 trainee taxi drivers from the beginning of their training to when qualified approximately 4 years later. Each received a brain scan at the beginning and end of their training. 👉 Before training, the aspiring taxi drivers showed no difference in hippocampus size compared to matched control volunteers. 👉 After training, the newly qualified taxi drivers were found to have larger hippocampi than they did 4 years ago and also larger than the control volunteers. In other words, even as an adult, learning the Knowledge has a strong effect on the brain that can be measured using MRI. Eleanor’s work has become one of the most well-known examples of #neuroplasticity, which is the brain’s remarkable ability to change and adapt throughout life. A few years ago, a group of students were visiting UCL’s Functional Imaging Lab. They had learned about her taxi study in their A-level psychology class so when they discovered that Eleanor worked there, there was a frenzy of excitement! They couldn’t believe that they got to meet the “Maguire” whose work they had read in school. It was absolutely charming! Although best known for work with taxi drivers, Eleanor made substantial contributions to memory and hippocampal function including: 👉 Discovering that patients with amnesia cannot imagine the future 👉 Showing that it is possible to decode individual memories by analysing patterns of activity in the hippocampus 👉 Clarifying the relation between memory for life episodes, the ability to imagine the future, and the ability to navigate spatial environments Eleanor’s work is a powerful reminder of the brain’s potential to adapt and grow throughout life. May her legacy inspire all of us to keep learning and exploring the frontiers of science.

The technologies of the future are created and commercialized in innovation hubs that combine scientific excellence with entrepreneurial ambition. There are thousands of such hubs around the world, and our Global Innovation Index (GII) 2025 seeks to shine a light on those doing well through the GII Ranking of World’s Top 100 Innovation Clusters. For the first time, we have included VC data alongside international patent filings and scientific publications. Adding the VC lens has shifted the top of the table slightly, helping to push China’s Greater Bay Area into number one spot, nudging the Tokyo-Yokohama cluster into second, and lifting Silicon Valley from sixth to third spot this year. Beijing was ranked fourth. Each of those clusters led in a different way. Tokyo-Yokohama was the single biggest source of international patent filings, while the Silicon Valley cluster (around San Jose and San Francisco) attracted more venture capital than anywhere else. Beijing led the world in terms of the number of scientific publications. The Greater Bay Area, which encompasses Shenzhen, Hong Kong and Guangzhou, did not lead in any of the three categories, but its strong showings across the board gave it a balanced profile and put it in first place overall. This cluster ranking, as well as our flagship Global Innovation Index (out on 16 September), is designed to help policymakers, business leaders and researchers better understand the local and global innovation landscape, and to design policies that make innovation ecosystems more vibrant. 33 economies are covered by our list of the top 100 clusters, including Germany (which has seven clusters), India and the United Kingdom (four each) and Canada and the Republic of Korea (which has three, like Japan). Propelled by the new methodology and strong performance in VC deals, Indian clusters have made remarkable advancements, with Bengaluru jumping from 56th to 21st position, Delhi to 26th (compared to 63rd) and Mumbai to 46th (compared to 88th). In addition to the dynamic hubs in China and India, six vibrant innovation hubs from middle-income countries also feature in the top 100: Brazil (São Paulo), Egypt (Cairo – the top-100 cluster in Africa), Iran (Tehran), Malaysia (Kuala Lumpur), Türkiye (Istanbul) and Mexico (Mexico City) – which enters the top 100 this year for the first time and makes up the second innovation cluster within Latin America. Outside the top 100, some of the leading middle-income economy innovation clusters are Ankara (Türkiye), Bangkok (Thailand), Buenos Aires (Argentina), Islamabad and Lahore (Pakistan), and Rio De Janeiro and Porto Alegre (Brazil). These clusters show how the combination of strategic investments coupled with supportive policy frameworks can build thriving ecosystems. More: https://lnkd.in/e882jzRp #WIPO #GlobalInnovationIndex #GII2025