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Radialis: Organ-Targeted PET Imaging for Precision Medicine
Positron Emission Tomography (PET) is a medical imaging technique widely used to diagnose and monitor cancer patients. Before undergoing a PET scan, a clinician injects radiotracers into a patient’s bloodstream, which accumulate in different tissues. These radiotracers emit radiation that can be detected by the PET scanner, resulting in an image that shows their distribution throughout the body. By analyzing the images, a clinician can identify problematic tissues based on differences in radiotracer distribution. For example, certain radiotracers accumulate more in cancer cells, meaning that tumors appear brighter on a PET image. Unfortunately, PET scans expose patients to potentially harmful amounts of ionizing radiation.
Professor Kathryn Toghill | Storing Renewable Energy by Converting Carbon Dioxide to Formic Acid
Before they can replace fossil fuels entirely, wind and solar power plants will need to provide electricity to the grid at all times of the day, and in unpredictable weather conditions. To ensure a consistent output, renewable sources can be coupled with energy-storing batteries. Ideally, these batteries can be charged up when excess energy is generated, and then release their energy when the grid’s demand for power outpaces its supply. However, even the most well-designed battery systems only have a limited storage capacity. If this limit is exceeded, any excess energy will simply be wasted. One possible solution to this problem is to combine electrical batteries with chemical energy storage.
Dr Lars Wojtecki | Treating Alzheimer’s Disease with a New Brain Stimulation Technique
Alzheimer’s disease is a brain disorder that causes problems with memory, mood, and the ability to perform daily activities. Although there are medicines available to ease the symptoms of Alzheimer’s, there is currently no cure. Therefore, patients slowly deteriorate over time due to neural damage that prevents the exchange of messages between cells. The search for a treatment to slow or even reverse the progression of the disease is ongoing. Recently, a new type of brain-stimulation therapy, called transcranial pulse stimulation, or TPS, has been approved for use in Alzheimer’s patients.
Professor Zhiliang Zhang | The Super-tough Coating that Repels Ice
Ice can cause serious damage to vehicles and infrastructure, including aircraft, pavements, power lines, and wind turbines. It is important to remove ice before it causes damage, but doing this manually is often expensive and energy-intensive, and sometimes even dangerous. Researchers have begun to develop so-called ‘super-hydrophobic’ coatings, which can repel incoming water droplets before they freeze. This not only prevents ice from building up; it also weakens the adhesion of ice that does freeze to the surface, allowing it be removed more easily.
RECROP COST Action: Ensuring Crop Resilience in Extreme Climate Conditions
In a world increasingly shaped by extreme climate conditions, our agricultural systems face unprecedented threats. Rising temperatures, prolonged droughts, and intense rainfall events put immense pressure on crops, especially during their most vulnerable stage: reproduction. Plant reproduction is crucial for producing the seeds and fruits that form the backbone of our food supply. Yet, extreme weather can disrupt this delicate process, leading to reduced yields and threatening global food security. RECROP, a visionary COST Action consortium, is dedicated to addressing these challenges.
Dr Xavier Alameda-Pineda | Evaluating the Potential of Social Robots in Geriatric Healthcare
Social robots will become increasingly widespread in the coming decades. So far, they have only been introduced in a few real-world environments, including some airports, museums, and hospitals. Dr Xavier Alameda-Pineda at Inria, the French National Institute for Research in Digital Science and Technology, and all the partners of the Horizon 2020 SPRING project recently set out to evaluate the potential of social robots in the context of geriatric healthcare.
GenBench: Mapping out the Landscape of Generalization Research
From ChatGPT to Google Gemini, large language models are now increasingly important in our everyday lives. These models are part of the field of natural language processing – or ‘NLP’ – which studies how machines understand and generate human language. Most NLP systems are built using machine learning, and vast amounts of language data are used as training material. Afterwards, a successfully trained model should be able to handle new scenarios. This ability is called ‘generalization’. For large language models that generalize well, a conversation about a topic it hasn’t been trained on, such as new scientific discoveries, should not be a problem.
Professor Erik Folven | Gaining Tighter Control Over Artificial Spin Ices for Technological Applications
The energy demands required to operate our increasingly connected society is unsustainable. Data-centres, the Internet of Things, and Artificial Intelligence all create unsustainable power demands. As such, new energy-efficient technologies are needed to fulfil humanity’s computing needs into the future. Spin-based technologies could greatly reduce the energy requirements of computing. One reason that such technologies are more energy efficient is that far less energy is wasted as heat. Additionally, computation and memory can both occur within the same spin-based device. One promising spin-based technology is artificial spin ice (ASI).
Dr Martin Haesemeyer | A Deep-learning Framework that Links Brain Activity with Behavior
Neuroscientists have been trying to uncover the relationships between brain activity and behavior for decades. Identifying these links could shed new light on the functions of different brain regions, while also highlighting possible therapeutic targets for psychological disorders. In recent years, researchers have gathered a vast amount of brain activity recordings alongside data describing the behavior of animals or humans while these recordings were collected. Recent advances in deep-learning algorithms have now opened new possibilities for analyzing this wide pool of data.
Dr Elif Miskioğlu – Dr Kaela Martin – Dr Adam Carberry | Fostering Intuition in Engineering Students to Solve 21st Century Challenges
Experienced engineers typically have advanced technical knowledge and unique skillsets. Many also develop impressive intuition through years of experience, which helps them to devise solutions to complex real-world problems. Cultivating such intuition in engineering students could better equip them to tackle humanity’s increasingly complex challenges. Before we can design classroom interventions that foster intuition in prospective engineers, we need methods that can reliably assess intuition. Using such methods, the effectiveness of a given intervention could be measured by assessing students’ intuition before and after they take part.
Damian Nowak – Adam Bachorz – Professor Marcin Hoffmann | Using Machine Learning to Discover New Medicines
Many researchers today are dedicated to the discovery of new medicines. Over the past few decades, their tireless efforts have culminated in a database of around 100 million known drug molecules. This value may already sound vast, but by current estimates, the true number of small drug-like molecules could actually range anywhere between 1023 – already more than the number of grains of sand on Earth – and 1060 – comparable to the number of atoms in an entire galaxy. With existing approaches, researchers ultimately need to test the medical potential of these molecules individually, taking up vast amounts of time and computing power.
Amit Kumar | A Circular Economy for Electric Vehicle Batteries
Electric vehicles – or EVs – are a cornerstone for curbing greenhouse gas emissions. They’re far better for the environment than their fossil-fuel-burning counterparts, but there’s one major catch: the toxic materials found in their batteries still present a serious environmental risk. So, how can we address this? By embracing a circular economy for EV batteries! In a circular economy, used batteries are repurposed for a second life, or are recycled to recover strategic raw materials, which can be processed further to manufacture new batteries. But before we get there, there are a number of hurdles to overcome.
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