It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Tuesday, June 17, 2025
Mealworms need more than plastic to be a nutritious food source
Mealworms need a minimum level of protein to grow and become a sustainable food source, according to a new study that challenges the myth that insects have superpowers of taking plastic waste and converting it to a nutritionally valuable product.
Nutritional scientists from the University of Nottingham have tested diets comprising protein and all other nutrients against those containing little and none, and found that whilst mealworms could survive eating no protein they do need a minimum amount of protein to grow and pupate. Their findings have been published in the Journal of Insects as Food and Feed.
The larvae of the beetle Tenebrio molitor (yellow mealworms) were studied, the insect’s main components are protein, fat and fibre giving them high nutritional value, and the potential to be a sustainable alternative protein source, which is likely to be as animal feed but is also being explored as a possible sustainable food source for humans.
These mealworms have the versatility of being able to grow on relatively low quality food sources, such as wheat bran and other cereals as well as industry by-products such as distiller’s grains and garden and vegetable waste.
Recent research has also shown certain types of mealworm can be fed on polystyrene. This new research shows that this is not enough to produce the levels of growth and nutrition required to provide a food source and that the crude protein and fat composition of mealworms varies considerably, dependent on the feed utilised.
To prove that a minimum level of nutrition is required the teams fed groups of mealworms different diets containing varying amounts of nutritional components and protein. Mealworms fed the protein-free diets appeared to halt growth and didn’t enter the pupation stage of their life-cycle which is vital for breeding. This casts considerable doubt of the value of substrates free of protein (such as plastics) as viable feed sources for commercial production of mealworms.
John Brameld, Professor of Nutritional Chemistry at the University of Nottingham said: “Our research is focused on mealworms as an effective and sustainable alternative source of protein, and we are trying to find the optimum composition of nutrients to achieve this. This research is an important step towards that as we now know that despite what previous research has suggested, mealworms need all nutrients, including protein to be able to grow and pupate. Eating plastics alone or another non-protein diet does allow them to survive, but doesn’t provide the nutrients needed for the mealworms to be used as food.”
Tim Parr, Professor in Nutritional Biochemistry added: “Understanding the miniumum nutritional requirements for production animals such as mealworms is a vital part of being able to move towards using them at scale as a nutritious alternative food source. We now have that baseline and know that protein is a key requirement, so we can build on this with further work to fine tune the nutritional density and quantities of feed until we find a formula that is optimal for growth of the mealworm and delivery of key nutrients in a way that is is cost effective and sustainable.”
Firms with progressive LGBTQ policies produce more patents, have more patent citations, and have higher innovation quality as measured by patent originality, generality, and internationality, says the study.
The quantity and quality of patents in large US firms gets a boost when they score highly across LGBTQ-friendly metrics.
LGBTQ-friendly policies can have a significant impact on innovation in major US firms, according to new research from Aalto University and the University of Vaasa. Existing studies have found a link between profitability and workplace diversity more generally, yet this is the first to specifically examine sexuality and gender-inclusivity as it relates to innovation.
Researchers used scores from the Corporate Equality Index (CEI) in conjunction with data from the US Patent and Trademark Office and public databases — on patent counts, citations, quality and the number of innovators in a firm — to evaluate the relationship between LGBTG-friendliness and innovation.
The findings were notable: for every standard deviation increase in a company’s CEI, the number of patents increased by 20 percent. LGBTQ-friendly firms also demonstrated an almost 25 percent increase in the number of patent citations (an indication of how other companies value the innovativeness of a patent).
‘Our results demonstrate that firms with progressive LGBTQ policies produce more patents, have more patent citations, and have higher innovation quality as measured by patent originality, generality, and internationality,’ says Jukka Sihvonen, from Aalto University School of Business.
The study spans from 2003-2017 and was just published this week in the peer-reviewed International Review of Financial Analysis. Furthermore, the research team has also processed additional data up until 2024, with indications that the positive trend may be intensifying over time, notes co-author Veda Fatmy, from the University of Vaasa.
Findings ‘not just a blue state phenomenon’
A range of analytical methods were used to control for bias, with a link between inclusivity and innovation presenting regardless of the differing political or societal context.
‘It’s not as politically polarised as one might think,’ says Sami Vähämaa, who also led the research. ‘The results get marginally stronger when most conservative states are excluded, but the difference is really minor, and the findings remain largely the same when the most liberal states are left out.’
‘This is not just a blue state phenomenon,’ adds Sihvonen.
With diversity, equity and inclusion (DEI) currently a subject of immense controversy in the US, the research brings crucial data to discussions around the impact of corporate policy in shaping effective business strategies.
‘Innovation is the fuel that drives both growth and profitability. Companies need innovation,’ says Sihvonen. ‘The magnitudes of impact linked to LGBTQ-friendliness are big — and that means that the economic significance is too.’
The full study ‘LGBTQ-friendly employee policies and corporate innovation’, published 16 June, 2025, is available here
See also the team’s 2022 study on the link between stock market valuation, financial performance and LGBTQ-friendly policies
LGBTQ-friendly employee policies and corporate innovation
Article Publication Date
16-Jun-2025
Pushing the limits of observation
A research team led by Peter Baum from the University of Konstanz aims to film and visualize previously hidden processes at the atomic level in space and time
Almost all the visible properties of the matter surrounding us are defined internally by the spatial arrangement of atoms and electrons. Any kind of process or mechanism that changes the structure of matter – for example a chemical reaction, an electronic switching process or the folding of a protein in our cells – is therefore based on the movement and reorganization of atoms and electrons. The time periods in which such reactions take place are incredibly short and can be in the femtosecond to attosecond range – a billionth of a billionth of a second. In terms of space, too, these movements are extremely small and in the order of nanometres or even picometres – trillionths of a metre.
Studying processes in these tiny spatial and temporal dimensions requires the most cutting-edge devices, such as an ultrafast electron microscope. Such apparatuses combine the very high spatial resolution of a traditional electron microscope with the temporal resolution of ultrashort laser pulses. A particularly high-resolution device, an attosecond electron microscope, which can even visualize the electrical oscillations of light, has been recently developed by Peter Baum's research group at the University of Konstanz. "So far, however, this method can only be used to measure processes that are specifically and decidedly excited with a high-energy laser pulse. We have not been able to observe reactions that are triggered electrically, magnetically or otherwise, processes which often occur in technical devices or natural environments", says Baum.
A new direction in ultrafast electron microscopy In their new project, funded with an Advanced Grant from the European Research Council (ERC) of 3.1 million euros, Baum and his team aim to develop new types of electron microscopes that will overcome this restriction. The researchers will apply specifically generated sequences and spatial patterns of ultrashort electron pulses. "We will generate several electrons using specially designed laser pulses and then control their spatial and temporal properties using terahertz radiation in order to make correlation measurements", Baum explains.
In this manner, researchers can conduct a controlled examination of almost any processes taking place in the object being analyzed. This should make it possible to observe the movements of atoms and electrons in more general ways than so far and to visualize processes in space and time that were not accessible until now. "With these new possibilities, we want to gain deeper insights into the fundamental mechanisms that determine material properties and transitions on atomic scales, and thus contribute to progress in the fields of nanotechnology, optics, materials science and quantum physics", Baum concludes.
About the ERC Advanced Grant The ERC Advanced Grant is one of the most prestigious and lucrative European research prizes. It recognizes and supports ambitious research projects by established scientists who have produced significant research achievements over a period of at least ten years. The funding period of the ERC Advanced Grants is five years; the maximum funding amount per research project is 2.5 million euros. In exceptional cases, higher funding amounts are possible.
Key facts:
Konstanz physicist Professor Peter Baum receives an Advanced Grant from the European Research Council (ERC) amounting to 3.1 million euros.
Research objective: advanced methods and developments in ultrafast electron microscopy for the purpose of studying previously unobservable processes at the atomic level.
“How can we balance real-time computation and communication in autonomous vehicles?” DGIST is developing a simulator to optimize the distribution of resources for autonomous driving
DGIST (Daegu Gyeongbuk Institute of Science and Technology)
Credit: Traffic-Cognitive Integrated Network-Computing Load Distribution Simulator
Through industry–academia collaboration, a joint research team consisting of professors Choi Ji-woong, Jwa Hoon-seung, and Kim Baek-gyu from the Department of Electrical Engineering and Computer Science at DGIST (President Kunwoo Lee) developed an Integrated Network-Computing Load Balancing (“INCL Balancing”) simulator optimized for next-generation 6G services. This is the world’s first research project to implement a load-balancing simulator that integrates network and computational resources in an autonomous driving environment. It is expected to markedly improve the safety, real-time control performance, and energy efficiency of autonomous vehicles linked to vehicular edge computing (VEC).
Currently, autonomous vehicle systems typically process all sensor data inside the vehicle or offload some data to a VEC server. However, in situations with high data collection and processing volumes, such as in urban traffic environments, bottlenecks in network and computing resources can occur in a complex manner, affecting the stability of autonomous driving. To deal with this problem, Prof. Choi Ji-woong’s team at DGIST collaborated with Prof. Kwak Jung-ho’s team at Korea University to design a simulator framework that integrates computational and communications resources between the onboard unit (OBU) in the vehicle, the VEC server, and the cloud server. On this basis, they also developed a dynamic offloading and dynamic voltage and frequency scaling (DVFS) algorithm.
The newly developed INCL Balancing simulator combines an autonomous driving simulator (Virtual Test Drive (VTD)) based on real-world road scenarios and a MATLAB-based network computing simulator. It enables real-time control by comprehensively considering network quality, computing resource status, and energy consumption based on changes in time and space.
Using eight scenarios reflecting real-world road conditions (e.g., platooning, road intersections, merging road lanes, and accident response) and real-world road data from Cheongna District, Incheon, the research team experimentally verified how effectively the proposed technology distributes traffic and computational load and reduces latency and power consumption compared with existing technologies.
In particular, the research team mathematically designed a load optimization algorithm that considers the reliability of the vehicle-to-vehicle communications link (Packet Delivery Ratio (PDR)), processing delay, and energy consumption. This ensures greater safety and performance than the existing fixed offloading method. Simulation results showed an average energy saving of 21.7% compared with a simple VEC offloading method and a 73.3% improvement in throughput rate compared with the existing cost-minimization-based algorithm. These results demonstrate the potential for substantial performance improvements in autonomous vehicles.
“This research is significant because it enables precise simulation-based analysis of the balance between latency, energy efficiency, and safety in an autonomous driving environment where communication and computational resources fluctuate in real time,” said Prof. Choi Ji-woong of DGIST. “It is expected to be widely applied to various 6G-based application services, such as highway platooning, smart city road intersection control, and emergency vehicle priority passage control, in the future. It can be utilized by autonomous driving operators, vehicle cloud platforms, and mobile communication operators and can also be extended to digital twin–based services.”
The research was conducted in collaboration with Seoul National University, Hanyang University, Hanbat National University, Korea University, the Korea National University of Transportation, iVH, and the Korea Intelligent Automotive Parts Promotion Institute for three years, and it was funded by the “Network Load Balancing Technology Development Based on Multiple Communication Technologies” project of the Institute for Information and Communication Technology Planning and Evaluation (IITP). The research results were published in June in IEEE Communications Magazine, the world’s leading journal in the communications field.
An Integrated Network-Computing Load Balancing Simulator for VEC-Assisted Autonomous Vehicles
A revolution for R&D with the missing link of machine learning — project envisions human-AI expert teams to solve grand challenges
Robust, deployable and collaborative machine learning (ML) methods are needed for AI to become truly useful. This ERC-funded research aims to solve a major ML bottleneck and will form a cornerstone of the newly established ELLIS Institute Finland
Real-world scientific research, for example, iteratively improves through learning in the design-build-test-learn loop (on the right). On the left, active re-learning from expert human knowledge in parallel with simulation in the design-build-test-loop. In combination, a solution for machine learning that can be robustly deployed ‘out-of-distribution’ i.e. outside of its learning context, which can lead to accelerated breakthroughs in R&D.
The founding director of the institute, Aalto University professor Samuel Kaskihas received the European Research Council Advanced Grant to develop new types of machine learning.
Many popular and widely available AI tools appear to be extremely versatile and agile, but there is still a hole in the underlying machine learning, argues Kaski. "The basic tenet of machine learning is to apply a model trained on a learning data set. But that only works if the set is representative of the deployment setting — and that seldom holds, because life happens. Unexpected factors, statistically speaking covariates or confounders, may kick in and drive the system outside the training distribution." These failures in ‘out-of-distribution’ deployment are precisely what Kaski’s five-year project aims to address.
An important example is scientific research and R&D process itself, where developing something new necessarily requires going outside the existing data. "Design processes involve a particularly important ingredient which I believe is necessary for introducing the missing link: domain expertise," explains Kaski. "Including the expert in the loop, while aiming to minimize their workload, may be a way around the out-of-distribution deployment problem—alternatives like collecting a lot of new data may be costly or even impossible."
"A very nice additional result would be that we may be able to improve the core element of all design problems, from scientific experimental design to product design, R&D or complex decision making: the design-build-test-learn loop," says Kaski. "If we can make this loop more effective, with machine learning and a human expert at the core, the cumulative impact could be massive."
A virtual, simulation-based laboratory, in which scientists receive AI assistance and part of the scientific process can be automated, is one example of how the new machine learning results can make ‘AI4Science’ a reality. The purpose of automation is not to remove scientists from the process or humans from the eventual output. "I am working towards a future where humans are involved one way or the other, and then the real, scientifically most interesting challenge is how do we automate with humans explicitly in the loop," says Kaski. "A part of the solution needs to be that the outputs are useful and make sense to users, whether they are scientific experts or people using AI assistants on their phones."
For AI to become an effective team player with humans, it needs to develop what psychologists call theory of mind—in R&D, this would mean an understanding of scientists’ often tacit objectives. Kaski believes that developing machine learning to better understand the scientist will unlock new solutions to tough R&D challenges.
"Some of the biggest problems society is facing today require truly interdisciplinary scientific teamwork. If we can engage humans and AI in the problem-solving loop, we can combine expertise, reasoning and optimal decision-making for groundbreaking outcomes." AI has to learn to understand that human teamwork is cooperative, iterative and adaptive, with shifting goals, feedback and consensus mechanisms. "We think we can make AI agents that can reason about and optimize over the behaviors of multiple experts," says Kaski.
Ultimately, the ERC-funded project is about making machine learning more applicable, which is also a key aim of ELLIS Institute Finland, the new research center that Kaski directs. A partnership of 13 Finnish universities, the institute is a recent major expansion of ELLIS, the European Laboratory for Learning and Intelligent Systems.
ELLIS Institute Finland is in the process of recruiting its first principal investigators and creating a cross-domain collaborative environment where academics and companies can advance fundamental research towards applications.
"I look forward to welcoming new colleagues to the ERC project and also to work in and collaborate with the ELLIS Institute," says Kaski. "We welcome our excellent colleagues and aspiring new AI and ML talent globally to work with us in Finland
How artificial delegates can help us act more socially – yet still fail to achieve collective goals
"Thinking that you can leave everything to technology without investing in it yourself is a dangerous illusion"
The study demonstrates that people who delegate their choices to artificial agents contribute more to the collective good, even when they have previously experienced negative outcomes or inequality. “What we observe is that, once people take a step back and allow a configurable AI to decide for them in a social dilemma, their contributions tend to be greater than when they make the decisions themselves,” explains Professor Tom Lenaerts. “They appear more willing to do their part—an interesting behavioural shift.”
Yet, this increased willingness does not translate into more successful group outcomes. Artificial tools are consistent but lack the human ability to adapt flexibly to the actions of others in the setting. “They struggle to respond effectively to unexpected circumstances or last-minute decisions. They are well-programmed, but not perfect,” Lenaerts notes.
Although the use of digital representatives encourages more positive behaviour, this alone is not sufficient to tackle complex group challenges effectively. The key lies in sustained human engagement in programming these representatives. “Delegating to these tools only works if people continue to think actively about how they are designed and configured,” Lenaerts emphasises. “The notion that we can simply hand everything over to technology without investing ourselves is a dangerous illusion.”
The findings reveal a crucial dilemma in the evolution towards increasingly digital decision-making: technology can amplify social intentions but does not guarantee collective success. In fields such as climate policy or public health, this could have far-reaching implications. “Artificial agents certainly have potential, but they are not a magical solution,” Lenaerts concludes. “If we want them to truly work in practice, we as humans must continue to take responsibility—not only in the decisions themselves but also in building the systems that make those decisions.”
The findings are part of the doctoral research conducted by Dr Ines Terrucha, in collaboration with both national and international researchers. The study was published under the title Humans program artificial delegates to accurately solve collective-risk dilemmas but lack precision in the scientific journal PNAS (Proceedings of the National Academy of Sciences USA).
