The coin, housed at The Hunterian collection at the University of Glasgow, was among a handful of coins of the same design unearthed in Transylvania, in present-day Romania, in 1713. They have been regarded as fakes since the mid-19^th-century, due to their crude, strange design features and jumbled inscriptions.

In the new study, published in PLOS ONE, researchers compared the Sponsion coin with other Roman coins kept at The Hunterian, including two that are known to be genuine.

They found minerals on the coin’s surface that were consistent with it being buried in soil over a long period of time, and then exposed to air. These minerals were cemented in place by silica — cementing that would naturally occur over a long time in soil. The team also found a pattern of wear and tear that suggested the coin had been in active circulation.

Lead author Professor Paul N. Pearson (UCL Earth Sciences) said: “Scientific analysis of these ultra-rare coins rescues the emperor Sponsian from obscurity. Our evidence suggests he ruled Roman Dacia, an isolated gold mining outpost, at a time when the empire was beset by civil wars and the borderlands were overrun by plundering invaders.”

The Roman province of Dacia, a territory overlapping with modern-day Romania, was a region prized for its gold mines. Archaeological studies have established that the area was cut off from the rest of the Roman empire in around 260 CE. Surrounded by enemies, Sponsian may have been a local army officer forced to assume supreme command during a period of chaos and civil war, protecting the military and civilian population of Dacia until order was restored, and the province evacuated between 271 and 275 CE.

Coinage has always been an important symbol of power and authority. Recognising this and unable to receive official issues from the mint in Rome, Sponsian seems to have authorised the creation of locally produced coins, some featuring an image of his face, to support a functioning economy in his isolated frontier territory.

When the coins were discovered in the early 18th century, they were thought to be genuine and classed alongside other imitations of Roman coins made beyond the fringes of the empire. However, from the mid-19th century, attitudes changed. Coins from the hoard were dismissed as fakes because of the way they looked. This has been the accepted view until now.

The new study is the first time scientific analysis has been undertaken on any of the Sponsian coins. The research team used powerful microscopes in visible and ultraviolet light, as well as scanning electron microscopy and spectroscopy — studying how light at different wavelengths is absorbed or reflected — to study the coins’ surface.

Only four coins featuring Sponsian are known to have survived to the present day, all apparently originally from the 1713 hoard. Another is in Brukenthal National Museum in Sibiu, Romania. High magnification microscopic analysis performed there, following the research on the coin at The Hunterian, has revealed similar evidence of authenticity.

Curator of Numismatics at The Hunterian, Jesper Ericsson, said: “This has been a really exciting project for The Hunterian and we’re delighted that our findings have inspired collaborative research with museum colleagues in Romania. Not only do we hope that this encourages further debate about Sponsian as a historical figure, but also the investigation of coins relating to him held in other museums across Europe.”

The interim manager of the Brukenthal National Museum, Alexandru Constantin Chituță, said: “For the history of Transylvania and Romania in particular, but also for the history of Europe in general, if these results are accepted by the scientific community they will mean the addition of another important historical figure in our history.

“It is a wonderful thing for the Brukenthal National Museum, because the museum in Sibiu, Romania, is the holder of the only known coin belonging to Sponsian from the territory of Romania. I would like to express my gratitude to the colleagues from the Brukenthal Național Museum — History Museum Altemberger House and especially to the leader of the scientific team, Professor Paul N. Pearson from UCL, for their commitment, hard work and their impressive result.”

Four gold coins analysed by researchers, including the Sponsian coin and other Roman coins previously dismissed as forgeries, are on display in The Hunterian at the University of Glasgow, while the Sponsian coin in the Brukenthal National Museum is also on public display.

However, using real image data can raise practical and ethical concerns: The images could run afoul of copyright laws, violate people’s privacy, or be biased against a certain racial or ethnic group. To avoid these pitfalls, researchers can use image generation programs to create synthetic data for model training. But these techniques are limited because expert knowledge is often needed to hand-design an image generation program that can create effective training data.

Researchers from MIT, the MIT-IBM Watson AI Lab, and elsewhere took a different approach. Instead of designing customized image generation programs for a particular training task, they gathered a dataset of 21,000 publicly available programs from the internet. Then they used this large collection of basic image generation programs to train a computer vision model.

These programs produce diverse images that display simple colors and textures. The researchers didn’t curate or alter the programs, which each comprised just a few lines of code.

The models they trained with this large dataset of programs classified images more accurately than other synthetically trained models. And, while their models underperformed those trained with real data, the researchers showed that increasing the number of image programs in the dataset also increased model performance, revealing a path to attaining higher accuracy.

“It turns out that using lots of programs that are uncurated is actually better than using a small set of programs that people need to manipulate. Data are important, but we have shown that you can go pretty far without real data,” says Manel Baradad, an electrical engineering and computer science (EECS) graduate student working in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and lead author of the paper describing this technique.

Co-authors include Tongzhou Wang, an EECS grad student in CSAIL; Rogerio Feris, principal scientist and manager at the MIT-IBM Watson AI Lab; Antonio Torralba, the Delta Electronics Professor of Electrical Engineering and Computer Science and a member of CSAIL; and senior author Phillip Isola, an associate professor in EECS and CSAIL; along with others at JPMorgan Chase Bank and Xyla, Inc. The research will be presented at the Conference on Neural Information Processing Systems.

Rethinking pretraining

Machine-learning models are typically pretrained, which means they are trained on one dataset first to help them build parameters that can be used to tackle a different task. A model for classifying X-rays might be pretrained using a huge dataset of synthetically generated images before it is trained for its actual task using a much smaller dataset of real X-rays.

These researchers previously showed that they could use a handful of image generation programs to create synthetic data for model pretraining, but the programs needed to be carefully designed so the synthetic images matched up with certain properties of real images. This made the technique difficult to scale up.

In the new work, they used an enormous dataset of uncurated image generation programs instead.

They began by gathering a collection of 21,000 images generation programs from the internet. All the programs are written in a simple programming language and comprise just a few snippets of code, so they generate images rapidly.

“These programs have been designed by developers all over the world to produce images that have some of the properties we are interested in. They produce images that look kind of like abstract art,” Baradad explains.

These simple programs can run so quickly that the researchers didn’t need to produce images in advance to train the model. The researchers found they could generate images and train the model simultaneously, which streamlines the process.

They used their massive dataset of image generation programs to pretrain computer vision models for both supervised and unsupervised image classification tasks. In supervised learning, the image data are labeled, while in unsupervised learning the model learns to categorize images without labels.

Improving accuracy

When they compared their pretrained models to state-of-the-art computer vision models that had been pretrained using synthetic data, their models were more accurate, meaning they put images into the correct categories more often. While the accuracy levels were still less than models trained on real data, their technique narrowed the performance gap between models trained on real data and those trained on synthetic data by 38 percent.

“Importantly, we show that for the number of programs you collect, performance scales logarithmically. We do not saturate performance, so if we collect more programs, the model would perform even better. So, there is a way to extend our approach,” Manel says.

The researchers also used each individual image generation program for pretraining, in an effort to uncover factors that contribute to model accuracy. They found that when a program generates a more diverse set of images, the model performs better. They also found that colorful images with scenes that fill the entire canvas tend to improve model performance the most.

Now that they have demonstrated the success of this pretraining approach, the researchers want to extend their technique to other types of data, such as multimodal data that include text and images. They also want to continue exploring ways to improve image classification performance.

“There is still a gap to close with models trained on real data. This gives our research a direction that we hope others will follow,” he says.

Academics from the Universities of Cambridge and Manchester analysed the well-being and self-esteem of more than 11,000 young people from across the UK, using data collected when they were 11, and again when they were 14. The adolescents’ overall ‘subjective well-being’ — their satisfaction with different aspects of life (such as friends, school and family) — dropped significantly during the intervening years.

It is widely accepted that young people’s well-being and mental health are influenced by factors such as economic circumstances and family life. The research shows that notwithstanding this, well-being tends to fall steeply and across the board during early adolescence.

That decline is probably linked to the transition to secondary school at age 11. The study identified that the particular aspects of well-being which changed in early adolescence were typically related to school and peer relationships, suggesting a close connection with shifts in these young people’s academic and social lives.

In addition, students with higher self-esteem at age 11 experienced a less significant drop in well-being at age 14. This indicates that structured efforts to strengthen adolescents’ self-esteem, particularly during the first years of secondary school, could mitigate the likely downturn in well-being and life satisfaction.

Ioannis Katsantonis, a doctoral researcher at the Faculty of Education, University of Cambridge, who led the study said: “Even though this was a large, diverse group of adolescents, we saw a consistent fall in well-being. One of the most striking aspects was the clear association with changes at school. It suggests we urgently need to do more to support students’ well-being at secondary schools across the UK.”

Ros McLellan, Associate Professor at the University of Cambridge, specialist in student well-being, and co-author, said: “The link between self-esteem and well-being seems especially important. Supporting students’ capacity to feel positive about themselves during early adolescence is not a fix-all solution, but it could be highly beneficial, given that we know their well-being is vulnerable.”

Globally, adolescent well-being is in decline. In the UK, the Children’s Society has shown that 12% of young people aged 10 to 17 have poor well-being. Dr Jose Marquez, a Research Associate at the Institute of Education, University of Manchester, and co-author, said: “Until now, we haven’t fully understood how universally poor well-being is experienced. The relationship between well-being and self-esteem has also been unclear.”

The researchers used data from the Millennium Cohort Study, which involves a nationally representative sample of people born between 2000 and 2002 and incorporates standard questionnaires about well-being and self-esteem. They then calculated a well-being ‘score’ for each student, balanced to control for other factors that influence well-being — such as economic advantage, bullying, and general feelings of safety.

While most adolescents were satisfied with life at age 11, the majority were extremely dissatisfied by age 14. By that age, the well-being scores of 79% of the participants fell below what had been the average score for the entire group three years earlier. “This is a statistically significant drop,” Katsantonis said. “It goes far beyond anything we would classify as moderate.”

The study also captured information about the adolescents’ satisfaction with specific aspects of their lives, such as schoolwork, personal appearance, family and friends. This suggested that the most dramatic downturns between 11 and 14 were probably related to school and relationships with peers.

Despite the overall fall, students with better well-being at age 14 tended to be those who had higher self-esteem at age 11. The pattern did not apply in reverse, however: better well-being at age 11 did not predict better self-esteem later. This implies a causal link in which self-esteem seems to protect adolescents from what would otherwise be sharper declines in well-being.

“Supporting self-esteem is not the only thing we need to do to improve young people’s well-being,” Katsantonis said. “It should never, for example, become an excuse not to tackle poverty or address bullying — but it can be used to improve young people’s life satisfaction at this critical stage.”

The researchers identify various ways in which schools could support this. At a basic level, Katsantonis suggested that celebrating students’ achievements, underlining the value of things they had done well, and avoiding negative comparisons with other students, could all help.

More strategically, the study suggests incorporating more features that promote self-esteem into England’s well-being curriculum, and stresses the need to ensure that similar efforts are made across the UK. Recent studies have, for example, highlighted the potential benefits of mindfulness training in schools, and of ‘positive psychology’ initiatives which teach adolescents to set achievable personal goals, and to acknowledge and reflect on their own character strengths.

McLellan added: “It’s really important that this is sustained — it can’t just be a case of doing something once when students start secondary school, or implementing the odd practice here and there. A concerted effort to improve students’ sense of self-worth could have really positive results. Many good teachers are doing this already, but it is perhaps even more important than we thought.”

“The computational model and toolkit we developed could pave the way toward mass-manufacturable, sustainable optical devices and more efficient light harvesting tools that are based on diatom shells,” said research team member Santiago Bernal from McGill University in Canada. “This could be used for biomimetic devices for sensing, new telecommunications technologies or affordable ways to make clean energy.”

Diatoms are single-celled organisms found in most bodies of water. Their shells are covered in holes that respond to light differently depending on their size, spacing and configuration. In the journal Optical Materials Express, the researchers, led by McGill University’s David V. Plant and Mark Andrews, report the first optical study of an entire diatom shell. They analyzed how different sections of the shell, or frustule, respond to sunlight and how this response is connected to photosynthesis.

“Based on our findings, we estimate that the frustule can contribute a 9.83 percent boost to photosynthesis, especially during transitions from high to low sunlight,” said Yannick D’Mello, first author of the paper. “Our model is the first to explain the optical behavior of the entire frustule. So, it contributes to the hypothesis that the frustule enhances photosynthesis in diatoms.”

Combining microscopy and simulation

Diatoms have evolved for millions of years to survive in any aquatic environment. This includes their shell, which is composed of many regions that work together to harvest sunlight. To study the optical response of diatom frustules, the researchers combined computer optical simulations with several microscopy techniques.

The researchers began by imaging the architecture of the frustule using four high-resolution microscopy techniques: scanning near-field optical microscopy, atomic force microscopy, scanning electron microscopy and dark field microscopy. They then used these images to inform a series of models that the researchers built to analyze each part of the frustule via 3D simulations.

Using these simulations, the researchers examined how different colors of sunlight interacted with the structures and identified three primary solar harvesting mechanisms: capture, redistribution and retention. This approach allowed them to combine the different optical aspects of the frustule and show how they work together to aid photosynthesis.

“We used different simulations and microscopy techniques to examine each component separately,” said D’Mello. “We then used that data to build a study of how light interacts with the structure, from the moment it gets captured, to where it gets distributed after that, how long it is retained, and until the moment it likely gets absorbed by the cell.”

Boosting photosynthesis

The study revealed that the wavelengths with which the shell interacted coincided with those absorbed during photosynthesis, suggesting it could have evolved to help capture sunlight. The researchers also found that different regions of the frustule could redistribute light to be absorbed across the cell. This suggests that the shell evolved to maximize the exposure of the cell to ambient light. Their findings also indicated that the light circulates inside the frustule long enough to aid photosynthesis during periods of transition from high to low illumination.

The new frustule model could make it possible to cultivate diatom species that harvest light at different wavelengths, allowing them to be customized for specific applications. “These light harvesting mechanisms of diatoms could be used to improve the absorption of solar panels by allowing sunlight to be collected at more angles, therefore partially removing the dependency of the panel to directly face the sun,” said Bernal.

The researchers are now working to refine their model and plan to apply their new toolkit to study other species of diatoms. After that, they plan to extend the model beyond the light interactions within a single frustule to examine behaviors between multiple frustules.

This work commemorates Dan Petrescu, who passed away last year. The research would not have been possible without his insights, assistance and dedication.

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“Our technique uses embroidery, which is pretty simple — you can stitch our yarns directly on the fabric,” said the study’s lead author Rong Yin, assistant professor of textile engineering, chemistry and science at North Carolina State University. “During fabric production, you don’t need to consider anything about the wearable devices. You can integrate the power-generating yarns after the clothing item has been made.”

In the study published in Nano Energy, researchers tested multiple designs for power-generating yarns. To make them durable enough to withstand the tension and bending of the embroidery stitching process, they ultimately used five commercially available copper wires, which had a thin polyurethane coating, together. Then, they stitched them onto cotton fabric with another material called PTFE.

“This is a low-cost method for making wearable electronics using commercially available products,” Yin said. “The electrical properties of our prototypes were comparable to other designs that relied on the same power generation mechanism.”

The researchers relied on a method of generating electricity called the “triboelectric effect,” which involves harnessing electrons exchanged by two different materials, like static electricity. They found the PTFE fabric had the best performance in terms of voltage and current when in contact with the polyurethane-coated copper wires, as compared to other types of fabric that they tested, including cotton and silk. They also tested coating the embroidery samples in plasma to increase the effect.

“In our design, you have two layers — one is your conductive, polyurethane-coated copper wires, and the other is PTFE, and they have a gap between them,” Yin said. “When the two non-conductive materials come into contact with each other, one material will lose some electrons, and some will get some electrons. When you link them together, there will be a current.”

Researchers tested their yarns as motion sensors by embroidering them with the PTFE fabric on denim. They placed the embroidery patches on the palm, under the arm, at the elbow and at the knee to track electrical signals generated as a person moves. They also attached fabric with their embroidery on the insole of a shoe to test its use as a pedometer, finding their electrical signals varied depending on whether the person was walking, running or jumping.

Lastly, they tested their yarns in a textile-based numeric keypad on the arm, which they made by embroidering numbers on a piece of cotton fabric, and attaching them to a piece of PTFE fabric. Depending on the number that the person pushed on the keypad, they saw different electrical signals generated for each number.

“You can embroider our yarns onto clothes, and when you move, it generates an electrical signal, and those signals can be used as a sensor,” Yin said. “When we put the embroidery in a shoe, if you are running, it generates a higher voltage than if you were just walking. When we stitched numbers onto fabric, and press them, it generates a different voltage for each number. It could be used as an interface.”

Since textile products will inevitably be washed, they tested the durability of their embroidery design in a series of washing and rubbing tests. After hand washing and rinsing the embroidery with detergent, and drying it in an oven, they found no difference or a slight increase in voltage. For the prototype coated in plasma, they found weakened but still superior performance compared with the original sample. After an abrasion test, they found that there was no significant change in electrical output performance of their designs after 10,000 rubbing cycles.

In future work, they plan to integrate their sensors with other devices to add more functions.

“The next step is to integrate these sensors into a wearable system,” Yin said.

The study, “Flexible, durable and washable triboelectric yarn and embroidery for self-powered sensing and human-machine interaction,” was published online in Nano Energy. Co-authors included Yu Chen, Erdong Chen, Zihao Wang, Yali Ling, Rosie Fisher, Mengjiao Li, Jacob Hart, Weilei Mu, Wei Gao, Xiaoming Tao and Bao Yang. Funding was provided by North Carolina State University through the NC State Faculty Research & Professional Development Fund and the NC State Summer REU program.

“Fetal MRI is a highly specialized and safe examination method that allows us to make accurate statements about brain maturation prenatally,” said study senior author Gregor Kasprian, M.D., associate professor of radiology from the Department of Biomedical Imaging and Image-guided Therapy of the Medical University of Vienna in Austria.

Alcohol consumption during pregnancy can expose the fetus to a group of conditions called fetal alcohol spectrum disorders. Babies born with fetal alcohol spectrum disorders could develop learning disabilities, behavioral problems or speech and language delays.

“Unfortunately, many pregnant women are unaware of the influence of alcohol on the fetus during pregnancy,” said lead author Patric Kienast, M.D., a Ph.D. student in the Department of Biomedical Imaging and Image-Guided Therapy, Division of Neuroradiology and Musculoskeletal Radiology at the Medical University of Vienna. “Therefore, it is our responsibility not only to do the research but also to actively educate the public about the effects of alcohol on the fetus.”

For the study, researchers analyzed MRI exams of 24 fetuses with prenatal alcohol exposure. The fetuses were between 22 and 36 weeks of gestation at the time of MRI. Alcohol exposure was determined via anonymous surveys of the mothers. The questionnaires used were the Pregnancy Risk Assessment Monitoring System (PRAMS), a surveillance project of the Centers for Disease Control and Prevention and health departments, and the T-ACE Screening Tool, a measurement tool of four questions that identify risk drinking.

In fetuses with alcohol exposure, the fetal total maturation score (fTMS) was significantly lower than in the age-matched controls, and the right superior temporal sulcus (STS) was shallower. The STS is involved in social cognition, audiovisual integration and language perception.

“We found the greatest changes in the temporal brain region and STS,” Dr. Kasprian said. “We know that this region, and specifically the formation of the STS, has a great influence on language development during childhood.”

Brain changes were seen in the fetuses even at low levels of alcohol exposure.

“Seventeen of 24 mothers drank alcohol relatively infrequently, with average alcohol consumption of less than one alcoholic drink per week,” Dr. Kienast said. “Nevertheless, we were able to detect significant changes in these fetuses based on prenatal MRI.”

Three mothers drank one to three drinks per week, and two mothers drank four to six drinks per week. One mother consumed an average of 14 or more drinks per week. Six mothers also reported at least one binge drinking event (exceeding four drinks on one occasion) during pregnancy.

According to the researchers, delayed fetal brain development could be specifically related to a delayed stage of myelination and less distinct gyrification in the frontal and occipital lobes.

The myelination process is critical to brain and nervous system function. Myelin protects nerve cells, allowing them to transmit information faster. Important developmental milestones in infants, as rolling over, crawling and language processing are directly linked to myelination.

Gyrification refers to the formation of the folds of the cerebral cortex. This folding enlarges the surface area of the cortex with limited space in the skull, enabling an increase in cognitive performance. When gyrification is diminished, functionality is reduced.

“Pregnant women should strictly avoid alcohol consumption,” Dr. Kienast said. “As we show in our study, even low levels of alcohol consumption can lead to structural changes in brain development and delayed brain maturation.”

It is unclear how these structural changes will affect brain development in these babies after birth.

“To assess this accurately, we need to wait for the children who were examined as fetuses at that time to get a little older, so that we can invite them back for further examinations,” Dr. Kienast said. “However, we can strongly assume that the changes we discovered contribute to the cognitive and behavioral difficulties that may occur during childhood.”

Co-authors are Marlene Stuempflen, M.D., Daniela Prayer, M.D., Benjamin Sigl, M.D., Mariana Schuette, M.D., Ph.D., and Sarah Glatter, M.D., M.M.Sc.