Computers Math

New study with 756 1st through 5th graders demonstrates that a six-week mashup of hoops and math has a positive effect on their desire to learn more, provides them with an experience of increased self-determination and grows math confidence among youth. The Basketball Mathematics study was conducted at five Danish primary and elementary schools by researchers from the University of Copenhagen’s Department of Nutrition, Exercise and Sports.
Over the past decades, there has been a considerable amount of attention paid to explore different approaches to stimulate children’s learning. Especially, there has been a focus on how physical activity, separated from the learning activities, can improve children’s cognitive performance and learning. Conversely, there has been less of a focus aimed at the potential of integrating physical activity into the learning activities. The main purpose of this study therefore was to develop a learning activity that integrates basketball and mathematics and examine how it might affect children’s motivation in mathematics.
Increased motivation, self-determination and mastery
756 children from 40 different classes at Copenhagen area schools participated in the project, where about half of the them — once a week for six weeks — had Basketball Mathematics during gym class, while the other half played basketball without mathematics.
“During classes with Basketball Mathematics, the children had to collect numbers and perform calculations associated with various basketball exercises. An example could be counting how many times they could sink a basket from three meters away vs. at a one-meter distance, and subsequently adding up the numbers. Both the math and basketball elements could be adjusted to suit the children’s levels, as well as adjusting for whether it was addition, multiplication or some other function that needed to be practiced,” explains Linn Damsgaard, who is writing her PhD thesis on the connection between learning and physical activity at the University of Copenhagen’s Department of Nutrition, Exercise and Sports.
The results demonstrate that children’s motivation for math integrated with basketball is 16% higher com-pared to classroom math learning. Children also experienced a 14% increase in self-determination compared with classroom teaching, while Basketball Mathematics increases mastery by 6% compared versus classroom-based mathematics instruction. Furthermore, the study shows that Basketball Mathematics can maintain children’s motivation for mathematics over a six-week period, while the motivation of the control group decreases significantly.
“It is widely acknowledged that youth motivation for schoolwork decreases as the school year progresses. Therefore, it is quite interesting that we don’t see any decrease in motivation when kids take part in Basketball Mathematics. While we can’t explain our results with certainty, it could be that Basketball Mathematics endows children with a sense of ownership of their calculations and helps them clarify and concretize abstract concepts, which in turn increases their motivation to learn mathematics through Basketball Mathematics,” says PhD student Linn Damsgaard
Active math on the school schedule
Associate Professor Jacob Wienecke of UCPH’s Department of Nutrition, Exercise and Sports, who supervised the study, says that other studies have proved the benefits of movement and physical activity on children’s academic learning. He expects for the results of Basketball Mathematics on children’s learning and academic performance to be published soon:
“We are currently investigating whether the Basketball Mathematics model can strengthen youth performance in mathematics. Once we have the final results, we hope that they will inspire school teachers and principals to prioritize more physical activity and movement in these subjects,” says Jacob Wienecke, who concludes:
“Eventually, we hope to succeed in having these tools built into the school system and the teacher’s education. The aim is that schools in the future will include “Active English” and “Active Mathematics” in the weekly schedule as subjects where physical education and subject-learning instructors collaborate to integrate this type of instruction with the normally more sedentary classwork.” More

A new algorithm can predict which genes cause cancer, even if their DNA sequence is not changed. A team of researchers in Berlin combined a wide variety of data, analyzed it with “Artificial Intelligence” and identified numerous cancer genes. This opens up new perspectives for targeted cancer therapy in personalized medicine and for the development of biomarkers.
In cancer, cells get out of control. They proliferate and push their way into tissues, destroying organs and thereby impairing essential vital functions. This unrestricted growth is usually induced by an accumulation of DNA changes in cancer genes — i.e. mutations in these genes that govern the development of the cell. But some cancers have only very few mutated genes, which means that other causes lead to the disease in these cases.
A team of researchers at the Max Planck Institute for Molecular Genetics (MPIMG) in Berlin and at the Institute of Computational Biology of Helmholtz Zentrum München developed a new algorithm using machine learning technology to identify 165 previously unknown cancer genes. The sequences of these genes are not necessarily altered — apparently, already a dysregulation of these genes can lead to cancer. All of the newly identified genes interact closely with well-known cancer genes and have been shown to be essential for the survival of tumor cells in cell culture experiments.
Additional targets for personalized medicine
The algorithm, dubbed “EMOGI” for Explainable Multi-Omics Graph Integration, can also explain the relationships in the cell’s machinery that make a gene a cancer gene. As the team of researchers headed by Annalisa Marsico describe in the journal Nature Machine Intelligence, the software integrates tens of thousands of data sets generated from patient samples. These contain information about DNA methylations, the activity of individual genes and the interactions of proteins within cellular pathways in addition to sequence data with mutations. In these data, a deep-learning algorithm detects the patterns and molecular principles that lead to the development of cancer.
“Ideally, we obtain a complete picture of all cancer genes at some point, which can have a different impact on cancer progression for different patients,” says Marsico, head of a research group at the MPIMG until recently and now at Helmholtz Zentrum München. “This is the foundation for personalized cancer therapy.”
Unlike with conventional cancer treatments such as chemotherapy, personalized therapy approaches tailor medication precisely to the type of tumor. “The goal is to select the best therapy for each patient — that is, the most effective treatment with the fewest side effects. Additionally, we would be able to identify cancers already at early stages, based on their molecular characteristics.” More

Ferroelectric materials are used in many devices, including memories, capacitors, actuators and sensors. These devices are commonly used in both consumer and industrial instruments, such as computers, medical ultrasound equipment and underwater sonars.
Over time, ferroelectric materials are subjected to repeated mechanical and electrical loading, leading to a progressive decrease in their functionality, ultimately resulting in failure. This process is referred to as ‘ferroelectric fatigue’.
It is a main cause of the failure of a range of electronic devices, with discarded electronics a leading contributor to e-waste. Globally, tens of millions of tonnes of failed electronic devices go to landfill every year.
Using advanced in-situ electron microscopy, the School of Aerospace, Mechanical and Mechatronic Engineering researchers were able to observe ferroelectric fatigue as it occurred. This technique uses an advanced microscope to ‘see’, in real-time, down to the nanoscale and atomic levels.
The researchers hope this new observation, described in a paper published in Nature Communications, will help better inform the future design of ferroelectric nanodevices.
“Our discovery is a significant scientific breakthrough as it shows a clear picture of how the ferroelectric degradation process is present at the nanoscale,” said co-author Professor Xiaozhou Liao, also from the University of Sydney Nano Institute.
Dr Qianwei Huang, the study’s lead researcher, said: “Although it has long been known that ferroelectric fatigue can shorten the lifespan of electronic devices, how it occurs has previously not been well understood, due to a lack of suitable technology to observe it.”
Co-author Dr Zibin Chen said: “With this, we hope to better inform the engineering of devices with longer lifespans.”
Observational findings spark new debate
Nobel laureate Herbert Kroemer once famously asserted “The interface is the device.” The observations by the Sydney researchers could therefore spark a new debate on whether interfaces — which are physical boundaries separating different regions in materials — are a viable solution to the unreliability of next-generation devices.
“Our discovery has indicated that interfaces could actually speed up ferroelectric degradation. Therefore, better understanding of these processes is needed to achieve the best performance of devices,” Dr Chen said.
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Many Mario Kart enthusiasts are familiar with the rush of racing down Rainbow Road, barely squeaking around a corner, and catching a power-up from one of the floating square icons on the screen — or, less ideally, slipping on a banana peel laid by another racer and flying off the side of the road into oblivion. This heated competition between multiple players, who use a variety of game tokens and tools to speed ahead or thwart their competitors, is part of what makes the classic Nintendo racing game that has been around since the early 1990s so appealing.
“It’s been fun since I was a kid, it’s fun for my kids, in part because anyone can play it,” says Andrew Bell, a Boston University College of Arts & Sciences assistant professor of earth and environment. But as a researcher studying economic principles, Bell also sees Mario Kart as much more than just a racing game.
In a recent paper, Bell argues that the principles of Mario Kart — especially the parts of it that make it so addictive and fun for players — can serve as a helpful guide to create more equitable social and economic programs that would better serve farmers in low-resource, rural regions of the developing world. That’s because, even when you’re doing horribly in Mario Kart — flying off the side of Rainbow Road, for example — the game is designed to keep you in the race.
“Farming is an awful thing to have to do if you don’t want to be a farmer,” Bell says. “You have to be an entrepreneur, you have to be an agronomist, put in a bunch of labor…and in so many parts of the world people are farmers because their parents are farmers and those are the assets and options they had.” This is a common story that Bell has come across many times during research trips to Pakistan, Bangladesh, Cambodia, Malawi, and other countries in southern Africa, and is what largely inspired him to focus his research on policies that could aid in development.
In his new paper, Bell argues that policies that directly provide assistance to farmers in the world’s poorest developing regions could help reduce poverty overall, while increasing sustainable and environmentally friendly practices. Bell says the idea is a lot like the way that Mario Kart gives players falling behind in the race the best power-ups, designed to bump them towards the front of the pack and keep them in the race. Meanwhile, faster players in the front don’t get these same boosts, and instead typically get weaker powers, such as banana peels to trip up a racer behind them or an ink splat to disrupt the other players’ screens. This boosting principle is called “rubber banding,” and it’s what keeps the game fun and interesting, Bell says, since there is always a chance for you to get ahead.
“And that’s exactly what we want to do in development,” he says. “And it is really, really difficult to do.”
In the video game world, rubber banding is simple, since there are no real-world obstacles. But in the real world, the concept of rubber banding to extend financial resources to agricultural families and communities who need it the most is extremely complicated. More

Nobel laureate in physics Richard Feynman once described turbulence as “the most important unsolved problem of classical physics.”
Understanding turbulence in classical fluids like water and air is difficult partly because of the challenge in identifying the vortices swirling within those fluids. Locating vortex tubes and tracking their motion could greatly simplify the modeling of turbulence.
But that challenge is easier in quantum fluids, which exist at low enough temperatures that quantum mechanics — which deals with physics on the scale of atoms or subatomic particles — govern their behavior.
In a new study published in Proceedings of the National Academy of Sciences, Florida State University researchers managed to visualize the vortex tubes in a quantum fluid, findings that could help researchers better understand turbulence in quantum fluids and beyond.
From left, Wei Guo, an associate professor of mechanical engineering at the FAMU-FSU College of Engineering, and Yuan Tang, a postdoctoral researcher at the National High Magnetic Field Laboratory, in front of the experimental setup. (Courtesy of Wei Guo)
“Our study is important not only because it broadens our understanding of turbulence in general, but also because it could benefit the studies of various physical systems that also involve vortex tubes, such as superconductors and even neutron stars,” said Wei Guo, an associate professor of mechanical engineering at the FAMU-FSU College of Engineering and the study’s principal investigator. More

Researchers have developed a new algorithm capable of identifying features of male zebra finch songs that may underlie the distinction between a short phrase sung during courtship, and the same phrase sung in a non-courtship context. Sarah Woolley of McGill University in Montreal, Canada, and colleagues present these findings in the open-access journal PLOS Computational Biology.
Like many animals, male zebra finches adjust their vocal signals for their audience. They may sing the same sequence of syllables during courtship interactions with females as when singing alone, but with subtle modifications. However, humans cannot detect these differences, and it was not clear that female zebra finches could, either.
For the new study, Woolley and colleagues first conducted behavioral experiments demonstrating that female zebra finches are indeed highly adept at discriminating between short segments of males’ songs recorded in courtship versus non-courtship settings.
Next, they sought to expand on earlier studies that have focused on just a few specific song features that may underlie the distinction between courtship and non-courtship song. Taking a “bottom-up” approach, the researchers extracted over 5,000 song features from recordings and trained an algorithm to use those features to distinguish between courtship and non-courtship song phrases.
The trained algorithm uncovered features that may be key for song perception, some of which had not been identified previously. It also made predictions about the distinction capabilities of female zebra finches that aligned well with the results of the behavioral experiments.
These findings highlight the potential for bottom-up approaches to reveal acoustic features important for communication and social discrimination.
“As vocal communicators ourselves, we have a tendency to focus on aspects of communication signals that are salient to us,” Woolley says. “Using our bottom-up approach, we identified features that might never have been on our radar.”
Next, the researchers plan to test whether manipulating the acoustic features they discovered alters what female finches think about those songs. They also hope to evaluate how well their findings might generalize to courtship and non-courtship songs in other species.
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How can large amounts of data be transferred or processed as quickly as possible? One key to this could be graphene. The ultra-thin material is only one atomic layer thick, and the electrons it contains have very special properties due to quantum effects. It could therefore be very well suited for use in high-performance electronic components. Up to this point, however, there has been a lack of knowledge about how to suitably control certain properties of graphene. A new study by a team of scientists from Bielefeld and Berlin, together with researchers from other research institutes in Germany and Spain, is changing this. The team’s findings have been published in the journal Science Advances.
Consisting of carbon atoms, graphene is a material just one atom thick where the atoms are arranged in a hexagonal lattice. This arrangement of atoms is what results in graphene’s unique property: the electrons in this material move as if they did not have mass. This “massless” behavior of electrons leads to very high electrical conductivity in graphene and, importantly, this property is maintained at room temperature and under ambient conditions. Graphene is therefore potentially very interesting for modern electronics applications.
It was recently discovered that the high electronic conductivity and “massless” behavior of its electrons allows graphene to alter the frequency components of electric currents that pass through it. This property is highly dependent on how strong this current is. In modern electronics, such a nonlinearity comprises one of the most basic functionalities for switching and processing of electrical signals. What makes graphene unique is that its nonlinearity is by far the strongest of all electronic materials. Moreover, it works very well for exceptionally high electronic frequencies, extending into the technologically important terahertz (THz) range where most conventional electronic materials fail.
In their new study, the team of researchers from Germany and Spain demonstrated that graphene’s nonlinearity can be very efficiently controlled by applying comparatively modest electrical voltages to the material. For this, the researchers manufactured a device resembling a transistor, where a control voltage could be applied to graphene via a set of electrical contacts. Then, ultrahigh-frequency THz signals were transmitted using the device: the transmission and subsequent transformation of these signals were then analyzed in relation to the voltage applied. The researchers found that graphene becomes almost perfectly transparent at a certain voltage — its normally strong nonlinear response nearly vanishes. By slightly increasing or lowering the voltage from this critical value, graphene can be turned into a strongly nonlinear material, significantly altering the strength and the frequency components of the transmitted and remitted THz electronic signals.
“This is a significant step forward towards implementation of graphene in electrical signal processing and signal modulation applications,” says Prof. Dmitry Turchinovich, a physicist at Bielefeld University and one of the heads of this study. “Earlier we had already demonstrated that graphene is by far the most nonlinear functional material we know of. We also understand the physics behind nonlinearity, which is now known as thermodynamic picture of ultrafast electron transport in graphene. But until now we did not know how to control this nonlinearity, which was the missing link with respect to using graphene in everyday technologies.”
“By applying the control voltage to graphene, we were able to alter the number of electrons in the material that can move freely when the electrical signal is applied to it,” explains Dr. Hassan A. Hafez, a member of Professor Dr. Turchinovich’s lab in Bielefeld, and one of the lead authors of the study. “On one hand, the more electrons can move in response to the applied electric field, the stronger the currents, which should enhance the nonlinearity. But on the other hand, the more free electrons are available, the stronger the interaction between them is, and this suppresses the nonlinearity. Here we demonstrated — both experimentally and theoretically — that by applying a relatively weak external voltage of only a few volts, the optimal conditions for the strongest THz nonlin-earity in graphene can be created.”
“With this work, we have reached an important milestone on the path towards to using graphene as an extremely efficient nonlinear functional quantum material in devices like THz frequency converters, mixers, and modulators,” says Professor Dr. Michael Gensch from the Institute of Optical Sensor Systems of the German Aerospace Center (DLR) and the Technical University of Berlin, who is the other head of this study. “This is extremely relevant because graphene is perfectly compatible with existing electronic ultrahigh-frequency semiconductor technology such as CMOS or Bi-CMOS. It is therefore now possible to envision hybrid devices in which the initial electric signal is generated at lower frequency using existing semiconductor technology but can then very efficiently be up-converted to much higher THz frequencies in graphene, all in a fully controllable and predictable manner.”
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Powerful algorithms used by Netflix, Amazon and Facebook can ‘predict’ the biological language of cancer and neurodegenerative diseases like Alzheimer’s, scientists have found.
Big data produced during decades of research was fed into a computer language model to see if artificial intelligence can make more advanced discoveries than humans.
Academics based at St John’s College, University of Cambridge, found the machine-learning technology could decipher the ‘biological language’ of cancer, Alzheimer’s, and other neurodegenerative diseases.
Their ground-breaking study has been published in the scientific journal PNAS today (April 8 2021) and could be used in the future to ‘correct the grammatical mistakes inside cells that cause disease’.
Professor Tuomas Knowles, lead author of the paper and a Fellow at St John’s College, said: “Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer. Ultimately, the aim will be to use artificial intelligence to develop targeted drugs to dramatically ease symptoms or to prevent dementia happening at all.”
Every time Netflix recommends a series to watch or Facebook suggests someone to befriend, the platforms are using powerful machine-learning algorithms to make highly educated guesses about what people will do next. Voice assistants like Alexa and Siri can even recognise individual people and instantly ‘talk’ back to you. More