News Feeds

  • In response to Stephen Colbert, professor says ‘spice it up’
    on February 17, 2021 at 3:51 pm

    To provoke more interest and excitement for students and lecturers alike, a professor from Florida Atlantic University’s College of Engineering and Computer Science is spicing up the study of complex differential mathematical equations using relevant history of algebra. In a paper published in the Journal of Humanistic Mathematics, Isaac Elishakoff, Ph.D., provides a refreshing perspective and a special “shout out” to Stephen Colbert, comedian and host of CBS’s The Late Show with Stephen Colbert. His motivation? Colbert previously referred to mathematical equations as the devil’s sentences and an unnatural commingling of letters and numbers—with the worst being the quadratic equation—an infernal salad of numbers, letters and symbols.

  • Mathematician suggests a scheme for solving telegraph equations
    on February 11, 2021 at 3:56 pm

    A mathematician from RUDN University suggested a stable difference scheme for solving inverse problems for elliptic-telegraph and differential equations that are used to describe biological, physical, and sociological processes. The results of the study were published in the Numerical Methods for Partial Differential Equations journal.

  • Mathematicians develop new classes of stellar dynamics systems solutions
    on February 5, 2021 at 4:06 pm

    The Vlasov-Poisson equations describe many important physical phenomena such as the distribution of gravitating particles in interstellar space, high-temperature plasma kinetics, and the Landau damping effect. A joint team of scientists from the Mathematical Institute of RUDN University and the Mathematical Institute of the University of Munich suggested a new method to obtain stationary solutions for a system of Vlasov-Poisson equations in a three-dimensional case. The obtained solutions describe the phenomena of stellar dynamics. The results of the study were published in the Doklady Mathematics journal.

  • The Ramanujan Machine: Researchers have developed a ‘conjecture generator’ that creates mathematical conjectures
    on February 5, 2021 at 4:02 pm

    Using AI and computer automation, Technion researchers have developed a ‘conjecture generator’ that creates mathematical conjectures, which are considered to be the starting point for developing mathematical theorems. They have already used it to generate a number of previously unknown formulas. The study, which was published in the journal Nature, was carried out by undergraduates from different faculties under the tutelage of Assistant Professor Ido Kaminer of the Andrew and Erna Viterbi Faculty of Electrical Engineering at the Technion.

  • How game theory could have reduced costs of PPE for frontline healthcare workers
    on February 2, 2021 at 2:44 pm

    Kingston University London researchers have used a mathematical model known as game theory to explore how the challenge of securing sufficient levels of vital personal protective equipment (PPE) for healthcare workers during the peak of the COVID-19 pandemic could have been mitigated.

  • An app-based recommendation framework for investor adoption of crypto assets
    on January 27, 2021 at 4:59 pm

    Consumers regularly choose books, music, travel destinations and other activities based on recommendations by many people on e-commerce or social media platforms.

  • Simulating cities under pandemic conditions to make predictions about future outbreaks
    on January 27, 2021 at 2:20 pm

    An international team of researchers has used modeling techniques borrowed from chemistry applications to create a new kind of city simulator. In their paper published in the journal Proceedings of the Royal Society A, the group describes using their models to create simulations of of COVID-19 spread for two real-world cities: Birmingham England and Bogota Columbia.

  • Researchers find value in comparison of multiple strategies for mathematics teaching and learning
    on January 25, 2021 at 2:34 pm

    How can cognitive science principles support the deepening of mathematics education? A team of researchers from Vanderbilt University’s Peabody College of education and human development and Harvard University’s graduate school of education explored how using a basic learning process—comparison—could lead to stronger outcomes for K-12 students in mathematics, and analyzed different approaches for incorporating comparison into curriculum. A summary of the research findings from Peabody College researchers Bethany Rittle-Johnson and Kelley Durkin, in collaboration with Jon Star from Harvard University, was recently published in the December 2020 edition of Current Directions in Psychological Sciences.

  • A mathematical framework enables accurate characterization of shapes
    on January 21, 2021 at 6:00 pm

    In nature, many things have evolved that differ in size, color and, above all, in shape. While the color or size of an object can be easily described, the description of a shape is more complicated. In a study now published in Nature Communications, Jacqueline Nowak of the Max Planck Institute of Molecular Plant Physiology and her colleagues have outlined a new and improved way to describe shapes based on a network representation that can also be used to reassemble and compare shapes.

  • Data-driven rating system makes it easier to select sports teams
    on January 15, 2021 at 2:24 pm

    Picking the right sports team for a particular event or to play in certain conditions is many a selector’s nightmare.

  • How probability forecasts are phrased affects how people make predictions
    on January 11, 2021 at 2:20 pm

    A regular traveler is planning an overseas trip but hasn’t purchased her plane ticket. So she visits various websites that can predict whether the cost of her ticket will rise or fall.

  • What is a margin of error? This statistical tool can help you understand vaccine trials and political polling
    on January 7, 2021 at 2:20 pm

    In the last year, statistics have been unusually important in the news. How accurate is the COVID-19 test you or others are using? How do researchers know the effectiveness of new therapeutics for COVID-19 patients? How can television networks predict the election results long before all the ballots have been counted?

  • Studying abstract mathematical equations using tangible surfaces
    on January 4, 2021 at 2:31 pm

    On January 5, Rosa Winter will obtain her doctorate in arithmetic geometry. She researched solutions of equations that define so-called ‘del Pezzo surfaces.” “I like geometry because I can imagine and draw the shapes and objects,” says Winter. “That makes abstract mathematics feel more tangible.”

  • Mathematicians develop a new model for predicting epidemics based on precedents
    on December 9, 2020 at 4:55 pm

    Scientists of the Intelligent Logistics Centre at St Petersburg University have developed a new Case-Based Rate Reasoning (CBRR) model for predicting the dynamics of epidemics. Using this method, the researchers are preparing forecasts for the spread of COVID-19 in Russia. The predictions are based on data on the dynamics of the epidemic in countries where the disease was recorded earlier.

  • Mathematician suggests new approach to cooperative game
    on December 1, 2020 at 6:01 pm

    A mathematician from RUDN University developed a matrix representation of set functions. This approach is vivid and easy to check, and it makes the calculations easier. Among other things, the new development can be applied to cooperative game theory. The results of the work were published in the Information Sciences journal.

  • Study: Students falling behind in math during pandemic
    on December 1, 2020 at 9:18 am

    A disproportionately large number of poor and minority students were not in schools for assessments this fall, complicating efforts to measure the pandemic’s effects on some of the most vulnerable students, a not-for-profit company that administers standardized testing said Tuesday.

  • ‘Fairmandering’ draws fair districts using data science
    on November 25, 2020 at 2:47 pm

    It’s almost impossible for humans to draw unbiased maps, even when they’re trying.

  • Six years in 120 pages: Researchers shed light on Ricci flows
    on November 23, 2020 at 3:11 pm

    Differential geometry is the study of space geometry. Multiple natural phenomena, from universal expansion to thermal expansion and contraction, can come down to spatial evolution. The two core conjectures in this field, the Hamilton-Tian conjecture and the Partial C0 conjecture, were unsolved puzzles for more than 20 years.

  • A student’s experience with math is affected by the composition of the group they are in
    on November 17, 2020 at 3:37 pm

    Weak students in high-performing math classes, especially boys, feel more shame compared to students in low-performing math classes. Stronger students, in turn, feel more bored and enjoy mathematics less in high-performing math classes, according to a new study.

  • Secrets behind ‘Game of Thrones’ unveiled by data science and network theory
    on November 2, 2020 at 8:00 pm

    What are the secrets behind one of the most successful fantasy series of all time? How has a story as complex as “Game of Thrones” enthralled the world and how does it compare to other narratives?

  • Mathematicians specify the criteria for the emergence of Turing patterns
    on November 2, 2020 at 1:33 pm

    Turing patterns are mathematical expressions of the structures formed in chemical and biological systems, such as spots and stripes on the animal skin. A team of scientists from RUDN University found out that the traditional mathematical conditions of their existence failed to describe the whole range of real-life cases, and that the criteria of their emergence are more flexible. The results of the study were published in Chaos: An Interdisciplinary Journal of Nonlinear Science.

  • Forecasting elections with a model of infectious diseases
    on October 28, 2020 at 9:50 pm

    Forecasting elections is a high-stakes problem. Politicians and voters alike are often desperate to know the outcome of a close race, but providing them with incomplete or inaccurate predictions can be misleading. And election forecasting is already an innately challenging endeavor—the modeling process is rife with uncertainty, incomplete information, and subjective choices, all of which must be deftly handled. Political pundits and researchers have implemented a number of successful approaches for forecasting election outcomes, with varying degrees of transparency and complexity. However, election forecasts can be difficult to interpret and may leave many questions unanswered after close races unfold.

  • A mathematical model facilitates inventory management in the food supply chain
    on October 28, 2020 at 6:24 pm

    It is a long journey from harvesting in the field to the cooked dish that reaches the dinner table. The food supply chain covers all those processes and the actors involved in satisfying the consumer’s needs. To ensure that the chain is successful requires correct administration of the products in the warehouse, inventory, transport management and coordination between warehouses, transport and destination.

  • Assessing consistency in meta-analysis: A new measure considers statistical power
    on October 27, 2020 at 6:02 pm

    Researchers have improved the assessment of consistency in meta-analysis. The improved consistency measure considers statistical power, and it has potential to alter the interpretation of meta-analyses. The new measure was published in the European Journal for Philosophy of Science.

  • Novel method for measuring spatial dependencies turns less data into more data
    on October 21, 2020 at 8:26 pm

    The identification of human migration driven by climate change, the spread of COVID-19, agricultural trends, and socioeconomic problems in neighboring regions depends on data—the more complex the model, the more data is required to understand such spatially distributed phenomena. However, reliable data is often expensive and difficult to obtain, or too sparse to allow for accurate predictions.

  • Interactions within larger social groups can cause tipping points in contagion flow
    on October 20, 2020 at 4:00 pm

    Contagion processes, such as opinion formation or disease spread, can reach a tipping point, where the contagion either rapidly spreads or dies out. When modeling these processes, it is difficult to capture this complex transition, making the conditions that affect the tipping point a challenge to uncover.

  • Statistical tools for valid causal inference with fewer assumptions
    on October 16, 2020 at 3:20 pm

    Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference difficult without making overly optimistic or idealistic assumptions. In a new article published in the Journal of the American Statistical Association, researchers at Karolinska Institutet develop new statistical methods to make causal inference possible in some settings without making such assumptions.

  • ‘Universal law of touch’ will enable new advances in virtual reality
    on October 9, 2020 at 7:00 pm

    Seismic waves, commonly associated with earthquakes, have been used by scientists to develop a universal scaling law for the sense of touch. A team, led by researchers at the University of Birmingham, used Rayleigh waves to create the first scaling law for touch sensitivity. The results are published in Science Advances.

  • Fractal study describes COVID-19 transmission pattern
    on October 9, 2020 at 1:46 pm

    The most widely used model to describe the epidemic evolution of a disease over time is called SIR, short for susceptible (S), infected (I), and removed (R). A susceptible person can be infected, and the infected person will eventually be removed owing to either immunization or death. The number of people in each class varies, whereas the total population, given by the sum of individuals in all three classes, is considered constant in the time scale of epidemic contamination.

  • Study uses mathematical modeling to identify an optimal school return approach
    on October 8, 2020 at 12:07 pm

    In a recent study, NYU Abu Dhabi Professor of Practice in Mathematics Alberto Gandolfi has developed a mathematical model to identify the number of days students could attend school to allow them a better learning experience while mitigating infections of COVID-19.