A proposal to form a SIAM Activity Group (SIAG) on Education was approved by the SIAM Council and Board at their meeting earlier this month. The SIAG will officially start operation on January 1, 2015.
The proposed SIAG will focus on all aspects promoting excellence in applied mathematics educational programs, courses and practice. Broadly inclusive, it will cover industrial mathematics, computational science, modeling, data sciences, applied statistics and the application domains. The primary focus will be undergraduate education but extension of this to graduate and pre-college education is included. A key activity will be to hold a regular conference. Read the rest of this entry »
Philadelphia, PA—A few recent SIAM journal papers you should know about:
Cell migration, which is involved in wound healing, cancer and tumor growth, and embryonic growth and development, has been a topic of interest to mathematicians and biologists for decades.
In a paper published recently in the SIAM Journal on Applied Dynamical Systems, authors Kristen Harley, Peter van Heijster, Robert Marangell, Graeme Pettet, and Martin Wechselberger study a model describing cell invasion through directional outgrowth or movement in the context of malignant tumors, in particular, melanoma or skin cancer. Tumor cells move up a gradient, based on the presence of a chemical or chemoattractant – this process is called haptotaxis. Receptors on the exterior of cell walls detect and allow passing of the chemoattractant. Based on the locations of these receptors, cells determine the most favorable migration direction. Read the rest of this entry »
News & announcements for the SIAM membership community
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Dear SIAM members,
Did you know that SIAM offers discounted member rates for members of other mathematical societies? SIAM has a reciprocity agreement with 12 societies: view the entire list. If you would like to change your membership to a “reciprocal” category, contact SIAM Customer Service at email@example.com.
SIAM is pleased to announce the 2014 Class of SIAM Fellows. These distinguished members were nominated for their exemplary research as well as outstanding service to the community. Through their contributions, SIAM Fellows help advance the fields of applied mathematics and computational science.
SIAM would like to congratulate these 32 members of the community listed below in alphabetical order:
Mark Ainsworth, Brown University
John S. Baras, University of Maryland, College Park
Lorenz T. Biegler, Carnegie Mellon University
Åke Björck, Linköping University, Emeritus
Each year, the Society for Industrial and Applied Mathematics (SIAM) designates as Fellows of the society members who have made outstanding contributions to fields served by SIAM.
This year, SIAM is happy to recognize 32 members of the community for this honor. Fellows are nominated by peers for their distinguished contributions to the fields of applied mathematics and computational science and related disciplines.
The book, Mathematics and Climate, published by SIAM last October, has been honored by the Atmospheric Science Librarians International (ASLI) as the best book of 2013 in the fields of meteorology, climatology, and atmospheric sciences.
Mathematics and Climate is a timely textbook with wide appeal. It is aimed at students and researchers in mathematics and statistics who are interested in current issues of climate science, as well as at climate scientists who wish to become familiar with qualitative and quantitative methods of mathematics and statistics. The authors emphasize conceptual models that capture important aspects of Earth’s climate system and present the mathematical and statistical techniques that can be applied to their analysis. Topics from climate science include the Earth’s energy balance, temperature distribution, ocean circulation patterns such as El Niño–Southern Oscillation, ice caps and glaciation periods, the carbon cycle, and the biological pump. Among the mathematical and statistical techniques presented in the text are dynamical systems and bifurcation theory, Fourier analysis, conservation laws, regression analysis, and extreme value theory. Read the rest of this entry »
Improving radiation therapies for cancer mathematically
In a paper published in December in the SIAM Journal on Scientific Computing, authors Li-Tien Cheng, Bin Dong, Chunhua Men, Xun Jia, and Steve Jiang propose a method to optimize radiation therapy treatments in cancer patients.
Radiation therapy is one of the primary methods used for cancer treatment, along with chemotherapy and surgery. While doses of radiation are delivered to eliminate cancerous tissue, care is taken to keep radiation within acceptable levels so as not to affect neighboring tissues and organs. The most common type of therapy delivers high-energy radiation via a medical linear accelerator mounted on a rotating apparatus to adjust the direction, and a collimator to shape the beam of radiation. In the recently developed volumetric modulated arc therapy (VMAT), beams continuously deliver doses as the delivery device rotates around the patient. Enhancement of radiotherapy treatment is challenged by complexities of shape optimization, due to the mechanics of the equipment involved as well as the apertures of devices delivering the beams of radiation. Read the rest of this entry »
Philadelphia, PA—Vast amounts of data related to climate change are being compiled by research groups all over the world. Data from these many and varied sources results in diﬀerent climate projections; hence, the need arises to combine information across data sets to arrive at a consensus regarding future climate estimates.
In a paper published last December in the SIAM Journal on Uncertainty Quantification, authors Matthew Heaton, Tamara Greasby, and Stephan Sain propose a statistical hierarchical Bayesian model that consolidates climate change information from observation-based data sets and climate models.
“The vast array of climate data—from reconstructions of historic temperatures and modern observational temperature measurements to climate model projections of future climate—seems to agree that global temperatures are changing,” says author Matthew Heaton. “Where these data sources disagree, however, is by how much temperatures have changed and are expected to change in the future. Our research seeks to combine many different sources of climate data, in a statistically rigorous way, to determine a consensus on how much temperatures are changing.” Read the rest of this entry »