BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Claremont Center for the Mathematical Sciences - ECPv6.15.17.1//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Claremont Center for the Mathematical Sciences X-ORIGINAL-URL:https://colleges.claremont.edu/ccms X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20200308T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20201101T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20210314T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20211107T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20220313T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20221106T090000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20230312T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20231105T090000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220223T161500 DTEND;TZID=America/Los_Angeles:20220223T173000 DTSTAMP:20260518T150836 CREATED:20220216T183109Z LAST-MODIFIED:20220217T003329Z UID:2626-1645632900-1645637400@colleges.claremont.edu SUMMARY:Modeling Zoonotic Infectious Diseases from Wildlife to Humans (Prof. Linda J. S. Allen) DESCRIPTION:Title: Modeling  Zoonotic Infectious Diseases from Wildlife to Humans \nSpeaker: Prof. Linda J. S. Allen\, P. W. Horn Distinguished Professor Emeritus Texas Tech University \nAbstract: Zoonotic infectious diseases are diseases transmitted from animals to humans. It is estimated that over 60% of human infectious diseases are zoonotic. The Centers for Disease Control and Prevention has identified eight priority zoonoses in the US. Three of the priority zoonoses are avian influenza\, Lyme disease\, and emerging coronaviruses. Spillover of infections from animals to humans depends on a complex pathway from the natural wildlife reservoir.  The natural reservoir for avian influenza virus is wild birds but it is spread to humans from infected chickens. The natural reservoir for the bacterial pathogen causing Lyme disease is mice but it is transmitted to humans through the bite of an infected tick vector.    In this presentation\, we discuss a few of the modeling efforts to better understand the spread of infection in the natural reservoir and the spillover to humans as well as the impacts of demographic and environmental variability on timing of spillover.  \n___________________________________________________________________________________________________ \nLinda J. S. Allen received her PhD in Mathematics from University of Tennessee and was a Professor of Mathematics at Texas Tech University until 2019.  She is currently an Adjunct  Graduate Faculty at Texas Tech University. Her research interests are in mathematical ecology\, epidemiology\, and immunology.\nhttps://www.math.ttu.edu/~lallen/\nhttps://www.depts.ttu.edu/provost/scholars/lindaallen.php\n\nResearch Experiences for Undergraduates at Texas Tech University “Mathematical\, Statistical\, and Computational Methods for Problems in the Life Sciences”\n June 6-July 20\, 2022\n\nREU Applications Due: March 6\, 2022:\nhttps://www.math.ttu.edu/undergraduate/reu2022/ URL:https://colleges.claremont.edu/ccms/event/modeling-zoonotic-infectious-diseases-from-wildlife-to-humans-prof-linda-j-s-allen/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220216T161500 DTEND;TZID=America/Los_Angeles:20220216T173000 DTSTAMP:20260518T150836 CREATED:20220128T164956Z LAST-MODIFIED:20220214T180454Z UID:2577-1645028100-1645032600@colleges.claremont.edu SUMMARY:Solving the Race in Backgammon (Prof. Arthur Benjamin) DESCRIPTION:Title: Solving the Race in Backgammon\n \nSpeaker: Prof. Arthur Benjamin\nSmallwood Family Professor of Mathematics\nHarvey Mudd College\n \nAbstract: Backgammon is perhaps the oldest game that is still played today. It is a game that combines luck with skill\, where two players take turns rolling dice and decide how to move their checkers in the best possible way. It is the ultimate math game\, where players who possess a little bit of mathematical knowledge can have a big advantage over their opponents.  Players also have the opportunity to double the stakes of a game using something called the doubling cube\, which—when used optimally—leads to players winning more in the long run. Optimal use of the doubling cube relies on a player’s ability to estimate their winning chances at any stage of the game.\n\nWhen played to completion\, every game of backgammon eventually becomes a race\, where each player attempts to remove all of their checkers before their opponent does. The goal of our research is to be able to determine the optimal doubling cube action for any racing position\, and approximate the game winning chances for both sides. By calculating the Effective Pip Count for both players and identifying the positions’ Variance Types\, we arrive at a reasonably simple method for achieving this which is demonstrably superior to other popular methods.\n\n\n\n\nArthur Benjamin\, PhD\, Smallwood Family Professor of Mathematics\, is recognized nationally for his ability to perform rapid mental calculations. In 2020 he won the inaugural American Backgammon Tour Online (ABTO) with the best overall performance in a series of 17 national tournaments.  He has published several books on how to make math both fun and easy.  He is also a professional mathemagician and frequently performs at the Magic Castle in Hollywood and nationwide. URL:https://colleges.claremont.edu/ccms/event/solving-the-race-in-backgammon-prof-arthur-benjamin/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20220202T161500 DTEND;TZID=America/Los_Angeles:20220202T173000 DTSTAMP:20260518T150836 CREATED:20220128T183638Z LAST-MODIFIED:20220131T193506Z UID:2581-1643818500-1643823000@colleges.claremont.edu SUMMARY:Exploiting metric structure for more accurate classification (Prof. Mike Izbicki) DESCRIPTION:Title: Exploiting metric structure for more accurate classification \nSpeaker: Mike Izbicki\, Department of Mathematical Sciences\, Claremont McKenna College \nAbstract: Classification problems often have many semantically similar classes.  For example\, the famous ImageNet dataset contains classes for 80 different dog breeds\, 40 different bird species\, and 25 types of vehicles.  This semantic structure can be formalized using a metric space\, with semantic similarity of classes encoded by the distance function.  In this talk\, I’ll describe the “tree loss”\, which is the first technique with provable performance guarantees for exploiting this metric structure.  I’ll also show that the tree loss has better empirical performance than competing algorithms on image\, text\, and vector data. \n\nMike studies machine learning theory\, focusing on applications to natural language and social media.  He has been at CMC for 3 years now\, where he teaches computer and data science classes.  Prior to his academic career\, Mike spent 7 years in the US Navy.  Highlights include converting >10g of Uranium into pure energy as a nuclear submarine officer\, and doing [redacted] for the NSA.  After leaving the navy\, Mike went to North Korea to teach computer science as part of an academic exchange program designed to improve relations between the US and North Korea.  He earned his phd from UC Riverside. URL:https://colleges.claremont.edu/ccms/event/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20211006T163000 DTEND;TZID=America/Los_Angeles:20211006T174500 DTSTAMP:20260518T150836 CREATED:20210831T035746Z LAST-MODIFIED:20210831T035746Z UID:2257-1633537800-1633542300@colleges.claremont.edu SUMMARY:Interrupted Time Series Models for Assessing Complex Health Care Interventions (Maricela Cruz\, PhD) DESCRIPTION:Title: Interrupted Time Series Models for Assessing Complex Health Care Interventions \nMaricela Cruz\, PhD\nAssistant Investigator\nBiostatistics Unit\nKaiser Permanente Washington Health Research Institute \nAbstract:  Assessing the impact of complex interventions on measurable health outcomes is a growing concern in health care and health policy. According to the 2018 Annual Review of Public Health\, interrupted time series (ITS) designs may be the only feasible recourse for studying the impacts of large-scale public health policies. Statistical models used to analyze ITS data a priori restrict the interruption’s effect to a predetermined time point or censor data for which the intervention effects may not be fully realized\, and neglect changes in the temporal dependence and variability. In addition\, current methods limit the analysis to one hospital unit or entity and are not well specified for discrete outcomes (e.g.\, patient falls). In this talk\, I present novel ITS methods based on segmented regression that address the aforementioned limitations and provide a testing paradigm for the existence of a change point in the time series. The methodology is illustrated by analyzing patient centered data from a hospital that implemented and evaluated a new care delivery model in multiple units.\n  \nMaricela Cruz is an Assistant Investigator and Biostatistician at Kaiser Permanente Washington Health Research Institute and Affiliate Assistant Professor at the University of Washington Department of Biostatistics.  She received her PhD in statistics from the University of California Irvine and was a National Science Foundation Graduate Research Fellowship awardee and Eugene Cota-Robles fellow during her time there. Maricela’s research primarily focuses on developing novel statistical methods to assess and evaluate the impact of complex health interventions. URL:https://colleges.claremont.edu/ccms/event/interrupted-time-series-models-for-assessing-complex-health-care-interventions-maricela-cruz-phd/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210922T163000 DTEND;TZID=America/Los_Angeles:20210922T174500 DTSTAMP:20260518T150836 CREATED:20210817T140933Z LAST-MODIFIED:20210817T141610Z UID:2198-1632328200-1632332700@colleges.claremont.edu SUMMARY:Quantitative Approaches to Social Justice (Prof. Chad Topaz) DESCRIPTION:Title: Quantitative Approaches to Social Justice \nProf. Chad Topaz (he/him/his)\nCo-Founder and Executive Director of Research\, QSIDE Institute\nProfessor of Mathematics\, Williams College \nAbstract: Civil rights leader\, educator\, and investigative journalist Ida B. Wells said that “the way to right wrongs is to shine the light of truth upon them.” This talk will demonstrate how quantitative and computational approaches can shine a light on social injustices and help build solutions to remedy them. We will present quantitative social justice projects on topics ranging from diversity in art museums to equity in criminal sentencing to affirmative action\, health care access\, and other fields. The tools engaged include crowdsourcing\, data cleaning\, clustering\, hypothesis testing\, statistical modeling\, Markov chains\, data visualization\, and much more. I hope that this talk leaves you informed about the breadth of social justice applications that one can tackle using mathematical and data science tools in careful collaboration with other scholars and activists. \nProf. Chad Topaz (he/him/his) is the co-Founder and Executive Director of Research at the QSIDE Institute which promote the quantitative study of inclusion\, diversity\, and equity. He is also a Professor of Mathematics\, Williams College. \nThis colloquium will be virtual and a Zoom link will be distributed via the CCMS Email list. URL:https://colleges.claremont.edu/ccms/event/prof-chad-topaz/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210915T163000 DTEND;TZID=America/Los_Angeles:20210915T174500 DTSTAMP:20260518T150836 CREATED:20210831T233907Z LAST-MODIFIED:20210907T223233Z UID:2274-1631723400-1631727900@colleges.claremont.edu SUMMARY:Topic Models\, Methods\, and Medicine (Prof. Jamie Haddock) DESCRIPTION:Title: Topic Models\, Methods\, and Medicine \nSpeaker: Prof. Jamie Haddock (Harvey Mudd College) \nAbstract: There is currently an unprecedented demand for efficient\, quantitative\, and interpretable methods to study large-scale (often multi-modal) data. One key area of interest is that of topic modeling\, which seeks to automatically learn latent trends or topics of complex data sets\, providing practitioners a view of what is “going on” inside their data. This talk will survey several new tools for topic modeling on matrix and tensor data which allow for use of various forms of supervision and which learn hierarchical structure amongst topics.  These tools are of interest across the many fields and industries producing\, capturing\, and analyzing big data\, but are of particular interest in applications where expert supervision is available and often essential (e.g.\, medicine).  We will describe two applications of these methods to medical data; an application to a large-scale patient survey database and an ongoing application to cardiovascular imaging data. \n  \nProf. Jamie Haddock is an Assistant Professor in the Mathematics Department at Harvey Mudd College URL:https://colleges.claremont.edu/ccms/event/jamie-haddock-harvey-mudd-college/ LOCATION:Zoom meeting\, United States CATEGORIES:Colloquium ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210426T150000 DTEND;TZID=America/Los_Angeles:20210426T160000 DTSTAMP:20260518T150836 CREATED:20210128T180721Z LAST-MODIFIED:20210426T165641Z UID:2155-1619449200-1619452800@colleges.claremont.edu SUMMARY:Applied Math. Talk: Balancing Geometry and Density: Path Distances on High-Dimensional Data by Anna Little\, University of Utah DESCRIPTION: Abstract: This talk discusses multiple methods for clustering\nhigh-dimensional data\, and explores the delicate balance between utilizing\ndata density and data geometry. I will first present path-based spectral\nclustering\, a novel approach which combines a density-based metric with\ngraph-based clustering. This density-based path metric allows for fast\nalgorithms and strong theoretical guarantees when clusters concentrate\naround low-dimensional sets. However\, the method suffers from a loss of\ngeometric information\, information which is preserved by simple linear\ndimension reduction methods such as classic multidimensional scaling\n(CMDS). The second part of the talk will explore when CMDS followed by a\nsimple clustering algorithm can exactly recover all cluster labels with\nhigh probability. However\, scaling conditions become increasingly\nrestrictive as the ambient dimension increases\, and the method will fail\nfor irregularly shaped clusters. Finally\, I will discuss how a more\ngeneral family of path metrics\, when combined with CMDS\, give\nlow-dimensional embeddings which respect both data density and data\ngeometry. This new method exhibits promising performance on single cell\nRNA sequence data and can be computed efficiently by restriction to a\nsparse graph. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-anna-little-university-of-utah/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210419T150000 DTEND;TZID=America/Los_Angeles:20210419T160000 DTSTAMP:20260518T150836 CREATED:20210112T180844Z LAST-MODIFIED:20210417T022158Z UID:2112-1618844400-1618848000@colleges.claremont.edu SUMMARY:Applied math. talk: Adversarially robust classification via geometric flows\, by Ryan Murray\, North Caroline State University DESCRIPTION:Abstract: Classification is a fundamental task in data science and machine learning\, and in the past ten years there have been significant improvements on classification tasks (e.g. via deep learning). However\, recently there have been a number of works demonstrating that these improved algorithms can be “fooled” using specially constructed adversarial examples. In turn\, there has been increased attention given to creating machine learning algorithms which are more robust against adversarial attacks. In this talk I will describe a recently proposed framework for optimal adversarial robustness which is related to optimal transportation. I will then discuss some recent work\, with Nicolas Garcia Trillos\, which characterizes solutions of the optimal adversarial robust classification problem by using a geometric evolution equation. Surprisingly\, this geometric evolution equation asymptotically takes the form of a weighted mean curvature flow\, which suggests new analytical and computational approaches to the problem. I will also discuss a number of related open questions. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-ryan-murray-north-caroline-state-university/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210412T150000 DTEND;TZID=America/Los_Angeles:20210412T160000 DTSTAMP:20260518T150836 CREATED:20210112T180713Z LAST-MODIFIED:20210406T193121Z UID:2110-1618239600-1618243200@colleges.claremont.edu SUMMARY:Applied math. talk: Large Eddy Simulation Reduced Order Models by Traian Iliescu\, Virginia Tech DESCRIPTION:In this talk\, we present reduced order models (ROMs) for turbulent flows\,\nwhich are constructed by using ideas from large eddy simulation (LES) and\nvariational multiscale (VMS) methods.  First\, we give a\ngeneral introduction to reduced order modeling and emphasize the\nconnection to classical Galerkin methods (e.g.\, the finite element method)\nand the central role played by data.  Then\, we describe the closure\nproblem\, which represents one of the main obstacles in the development of\nROMs for realistic\, turbulent flows.  To tackle the ROM closure problem\,\nwe use ROM spatial filters (e.g.\, the ROM projection and the ROM\ndifferential filter) and build new LES-ROMs that capture the large scale\nROM features and model the interaction between these large scales and the\nsmall scale ROM features. Finally\, we present results for these LES-ROMs\nin the numerical simulation of\nunder-resolved engineering flows (e.g.\, flow past a cylinder and\nturbulent channel flow) and the quasi-geostrophic equations (which model\nthe large scale ocean circulation). URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-traian-iliescu-virginia-tech/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210329T150000 DTEND;TZID=America/Los_Angeles:20210329T160000 DTSTAMP:20260518T150836 CREATED:20210113T011843Z LAST-MODIFIED:20210325T164523Z UID:2115-1617030000-1617033600@colleges.claremont.edu SUMMARY:Applied math. talk: Hyperbolicity-Preserving Stochastic Galerkin Method for Shallow Water Equations by Dihan Dai\, Department of Mathematics\, University of Utah DESCRIPTION:Abstract: The system of shallow water equations and related models are\nwidely used in oceanography to model hazardous phenomena such as tsunamis\nand storm surges. Unfortunately\, the inherent uncertainties in the system\nwill inevitably damage the credibility of decision-making based on the\ndeterministic model. The stochastic Galerkin (SG) method seeks a solution\nby applying the Galerkin method to the stochastic domain of the equations\nwith uncertainty. However\, the resulting system may fail to preserve the\nhyperbolicity of the original model. In this talk\, we will discuss a\nstrategy to preserve the hyperbolicity of the stochastic systems. We will\nalso discuss a well-balanced hyperbolicity-preserving central-upwind\nscheme for the random shallow water equations and illustrate the\neffectiveness of our schemes on some challenging numerical tests. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-dihan-dai-department-of-mathematics-university-of-utah/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210322T150000 DTEND;TZID=America/Los_Angeles:20210322T160000 DTSTAMP:20260518T150836 CREATED:20210112T180523Z LAST-MODIFIED:20210317T211201Z UID:2108-1616425200-1616428800@colleges.claremont.edu SUMMARY:Applied math. talk: Periodic travelling waves in nonlinear wave equations: modulation instability and rogue waves by Dmitry Pelinovsky\, McMaster University\, Canada DESCRIPTION:Abstract:     I will overview the following different wave phenomena in\nintegrable nonlinear wave equations: \n(1) universal patterns in the dynamics of fluxon condensates in the\nsemi-classical limit;\n(2) modulational instability of periodic travelling waves;\n(3) rogue waves on the background of periodic and double-periodic waves. \nMain examples include the sine-Gordon equation\, the nonlinear\nSchroedinger equation\, and the derivative nonlinear Schroedinger\nequation. For the latter equation\, in collaboration with Jinbing Chen\n(South East University\, China) and Jeremy Upsal (University of\nWashington\, USA)\, we adapted the method of nonlinearization of the Lax\nsystem in order to characterize the existence and modulation stability\nof periodic travelling waves. We give precise information on the\nlocation of Lax and stability spectra\, with assistance of numerical\npackage based on the so-called Hill’s method. Particularly interesting\noutcome is the explicit relation between the onset of modulation\ninstability and the existence of a rogue wave (localized solution in\nspace and time) on the background of periodic travelling waves. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-periodic-travelling-waves-in-nonlinear-wave-equations-modulation-instability-and-rogue-waves-by-dmitry-pelinovsky-mcmaster-university-canada/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210315T150000 DTEND;TZID=America/Los_Angeles:20210315T160000 DTSTAMP:20260518T150836 CREATED:20210114T012637Z LAST-MODIFIED:20210114T012637Z UID:2118-1615820400-1615824000@colleges.claremont.edu SUMMARY:Applied Math. Talk: by a guest University of UTAH DESCRIPTION:TBA URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-a-guest-university-of-utah/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210308T150000 DTEND;TZID=America/Los_Angeles:20210308T160000 DTSTAMP:20260518T150836 CREATED:20210112T180325Z LAST-MODIFIED:20210223T174630Z UID:2106-1615215600-1615219200@colleges.claremont.edu SUMMARY:Applied math. talk: Optimal control of the SIR model in the presence of transmission and treatment uncertainty by Henry Schellhorn\, CGU DESCRIPTION:Abstract \nThe COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes\, or submodels\, of the stochastic SIR model\, where the population consists of three groups: susceptible\, infected and recovered. In the first regime the proportion of infected is very low\, and the proportion of susceptible is very close to 100%.  This corresponds to a disease with few deaths and where recovered individuals do not acquire immunity. In a second regime\, the proportion of infected is moderate\, but not negligible. We show that the first regime corresponds almost exactly to a well-known problem in finance\, the problem of portfolio and consumption decisions under mean-reverting returns (Wachter\, JFQA 2002)\, for which the optimal control has an analytical solution. We develop a perturbative solution for the second problem. To our knowledge\, this paper represents one of the first attempts to develop analytical/perturbative solutions\, as opposed to numerical solutions to stochastic SIR models. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-optimal-control-of-the-sir-model-in-the-presence-of-transmission-and-treatment-uncertainty-by-henry-schellhorn-cgu/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210301T150000 DTEND;TZID=America/Los_Angeles:20210301T160000 DTSTAMP:20260518T150836 CREATED:20210112T180006Z LAST-MODIFIED:20210210T190755Z UID:2104-1614610800-1614614400@colleges.claremont.edu SUMMARY:Applied math. talk: Blowup rate estimates of a singular potential in the Landau-de Gennes theory for liquid crystals by Xiang Xu\, Old Dominion University. DESCRIPTION:Abstract: The Landau-de Gennes theory is a type of continuum theory that\ndescribes nematic liquid crystal configurations in the framework of the\nQ-tensor order parameter. In the free energy\, there is a singular bulk\npotential which is considered as a natural enforcement of a physical\nconstraint on the eigenvalues of symmetric\, traceless Q-tensors. In this\ntalk we shall discuss some analytic properties related to this singular\npotential. More specifically\, we provide precise estimates of both this\nsingular potential\nand its gradient as the Q-tensor approaches its physical boundary. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-xiang-xu-old-dominion-university/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210222T150000 DTEND;TZID=America/Los_Angeles:20210222T160000 DTSTAMP:20260518T150836 CREATED:20210112T175752Z LAST-MODIFIED:20210213T053831Z UID:2102-1614006000-1614009600@colleges.claremont.edu SUMMARY:Applied math. talk: Heatmap centrality: a new measure to identify super-spreader nodes in scale-free networks by Christina Duron\, the University of Arizona DESCRIPTION:Abstract: The identification of potential super-spreader nodes within a network is a critical part of the study and analysis of real-world networks. Motivated by a new interpretation of the “shortest path” between two nodes\, this talk will explore the properties of the recently proposed measure\, the heatmap centrality\, by comparing the farness of a node with the average sum of farness of its adjacent nodes in order to identify influential nodes within the network. As many real-world networks are often claimed to be scale-free\, numerical experiments based upon both simulated and real-world undirected and unweighted scale-free networks are used to illustrate the effectiveness of the new “shortest path” based measure with regards to its CPU run time and ranking of influential nodes. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-heatmap-centrality-a-new-measure-to-identify-super-spreader-nodes-in-scale-free-networks-by-christina-duron-the-university-of-arizona/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210215T150000 DTEND;TZID=America/Los_Angeles:20210215T160000 DTSTAMP:20260518T150836 CREATED:20210114T013414Z LAST-MODIFIED:20210127T210557Z UID:2120-1613401200-1613404800@colleges.claremont.edu SUMMARY:Applied Math. Talk: Modeling and Simulation of Ultrasound-mediated Drug Delivery to the Brain by Peter Hinow\, University of Wisconsin\, Milwaukee DESCRIPTION:We use a mathematical model to describe the delivery of a drug to a specific region of the brain. The drug is carried by liposomes that can release their cargo by application of focused ultrasound. Thereupon\, the drug is absorbed through the endothelial cells that line the brain capillaries and form the physiologically important blood-brain barrier. We present a compartmental model of a capillary that is able to capture the complex binding and transport processes the drug undergoes in the blood plasma and at the blood-brain barrier. We apply this model to the delivery of L-dopa\, (used to treat Parkinson’s disease) and doxorubicin (an anticancer agent). The goal is to optimize the delivery of drug while at the same time minimizing possible side effects of the ultrasound. In a second project\, we present a mathematical model for drug delivery through capillary networks with increasingly complex topologies with the goal to understand the scaling behavior of model predictions on a coarse-to-fine sequence of grids. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-by-peter-hinow-university-of-wisconsin-milwaukee/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20210125T150000 DTEND;TZID=America/Los_Angeles:20210125T160000 DTSTAMP:20260518T150836 CREATED:20210112T173655Z LAST-MODIFIED:20210112T174359Z UID:2092-1611586800-1611590400@colleges.claremont.edu SUMMARY:Applied math. talk: Minimization of the first nonzero eigenvalue problem for two-phase conductors with Neumann boundary conditions by Chiu-Yen Kao\, CMC DESCRIPTION:Abstract: We consider the problem of minimizing the first nonzero eigenvalue of an elliptic operator with Neumann boundary conditions with respect to the distribution of two conducting materials with a prescribed area ratio in a given domain. In one dimension\, we show monotone properties of the first nonzero eigenvalue with respect to various parameters and find the optimal distribution of two conducting materials on an interval under the assumption that the region that has lower conductivity is simply connected. On a rectangular domain in two dimensions\, we show that the strip configuration of two conducting materials can be a local minimizer. For general domains\, we propose a rearrangement algorithm to find the optimal distribution numerically. Many results on various domains are shown to demonstrate the efficiency and robustness of the algorithms. Topological changes of the optimal configurations are discussed on circles\, ellipses\, annuli\, and L-shaped domains. URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-minimization-of-the-first-nonzero-eigenvalue-problem-for-two-phase-conductors-with-neumann-boundary-conditions-by-chiu-yen-kao-cmc/ LOCATION:Zoom meeting\, United States CATEGORIES:Applied Math Seminar END:VEVENT END:VCALENDAR