{"title":"William Schiesser","description":null,"products":[{"product_id":"biomedical-applications-in-r-moving-boundary-pde-analysis-book-william-schiesser-9780415003223","title":"Biomedical Applications in R: Moving Boundary PDE Analysis","description":"This collection of over 3000 quotations not only records the diverse responses inspired by artists and their art through the ages, but also the \"bons mots\" of the artists themselves.","brand":"WoB","offers":[{"title":"GB \/ WELL_READ \/ INTERNAL","offer_id":49595523170577,"sku":"GOR009828326","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ GOOD \/ INTERNAL","offer_id":49630424727825,"sku":"GOR002823865","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":49642171400465,"sku":"GOR005121310","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0415003229.jpg?v=1751292364"},{"product_id":"chemotaxis-modeling-of-autoimmune-inflammation-book-william-schiesser-9781032317649","title":"Chemotaxis Modeling of Autoimmune Inflammation","description":"In response to an infection (e.g., from pathogens such as bacteria and viruses), the immune system can deplete macrophages (specialized white blood cells) and produce cytokines that are pro-inflammatory or anti-inflammatory. This counterproductive autoimmune response is represented mathematically as nonlinear chemotaxis diffusion.  This book is directed to the computer-based modeling of chemotaxis inflammation. The spatiotemporal analysis is  based on a model of three partial differential equations (PDEs).   The three PDE model is coded (programmed) as a set of routines in R, a quality, open-source, scientific programming system. The numerical integration (solution) of the PDEs is by the method of lines (MOL).  The three PDE model can be used for computer-based experimentation, for example, parameter variation and changes in the model equations or alternate models, to enhance a quantitative understanding of a postulated  inflammation.  This experimentation is illustrated by chapters pertaining to: (1) the computation and display of the PDE time derivatives, (2) the RHS terms of the PDEs with emphasis on the chemotaxis terms, (3) parameter variations to demonstrate parameter effects and sensitivities and (4) additonal terms in the PDEs to include PDE coupling and extensions of the basic PDE model.","brand":"WoB","offers":[{"title":"US \/ NEW \/ INGRAM","offer_id":51225475350801,"sku":"NIN9781032317649","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":53078822584593,"sku":"NLS9781032317649","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1032317647.jpg?v=1750751343"},{"product_id":"ode-pde-analysis-of-multiple-myeloma-book-william-schiesser-9780367495510","title":"ODE\/PDE Analysis of Multiple Myeloma","description":"Multiple myeloma is a form of bone cancer. Specifically, it is a cancer of the plasma cells found in bone marrow (bone soft tissue). Normal plasma cells are an important part of the immune system.  Mathematical models for multiple myeloma based on ordinary and partial differential equations (ODE\/PDEs) are presented in this book, starting with a basic ODE model in Chapter 1, and concluding with a detailed ODE\/PDE model in Chapter 4 that gives the spatiotemporal distribution of four dependent variable components in the bone marrow and peripheral blood: (1) protein produced by multiple myeloma cells, termed the M protein, (2) cytotoxic T lymphocytes (CTLs), (3) natural killer (NK) cells, and (4) regulatory T cells (Tregs).  The computer-based implementation of the example models is presented through routines coded (programmed) in R, a quality, open-source scientific computing system that is readily available from the Internet. Formal mathematics is minimized, e.g., no theorems and proofs. 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The book has particular relevance to the coronavirus pandemic since long-Covid neurological impairment may be the result of brain inflammation.","brand":"WoB","offers":[{"title":"US \/ NEW \/ INGRAM","offer_id":51296780353809,"sku":"NIN9781032316062","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52459187831057,"sku":"NLS9781032316062","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1032316063.jpg?v=1751143059"},{"product_id":"numerical-modeling-of-covid-19-neurological-effects-book-william-schiesser-9781032152110","title":"Numerical Modeling of COVID-19 Neurological Effects","description":"Covid-19 is primarily a respiratory disease which results in impaired oxygenation of blood. The O2-deficient blood then moves through the body, and for the study in this book, the focus is on the blood flowing to the brain. The dynamics of blood flow along the brain capillaries and tissue is modeled as systems of ordinary and partial differential equations (ODE\/PDEs).  The ODE\/PDE methodology is presented through a series of examples,  1. A basic one PDE model for O2 concentration in the brain capillary blood.  2. A two PDE model for O2 concentration in the brain capillary blood and in the brain tissue, with O2 transport across the blood brain barrier (BBB).  3. The two model extended to three PDEs to include the brain functional neuron cell density.  Cognitive impairment could result from reduced neuron cell density in time and space (in the brain) that follows from lowered O2 concentration (hypoxia).   The computer-based implementation of the example models is presented through routines coded (programmed) in R, a quality, open-source scientific computing system that is readily available from the Internet. Formal mathematics is minimized, e.g., no theorems and proofs. Rather, the presentation is through detailed examples that the reader\/researcher\/analyst can execute on modest computers. The PDE analysis is based on the method of lines (MOL), an established general algorithm for PDEs, implemented with finite differences.  The routines are available from a download link so that the example models can be executed without having to first study numerical methods and computer coding. 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