1,518 research outputs found
Continuum structure of Ca40
The total S1- matrix of Ca40 has been calculated for excitation energies between 11 and 28 MeV. As typical results, the (γ, p0) and the total absorption cross sections are shown and compared with experiments. It is shown that the proper treatment of the one-particle, one-hole shell-model continuum accounts for most of the observed structures
A Classification Scheme for Phenomenological Universalities in Growth Problems
A classification in universality classes of broad categories of
phenomenologies, belonging to different disciplines, may be very useful for a
crossfertilization among them and for the purpose of pattern recognition. We
present here a simple scheme for the classification of nonlinear growth
problems. The success of the scheme in predicting and characterizing the well
known Gompertz, West and logistic models suggests to us the study of a hitherto
unexplored class of nonlinear growth problems.Comment: 4 pages,1 figur
Reaction time and speed of movement of junior high school students grades 8-9.
Thesis (Ed.M.)--Boston Universit
Does Cancer Growth Depend on Surface Extension?
We argue that volumetric growth dynamics of a solid cancer depend on the
tumor system's overall surface extension. While this at first may seem evident,
to our knowledge, so far no theoretical argument has been presented explaining
this relationship explicitly. In here, we therefore develop a conceptual
framework based on the universal scaling law and then support our conjecture
through evaluation with experimental data.Comment: 11 pages, 1 figur
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DEVELOPMENT OF A DECISION SUPPORT SYSTEM WEBTOOL FOR HISTORIC AND FUTURE LOW FLOW ESTIMATION IN THE NORTHEAST UNITED STATES WITH APPLICATIONS OF MACHINE LEARNING FOR ADVANCING PHYSICAL AND STATISTICAL METHODOLOGIES
Droughts are a global challenge and anthropogenic climate change is expected to increase the frequency and severity of extreme low flow events. A major challenge for resource managers is how best to incorporate future climate change projections into low flow event estimations, especially in ungaged basins. Using both physically based hydrology models and statistical models, this dissertation contributes novel methodologies to three key challenges associated with 7-day, 10-year low flow (7Q10) estimation in the northeast United States. Chapter 2 builds upon statistically based 7Q10 estimation in ungaged basins by comparing multiple machine learning algorithms to classical statistical methodologies. This chapter’s objective is to identify a robust statistical methodology applicable for the entire northeast U.S. that includes statistically significant climate variables that allow for the incorporation of climate change. Results suggest that the random forest method can provide regional 7Q10 estimates with similar errors to current, state-by-state 7Q10 estimates. Chapter 3 tests the applicability of a novel machine learning algorithm, Fuzzy C-Means clustering, to calibrate rainfall-runoff models in ungaged basins for both daily streamflow and 7Q10 estimation. Future updates to national rainfall-runoff models, which can directly incorporate climate change projections into calculations, will allow these models to be created in ungaged basins, but they will require extensive calibration and/or verification. Results suggest that this methodology significantly improves daily streamflow estimation but fails to improve 7Q10 estimation. Chapter 4 summarizes the development of a stakeholder-driven decision support system (DSS) web-application for calculating the 7Q10 at gages and estimating the 7Q10 in ungaged basins with projected climate changes. By incorporating the statistical model from Chapter 2 into the DSS and comparing the results to the physical modeling from Chapter 3, the DSS can estimate the impact of future temperature and precipitation changes on 7Q10s. This work highlights advancements in physical and statistical modeling techniques for 7Q10 estimation in ungaged basins and assists resource managers in addressing a growing need for incorporating anticipated climate change into drought calculations
A New Computational Tool for the Phenomenological Analysis of Multipassage Tumor Growth Curves
Multipassage experiments are performed by subcutaneous implantation in lab animals (usually mice) of a small number of cells from selected human lines. Tumor cells are then passaged from one mouse to another by harvesting them from a growing tumor and implanting them into other healthy animals. This procedure may be extremely useful to investigate the various mechanisms involved in the long term evolution of tumoral growth. It has been observed by several researchers that, contrary to what happens in in vitro experiments, there is a significant growth acceleration at each new passage. This result is explained by a new method of analysis, based on the Phenomenological Universalities approach. It is found that, by means of a simple rescaling of time, it is possible to collapse all the growth curves, corresponding to the successive passages, into a single curve, belonging to the Universality Class U2. Possible applications are proposed and the need of further experimental evidence is discussed
A Growth Model for Multicellular Tumor Spheroids
Most organisms grow according to simple laws, which in principle can be
derived from energy conservation and scaling arguments, critically dependent on
the relation between the metabolic rate B of energy flow and the organism mass
m. Although this relation is generally recognized to be of the form B(m) = mp,
the specific value of the exponent p is the object of an ongoing debate, with
many mechanisms being postulated to support different predictions. We propose
that multicellular tumor spheroids provide an ideal experimental model system
for testing these allometric growth theories, especially under controlled
conditions of malnourishment and applied mechanical stress
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