Medical Errors

Overview: Time of Death: 5:07 p.m. – Proceeding the solemn afternoon of February 22nd 2003, the Santillian family listened on as doctors told them that their cherished loved one was officially pronounced brain dead and would soon have to be taken off life support. Two weeks prior to this, seventeen-year-old Jesica Santillian received the thrilling news that she had finally been matched with a heart-lung donor and would be admitted to Duke University Medical Center in early February for a double-organ transplant. After years of living in pain brought on by her failing organs, Jesica was supposed to be one of the lucky ones, that is, until an ill-fated call received an hour after the new organs had been put in turned her luck upside down. The call was from a technician in the immunology lab saying that something had gone terribly wrong; Jesica’s blood type, type O, did not match the blood type her new organs, which were type A. What that meant was that Jesica’s life was in serious danger because the antibodies in her blood would shortly start attacking and destroying her new organs. Two weeks and an odds-shattering second set of donated organs later, the near death teenager’s family said their last goodbyes as the medication that kept her heart going was discontinued and her heart took its last untimely beat seven minutes later (Kopp 1)

Diversification of Wairarapa hill country : the potential for agroforestry : a thesis presented in partial fulfilment of the requirements for the degree of Master of Agricultural Science at Massey University

The purpose of this study was to investigate the potential for agroforestry on Wairarapa Hill Country farms. It was set against a background of a marked decline in real farm income on hill country sheep and beef farms in recent years. A broad perspective on project evaluation was taken with a review of the system components presented; covering hill country farming in New Zealand, the Wairarapa, Forestry in New Zealand, and Agroforestry. The results of an intertemporal linear programming model covering a 21 year period, suggest that agroforestry can be both a profitable and feasible investment for Wairarapa Hill Country farmers. Profitability is shown to be strongly influenced by the suitability of planting sites and final timber value. With respect to feasibility, cash-flow considerations are of overriding importance. Together with factors considered outside the model, particularly the management of an integrated livestock and agroforestry property, the need for individual evaluation of each circumstance is stressed. It is recommended that significant development of agroforestry in the Wairarapa will require some form of District Association to co-ordinate planting and marketing, and provide suitable extension and management services. Further development of the model for both agroforestry and land use evaluation is suggested

A numerical study of three-dimensional vortex breakdown

A numerical simulation of bubble-type vortex breakdown using a unique discrete form of the full 3-D, unsteady incompressible Navier-Stokes equations was performed. The Navier-Stokes equations were written in a vorticity-velocity form and the physical problem was not restricted to axisymmetric flow. The problem was parametized on a Rossby- Reynolds-number basis. Utilization of this parameter duo was shown to dictate the form of the free-field boundary condition specification and allowed control of axial breakdown location within the computational domain. The structure of the breakdown bubble was studied through time evolution plots of planar projected velocity vectors as well as through plots of particle traces and vortex lines. These results compared favorably with previous experimental studies. In addition, profiles of all three velocity components are presented at various axial stations and a Fourier analysis was performed to identify the dominant circumferential modes. The dynamics of the breakdown process were studied through plots of axial variation of rate of change of integrated total energy and rate of change of integrated enstrophy, as well as through contour plots of velocity, vorticity and pressure

Thermally forced transients in the thermohaline circulation

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 45 (2015): 2820–2835, doi:10.1175/JPO-D-15-0101.1.The response of a convective ocean basin to variations in atmospheric temperature is explored using numerical models and theory. The results indicate that the general behavior depends strongly on the frequency at which the atmosphere changes relative to the local response time to air–sea heat flux. For high-frequency forcing, the convective region in the basin interior is essentially one-dimensional and responds to the integrated local surface heat flux anomalies. For low-frequency forcing, eddy fluxes from the boundary current into the basin interior become important and act to suppress variability forced by the atmosphere. A theory is developed to quantify this time-dependent response and its influence on various oceanic quantities. The amplitude and phase of the temperature and salinity of the convective water mass, the meridional overturning circulation, the meridional heat flux, and the air–sea heat flux predicted by the theory compare well with that diagnosed from a series of numerical model calculations in both strongly eddying and weakly eddying regimes. Linearized analytic solutions provide direct estimates of each of these quantities and demonstrate their dependence on the nondimensional numbers that characterize the domain and atmospheric forcing. These results highlight the importance of mesoscale eddies in modulating the mean and time-dependent ocean response to atmospheric variability and provide a dynamical framework with which to connect ocean observations with changes in the atmosphere and surface heat flux.This study was supported by the National Science Foundation under Grant OCE-1232389.2016-05-0

Control of Complex Dynamic Systems by Neural Networks

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations

On the circulation of Atlantic Water in the Arctic Ocean

Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 43 (2013): 2352–2371, doi:10.1175/JPO-D-13-079.1.An idealized eddy-resolving numerical model and an analytic three-layer model are used to develop ideas about what controls the circulation of Atlantic Water in the Arctic Ocean. The numerical model is forced with a surface heat flux, uniform winds, and a source of low-salinity water near the surface around the perimeter of an Arctic basin. Despite this idealized configuration, the model is able to reproduce many general aspects of the Arctic Ocean circulation and hydrography, including exchange through Fram Strait, circulation of Atlantic Water, a halocline, ice cover and transport, surface heat flux, and a Beaufort Gyre. The analytic model depends on a nondimensional number, and provides theoretical estimates of the halocline depth, stratification, freshwater content, and baroclinic shear in the boundary current. An empirical relationship between freshwater content and sea surface height allows for a prediction of the transport of Atlantic Water in the cyclonic boundary current. Parameters typical of the Arctic Ocean produce a cyclonic boundary current of Atlantic Water of O(1 − 2 Sv; where 1 Sv ≡ 106 m3 s−1) and a halocline depth of O(200 m), in reasonable agreement with observations. The theory compares well with a series of numerical model calculations in which mixing and environmental parameters are varied, thus lending credibility to the dynamics of the analytic model. In these models, lateral eddy fluxes from the boundary and vertical diffusion in the interior are important drivers of the halocline and the circulation of Atlantic Water in the Arctic Ocean.This study was supported by the National Science Foundation under Grants OCE- 0850416, OCE-0959381, and OCE-1232389.2014-05-0

Optimal random perturbations for stochastic approximation using a simultaneous perturbation gradient approximation

The simultaneous perturbation stochastic approximation (SPSA) algorithm has recently attracted considerable attention for optimization problems where it is di cult or impossible to obtain a direct gradient of the objective (say, loss) function. The approach is based on a highly e cient simultaneous perturbation approximation to the gradient based on loss function measurements. SPSA is based on picking a simultaneous perturbation (random) vector in a Monte Carlo fashion as part of generating the approximation to the gradient. This paper derives the optimal distribution for the Monte Carlo process. The objective is to minimize the mean square error of the estimate. We also consider maximization of the likelihood that the estimate be con ned within a bounded symmetric region of the true parameter. The optimal distribution for the components of the simultaneous perturbation vector is found to be a symmetric Bernoulli in both cases. We end the paper with a numerical study related to the area of experiment design. 1

Variational quantum Monte Carlo simulations with tensor-network states

We show that the formalism of tensor-network states, such as the matrix product states (MPS), can be used as a basis for variational quantum Monte Carlo simulations. Using a stochastic optimization method, we demonstrate the potential of this approach by explicit MPS calculations for the transverse Ising chain with up to N=256 spins at criticality, using periodic boundary conditions and D*D matrices with D up to 48. The computational cost of our scheme formally scales as ND^3, whereas standard MPS approaches and the related density matrix renromalization group method scale as ND^5 and ND^6, respectively, for periodic systems.Comment: 4+ pages, 2 figures. v2: improved data, comparisons with exact results, to appear in Phys Rev Let