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At least 1,009 records · Page 56

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DSN system performance test Doppler noise models; noncoherent configuration

The newer model for variance, the Allan technique, now adopted for testing, is analyzed in the subject mode. A model is generated (including considerable contribution from the station secondary frequency standard), and rationalized with existing data. The variance model is definitely sound; the Allan technique mates theory and measure. The mean-frequency model is an estimate; this problem is yet to be rigorously resolved. The unaltered defining expressions are noncovergent, and the observed mean is quite erratic.

Bunce, R.↗

Hybrid random-sound test-control system

Controller develops gain-control signals by comparing detected sound levels in each band with reference set levels. By eliminating multiplexing network and single clock used in digital system, design allows servocontrol rate for each band to be adjusted independently.

Woodbury, R. C.↗

Preliminary design and development of a reflectance spectrometer instrument

An improved design for the reflectance spectrometer is described to be used on various terrestrial body missions. These improvements were made on the original Lunar Polar Orbiter design. These include a larger entrance mirror, rectangular aperture, multiple optical beams, spatial resolution, and a bandwidth extension to 5 microns. In addition, detailed electronic designs were produced for a charge amplifier and an amplifier/demodulator/integrator. Design of a microprocessor driven test system was begun. Laboratory tests were performed on a tuning fork chopper.

Mccord, T. B.↗

Rubidium frequency standard test program for NAVSTAR GPS

Test data of the RFS Program in the Production phase and computer automation are presented, as an essential element in the evaluation of the RFS performance in a simulated spacecraft environment. Typical production test data will be discussed for stabilities from 1 to 100,000 seconds averaging time and simulated time error accumulation test. Also, design considerations in developing the RFS test systems for the acceptance test in production are discussed.

Koide, F.↗