Meta Analysis in Model Implementation: Choice Sets and the Valuation of Air Quality Improvements

We document the sensitivity of welfare estimates derived from discrete choice models to assumptions about the choice set. Such assumptions can affect welfare estimates through both the estimated parameters of the model and, conditional on the parameters, the substitution among alternatives. Our analysis involves estimates of the benefits of air quality improvements in Los Angeles based on discrete choices of neighborhood and housing. We further illustrate the use of meta analysis to document and summarize voluminous information derived from repeated sensitivity analyses.Meta analysis, random utility model, choice set, air quality, housing

Validation of a 5-minute VPC Test to Assess and Compare Cognitively Intact Individuals and Individuals with Cognitive Impairments

The prevalence of cognitive impairments in the older adult population is growing. Finding treatment solutions to impede a cognitive decline can possibly lead to fewer cases of mild cognitive impairment, dementia, and Alzheimer’s disease. A Visual Paired Comparison (VPC) could serve as a tool to predict, monitor, and regulate people who are susceptible to a cognitive decline. The purpose of this study was to 1) to determine the validity of the Neurotrack 5-minute VPC test with the Neurotrack 30-minute VPC test, 2) to determine the test-retest reliability of the Neurotrack 5-minute VPC test, 3) to compare Neurotrack 5-minute VPC scores between individuals with cognitive impairment (Mild Cognitive Impairment and/or Alzheimer\u27s Disease) to cognitively intact adults, 4) lastly to compare Neurotrack VPC results with other cognitive tasks (MoCA, NIH toolbox, Dual task) performed within the study. This study included older adults age 60+ split into cognitively intact individuals and cognitively impaired individuals based from the MoCA. Analysis was ran on 28 subject in which 11 were cognitively impaired (mean=.687; Std=.137) and 17 were cognitively intact (mean=.851; Std=.044). The relationship between 5-minute VPC and the 30-minute VPC revealed a positive associations for both the first (r=.504; p=.006) and second (r=.420; p=.019) time points/trials. No significant differences between the 2 time points/trials (p=.212) which indicates a reliable 5-minute VPC test. A significant difference was found between the groups (p=.000). Domain-specific cognitive functions were examined through other assessments, in which the 5-minute VPC test was correlated to each of these tests. This study suggests that VPC to be a potentially reliable tool to assess cognitive function

Real-Time Filters

This project\u27s goal is to create a visual representation of digital signal processing using a Raspberry Pi Pico board. External components will interface with the Pico to supply digital signals and display the results after processing the signal. A microphone will supply the signal to the Pico which will perform a Fourier Transform on the data and output a spectrogram to a display. The display is named ILI9341 which includes an SPI interface, micro SD card slot, and a 2.2 inch screen. The spectrogram includes the magnitudes of the transformed signal at each frequency and time. Each magnitude is illustrated as a color that indicates what the magnitude is in decibels. Each color also has 32 different shades which also indicates if the magnitude is less or greater. Additionally, each of the 12 colors represents decibel ranges between 0 and 10. The frequency axis of the spectrogram ranges from 0 to 20,000Hz as this is the range for audio signals. In order to program the raspberry pi pico, the computer programming language C++ is used. C++ allows the user to implement instructions that will be executed. C++ can control the entire board with access to input and output pins. The code will read data sent by a microphone to an ADC pin and store the data as digital values. A Fourier Transform is performed on the input data which is sent to the pins connected to the ILI9341 LCD display. The sent data tells the display to draw pixels with color for each frequency and magnitude. The screen is refreshed as new data is collected and sent