Effects of an Acoustic Stimulus upon Growth, Antibody Synthesis and Leukocyte Values

Physiologic effects of an acoustic stimulus of 1.0 Khz at 96 db(A) upon female hooded rats are discussed. Six possible reasons are offered for failure to attain statistical significance, except in intermediate aspects, between control and experimental animals

Navigating an Undergraduate Teacher Licensure Program as a Non-Traditional Student

Nearly eight million “non-traditional” students face adversity beyond financial instability, childcare, or full or part-time work when seeking teacher licensure. They must manage logging clinical hours in schools far from home, feel isolated in cohorts of 18– 20-year-olds, and sometimes lack support and flexibility from their professors and advisors. We surveyed non-traditional, undergraduate, teacher licensure candidates at a large midwestern university to better understand current attending students\u27 demographics and determine if any relationship(s) existed between variables related to logistical decisions, supports received, or barriers faced/encountered. We summarized findings from 53 participants and offered suggestions to university administrators, professors, and staff to support the growing population of non-traditional teacher candidates

Life Sciences, Technology, and the Law - Symosium Transcript - March 7, 2003

Life sciences, Technology, and the Law Symposium held at the University of Michigan Law School Friday, March 7, 200

Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models

Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale cereale L.), triticale (Triticale × Triticosecale L.), vetch (Vicia sativa L.), and wheat (Triticum aestivum L.)] using high-throughput phenotyping and Machine Learning (ML) models. Destructive AGB sampling was performed three times during each spring season in 2022 and 2023. An array of morphological, spectral, thermal, and environmental features from the sensors were utilized as feature inputs of ML models. Moderately strong linear correlations between AGB and the selected features were observed. Four ML models, namely Random Forests Regression (RFR), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), and Artificial Neural Network (ANN), were investigated. Among the four models, PLSR achieved the highest Coefficient of Determination (R2) of 0.84 and the lowest Root Mean Squared Error (RMSE) of 892 kg/ha (Normalized RMSE (NRMSE) = 8.87%), indicating that PLSR could be the most appropriate method for estimating AGB of multiple cover crop species. Feature importance analysis ranked spectral features like Normalized Difference Red Edge (NDRE), Solarinduced Fluorescence (SIF), Spectral Reflectance at 485 nm (R485), and Normalized Difference Vegetation Index (NDVI) as top model features using PLSR. When utilizing fewer feature inputs, ANN exhibited better prediction performance compared to other models. Using morphological and spectral parameters as input features alone led to a R2 of 0.80 and 0.77 for AGB prediction using ANN, respectively. This study demonstrated the feasibility of high-throughput phenotyping and ML techniques for accurately estimating AGB of multiple cover crop species. Further enhancement of model performance could be achieved through additional destructive sampling conducted across multiple locations and years

Coherent control of flexural vibrations in dual-nanoweb fibers using phase-modulated two-frequency light

Coherent control of the resonant response in spatially extended optomechanical structures is complicated by the fact that the optical drive is affected by the back-action from the generated phonons. Here we report a new approach to coherent control based on stimulated Raman-like scattering, in which the optical pressure can remain unaffected by the induced vibrations even in the regime of strong optomechanical interactions. We demonstrate experimentally coherent control of flexural vibrations simultaneously along the whole length of a dual-nanoweb fiber, by imprinting steps in the relative phase between the components of a two-frequency pump signal,the beat frequency being chosen to match a flexural resonance. Furthermore, sequential switching of the relative phase at time intervals shorter than the lifetime of the vibrations reduces their amplitude to a constant value that is fully adjustable by tuning the phase-modulation depth and switching rate. The results may trigger new developments in silicon photonics, since such coherent control uniquely decouples the amplitude of optomechanical oscillations from power-dependent thermal effects and nonlinear optical loss.Comment: This 11 pages-long document includes the main text with 8 figures and an appendix with one figur

Price Discovery and the Accuracy of Consolidated Data Feeds in the U.S. Equity Markets

Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor, the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor, or SIP, we focus here on its accuracy. Relying on Trade and Quote data, we provide various measures of SIP latency relative to high-speed data feeds between exchanges, known as direct feeds. We use first differences to highlight not only the divergence between the direct feeds and the SIP, but also the fundamental inaccuracy of the SIP. We find that as many as 60 percent or more of trades are reported out of sequence for stocks with high trade volume, therefore skewing simple measures such as returns. While not yet definitive, this analysis supports our preliminary conclusion that the underlying infrastructure of the SIP is currently unable to keep pace with the trading activity in today's stock market.Comment: 18 pages, 20 figures, 2 table

Single exciton trapping in an electrostatically defined 2D semiconductor quantum dot

Interlayer excitons (IXs) in 2D semiconductors have long lifetimes and spin-valley coupled physics, with a long-standing goal of single exciton trapping for valleytronic applications. In this work, we use a nano-patterned graphene gate to create an electrostatic IX trap. We measure a unique power-dependent blue-shift of IX energy, where narrow linewidth emission exhibits discrete energy jumps. We attribute these jumps to quantized increases of the number occupancy of IXs within the trap and compare to a theoretical model to assign the lowest energy emission line to single IX recombination