HORNLESS CHIRPED PULSE FOURIER TRANSFORM MICROWAVE SPECTROMETER

Broadband horn antennas have been used for Fourier transform microwave spectroscopy for a little over a decade. In this report, we will show a more cost effective alternative in describing the reduced cost tandem cavity - chirped pulse FTMW spectrometer being constructed in Flint, Michigan

Quantum critical dynamics of the two-dimensional Bose gas

The dilute, two-dimensional Bose gas exhibits a novel regime of relaxational dynamics in the regime k_B T > |\mu| where T is the absolute temperature and \mu is the chemical potential. This may also be interpreted as the quantum criticality of the zero density quantum critical point at \mu=0. We present a theory for this dynamics, to leading order in 1/\ln (\Lambda/ (k_B T)), where \Lambda is a high energy cutoff. Although pairwise interactions between the bosons are weak at low energy scales, the collective dynamics are strongly coupled even when \ln (\Lambda/T) is large. We argue that the strong-coupling effects can be isolated in an effective classical model, which is then solved numerically. Applications to experiments on the gap-closing transition of spin gap antiferromagnets in an applied field are presented.Comment: 9 pages, 10 figure

Using Unsupervised and Supervised Learning and Digital Twin for Deep Convective Ice Storm Classification

Smart Ice Cloud Sensing (SMICES) is a small-sat concept in which a primary radar intelligently targets ice storms based on information collected by a lookahead radiometer. Critical to the intelligent targeting is accurate identification of storm/cloud types from eight bands of radiance collected by the radiometer. The cloud types of interest are: clear sky, thin cirrus, cirrus, rainy anvil, and convection core. We describe multi-step use of Machine Learning and Digital Twin of the Earth's atmosphere to derive such a classifier. First, a digital twin of Earth's atmosphere called a Weather Research Forecast (WRF) is used generate simulated lookahead radiometer data as well as deeper "science" hidden variables. The datasets simulate a tropical region over the Caribbean and a non-tropical region over the Atlantic coast of the United States. A K-means clustering over the scientific hidden variables was utilized by human experts to generate an automatic labelling of the data - mapping each physical data point to cloud types by scientists informed by mean/centroids of hidden variables of the clusters. Next, classifiers were trained with the inputs of the simulated radiometer data and its corresponding label. The classifiers of a random decision forest (RDF), support vector machine (SVM), Gaussian na\"ive bayes, feed forward artificial neural network (ANN), and a convolutional neural network (CNN) were trained. Over the tropical dataset, the best performing classifier was able to identify non-storm and storm clouds with over 80% accuracy in each class for a held-out test set. Over the non-tropical dataset, the best performing classifier was able to classify non-storm clouds with over 90% accuracy and storm clouds with over 40% accuracy. Additionally both sets of classifiers were shown to be resilient to instrument noise

Ultrafast reversible self-assembly of living tangled matter

Tangled active filaments are ubiquitous in nature, from chromosomal DNA and cilia carpets to root networks and worm blobs. How activity and elasticity facilitate collective topological transformations in living tangled matter is not well understood. Here, we report an experimental and theoretical study of California blackworms (Lumbriculus variegatus), which slowly form tangles over minutes but can untangle in milliseconds. Combining ultrasound imaging, theoretical analysis and simulations, we develop and validate a mechanistic model that explains how the kinematics of individual active filaments determines their emergent collective topological dynamics. The model reveals that resonantly alternating helical waves enable both tangle formation and ultrafast untangling. By identifying generic dynamical principles of topological self-transformations, our results can provide guidance for designing new classes of topologically tunable active materials

Mars Image Content Classification: Three Years of NASA Deployment and Recent Advances

The NASA Planetary Data System hosts millions of images acquired from the planet Mars. To help users quickly find images of interest, we have developed and deployed content-based classification and search capabilities for Mars orbital and surface images. The deployed systems are publicly accessible using the PDS Image Atlas. We describe the process of training, evaluating, calibrating, and deploying updates to two CNN classifiers for images collected by Mars missions. We also report on three years of deployment including usage statistics, lessons learned, and plans for the future.Comment: Published at the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). IAAI Innovative Application Award. 10 pages, 11 figures, 6 table

Cumulative effects of the Gulf oil spill and other disasters on mental health among reproductive-aged women: The Gulf Resilience on Women's Health study.

OBJECTIVE:To test whether effects of multiple (up to 5) disasters on mental health responses were cumulative (additive effects), or whether an earlier disaster produced sensitization (higher) or habituation (lower) responses to a later one. METHOD:The Gulf Resilience on Women's Health study interviewed 1,366 southern Louisiana women regarding their exposure to Hurricanes Katrina, Rita, Gustav, and Ike and the Gulf oil spill (measured several ways), and administered validated measures of symptoms of depression and posttraumatic stress disorder (PTSD). Multiple linear and logistic regression with disaster exposures entered singly, combined, and as an interaction were used to model mental health. RESULTS:Both exposure to the oil spill and hurricane disaster were associated with likely depression and PTSD, consistent with a cumulative model, but we did not find statistical interactions that would suggest sensitization or habituation. When results were examined with continuous symptom measures of depression and PTSD, they were similar, with the exception that exposure to the oil spill and experiencing illness or injury because of the hurricane disaster showed a significant interaction (p < .05) in a manner consistent with a sensitization effect when predicting PTSD symptoms. The results of this study point mainly to a cumulative risk for the mental health effects of multiple disasters, although some indication of sensitization occurred among those with particularly severe experiences. There was no evidence for habituation. CONCLUSIONS:These findings may guide efforts to assist those in regions experiencing multiple disasters that occur in close sequence. (PsycINFO Database Recor

Cumulative effects of the Gulf oil spill and other disasters on mental health among reproductive-aged women: The Gulf Resilience on Women's Health study.

OBJECTIVE:To test whether effects of multiple (up to 5) disasters on mental health responses were cumulative (additive effects), or whether an earlier disaster produced sensitization (higher) or habituation (lower) responses to a later one. METHOD:The Gulf Resilience on Women's Health study interviewed 1,366 southern Louisiana women regarding their exposure to Hurricanes Katrina, Rita, Gustav, and Ike and the Gulf oil spill (measured several ways), and administered validated measures of symptoms of depression and posttraumatic stress disorder (PTSD). Multiple linear and logistic regression with disaster exposures entered singly, combined, and as an interaction were used to model mental health. RESULTS:Both exposure to the oil spill and hurricane disaster were associated with likely depression and PTSD, consistent with a cumulative model, but we did not find statistical interactions that would suggest sensitization or habituation. When results were examined with continuous symptom measures of depression and PTSD, they were similar, with the exception that exposure to the oil spill and experiencing illness or injury because of the hurricane disaster showed a significant interaction (p < .05) in a manner consistent with a sensitization effect when predicting PTSD symptoms. The results of this study point mainly to a cumulative risk for the mental health effects of multiple disasters, although some indication of sensitization occurred among those with particularly severe experiences. There was no evidence for habituation. CONCLUSIONS:These findings may guide efforts to assist those in regions experiencing multiple disasters that occur in close sequence. (PsycINFO Database Recor

Pregnancy anxiety and preterm birth: The moderating role of sleep.

ObjectivePreterm birth (PTB) is a prevalent public health concern. Pregnancy anxiety, poor sleep quality, and short sleep duration have been associated with an increased risk of PTB. Theoretically, sleep variables could moderate the strength of the relationship between pregnancy anxiety and PTB; investigating this question was the primary aim of this study.MethodThe sample consisted of 290 pregnant women who were assessed at 2 time points in pregnancy: Time 1 (< 22 weeks gestational age [GA]; MGA = 15.04, SD = 3.55) and Time 2 (32 weeks GA; MGA = 32.44, SD = 0.99). Pregnancy anxiety was assessed with the Pregnancy-Related Anxiety Scale, sleep quality was assessed by the Pittsburgh Sleep Quality Index, and sleep duration was assessed via actigraphy. Data on gestational age at birth were obtained from the electronic medical record.ResultsAfter adjustment for relevant covariates, higher levels of pregnancy anxiety were associated with shorter gestational length and an increased risk of PTB. There were no direct associations between sleep quality or sleep duration and gestational length or PTB. Pregnancy anxiety interacted with sleep duration such that pregnancy anxiety was significantly associated with shorter gestational length and PTB only when women had relatively shorter sleep duration (approximately < 8.3 hr).ConclusionsThis study reveals new evidence of an interaction between pregnancy anxiety and sleep duration in the prediction of the timing of delivery. The findings point to avenues to better understand and potentially ameliorate risk for PTB. (PsycINFO Database Record (c) 2019 APA, all rights reserved)