Los Alamos Public Schools

Isomerization of molecular systems is ubiquitous in chemistry and biology, and is also important for many applications. Atomistic simulations can help determine the tunable parameters influencing this process. In this paper, we use the Nonadiabatic EXcited state Molecular Dynamics (NEXMD) software to study the photoisomerization of a representative molecule, 4-styrylquinoline (SQ). trans-SQ transforms into dihydrobenzophenanthridine (DHBP) upon irradiation with laser light, with the cis conformer acting as an intermediate. We study how varying three different external stimuli (i.e., apolar versus polar solvent, low versus high photoexcitation energy, and vacuum versus a constant temperature thermostat) affects the trans-to- cis photoisomerization of SQ. Our results show that polarization effects due to implicit solvation and the thermostat play a crucial role in the isomerization process, whereas photoexcitation energy plays a lesser role on the outcome and efficiency. We also show that NEXMD captures the correct energy profile between the ground and first singlet excited state, showing that there are two distinct reaction pathways to the final stable product that vary by the number of photons absorbed, in agreement with experiment. Ultimately, NEXMD proves to be an effective tool for investigating excited state single molecule dynamics subject to various environments and initial conditions.

Developing countries often have poor monitoring and reporting of weather and crop health, leading to slow responses to droughts and food shortages. Here I develop satellite analysis methods and software tools to predict crop yields two to four months before the harvest. This method measures relative vegetation health based on pixel-level monthly anomalies of NDVI, EVI and NDWI. Because no crop mask, tuning, or subnational ground truth data is required, this method can be applied to any location, crop, or climate, making it ideal for African countries with small fields and poor ground observations. Testing began in Illinois where there is reliable county-level crop data. Correlations were computed between corn, soybean, and sorghum yields and monthly vegetation health anomalies for every county and year. A multivariate regression using every index and month (up to 1600 values) produced a correlation of 0.86 with corn, 0.74 for soybeans, and 0.65 for sorghum, all with p-values less than 10e-6. The high correlations in Illinois show that this model has good forecasting skill for crop yields. Next, the method was applied to every country in Africa for each country’s main crops. Crop production was then predicted for the 2018 harvest and compared to actual production values. Twenty percent of the predictions had less than 2% error, and 40% had less than 5% error.

Most infrastructure in America is approaching or has exceeded the intended design life. As infrastructure ages, danger is presented to the citizens and the environment. Disasters like the failure of the Oroville Dam emphasize the importance of preventing failure of infrastructure. Despite Structural Health Monitoring (SHM) emerging as the key discipline to evaluate the integrity of structures, human-based visual inspections remain the dominant technique. Main factors behind the slow adoption of the SHM technology are its high installation and maintenance costs, the low confidence level of decision makers in the technology, and the structural community’s familiarity with visual inspections. One major drawback to visual inspection is that it can be highly subjective, relying on a small number of manually recorded data points. Inspectors use tape measures, digital cameras, and human senses. These tools are inadequate to capture and document the state of infrastructure at the resolution needed for tracking damage progression. When working with infrastructure, it is desirable to have high-resolution measurement techniques to detect, localize, and characterize the state of a structure. The present work investigates Augmented Reality (AR) to minimize visual inspection drawbacks. AR is a technology that can superimpose holograms onto the real world. In this work an AR headset is used to enhance the ability of human inspectors to perform infrastructure inspections. The headset features RGB and depth cameras, accelerometers, wireless communication, microphones, and stereo sound. These sensors can capture a high-resolution 3D measurement of the infrastructure being inspected along with RGB photos that can be overlaid on the geometry. The 3D measurement can be used to analyze the state of the structure over time, and track damage progression. The 3D model can also be used as a base to overlay data captured with diverse sensors. The proposed technique will ultimately improve inspectors’ ability to assess risk on site, make informed decisions faster, analyze defect growth over time, and create high-resolution documentation of structural inspections that will reduce the variability that occurs. Overall, AR is a promising technique for infrastructure inspection, mapping infrastructure on site, generating models, and providing consistency between inspectors. This technology has considerable potential for improving the quality of infrastructure inspections.

One hundred male and 100 female undergraduate students viewed erotic slides depicting a wide range of human sexual behaviors. Each subject rated the stimuli on three criteria: sexual stimulation, liking for the slide, and extremeness of the behavior portrayed. Following the rating session, subjects completed Thorne's Sex Inventory, which theoretically measures psychosexual adjustment. Results indicated that males and females reported minimal sexual stimulation and minimal liking for the slides, but males in general reported greater sexual stimulation and liking than did females. In terms of rated extremeness, males and females showed quite close agreement, differing significantly on only one slide. It was also found that males rated a greater number of the slides considered to be the more extreme as more sexually stimulating and more liked than did females. Both males and females, however, tended overall to rate the more extreme slides as less sexually stimulating and less liked. This relationship was stronger for females than for males. Results indicated that scales on the Sex Inventory did not correlate positively with ratings of sexual stimulation and liking for the slides, and scales theoretically indicating sexual maladjustment failed to consistently correlate negatively with ratings of sexual stimulation and liking for the slides, for males and females.