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Reducing the Risk of Groundwater Contamination by Improving Pesticide Storage and Handling
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Unfolding the Galactic Cosmic Ray Induced Neutron Environment at the Surface of Mars
No full textUnderstanding the long-term radiation environment at the surface of Mars allows us to estimate the exposure for future robotic and crewed missions. Current Martian exploration missions carry instruments sensitive to ionizing and non-ionizing radiation. The Dynamic Albedo Neutron (DAN) instrument onboard Mars Science Laboratory (MSL) can detect thermal and epithermal neutrons backscattered from a pulsed neutron generator or Galactic Cosmic Rays (GCR). In addition to DAN, there are two other radiation-measuring instruments currently operating at Mars: the MSL Radiation Assessment Detector (RAD), designed to characterize the dose exposures due to charged particles, gamma rays, and neutrons on the surface, and the Mars Odyssey High Energy Neutron Detector (HEND) detects a wide energy range of neutron from orbit. This research presents the numerical correlations with Monte Carlo simulations and DAN, RAD, and HEND instruments data fitting to derive the Martian neutron flux at different energies. The resulting measurement-based neutron spectrum covers a wide energy range and is used to estimate dose rates for various environmental conditions on Mars
From Tuberculosis Diagnostics to Therapy: Development of a Tail Fiber Protein-Derived Microfluidic Diagnostic Device and Utilization of Synergistic Properties of Antimycobacterial Drugs
Get PDFTuberculosis, the disease caused by the mycobacterial pathogen Mycobacterium tuberculosis, has been, prior to the COVID-19 pandemic, the world���s deadliest infectious disease. The illness has been afflicting humans for centuries, and despite decades long efforts to eradicate it and the availability of curative treatment options, tuberculosis remains prevalent across most of the globe. According to the WHO Tuberculosis Reports, approximately 1.7 billion people are estimated to be infected by the bacteria and 1.5 million people die from the disease every year. Effective diagnostics and treatment are key to combating any infectious disease pandemic and in this work, we present a novel approach to improving both. We created a magnetophoretic microfluidic device which uses recombinant mycobacteriophage tail fiber proteins bound to magnetic nanoparticles to pull down mycobacterial cells, selectively concentrating the cells before performing a diagnostic microbiological stain protocol. We have shown that we could lower the limit of detection of Mycobacterium tuberculosis from a synthetic sputum sample by 6 to 26-folds per milliliter of sample, without significantly altering the process used at point-of-care clinics. We also investigated the synergistic interactions between drugs, which we believe is a key element to improving efficacy of drug regimen, but also for the creation of new drug combinations, specifically designed to work together. We have shown that using low doses of Bedaquiline causes inhibitors of PEPCK to be synthetically lethal, despite their lack of whole cell activity on their own. This suggests that typical drug discovery campaign may be missing some valuable compounds, that could play an important part of a combination regimen. Furthermore, we have synthesized the necessary substrate required for the development of an enzymatic assay for peptidyl tRNA hydrolase. This assay could then be used to identify inhibitors of PTH, which could restore Mtb sensitivity to macrolides. These drug discovery campaigns seek to make a better use of synergistic drug interaction and use this information as an integral part of drug discovery
Electrochemical Testing of Diglyme-Based Structural Battery Electrolytes Produced by Polymerization-Induced Phase Separation for Low-Temperature Applications
Get PDFStructural batteries have generated significant interest in recent years due to the increasing electrification of the transportation sector. Structural electrolytes are typically composed of a composite material with both efficient ion transport and excellent mechanical strength with light weight. In addition, modern automobiles, aircraft, and spacecraft are required to operate at extremely low temperatures (< -40 ���). These temperatures are lower than the freezing point of most liquid electrolytes. Further, ion diffusion becomes extremely sluggish at lower temperatures. Liquid electrolytes provide high ionic conductivity but negligible mechanical strength, while solid electrolytes are mechanically robust but have slow ion diffusion kinetics. Bi-continuous electrolytes containing both a solid phase and a liquid phase have previously been created using different phase separation techniques. We have designed a diglyme-based liquid electrolyte having a high ionic conductivity of 4.49 x 10^-4 S/cm at a temperature of ��� 40 ��� and a bicontinuous structural electrolyte containing epoxy and liquid electrolyte capable of operating at a temperature of -40 ��� with an ionic conductivity of 7.44 x 10^-6 S/cm. These results have immediate relevance to the electrification of cars, spacecraft, and aircraft
Strategies for Distributed Bayesian Inference with Independent and Spatio-temporally Correlated Data
Get PDFDue to recent advancements in technology, the utilization of massive datasets, whether independent or correlated, has become prevalent across various fields such as forestry, ocean science, neuroimaging, and public health. Traditional Bayesian statistical approaches for analyzing such datasets operate on the assumption that all data from different units are stored and processed centrally. This centralized data processing paradigm necessitates significant computing and storage resources at the central server, while also raising valid privacy concerns for individual units contributing data. To address these challenges, a comprehensive Bayesian analysis framework has been devised, allowing for approximate Bayesian inference in a decentralized manner, with model computation distributed across multiple machines. This article presents a review of pertinent methods in distributed Bayesian inference developed in recent years, catering to both independent and spatio-temporally correlated data