John A. Pople: scientist and friend
This paper describes my interactions with Professor John A. Pople.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This paper describes my interactions with Professor John A. Pople.
Abstract Purpose of Review Coccidioidomycosis is an infectious disease that gained clinical significance in the early 20th century. Many of the foundational contributions to coccidioidomycosis research, including the discovery of the fungal disease agent, Coccidioides spp., were made by women. We review recent progress in Coccidioides research and big questions remaining in the field, while highlighting some of the contributions from women. Recent Findings New molecular-based techniques provide a promising method for detecting Coccidioides, which can help determine the dominate reservoir host and ideal environmental conditions for growth. Genetic and genomic analyses have allowed an understanding of population structure, species level diversity, and evolutionary histories. We present a current, comprehensive genome list, where women contributed many of these entries. Several efforts to develop a coccidioidomycosis vaccine are underway. Summary Women continue to pioneer research on Coccidioides, including the relationships between the fungi and the environment, genetics, and clinical observations. Significant questions remain in the field of Coccidioides, including the main host reservoir, the relationships between genotypic and phenotypic variation, and the underlying cause for chronic clinical coccidioidomycosis cases.
Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.
Not Available
Researchers learned machine learning methods during a boot camp, then applied their new knowledge to real-world research problems during a hackathon.
Abstract not provided.
Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.
This special issue celebrates the scientific legacy of Dr. Malcolm J. Andrews, former Editor of the ASME Journal of Fluids Engineering (2010–2018). Malcolm devoted his career to the development and applications of computational, experimental, and analytical tools to investigate and solve diverse, complex fluid dynamics, and heat transfer problems. Malcolm’s most notable research accomplishments include: (i) contributions to innovative experiments, simulations, and theory to understand buoyancydriven turbulent mixing due to Rayleigh–Taylor instability; (ii) development of the multiphase particle-in-cell method for understanding fragmentation in spray jets, coal-water slurry, and other dense particulate flows; (iii) mixing in nano- and biomaterials in applications ranging from protein glues to carbon nanotube composites; (iv) determining dispersion in proteins to improve therapeutic drug delivery via micro-encapsulation; (v) innovative methods for storing information using nanopinned dipole magnetic vortices in superconducting materials; and (vi) modeling and design modifications for shell-and-tube heat exchangers, as well as heat transfer in rotating systems such as turbine blades. The results of his research have been published in a long series of trend-setting journal and conference papers, book chapters, and patents.
An AI-powered system for generating, reviewing, ranking, and evolving research hypotheses. It leverages Large Language Models (LLMs) for various tasks, including hypothesis generation, reflection, and comparison. The system is designed to assist researchers in exploring a research space and identifying promising hypotheses.
Not Available
Abstract not provided.
He was a willing subject in countless scientific experiments, a superstar of health physics, as well as a favorite photo prop -- and not just around Halloween time. He was Plastic Man. Beginning in the mid-1950s, the Lab (then called Los Alamos Scientific Laboratory) often relied on several life-sized synthetic test subjects to avoid experimenting on people. In the early days of the Laboratory, not much was known about how different radioisotopes interacted with the human body and how much it absorbed from different radiation sources. Answering queries like these is where Plastic Man came in. For example, during the 1950s and 1960s, the Lab was tasked with developing nuclear rockets for space exploration under the Rover Program. One of the concerns was how astronauts might be affected when exposed to radiation from these rocket engines. So, the Lab’s health group set up an experiment in which Plastic Man was placed in close proximity to an experimental Rover nuclear rocket engine. Running experiments like this using Plastic Man kept humans safer. How life-like was he? There were actually two variations of Plastic Man. Both had hard plastic exteriors, but one of the models encased a real human skeleton. They also had movable joints and simulated organs, such as a liver, a spleen, kidneys, lungs and a thyroid. Although Plastic Man in its entirety was used in experiments, much of the data collected were from research conducted inside on these replicated organs. In time, technology advanced and Plastic Man was able to retire from the Lab. He found a new home in 1964 as a display at the Laboratory’s science museum, and is sometimes displayed today in the Bradbury Science Museum in downtown Los Alamos.
Abstract not provided.
The article addresses social aspects of living and working at Los Alamos during the Manhattan project. The focus area of this piece talks about food and morale building.
Abstract not provided.
Abstract not provided.
The notes presented in this presentation are an example of taking notes working at the computer while working with data files. The presenter helped collect the data in Antarctica, and they took notes while they collected the data. Later, to use the data once they were back home, the researcher spent many hours looking at the files on the computer to connect two types of data files: GPR and GPS.