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This presentation is a part of the DHS LSS spectroscopy training course and presents an overview of the following concepts: identification and measurement of gamma rays; use of gamma counts and energies in research. Understanding the basic physics of how gamma rays interact with matter can clarify how certain features in a spectrum were produced.
We present results from the grant entitled, Continuation of full-scale three-dimensional numerical experiments on high-intensity particle and laser beam-matter interactions. The research significantly advanced the understanding of basic high-energy density science (HEDS) on ultra intense laser and particle beam plasma interactions. This advancement in understanding was then used to to aid in the quest to make 1 GeV to 500 GeV plasma based accelerator stages. The work blended basic research with three-dimensions fully nonlinear and fully kinetic simulations including full-scale modeling of ongoing or planned experiments. The primary tool was three-dimensional particle-in-cell simulations. The simulations provided a test bed for theoretical ideas and models as well as a method to guide experiments. The research also included careful benchmarking of codes against experiment. High-fidelity full-scale modeling provided a means to extrapolate parameters into regimes that were not accessible to current or near term experiments, thereby allowing concepts to be tested with confidence before tens to hundreds of millions of dollars were spent building facilities. The research allowed the development of a hierarchy of PIC codes and diagnostics that is one of the most advanced in the world.
Coarse-grained model of DMA, containing the basic motif of the peptoid backbone, based on short ranged many-body ranged interactions.
University of Dallas (UD) physics majors are offered a variety of undergraduate research opportunities in nuclear physics through an established program at the University of Kentucky Accelerator Laboratory (UKAL). The 7-MV Model CN Van de Graaff accelerator and the neutron production and detection facilities located there are used by UD students to investigate how neutrons scatter from materials that are important in nuclear energy production and for our basic understanding of how neutrons interact with matter. Recent student projects include modeling of the laboratory using the neutron transport code MCNP to investigate the effectiveness of laboratory shielding, testing the long-term gain stability of C 6 D 6 liquid scintillation detectors, and deducing neutron elastic and inelastic scattering cross sections for 12 C. Finally, results of these student projects are presented that indicate the pit below the scattering area reduces background by as much as 30%; the detectors show no significant gain instabilities; and new insights into existing 12 C neutron inelastic scattering cross-section discrepancies near a neutron energy of 6.0 MeV are obtained.
HIV-1 Tat protein down regulates expression of the IL-7 receptor alpha-chain (CD127) from the surface of CD8 T cells resulting in impaired T cell proliferation and cytolytic capacity. We have previously shown that soluble Tat protein is taken up by CD8 T cells and interacts with the cytoplasmic tail of CD127 to induce receptor degradation. The N-terminal domain of Tat interacts with CD127 while the basic domain directs CD127 to the proteasome. We have also shown that upon IL-7 binding to its receptor, CD127 is phosphorylated resulting in CIS-mediated proteasomal degradation. Here, we show that Tat mimics this process by recruiting CIS to CD127 in the absence of IL-7 and receptor phosphorylation, leading to CD127 ubiquitination and degradation. Tat therefore acts as an adapter to induce cellular responses under conditions where they may not otherwise occur. Thusly, Tat reduces IL-7 signaling and impairs CD8 T cell survival and function. -- Highlights: •Soluble HIV-1 Tat decreases CD127 expression on CD8 T cells, causing dysfunction. •Tat induces CD127 ubiquitination without activating IL-7 signaling. •Tat binds CD127 and recruits the E3 ubiquitin ligase CIS via its basic domain. •Tat hijacks a normal cellular mechanism to degrade CD127 without IL-7 signaling.
Electrostatic interactions involving proteins depend on not only the ionic charges involved but also their chemical identities. Here we examine the origins of incompletely understood differences in the strength of association of different pairs of monovalent molecular ions that are relevant to protein–protein and protein–ligand interactions. Cationic analogues of the basic amino acid side chains are simulated, along with oxyanionic analogues of cation-exchange ligands and acidic amino acids. Experimentally observed association trends with respect to the cations, but not anions, are captured by a nonpolarizable model. An effective continuum correction to account for electronic polarizability can capture both trends better but at the expense of fidelity to the underlying free energy landscape for ion-pair association. Finally, a polarizable model proves decisive in capturing experimentally suggested trends with respect to both cations and anions; critically, the free energy landscape for ion-pair association is itself altered, thus altering configurational sampling.
The basic ion data such as interaction potential parameters, elastic and inelastic collision cross sections, transport coefficients (reduced mobility and diffusion coefficients) and reaction coefficients have been analysed and determined for the case of He{sup +}, N{sub 2}{sup +}, and O{sub 2}{sup +} in He-dry air mixtures. The ion transport and reaction coefficients have been determined from an optimized Monte Carlo simulation using calculated elastic and experimentally fitted inelastic collision cross sections. The elastic momentum transfer cross sections have been calculated from a semi-classical JWKB (Jeffreys Wentzel Kramers Brillouin) approximation based on a (6-4) rigid core interaction potential model. The inelastic cross sections have been fitted using the measured reaction coefficients, such as, for instance, the non resonant charge transfer coefficients. The cross section sets involving elastic and inelastic processes were then validated using either the measured reduced mobility whenever available in the literature or the zero-field mobility calculated from Satoh's relation, and potential parameters available in the literature. From the sets of elastic and inelastic collision cross sections thus obtained for the first time for He{sup +}/N{sub 2}, He{sup +}/O{sub 2}, N{sub 2}{sup +}/He, and O{sub 2}{sup +}/He systems, the ion transport and reaction coefficients were calculated in the pure gases over a wide range of the density reduced electric field E/N. Then, from the present cross section and other literature sets, the ion mobility and the longitudinal and transverse diffusion coefficients were calculated for different concentrations of air in He in the case of He{sup +}, N{sub 2}{sup +}, O{sub 2}{sup +}, and also O{sup -} ions.
Precise measurements of atomic transitions affected by electron-nucleus hyperfine interactions offer sensitivity to explore basic properties of the atomic nucleus and study fundamental symmetries, including the search for new physics beyond the standard model of particle physics. Specifically, such measurements, augmented by atomic and nuclear calculations, will enable extraction of the higher-order radial moments of the charge-density distribution in spherical and deformed nuclei. The new data impose higher precision requirements on a theoretical description. The nuclear charge density is composed of the proton point distribution folded with the nucleonic charge distributions. The latter induce subtle relativistic corrections due to the coupling of nucleon magnetic moments with the nuclear spin-orbit density. Additional corrections come from the effect of center-of-mass projection. We assess the precision of nuclear charge density calculations by studying the behavior of relativistic and center-of-mass motion corrections to the second and fourth charge radial moments. Special attention has been paid to the magnetic spin-orbit density associated with the local variations of the spin-orbit current. The calculations for semimagic and open-shell nuclei are performed in the framework of self-consistent mean-field theory using quantified energy density functionals and density-dependent pairing forces. We used the general expression for the spin-orbit form factor that is valid for spherical and deformed nuclei. We studied the impact of various correction terms on the charge radii, fourth radial moments, diffraction radii, and surface thickness of spherical and deformed nuclei. The spin-orbit corrections to charge radial moments and surface thickness show strong shell fluctuations which can make an appreciable effect when aiming at high-precision predictions of isotopic shifts. The inclusion of relativistic and center-of-mass corrections impacts the quality of energy density functionals optimized to charge radii data. To establish reliable constraints on the existence of new forces from isotope shift measurements, precise calculations of nuclear charge densities of deformed nuclei are needed. The proper inclusion of the spin-orbit charge density and other correction terms is essential when aiming at extraction of subtle effects which become particularly visible in isotopic trends. It is also important when developing high-quality nuclear energy density functionals optimized using heterogeneous datasets involving absolute charge radii, differential charge radii, and charge form factor properties deduced from electron-scattering data.
Layered structure and peculiar electronic properties of two-dimensional (2D) materials foster the concept of utilizing them as main components of lithium-ion batteries. Understanding basic physical mechanisms governing the interaction of Li with 2D crystals is of key importance to succeeding in a rational design of cathode and anode materials with superior functionalities. In this study density functional theory was applied to reveal the microscopic picture of Li interaction with 15 2D crystals, including several transition metal oxides and dichalcogenides, carbides of Group XIV elements, functionalized graphene, silicene, and germanene, as well as black phosphorus and Ti2C MXene. We found that the general trend in Li binding can be estimated from positions of conduction band minima of 2D materials, since the energy of the lowest empty electronic states shows a nice correlation with the strength of Li adsorption. At variance to the majority of studied surfaces where the electron transferred from Li is spread across the substrate, in monolayers of carbides of Group XIV elements the interaction with Li and the charge transfer are well localized. This gives rise to their capability to accommodate Li structures with a nearly constant binding energy of alkaline atoms over Li coverages ranging from well-separated adatoms to a full monolayer. © 2018 American Physical Society.
Lectins have been used at length for basic research and clinical applications. New insights into the molecular recognition properties enhance our basic understanding of carbohydrate–protein interactions and aid in the design/development of new lectins. In this study, we used a combination of cell‐based assays, glycan microarrays, and X‐ray crystallography to evaluate the structure and function of the recombinant Bauhinia forficata lectin (BfL). The lectin was shown to be cytostatic for several cancer cell lines included in the NCI ‐60 panel; in particular, it inhibited growth of melanoma cancer cells ( LOX IMVI ) by over 95%. BfL is dimeric in solution and highly specific for binding of oligosaccharides and glycopeptides with terminal N ‐acetylgalactosamine (Gal NA c). BfL was found to have especially strong binding (apparent K d = 0.5–1.0 n m ) to the tumor‐associated Tn antigen. High‐resolution crystal structures were determined for the ligand‐free lectin, as well as for its complexes with three Tn glycopeptides, globotetraose, and the blood group A antigen. Extensive analysis of the eight crystal structures and comparison to structures of related lectins revealed several unique features of Gal NA c recognition. Of special note, the carboxylate group of Glu126, lining the glycan‐binding pocket, forms H‐bonds with both the N ‐acetyl of Gal NA c and the peptide amido group of Tn antigens. Stabilization provided by Glu126 is described here for the first time for any Gal NA c‐specific lectin. Taken together, the results provide new insights into the molecular recognition of carbohydrates and provide a structural understanding that will enable rational engineering of BfL for a variety of applications. Database Structural data are available in the PDB under the accession numbers 5T50 , 5T52 , 5T55 , 5T54 , 5T5L , 5T5J , 5T5P , and 5T5O .
During germination, the emerging seedling relies on a limited supply of energy and nutrients stored within itself and the seed. This often occurs underground in darkness where seedlings undergo skotomorphogenesis, characterized by hypocotyl elongation, reduced root growth, and small closed cotyledons forming an apical hook to protect the shoot apical meristem as the seedling grows though the soil towards sunlight. Such long and pale dark-grown seedlings are commonly referred to as etiolated (from the French étiolier (to make pale)). However, a seedling must eventually find sunlight and make an irreversible shift to photoautotrophic growth (photomorphogenesis or de-etiolation). This leads to a dramatic change in physiology, including reduced hypocotyl elongation, increased root growth, expansion and unfolding of the cotyledons, and the biogenesis of photosynthetic plastids (i.e. chloroplasts). Furthermore, this shift is accompanied by a massive change in gene expression, with about one-third of genes being reprogrammed. A large amount of the transcriptional response is regulated by the plant photoreceptors (phytochromes and cryptochromes) that activate transcriptional networks. Furthermore, this involves the rapid degradation of PHYTOCHROME INTERACTING FACTORS (PIFs), which are basic helix-loop-helix domain-containing transcription factors that repress photomorphogenesis in the dark.
Purpose: The stochastic nature of the subatomic world presents a challenge for physics education. Even experienced physicists can be amazed at the varied behavior of electrons, x-rays, protons, neutrons, ions and the any short-lived particles that make up the overall behavior of our accelerators, brachytherapy sources and medical imaging systems. The all-particle Monte Carlo particle transport tool, TOPAS Tool for Particle Simulation, originally developed for proton therapy research, has been repurposed into a physics teaching tool, TOPAS-edu. Methods: TOPAS-edu students set up simulated particle sources, collimators, scatterers, imagers and scoring setups by writing simple ASCII files (in the TOPAS Parameter Control System format). Students visualize geometry setups and particle trajectories in a variety of modes from OpenGL graphics to VRML 3D viewers to gif and PostScript image files. Results written to simple comma separated values files are imported by the student into their preferred data analysis tool. Students can vary random seeds or adjust parameters of physics processes to better understand the stochastic nature of subatomic physics. Results: TOPAS-edu has been successfully deployed as the centerpiece of a physics course for master’s students at Queen’s University Belfast. Tutorials developed there takes students through a step by step course on the basics of particle transport and interaction, scattering, Bremsstrahlung, etc. At each step in the course, students build simulated experimental setups and then analyze the simulated results. Lessons build one upon another so that a student might end up with a full simulation of a medical accelerator, a water-phantom or an imager. Conclusion: TOPAS-edu was well received by students. A second application of TOPAS-edu is currently in development at Zurich University of Applied Sciences, Switzerland. It is our eventual goal to make TOPAS-edu available free of charge to any non-profit organization, along with associated tutorial materials developed by the TOPAS-edu community. Work supported in part by the U.S. Department of Energy under contract number DE-AC02-76SF00515. B. Villagomez-Bernabe is supported by CONACyT (Mexican Council for Science and Technology) project 231844.
The objectives of this presentation are to introduce the basic physics of neutron production, interactions and detection; identify the processes that generate neutrons; explain the most common neutron mechanism, spontaneous and induced fission and (a,n) reactions; describe the properties of neutron from different sources; recognize advantages of neutron measurements techniques; recognize common neutrons interactions; explain neutron cross section measurements; describe the fundamental of 3 He detector function and designs; and differentiate between passive and active assay techniques.
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The NOvA neutrino experiment is attempting to measure properties of neutrinos in order to figure out information about the universe. To detect the signal neutrino interactions, we must determine methods to identify and isolate background events. Research focused on a specific background interaction called a single prong neutral current $\pi^0$ interaction. To do this, a basic cuts based analysis was performed, followed by feeding data into a multi-variate analysis package using a boosted decision tree (BDT) algorithm. Using the BDT, a a new variable was generated which separates signal and background very efficiently. Further work must still be done in order to continue improving the performance of the BDT. This research is valuable to the field of studying neutrino cross sections as it is a background which will always be present in this type of analysis.
Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.
In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.
Molecular recognition is fundamental in biology, underpinning intricate processes through specific protein–ligand interactions. This understanding is pivotal in drug discovery, yet traditional experimental methods face limitations in exploring the vast chemical space. Computational approaches, notably quantitative structure–activity/property relationship analysis, have gained prominence. Molecular fingerprints encode molecular structures and serve as property profiles, which are essential in drug discovery. While two-dimensional (2D) fingerprints are commonly used, three-dimensional (3D) structural interaction fingerprints offer enhanced structural features specific to target proteins. Machine learning models trained on interaction fingerprints enable precise binding prediction. Recent focus has shifted to structure-based predictive modeling, with machine-learning scoring functions excelling due to feature engineering guided by key interactions. Notably, 3D interaction fingerprints are gaining ground due to their robustness. Various structural interaction fingerprints have been developed and used in drug discovery, each with unique capabilities. This review recapitulates the developed structural interaction fingerprints and provides two case studies to illustrate the power of interaction fingerprint-driven machine learning. The first elucidates structure–activity relationships in β2 adrenoceptor ligands, demonstrating the ability to differentiate agonists and antagonists. The second employs a retrosynthesis-based pre-trained molecular representation to predict protein–ligand dissociation rates, offering insights into binding kinetics. Despite remarkable progress, challenges persist in interpreting complex machine learning models built on 3D fingerprints, emphasizing the need for strategies to make predictions interpretable. Binding site plasticity and induced fit effects pose additional complexities. Interaction fingerprints are promising but require continued research to harness their full potential.