Nuclear War Simulator Beta Download
Wei Spinks
In nuclear medicine therapies, people working with beta radiators such as (90)Y may be exposed to non-negligible partial body doses. For radiation protection, it is important to know the characteristics of the radiation field and possible dose exposures at relevant positions in the working area. Besides extensive measurements, simulations can provide these data. For this purpose, a movable hand phantom for Monte Carlo simulations was developed. Specific beta radiator handling scenarios can be modelled interactively with forward kinematics or automatically with an inverse kinematics procedure. As a first investigation, the dose distribution on a medical doctor's hand injecting a (90)Y solution was measured and simulated with the phantom. Modelling was done with the interactive method based on five consecutive frames from a video recorded during the injection. Owing to the use of only one camera, not each detail of the radiation scenario is visible in the video. In spite of systematic uncertainties, the measured and simulated dose values are in good agreement.
Karyopherin β family proteins mediate the nuclear/cytoplasmic transport of various proteins through the nuclear pore complex (NPC), although they are substantially larger than the size limit of the NPC.To elucidate the molecular mechanism underlying this paradoxical function, we focused on the unique structures called HEAT repeats, which consist of repetitive amphiphilic α helices. An in vitro transport assay and FRAP analyses demonstrated that not only karyopherin β family proteins but also other proteins with HEAT repeats could pass through the NPC by themselves, and serve as transport mediators for their binding partners. Biochemical and spectroscopic analyses and molecular dynamics simulations of purified HEAT-rich proteins revealed that they interact with hydrophobic groups, including phenyl and alkyl groups, and undergo reversible conformational changes in tertiary structures, but not in secondary structures. These results show that conformational changes in the flexible amphiphilic motifs play a critical role in translocation through the NPC.
For the first time, an international team including scientists at Lawrence Livermore National Laboratory (LLNL) has found the answer to a 50-year-old puzzle that explains why beta decays of atomic nuclei are slower than expected.
Using advanced nuclear model simulations, the team, including LLNL nuclear physicists Kyle Wendt (a Lawrence fellow), Sofia Quaglioni and twice-summer intern Peter Gysbers (UBC/TRIUMF), found their results to be consistent with experimental data showing that beta decays of atomic nuclei are slower than what is expected, based on the beta decays of free neutrons.
Historically, calculations of beta decay rates have been much faster than what is seen experimentally. Nuclear physicists have worked around this discrepancy by artificially scaling the interaction of single nucleons with the electroweak force, a process referred to as "quenching." This allowed physicists to describe beta decay rates, but not predict them. While nuclei near each other in mass would have similar quenching factors, the factors could differ dramatically for nuclei well separated in mass.
Predictive calculations of beta decay require not just accurate calculations of the structure of both the mother and daughter nuclei, but also of how nucleons (both individually and as correlated pairs) couple to the electroweak force that drives beta decay. These pairwise interactions of nucleons with the weak force represented an extreme computational hurdle due to the strong nuclear correlations in nuclei.
The team simulated beta decays from light to heavy nuclei, up to tin-100 decaying into indium-100, demonstrating their approach works consistently across the nuclei where ab initio calculations are possible. This sets the path toward accurate predictions of beta decay rates for unstable nuclei in violent astrophysical environments, such as supernova explosions or neutron star mergers that are responsible for producing most elements heavier than iron.
"The methodology in this work also may hold the key to accurate predictions of the elusive neutrinoless double-beta decay, a process that if seen would revolutionize our understanding of particle physics," Quaglioni said.
Nuclear war simulator is a detailed realistic simulation and visualization of large-scale nuclear conflicts with a focus on humanitarian consequences. There are currently over 13000 nuclear weapons on this planet of which over 9000 are in military stockpiles. This software should help you answer the questions: what will happen if Russia and the United States or India and Pakistan use their arsenals? What will happen to the population of a country in a nuclear war? What will happen to me and my family?
You can design warheads, missiles, and carriers, place them on the map and execute attack plans to tell a credible story about how nuclear conflicts play out and what the consequences are. Using a high-resolution population density map and realistic weapons effects like blast, heat, and radiation you can make an estimate of how many people will die in a conflict. Individual humans can be placed on the map, travel, and take shelter to analyze the effects and estimate injuries and survival probability.
You can design realistic large-scale scenarios between major powers with thousands of warheads. Scenarios can be created manually where you can assign each warhead individually or with the assistance of an AI. A database of all known nuclear weapons deployed today and some historical nuclear weapons is available for faster scenario creation. You can download scenarios created by other people and upload your scenarios to the mods.io server.
The simulation includes a high-resolution population density grid. The effects of blast, heat, fires and radiation are calculated and visualized for each population cell to estimate fatalities. The destruction of military targets is simulated using a model considering the CEP of the weapon, target hardness and cratering. The amount of burnt fuel and produced soot are also calculated to estimate the effects of nuclear winter using a simplified model. Integration with the particle transport model HYSPLIT is available for detailed fallout simulation.
You can place yourself, your family, and your friends into the simulation to estimate the expected injuries and survival probability.
Tritium is a radioactive isotope of hydrogen. It has the same number of protons and electrons as hydrogen but has 2 neutrons, whereas regular hydrogen does not have any. This makes tritium unstable and radioactive. Tritium is produced naturally from interactions of cosmic rays with gases in the upper atmosphere, and is also a by-product of nuclear reactors.
We calculate the simulation of T-violating correlations induced by final state electromagnetic interactions in nuclear beta decay. RADIOACTIVITY Nuclear beta decay, calculated final state Coulomb simulation of T violation.
The transport of proteins in and out of the nucleus is a major cellular process (Görlich and Kutay, 1999; Macara, 2001; Weis, 2002). Transport not only localizes proteins destined for the nucleus or cytoplasm, but also functions as a key step in signal transduction pathways and in the regulation of cell cycle progression. The nuclear pore complex is a large multi-protein assembly that penetrates the nuclear envelope and connects the cytoplasm to the nucleus (Fahrenkrog and Aebi, 2003; Suntharalingam and Wente, 2003). Although small proteins
The gradient of RanGTP between the nucleus and cytoplasm provides the motive force to drive transport. This gradient is created by an asymmetric distribution of the nucleotide exchange factor RCC1 (also called RanGEF) and of RanGAP. RCC1 is a resident nuclear protein that promotes the exchange of RanGDP to RanGTP (Bischoff and Ponstingl, 1991a). Excluded from the nucleus, RanGAP acts to maintain Ran in the GDP-bound state in the cytoplasm (Fig. 1). The Ran gradient is highly dynamic, with RanGDP rapidly imported by transport factor NTF2 (Ribbeck et al., 1998; Smith et al., 1998).
To compare simulation results with Ran flux in live cells, a fluorescently tagged Ran (RanFl) was injected into BHK21 cells and imaged using confocal microscopy. Time-lapse images were used to quantify nuclear accumulation and import rate of the Ran. Co-injected NTF2 produced positive changes in the initial rate of import and steady-state N/C ratio of Ran, as predicted by the model. RanGAP produced no changes, which also is consistent with the model. RCC1 depletion was tested using tsBN2 cells. These cells possess a temperature-sensitive RCC1 mutation, so that at 39.5C the mutant RCC1 is rapidly degraded (Uchida et al., 1990). Temperature-shifted tsBN2 cells showed reduced nuclear accumulation of Ran but only small affects on initial rate of Ran import, which is consistent with the model.
In summary, the Smith and Görlich kinetic models show how the RanGTP gradient is established and used to drive a nuclear cargo gradient, and that even a simple system of interacting proteins can generate behavior that would difficult to predict using a static model.
The computer model was first run in the absence of any perturbation for a period of 1,000 s, to bring the system to steady state. A RanGTP gradient becomes established, and the transport factors distribute between the cytoplasmic and nuclear compartments (Table IV).
To simulate the micro-injection of labeled cargo, the cytoplasmic concentration of labeled cargo was stepped up from zero to some chosen initial value, and the simulation was run for an additional 500 s to track the import of this cargo into the nuclear compartment. Initial rates of cargo import were calculated from the rates of nuclear accumulation during the first 60 s after the addition of labeled cargo. To compare the results of the model with import in vivo, we injected GST-GFP-NLS (GGNLS) into the cytoplasm of whole cells and imaged nuclear import by confocal microscopy (Fig. 2 A). Both the initial rate and steady-state concentration of the virtual cargo compare well with the nuclear transport of GGNLS observed in live cells (Fig. 2 B).
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