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Designer membraneless organelles sequester native factors for control of cell behavior
Subcellular compartmentalization of macromolecules increases flux and prevents inhibitory interactions to control biochemical reactions. Inspired by this functionality, we sought to build designer compartments that function as hubs to regulate the flow of information through cellular control systems. Here we report a synthetic membraneless organelle platform to control endogenous cellular activities through sequestration and insulation of native proteins. We engineer and express a disordered protein scaffold to assemble micron size condensates and recruit endogenous clients via genomic tagging with high-affinity dimerization motifs. By relocalizing up to ninety percent of a targeted enzymes to synthetic condensates, we efficiently control cellular behaviors, including proliferation, division, and cytoskeletal organization. Further, we demonstrate multiple strategies for controlled cargo release from condensates to switch cells between functional states. These synthetic organelles offer a powerful and generalizable approach to modularly control cell decision-making in a variety of model systems with broad applications for cellular engineering.
The von Willebrand factor D;#8242;D3 assembly and structural principles for factor VIII binding and concatemer biogenesis
Abstract not provided
Air Exchange Rate Impact on Actinon, Thoron, and Radon Activity Equilibrium Factor and Inhalation Fractional Equilibrium Factor Determination in Vapor Intrusion Risk and Dose Models
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Human factors and space technology: Notes on space related human factors research and development, history, faculties and future requirements
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Crew factors in flight operations. 8: Factors influencing sleep timing and subjective sleep quality in commercial long-haul flight crews
How flight crews organize their sleep during layovers on long-haul trips is documented. Additionally, environmental and physiological constraints on sleep are examined. In the trips studied, duty periods averaging 10.3 hr alternated with layovers averaging 24.8 hr, which typically included two subject-defined sleep episodes. The circadian system had a greater influence on the timing and duration of first-sleeps than second-sleeps. There was also a preference for sleeping during the local night. The time of falling asleep for second-sleeps was related primarily to the amount of sleep already obtained in the layover, and their duration depended on the amount of time remaining in the layover. For both first- and second-sleeps, sleep durations were longer when subjects fell asleep earlier with respect to the minimum of the circadian temperature cycle. Naps reported during layovers and on the flight deck may be a useful strategy for reducing cumulative sleep loss. The circadian system was not able to synchronize with the rapid series of time-zone shifts. The sleep/wake cycle was forced to adopt a period different from that of the circadian system. Flight and duty time regulations are a means of ensuring that reasonable minimum rest periods are provided. This study clearly documents that there are physiologically and environmentally determined preferred sleep times within a layover. The actual time available for sleep is thus less than the scheduled rest period.
Space Flight Human System Standards (SFHSS): Human Factors, Habitability and Environmental Factors" and Human Integration Design Handbook (HIDH) - Volume 2
This viewgraph presentation reviews the standards for space flight hardware based on human capabilities and limitations. The contents include: 1) Scope; 2) Applicable documents; 3) General; 4) Human Physical Characteristics and Capabilities; 5) Human Performance and Cognition; 6) Natural and Induced Environments; 7) Habitability Functions; 8) Architecture; 9) Hardware and Equipment; 10) Crew Interfaces; 11) Spacesuits; 12) Operatons: Reserved; 13) Ground Maintenance and Assembly: Reserved; 14) Appendix A-Reference Documents; 15) Appendix N-Acronyms and 16) Appendix C-Definition. Volume 2 is supported by the Human Integration Design Handbook (HIDH)s.
Information Presentation: Human Research Program - Space Human Factors and Habitability, Space Human Factors Engineering Project
The goal of the Information Presentation Directed Research Project (DRP) is to address design questions related to the presentation of information to the crew. The major areas of work, or subtasks, within this DRP are: 1) Displays, 2) Controls, 3) Electronic Procedures and Fault Management, and 4) Human Performance Modeling. This DRP is a collaborative effort between researchers atJohnson Space Center and Ames Research Center. T
A Human Factor Analysis to Mitigate Fall Risk Factors in an Aerospace Environment
This slide presentation reviews the study done to quanitfy the risks from falls from three locations (i.e., Shuttle Landing Facility Launch Complex Payloads and Vehicle Assembly Building) at the Kennedy Space Center. The Analytical Hierarchy Process (AHP) is reviewed and the mathematical model developed is detailed.
Using Life-Cycle Human Factors Engineering to Avoid Costs: Lessons Learned from NASA's Human Factors Verification Process for Space Payloads
No abstract available
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior
Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.
Post-Flight Back Pain Following International Space Station Missions: Evaluation of Spaceflight Risk Factors
INTRODUCTION Back pain during spaceflight has often been attributed to the lengthening of the spinal column due to the absence of gravity during both short and long-duration missions. Upon landing and re-adaptation to gravity, the spinal column reverts back to its original length thereby causing some individuals to experience pain and muscular spasms, while others experience no ill effects. With International Space Station (ISS) missions, cases of back pain and injury are more common post-flight, but little is known about the potential risk factors. Thus, the purpose of this project was to perform an initial evaluation of reported post-flight back pain and injury cases to relevant spaceflight risk factors in United States astronauts that have completed an ISS mission. METHODS All US astronauts who completed an ISS mission between Expeditions (EXP) 1 and 41 (2000-2015) were included in this evaluation. Forty-five astronauts (36 males and 9 females) completed 50 ISS missions during the study time period, as 5 astronauts completed 2 ISS missions. Researchers queried medical records of the 45 astronauts for occurrences of back pain and injury. A case was defined as any reported event of back pain or injury to the cervical, thoracic, lumbar, sacral, or coccyx spine regions. Data sources for the cases included the Flight Medicine Clinic's electronic medical record; Astronaut Strength, Conditioning and Rehabilitation electronic documentation; the Private Medical Conference tool; and the Space Medicine Operations Team records. Post-flight cases were classified as an early case if reported within 45 days of landing (R + 45) or a late case if reported from R + 46 to R + 365 days after landing (R + 1y). Risk factors in the astronaut population for back pain include age, sex, prior military service, and prior history of back pain. Additionally, spaceflight specific risk factors such as type of landing vehicle and onboard exercise countermeasures were included to evaluate their contribution to post-flight cases. Prior history of back pain included back pain recorded in the medical record within 3 years prior to launch. Landing vehicle was included in the model to discern if more astronauts experienced back pain or injury following a Shuttle or Soyuz landing. Onboard exercise countermeasures were noted for those astronauts who had a mission following 2009 deployment of the Advanced Resistive Exercise Device (aRED) (EXP 19 to 41). T-test and chi-squared tests were performed to evaluate the association between each individual risk factor and post-flight case. Logistic regression was used to evaluate the combined contribution of all the risk factors on post-flight cases. Separate models were calculated for cases reported by R + 45 and R + 1y. RESULTS During the study time period, there were 13 post-flight cases reported by R + 45 and an additional 5 reported by R + 1y. Most of these cases have been reported since EXP 19 with 10 cases by R + 45 and 4 by R + 1y. Individual risk factors of age, sex, landing vehicle, and prior military service were not significantly associated with post-flight cases identified at R + 45 or R + 1y (p greater than 0.05). Having back pain or injury within 3 years prior to launch significantly increased the likelihood of becoming a case by R + 1y (p = 0.041), but not at R+45 (p=0.204). Additionally, astronauts who experienced onboard exercise countermeasures that included aRED had a significantly increased risk of becoming a case at R + 45 (p = 0.024) and R + 1y (p=0.003). Multiple logistic regression evaluating all the risk factors for cases identified no significant risk factors at either the R + 45 or R + 1y time period (p greater than 0.05). Overall model fit was poor for both the R + 45 (R(exp 2) = 0.132) and R + 1y (R(exp 2) = 0.186) cases showing that there are risk factors not represented in our model. CONCLUSIONS Regardless of cause, post-flight cases are reported more often since aRED was deployed in 2009. This may reflect improved documentation or unidentified risk factors. No spaceflight risk factor explains the data fully. Post-flight cases are probably due to multi-faceted factors that are not easily elucidated in the medical data.
Distributed-memory lattice H-matrix factorization
We parallelize the LU factorization of a hierarchical low-rank matrix (H-matrix) on a distributed-memory computer. This is much more difficult than the H-matrix-vector multiplication due to the dataflow of the factorization, and it is much harder than the parallelization of a dense matrix factorization due to the irregular hierarchical block structure of the matrix. Block low-rank (BLR) format gets rid of the hierarchy and simplifies the parallelization, often increasing concurrency. However, this comes at a price of losing the near-linear complexity of the H-matrix factorization. In this work, we propose to factorize the matrix using a “lattice H-matrix” format that generalizes the BLR format by storing each of the blocks (both diagonals and off-diagonals) in the H-matrix format. These blocks stored in the H-matrix format are referred to as lattices. Thus, this lattice format aims to combine the parallel scalability of BLR factorization with the near-linear complexity of H-matrix factorization. We first compare factorization performances using the H-matrix, BLR, and lattice H-matrix formats under various conditions on a shared-memory computer. Our performance results show that the lattice format has storage and computational complexities similar to those of the H-matrix format, and hence a much lower cost of factorization than BLR. In conclusion, we then compare the BLR and lattice H-matrix factorization on distributed-memory computers. Our performance results demonstrate that compared with BLR, the lattice format with the lower cost of factorization may lead to faster factorization on the distributed-memory computer.
On the perturbation effect and LET dependence of beam quality correction factors in carbon ion beams
Background: In a recent study, we reported beam quality correction factors, f Q , in carbon ion beams using Monte Carlo (MC) methods for a cylindrical and a parallel-plate ionization chamber (IC). A non-negligible perturbation effect was observed; however, the magnitude of the perturbation correction due to the specific IC subcomponents was not included. Furthermore, the stopping power data presented in the International Commission on Radiation Units and Measurements (ICRU) report 73 were used, whereas the latest stopping power data have been reported in the ICRU report 90. Purpose: The aim of this study was to extend our previous work by computing f Q correction factors using the ICRU 90 stopping power data and by reporting IC-specific perturbation correction factors. Possible energy or linear energy transfer (LET) dependence of the f Q correction factor was investigated by simulating both pristine beams and spread-out Bragg peaks (SOBPs). Methods: The TOol for PArticle Simulation (TOPAS)/GEANT4 MC code was used in this study. A 30 × 30 × 50 cm 3 water phantom was simulated with a uniform 10 × 10 cm 2 parallel beam incident on the surface. A Farmer-type cylindrical IC (Exradin A12) and two parallel-plate ICs (Exradin P11 and A11) were simulated in TOPAS using the manufacturer-provided geometrical drawings. The f Q correction factor was calculated in pristine carbon ion beams in the 150–450 MeV/u energy range at 2 cm depth and in the middle of the flat region of four SOBPs. The k Q correction factor was calculated by simulating the f Qo correction factor in a 60 Co beam at 5 cm depth. The perturbation correction factors due to the presence of the individual IC subcomponents, such as the displacement effect in the air cavity, collecting electrode, chamber wall, and chamber stem, were calculated at 2 cm depth for monoenergetic beams only. Additionally, the mean dose-averaged and track-averaged LET was calculated at the depths at which the f Q was calculated. Results: The ICRU 90 f Q correction factors were reported. The p dis correction factor was found to be significant for the cylindrical IC with magnitudes up to 1.70%. The individual perturbation corrections for the parallel-plate ICs were <1.0% except for the A11 p cel correction at the lowest energy. The f Q correction for the P11 IC exhibited an energy dependence of >1.00% and displayed differences up to 0.87% between pristine beams and SOBPs. Conversely, the f Q for A11 and A12 displayed a minimal energy dependence of <0.50%. The energy dependence was found to manifest in the LET dependence for the P11 IC. A statistically significant LET dependence was found only for the P11 IC in pristine beams only with a magnitude of <1.10%. Conclusions: The perturbation and k Q correction factor should be calculated for the specific IC to be used in carbon ion beam reference dosimetry as a function of beam quality.
Nonlinear control of the minimum safety factor in tokamaks by optimal allocation of spatially moving electron cyclotron current drive
The minimum value of the safety factor profile is related to the magnetohydrodynamic (MHD) stability of the plasma confined in a tokamak. Therefore, active control of the minimum safety factor may mitigate MHD instabilities that can degrade or even terminate plasma confinement. Typically, in most tokamak scenarios, the minimum safety factor evolves spatially with time, i.e., the location at which the safety factor achieves the minimum value changes with time. In addition to the inherent nonlinearities in the minimum safety factor evolution, its spatial variation makes the control design challenging. In particular, complexity in control design may arise from the need for time-dependent nonlinear models that account for spatial variation of the minimum safety factor. Furthermore, the minimum safety factor may drift to locations where the actuator authority is low. The problem of minimum safety factor control with target location tracking and moving electron cyclotron current drive (ECCD) is addressed in this work. A nonlinear time-dependent model that incorporates the spatial variation of the minimum safety factor is presented. A nonlinear controller based on optimal feedback linearization is developed to track a target minimum safety factor. The proposed controller treats the ECCD position as a controllable variable. In other words, the controller prescribes the ECCD position (in addition to the non-inductive powers) in real time based on an optimal criterion that is defined a priori. This work also presents the steps necessary to integrate the minimum safety factor controller with a total energy controller to achieve multiple control objectives simultaneously. In conclusion, the proposed integrated control algorithm is tested using nonlinear simulations in the Control Oriented Transport SIMulator (COTSIM) for a DIII-D tokamak scenario.
Update of Emission Factors of Greenhouse Gases and Criteria Air Pollutants, and Generation Efficiencies of the U.S. Electricity Generation Sector
The last decade has seen a steady evolution of the electricity generation sector. Fuels used for electricity generation have shifted from coal to cleaner energy sources such as natural gas and renewables including solar, wind, and other renewable sources. The share of U.S. electricity generated from coal decreased from 45% in 2010 to 24% in 2019, and is expected to decrease further to 13% by 2050. The conversion efficiency of electricity generation has also increased gradually for fuels such as natural gas due as less-efficient old generators are retired and more-efficient generators replace them. These changes in the electricity generation industry are likely to cause changes in the emissions from power generation units. Emission factors of greenhouse gases (GHG) including CO 2 , CH 4 , and N 2 O, and criteria air pollutants (CAPs) including CO, NO x , PM 10 , PM 2.5 , and SO x , from power plants are important parameters for estimating life-cycle emissions associated with vehicle electrification, energy systems, and the production of materials and chemicals. The electricity generation technologies and associated emission factors in the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model need to be updated to reflect recent developments in the electricity generation sector. The most recent update of the electricity generation emission factors in GREET adopted a mixed method. The emission factors of CH 4 , N 2 O, NO x , and SOx were estimated using a “topdown” approach by dividing the total emissions by the total net electricity generation, because emission data of these pollutants are readily available in the Emissions & Generation Resource Integrated Database (eGRID). For other CAPs such as CO, VOC, PM 10 , and PM 2.5 , emission data were not reported in eGRID. A “bottom-up” method was used to estimate the emission factors for these pollutants by considering generic uncontrolled emission factors and the pollutant removal efficiencies of emission control technologies adopted in the electricity generation sector. However, the uncontrolled emission factors and the emission removal efficiencies of various emission control technologies considered in the 2012 study came from the legacy AP-42 emission factors, and may not reflect the actual emission performances of the electricity generation sector of today. To leverage new data that recently became available, especially emission data measured from continuous emission monitoring systems (CEMS), we developed a new “top-down” approach to estimate efficiencies and GHG and CAP emission factors for electricity generation from combustion of individual fuel types by individual combustion technologies on the basis of power-generation data from U.S. Energy Information Administration’s (EIA’s) form EIA-923, and plant emission data from Environmental Protection Agency’s (EPA’s) Clean Air Markets Division (CAMD) dataset and National Emissions Inventory (NEI) dataset. Detailed discussion of the method and data used in this study can be found in Section 2.1. With this topdown approach, we aim to improve the estimates of energy efficiencies and emission factors for power plants using a more consistent methodology, and to update the emission factors, generation efficiencies, and generation technologies mixes in GREET to reflect recent technology advancements in the electricity generation sector.