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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
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.
TracKlinic: Diagnosis of Challenge Factors in Visual Tracking
Generic visual object tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracker, and when they work together can make things even more complicated. Despite a great amount of efforts devoted to understanding the behavior of trackers, reliable and quantifiable ways for studying the per factor tracking behavior remain barely available. Addressing this issue, in this paper we contribute to the community a tracking diagnosis toolkit, TracKlinic, for diagnosis of challenge factors of tracking algorithms. TracKlinic consists of two novel components focusing on the data and analysis aspects, respectively. For the data component, we carefully prepare a set of 2,390 annotated videos, each involving one and only one major challenge factor. When analyzing an algorithm for a specific challenge factor, such one-factor-per-sequence rule greatly inhibits the disturbance from other factors and consequently leads to more faithful analysis. For the analysis component, given the tracking results on all sequences, it investigates the behavior of the tracker under each individual factor and generates the report automatically. With TracKlinic, a thorough study is conducted on ten state-of-the-art trackers on nine challenge factors (including two compound ones). The results suggest that, heavy shape variation and occlusion are the two most challenging factors faced by most trackers. Besides, out-of-view, though does not happen frequently, is often fatal. By sharing TracKlinic1, we expect to make it much easier for diagnosing tracking algorithms, and to thus facilitate developing better ones.
Estimation of backgrounds from jets misidentified as τ-leptons using the Universal Fake Factor method with the ATLAS detector
Processes with τ$$\tau $$-leptons in the final state are important for Standard Model measurements and searches for physics beyond the Standard Model. The ATLAS experiment at the Large Hadron Collider observes τ$$\tau $$-leptons produced in proton–proton collisions only through their decay products. Data analyses involving hadronically decaying τ$$\tau $$-leptons face challenges due to backgrounds from jets misidentified as τ$$\tau $$-leptons that are not modelled reliably by Monte Carlo simulations. Data-driven methods such as the fake-factor method allow such misidentified backgrounds to be predicted by measuring transfer factors, known as fake factors, in data from dedicated regions. This paper describes a refined technique for determining the fake factors, the Universal Fake Factor method. It evaluates the fake factors for a signal region by using fake factors from samples enriched in different sources of jets misidentified as τ$$\tau $$-leptons (light-quark, gluon, b-quark, and pile-up jets). Each fake factor is calculated as a linear combination of fake factors measured in these different enriched samples. For the full Run 2 data set, the systematic uncertainty of the calculated fake factors, evaluated using W(μν)$$W(\mu u )$$ enriched event sample, ranges from 15 to 35% depending on the τ$$\tau $$-lepton’s transverse momentum and charged-particle decay multiplicity.
Ecological Quality Evolution and Its Driving Factors in Yunnan Karst Rocky Desertification Areas
Rocky desertification is a key element affecting regional ecological quality. Rocky desertification in Southwest China directly affects the ecological security of the Yangtze River and Pearl River basins and also restricts regional economic and social development. In order to clarify the evolution laws and key influencing factors of ecological quality in Yunnan karst rocky desertification areas, a quantitative analysis based on the remote sensing-based ecological index (RSEI) model was conducted to explore the overall evolution characteristics and change laws of ecological quality in Yunnan karst rocky desertification areas in the past 30 years. The correlation between RSEI, rock outcrop rate (Fr), and driving factors was determined by redundancy analysis. The results showed the following: (1) RSEI in Yunnan karst rocky desertification areas generally showed a decreasing trend, with a fluctuation in the mid-term, followed by a tendency to recover. It fell into three stages: decline, trough, and recovery, with fitting coefficients of -0.121, -0.057, and 0.157, respectively. In contrast, Fr showed an opposite tendency, illustrating the inverse relationship between RSEI and Fr, and the rate of sequential succession was much faster than that of the reverse succession under human measures of intervention. (2) The mean value of RSEI of Yunnan karst rocky desertification areas was generally lower than that of the total Yunnan Province land areas and Yunnan non-karst rocky desertification areas, but the mean value of Fr was generally more than that of both the above-mentioned areas. In addition, the RSEI and Fr of Yunnan karst rocky desertification areas both showed lower stability values than those of both the above-mentioned areas. This generally suggested a low ecological quality and a high degree of desertification under a low stability in Yunnan karst rocky desertification areas. (3) The correlation of RSEI and Fr with driving factors followed the order of topographic factors, soil factors > water factors > anthropogenic factors. Anthropogenic factors were the driving force changing the state of rocky desertification, geological factors such as topography and soil to a larger extent determined the original macroscopic ecological relationship of rocky desertification, and water factors lay between the above two. The findings of this research will provide theoretical support and a basis for the improvement of ecological quality and comprehensive control of karst rocky desertification in Yunnan Province.
Nonlinear control of safety factor gradient in tokamaks using spatially variable electron cyclotron current drives
Active control of plasma properties may be necessary to achieve stable operation of next-generation tokamaks over large time scales. Such control algorithms can regulate the plasma properties to avoid the onset of magnetohydrodynamic (MHD) instabilities. For instance, the global and local properties of the safety factor profile are linked to the onset of neoclassical tearing modes (NTMs). This work proposes a model-based control approach for deterring/delaying NTMs through active modulation of one of the safety factor properties - the gradient of the safety factor profile at a particular rational safety factor surface. In particular, a novel control-oriented model for the local safety factor gradient is developed. The nonlinear control model is governed by a nonautonomous ordinary differential equation that accounts for a given rational safety factor surface’s spatial variation over time. Further, to improve the controllability of the spatially evolving parameter, the control model treats ECH&CD positions, along with noninductive powers, as controllable variables. A nonlinear control algorithm based on feedback linearization with optimization is synthesized to achieve the objective of regulating the safety factor gradient around a given target. The proposed algorithm allocates optimal ECH&CD positions, in addition to auxiliary powers, at each time instant as the rational safety factor surface drifts to locations with a low control authority. Stability guarantees of the proposed control law are also discussed in this work. The proposed algorithm is tested for a DIII-D tokamak scenario in nonlinear simulations carried out using the Control Oriented Transport SIMulator (COTSIM). Both fixed and moving ECH&CD cases are studied, and their outcomes are compared. Simulation results demonstrate that enthusiastic regulation of the safety factor gradient can be achieved during the ramp-up and flat-top phases of tokamak operation in both fixed and moving ECH&CD cases. However, real-time updates of ECH&CD positions can prevent the saturation of auxiliary powers.
Revisiting single inclusive jet production: timelike factorization and reciprocity
Factorization theorems for single inclusive jet production play a crucial role in the study of jets and their substructure. In the case of small radius jets, the dynamics of the jet clustering can be factorized from both the hard production dynamics, and the dynamics of the low scale jet substructure measurement, and is described by a matching coefficient that can be computed in perturbative Quantum Chromodynamics (QCD). A proposed factorization formula describing this process has been previously presented in the literature, and is referred to as the semi-inclusive, or fragmenting jets formalism. By performing an explicit two-loop calculation, we show the inconsistency of this factorization formula, in agreement with another recent result in the literature. Building on recent progress in the factorization of single logarithmic observables, and the understanding of reciprocity, we then derive a new all-order factorization theorem for inclusive jet production. The use of a jet algorithm, being only a modification of the infrared structure of the measurement, modifies the structure of convolutions in the factorization theorem, as compared to inclusive fragmentation, but maintains the universality of the inclusive hard function and its associated Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution, which are ultraviolet properties. However, the non-trivial structure of convolutions in the factorization theorem implies that the jet functions exhibit a modified evolution. We perform an explicit two-loop calculation of the jet function in both N = 4 super Yang-Mills (SYM), and for all color channels in QCD, finding exact agreement with the structure derived from our renormalization group equations. In addition, we derive several new results, including an extension of our factorization formula to jet substructure observables, a jet algorithm definition of a generating function for the energy correlators, and new results for exclusive jet functions. Our results are a key ingredient for achieving precision jet substructure at colliders.
Unified model of nucleon elastic form factors and implications for neutrino-oscillation experiments
Precise knowledge of the nucleon’s axial-current form factors is crucial for modeling GeV-scale neutrino-nucleus interactions. Unfortunately, the axial form factor remains insufficiently constrained to meet the precision requirements of upcoming long-baseline neutrino-oscillation experiments. This work studies the nucleon’s axial and vector form factors using the light-front approach to build a quark-diquark model of the nucleon with an explicit pion cloud. The light-front wave functions in both the quark and pion-baryon Fock spaces are first calibrated to existing experimental information on the nucleon’s electromagnetic form factors and then used to predict the axial form factor. The resulting squared charge radius of the axial pseudovector form factor is predicted to be $r$$^{2}_{A}$ = 0.29 ± 0.03 fm 2 , where the small error accounts for the model’s parametric uncertainty. We use our form factor results to explore the (quasi)elastic scattering of neutrinos by (nuclei)nucleons, with the result that the widely implemented dipole ansatz is an inadequate approximation of the full form factor for modeling both processes. Here, the approximation leads to a 5%–10% overestimation of the total cross section, depending on the (anti)neutrino energy. We project overestimations of similar size in the flux-averaged cross sections for the upcoming DUNE long-baseline neutrino-oscillation experiment.
GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs
Decomposing a matrix $\mathbf {A}$ into a lower matrix $\mathbf {L}$ and an upper matrix $\mathbf {U}$, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matrix, LU decomposition often introduces more nonzero entries in the $\mathbf {L}$ and $\mathbf {U}$ factors than in the original matrix. A symbolic factorization step is needed to identify the nonzero structures of $\mathbf {L}$ and $\mathbf {U}$ matrices. Attracted by the enormous potentials of the Graphics Processing Units (GPUs), an array of efforts have surged to deploy various LU factorization steps except for the symbolic factorization, to the best of our knowledge, on GPUs. This article introduces gSoFa, the first GPU-based symbolic factorization design with the following three optimizations to enable scalable LU symbolic factorization for nonsymmetric pattern sparse matrices on GPUs. First, here we introduce a novel fine-grained parallel symbolic factorization algorithm that is well suited for the Single Instruction Multiple Thread (SIMT) architecture of GPUs. Second, we tailor supernode detection into a SIMT friendly process and strive to balance the workload, minimize the communication and saturate the GPU computing resources during supernode detection. Third, we introduce a three-pronged optimization to reduce the excessive space consumption problem faced by multi-source concurrent symbolic factorization. Taken together, gSoFa achieves up to 31× speedup from 1 to 44 Summit nodes (6 to 264 GPUs) and outperforms the state-of-the-art CPU project, on average, by 5×. Notably, gSoFa also achieves up to 47 percent of the peak memory throughput of a V100 GPU in the Summit Supercomputer.
Band gap dependence of exciton Lande factor in lead halide perovskites
The optical properties of lead halide perovskite semiconductors in vicinity of the bandgap are controlled by excitons, so that investigation of their fundamental properties is of critical importance. The exciton Landé or g-factor g X is the key parameter, determining the exciton Zeeman spin splitting in magnetic fields. The exciton, electron, and hole carrier g-factors provide information on the band structure, including its anisotropy, and the parameters contributing to the electron and hole effective masses. Here, g X is measured by reflectivity in magnetic fields up to 60 T for lead halide perovskite crystals. The materials band gap energies at a liquid helium temperature vary widely across the visible spectral range from 1.520 up to 3.213 eV in hybrid organic–inorganic and fully inorganic perovskites with different cations and halogens: FA 0.9 Cs 0.1 PbI 2.8 Br 0.2 , MAPbI 3 , FAPbBr 3 , CsPbBr 3 , and MAPb(Br 0.05 Cl 0.95 ) 3 . The exciton g-factors are found to be nearly constant, ranging from +2.3 to +2.7. Thus, the strong dependences of the electron and hole g-factors on the bandgap roughly compensate each other when combining to the exciton g-factor. The same is true for the anisotropies of the carrier g-factors, resulting in a nearly isotropic exciton g-factor. The experimental data are compared favorably with model calculation results.
Extending the thermodynamic form factor bootstrap program: multiple particle-hole excitations, crossing symmetry, and reparameterization invariance
In this study, we further the thermodynamic bootstrap program which involves a set of recently developed ideas used to determine thermodynamic form factors of local operators in integrable quantum field theories. These form factors are essential building blocks for dynamic correlation functions at finite temperatures or non-equilibrium stationary states. In this work we extend this program in three ways. Firstly, we demonstrate that the conjectured annihilation pole axiom is valid in the low energy particle-hole excitations. Secondly, we introduce a crossing relation, which establishes a connection between form factors with different excitation content. Typically, the crossing relation is a consequence of Lorentz invariance, but due to the finite energy density of the considered states, Lorentz invariance is broken. Nonetheless a crossing relation involving excitations with both particles and holes can established using the finite volume representation of the thermodynamic form factors. Finally, we demonstrate that the thermodynamic form factors satisfy a reparameterization invariance, an invariance which encompasses crossing. Reparameterization invariance exploits the fact that the details of the representation of the thermodynamic state are unimportant. In the course of developing these results, we demonstrate the internal consistency of the thermodynamic form factor bootstrap program in a number of ways. Finally, we provide explicit computations of form factors of conserved charges and densities with crossed excitations and show our results can be used to infer information about thermodynamic form factors in the Lieb-Liniger model.