Statistical inference for transfer learning with high-dimensional quantile regression

Transfer learning has become an essential technique to exploit information from the source domain to boost performance of the target task. Despite the prevalence in high-dimensional data, heterogeneity and/or heavy tails are insufficiently accounted for by current transfer learning approaches and thus may undermine the resulting performance. We propose a transfer learning procedure in the framework of high-dimensional quantile regression models to accommodate the heterogeneity and heavy tails in the source and target domains. We establish error bounds of the transfer learning estimator based on delicately selected transferable source domains, showing that lower error bounds can be achieved for critical selection criterion and larger sample size of source tasks. We further propose valid confidence interval and hypothesis test procedures for individual component of high-dimensional quantile regression coefficients by advocating a double transfer learning estimator, which is the one-step debiased estimator for the transfer learning estimator wherein the technique of transfer learning is designed again. Simulation results demonstrate that the proposed method exhibits some favorable performances, further corroborating our theoretical results.Comment: 122 pages, 6 figure

Liquid Transport Rates during Binary Collisions of Unequally-sized Particles

In this paper, we study the liquid transport between particles of different sizes, as well as build a dynamic liquid bridge model to predict liquid transport between these two particles. Specifically, the drainage process of liquid adhering to two unequally-sized, non-porous wet particles is simulated using direct numerical simulations (DNS). Same as in our previous work (Wu et al., AIChE Journal, 2016, 62:1877–1897), we first provide an analytical solution of a proposed dynamic liquid bridge model. We find that such an analytical solution also describes liquid transport during collisions of unequally-sized particles very well. Finally, we show that our proposed model structure is sufficient to collapse all our direct numerical simulation data. Our model is hence able to predict liquid transport rates in size-polydisperse systems for a wide range of parameter

Activation of Interleukin-1β Release by the Classical Swine Fever Virus Is Dependent on the NLRP3 Inflammasome, Which Affects Virus Growth in Monocytes

Classical swine fever virus (CSFV) is a classic Flavivirus that causes the acute, febrile, and highly contagious disease known as classical swine fever (CSF). Inflammasomes are molecular platforms that trigger the maturation of proinflammatory cytokines to engage innate immune defenses that are induced upon cellular infection or stress. However, the relationship between the inflammasome and CSFV infection has not been thoroughly characterized. To understand the function of the inflammasome response to CSFV infection, we infected porcine peripheral blood monocytes (PBMCs) with CSFV. Our results indicated that CSFV infection induced both the generation of pro-interleukin-1β (pro-IL-1β) and its processing in monocytes, leading to the maturation and secretion of IL-1β through the activation of caspase 1. Moreover, CSFV infection in PBMCs induced the production and cleavage of gasdermin D (GSDMD), which is an inducer of pyroptosis. Additional studies showed that CSFV-induced IL-1β secretion was mediated by NLRP3 and that CSFV infection could sufficiently activate the assembly of the NLRP3 inflammasome in monocytes. These results revealed that CSFV infection inhibited the expression of NLRP3, and knockdown of NLRP3 enhanced the replication of CSFV. In conclusion, these findings demonstrate that the NLRP3 inflammasome plays an important role in the innate immune response to CSFV infection

A forcing fictitious domain/immersed boundary method for super-quadric shape of particulate flow simulation of cementitious material

Fictitious domain/immersed boundary method (FD/IBM) has recently been used for particulate flows and complex fluid-solid interaction problems. The advantage of FD/IBM over the body- fitted method is that it substantially simplifies grid generation for immersed geometries, and it is easier to handle moving boundary situations. FD/IBM even allows the use of a stationary and non- deformation background mesh, as well as it reduces the cost of computation by avoiding generation of a body-fitted mesh for each time step. In this work, we develop a new platform to directly simulate super-quadric (SQ) particles in fluid based on a forcing fictitious domain method. Specifically, a super-quadric particle function is used to represent particle with varying shapes and sizes as encountered for concrete and mortar. The immersion of particles in fluid is handled by imposing a rigidity solid body motion in the particle domain, as well as adding a forcing term to the Navier-stokes equation by integral of pressure gradient and particle related velocity over the whole particle domain. Particle shapes are given by changing the super-quadric parameters of SQ equation. Particle motions, which occur during pumping of cementitious material, can be calculated and tracked by solving Newton’s equations of motions using the extended discrete element method (XDEM)[4] while the data of fluid flow properties are obtained by solving the Navier-Stokes equations which govern the fluid phase. Hence, a particle interface resolving solver is developed by coupling XDEM and IBM. We validate our solver by performing flow around particles and free falling of a particle in the channel at different parameters in 2D and 3D. The final objective of this work is to develop a particle-resolved direct numerical simulation platform to predict highly packed fluids with different shapes of particles and over a wide range of particle sizes

Liquid Transport in Bi-disperse Particle Beds

Flow of highly saturated wet granular matter is encountered in wide range of engineering application, particularly in the pharmaceutics, food industry and energy sector , in addition, granular particles beds usually compose of various of particle properties (i.e.,, shape, size, density, etc.) and it well know that particle size polydispersity and shape significantly influence on the transport of mass and liquid in a fluidized bed system

The effect of liquid bridge model details on the dynamics of wet fluidized beds

Wet fluidized beds of particles in small periodic domains are simulated using the CFD-DEM approach. A liquid bridge is formed upon particle-particle collisions, which then ruptures when the particle separation exceeds a critical distance. The simulations take into account both surface tension and viscous forces due to the liquid bridge. We perform a series of simulations based on different liquid bridge formation models: (1) the static bridge model of Shi and McCarthy, (2) a simple static version of the model of Wu et al., as well as (3) the full dynamic bridge model of Wu et al. We systematically compare the differences caused by different liquid bridge formation models, as well as their sensitivity to system parameters. Finally, we provide recommendations for which systems a dynamic liquid bridge model must be used, and for which application this appears to be less importan

Ecologic shift and aridification in the northern Tibetan Plateau revealed by leaf wax n-alkane δ\u3csup\u3e2\u3c/sup\u3eH and δ\u3csup\u3e13\u3c/sup\u3eC records

Two competing factors, the global cooling and the uplift of Tibetan Plateau, have been proposed to drive the central Asian aridification, but their relative role has seldom been discriminated in paleoclimate and paleoenvironment records. Here, we reconstruct a 14-million-year-long record of paleohydrology and paleoecology in the western Qaidam Basin by applying the compound-specific hydrogen (δ H) and carbon (δ C) isotope analyses to terrestrial leaf wax long-chain n-alkanes. The δ H values are low during the interval of 14.6 to 13.0 Ma. Then the δ H increases from 13.0 to 12.2 Ma and maintains high values from 12.2 to 3.2 Ma with a peak high value of −156.1‰ at 8.0 Ma. After 3.2 Ma, the δ H values are low and vary larger than 30‰. The δ C values decrease from 14.6 to 13.0 Ma and are low from 13.0 to 3.2 Ma except a high value at 3.8 Ma. Then they decrease slightly after 3.2 Ma. Low δ H values indicate relatively wet climate between 14.6 and 13.0 Ma. The decreasing δ C values during the same time period support the ecologic shift with the decline of warm component of conifers after the Mid-Miocene Climatic Optimum. High δ H values since 13.0 Ma are synchronous with the uplift of northern Tibetan Plateau, implying tectonics-driven aridity. Large-amplitude variation in δ H values since ca. 3.2 Ma seen in East and West Qaidam and lower δ C values reveal the climatic cyclic responses to the Northern Hemisphere Glaciation. 2 13 2 2 2 13 2 13 2 2 1

The Maize Clade A PP2C Phosphatases Play Critical Roles in Multiple Abiotic Stress Responses

As the core components of abscisic acid (ABA) signal pathway, Clade A PP2C (PP2C-A) phosphatases in ABA-dependent stress responses have been well studied in Arabidopsis. However, the roles and natural variations of maize PP2C-A in stress responses remain largely unknown. In this study, we investigated the expression patterns of ZmPP2C-As treated with multiple stresses and generated transgenic Arabidopsis plants overexpressing most of the ZmPP2C-A genes. The results showed that the expression of most ZmPP2C-As were dramatically induced by multiple stresses (drought, salt, and ABA), indicating that these genes may have important roles in response to these stresses. Compared with wild-type plants, ZmPP2C-A1, ZmPP2C-A2, and ZmPP2C-A6 overexpression plants had higher germination rates after ABA and NaCl treatments. ZmPP2C-A2 and ZmPP2C-A6 negatively regulated drought responses as the plants overexpressing these genes had lower survival rates, higher leaf water loss rates, and lower proline accumulation compared to wild type plants. The natural variations of ZmPP2C-As associated with drought tolerance were also analyzed and favorable alleles were detected. We widely studied the roles of ZmPP2C-A genes in stress responses and the natural variations detected in these genes have the potential to be used as molecular markers in genetic improvement of maize drought tolerance

Comparison of numerical schemes for 3D Lattice Boltzmann simulations of moving rigid particles in thermal fluid flows

The Lattice Boltzmann method is an efficient numerical method for direct numerical simulations of particulate flows. For a variety of applications not only the flow but also the heat transfer between particle and fluid plays an important role. While for non-thermal flows numerous techniques to handle the moving boundaries of particles have been developed, appropriate techniques for the thermal Lattice Boltzmann method are still lacking. The following three issues are of special importance. First, the thermal boundary conditions (Dirichlet or Neumann) have to be fulfilled on the particle surface. Second, reasonable values have to be found for temperature distributions in grid nodes that are uncovered by moving particles. Third, the heat transfer between particulate and fluid phase has to be evaluated in many application, since it is an essential quantity of interest. In this work, we present new numerical schemes for all of these three key aspects. They rely to a great degree on existing schemes for the non-thermal Lattice Botzmann method. In four benchmark cases we assess which of them are the most favourable and we also show to what extend schemes based on the same principles behave similarly or differently in the flow and heat transfer simulation. The results demonstrate that the proposed techniques deliver accurate results and allow us to recommend the most advantageous approach

A Forcing Fictitious Domain Method to Simulate Fluid-particle Interaction of Particles with Super-quadric Shape

In this work, we develop a new framework to directly simulate super-quadric (SQ) particles in fluid flows based on a forcing fictitious domain method. Specifically, a super-quadric particle function is used to represent the particle shape of different types in a flexible manner. The immersion of particles in the fluid is handled by imposing rigid solid body motion in the particle domain, as well as adding a local forcing term to the Navier-Stokes equations by calculating the integral of both the pressure gradient and the particle velocity over the whole particle domain. Particle shapes are varied by changing the five super-quadric parameters of the SQ equation. We validate our approach by performing simulations of flow around a fixed particle and sedimentation of a particle in a channel in 2D and 3D. The validation results indicate that the current simulation results show a good agreement with experimental data. Moreover, our method is used to study the flow around fixed non-spherical particles with different orientations and particle Reynolds numbers. The particle Reynolds numbers vary from 0.1 to 3000. The super-quadric particles exemplarily considered in the current study are an ellipsoidal particle and fibre-like particles. We present the results for drag and lift coefficients at different particle orientations and different particle Reynolds numbers. The obtained results lay the foundation to apply the framework to flown through multi-particle systems in the near future