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Purposes To explore the dynamic performance of circulating fluidized bed(CFB) combustion ash subgrade under the driving load, the dynamic resilient modulus characteristics of GF and DTH combustion ashes under different curing ages, compaction degrees, water contents, and stress levels were investigated on the basis of laboratory dynamic triaxial tests. Methods With the aid of mercury intrusion porosimetry(MIP), the pore distribution characteristics of CFB combustion ash were analyzed. Findings The measured results reveal that within a certain range, the dynamic resilient modulus of CFB combustion ash increases with the increase of f-CaO and SO3 content and curing age, and increases significantly in 0~7 d, and slowly in 7~28 d; the increase of compaction degree, water content, confining pressures, and deviator stress increase the dynamic resilient modulus of CFB combustion ash. With the increase of compaction degree and water content, the improvement of dynamic resilient modulus gradually decreases. Both deviator stress and confining pressure affect the dynamic resilient modulus of CFB combustion ash, and the effect of confining pressure is relatively more significant. The results of MIP show that the total porosity and large pore diameter (>2 000 nm) density of GF combustion ash sample are lower than those of DTH combustion ash sample under the same conditions. With the decrease of water content, the total porosity and the large pore size density become higher, the dynamic resilient modulus becomes lower. Fitting the results of dynamic resilient modulus of two kinds of CFB combustion ash with different water contents and compaction degrees after curing for 28 days shows that the prediction results of the three-parameter theoretical model with bulk stress and octahedral shear stress as variables have a high correlation with the test results (R2>0.96), suggesting that the model can effectively predict the dynamic resilient modulus of CFB combustion ash.

In the context of green and low-carbon materials development, the influence of replacing cement with circulating fluidised bed fly ash (CFBFA) on the expansion properties of paste under different curing conditions was first systematically investigated. Then, self-compacting concretes (SCCs) with recycled aggregate (RA) and CFBFA were prepared for filling steel tubes. The experimental results showed that, because of its unique physicochemical properties, the incorporation of CFBFA significantly increased the water requirement needed to achieve standard consistency of the paste and the pore structure was optimised by a reduction in the number of large pores due to the formation of more expansion components (ettringite, gypsum and portlandite are the main expansive products of CFBFA–cement paste). The influence of factors such as curing condition, age and CFBFA on the expansion effect was notable. With a 40% CFBFA content, the RA SCC in the steel tube showed an expansion of 41 μm/m, while the 28-day compressive strength reached 48.9 MPa. [ABSTRACT FROM AUTHOR]

We propose a robust inference method for high‐dimensional single index models with an unknown link function and elliptically symmetrically distributed covariates, focusing on signal recovery and inference. The proposed method is built on the Huber loss and the estimation of the unknown link function is avoided. The ℓ1$$ {\ell}_1 $$ and ℓ2$$ {\ell}_2 $$ consistency of a Lasso estimator up to a multiplicative scalar is established. When the covariance matrix of the predictors satisfies the irrepresentable condition, our method is shown to recover the signed support of the true parameter under mild conditions. Based on a debiased Lasso estimator, we study component‐wise and group inference for the high‐dimensional index parameter. The finite‐sample performance of our method is evaluated through extensive simulation studies. An application to a riboflavin production dataset is provided to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

To improve the accessibility of polyimide aerogels (PAs) in diverse application scenarios, the major objective is to create PAs in dimension/geometry on demand. However, their ability to deliver excellent performance and expanded applications remains challenging. Herein, the three-dimensional (3D) printing of Pas, which simultaneously addresses the above concerns, is proposed using a combination of a one-step chemical-imidization sol–gel strategy and direct ink writing. The resultant 3D-printed PAs exhibit many desirable properties, such as high specific surface area (561.7 m2 g−1), low density (66.1 ± 1.4 kg m−3), low thermal conductivity (39.89 ± 0.16 mW m−1 K−1), low shrinkage (<7%), exceptional thermal stability (up to 450 °C) and good mechanical properties. They also possess excellent heat/cold preservation, heat/cold/moisture insulation, air/light permeability, and ammonia/moisture adsorption. All of these are highly desirable for addressing severe environmental concerns. Moreover, the application scalability of 3D-printed PAs is confirmed by the successful incorporation of carbon nanotubes, and the subsequent expanded functionality and application potential. The flexibility of inks/materials and the manipulability of the structures and functions, demonstrates great prospect for synergy management of thermal insulation, gas permeability and light absorption, thus expanding the application of PAs. [ABSTRACT FROM AUTHOR]

In this article, we propose a robust signal recovery method for high-dimensional linear log-contrast models, when the error distribution could be heavy-tailed and asymmetric. The proposed method is built on the Huber loss with ℓ 1 penalization. We establish the ℓ 1 and ℓ 2 consistency for the resulting estimator. Under conditions analogous to the irrepresentability condition and the minimum signal strength condition, we prove that the signed support of the slope parameter vector can be recovered with high probability. The finite-sample behavior of the proposed method is evaluated through simulation studies, and applications to a GDP satisfaction dataset an HIV microbiome dataset are provided. [ABSTRACT FROM AUTHOR]

A well‐designed pore structure and optimized interface will improve specific capacitances of carbon‐based supercapacitor electrodes significantly. Herein, a simple strategy is used to prepare the hierarchically porous 3D‐printed carbon aerogel (CA) electrodes via combining direct ink writing, freezing drying, carbonization, and polypyrrole (PPy) posttreatment. The 3D‐printed CA electrodes without PPy present a quasi‐proportional increase in areal capacitance as thickness, achieving an extremely high areal capacitance of 6875 mF cm–2 under a thickness of 2.2 mm. Additionally, PPy posttreated 3D‐printed CA (PPy@CA) electrode has improved wettability and contact conductivity, which shows a further significant increase of areal capacitance to 8126 mF cm–2. After 10 000 continuous cycles, the PPy@CA electrode exhibits an excellent cyclic stability similar to that of 3D‐printed CA electrode by maintaining 91% of its original capacitance. This simple strategy may provide a novel insight to dramatically boost the energy storage properties of supercapacitor electrodes and their functionalization. [ABSTRACT FROM AUTHOR]

The X-linked genetic association is overlooked in most of the genetic studies because of the complexity of X-chromosome inactivation process. In fact, the biological process of the gene at the same locus can vary across different subjects. Besides, the skewness of X-chromosome inactivation is inherently subject-specific (even tissue-specific within subjects) and cannot be accurately represented by a population-level parameter. To tackle this issue, a new model is proposed to incorporate the X-linked genetic association into right-censored survival data. The novel model can present that the X-linked genes on different subjects may go through different biological processes via a mixed distribution. Further, a random effect is employed to describe the uncertainty of the biological process for every subject. The proposed method can derive the probability for the escape of X-chromosome inactivation and derive the unbiased estimates of the model parameters. The Legendre-Gauss Quadrature method is used to approximate the integration over the random effect. Finite sample performance of this method is examined via extensive simulation studies. An application is illustrated with the implementation on a cancer genetic study with right-censored survival data. [ABSTRACT FROM AUTHOR]

Random effects two-part models have been applied to longitudinal studies for zero-inflated (or semi-continuous) data, characterized by a large portion of zero values and continuous non-zero (positive) values. Examples include monthly medical costs, daily alcohol drinks, relative abundance of microbiome, etc. With the advance of information technology for data collection and storage, the number of variables available to researchers can be rather large in such studies. To avoid curse of dimensionality and facilitate decision making, it is critically important to select covariates that are truly related to the outcome. However, owing to its intricate nature, there is not yet a satisfactory variable selection method available for such sophisticated models. In this paper, we seek a feasible way of conducting variable selection for random effects two-part models on the basis of the recently proposed "minimum information criterion" (MIC) method. We demonstrate that the MIC formulation leads to a reasonable formulation of sparse estimation, which can be conveniently solved with SAS Proc NLMIXED. The performance of our approach is evaluated through simulation, and an application to a longitudinal alcohol dependence study is provided. [ABSTRACT FROM AUTHOR]

Multilayer graphene platelet and expanded graphite were deposited on alumina disk surface and their effects on tribological performance of an alumina–alumina contact in different environments were evaluated using a pin-on-disk tribometer. Experimental results indicate that coefficients of friction at the contact are reduced by deposited particles due to their lubricating effect. It is interesting to find that wear of the contact in dry conditions is less than that under liquid lubrication. Tribofilm plays a key role in the wear reduction performance. In liquid media, however, formation of tribofilm is limited due to fluid flow and formed thin tribofilm is not able to protect the contact from wear. Experimental results show that formation of tribofilm is improved by both multilayer graphene platelet and expanded graphite. This is attributed to the higher adhesion force between graphene and alumina than that between alumina and alumina. The findings demonstrate that deposition of graphene-based materials onto alumina surface hold the promise of providing a new pathway to increase the anti-wear performance of alumina and possibly other ceramics. [ABSTRACT FROM AUTHOR]

In this article, we propose a general class of partially linear transformation models for recurrent gap time data, which extends the linear transformation models by incorporating non linear covariate effects and includes the partially linear proportional hazards and the partially linear proportional odds models as special cases. Both global and local estimating equations are developed to estimate the parametric and non parametric covariate effects, and the asymptotic properties of the resulting estimators are established. The finite-sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease is provided. [ABSTRACT FROM PUBLISHER]