Semiparametric function-on-function quantile regression model with dynamic single-index interactions.

In this paper we propose a new semiparametric function-on-function quantile regression model with time-dynamic single-index interactions. Our model is very flexible in taking into account of the nonlinear time-dynamic interaction effects of the multivariate longitudinal/functional covariates on the longitudinal response, that most existing quantile regression models for longitudinal data are special cases of our proposed model. We propose to approximate the bivariate nonparametric coefficient functions by tensor product B-splines, and employ a check loss minimization approach to estimate the bivariate coefficient functions and the index parameter vector. Under some mild conditions, we establish the asymptotic normality of the estimated single-index coefficients using projection orthogonalization technique, and obtain the convergence rates of the estimated bivariate coefficient functions. Furthermore, we propose a score test to examine whether there exist interaction effects between the covariates. The finite sample performance of the proposed method is illustrated by Monte Carlo simulations and an empirical data analysis.

ESTIMATION FOR EXTREME CONDITIONAL QUANTILES OF FUNCTIONAL QUANTILE REGRESSION.

Quantile regression as an alternative to modeling the conditional mean function provides a comprehensive picture of the relationship between a response and covariates. It is particularly attractive in applications focused on the upper or lower conditional quantiles of the response. However, conventional quantile regression estimators are often unstable at the extreme tails, owing to data sparsity, especially for heavy-tailed distributions. Assuming that the functional predictor has a linear effect on the upper quantiles of the response, we develop a novel estimator for extreme conditional quantiles using a functional composite quantile regression based on a functional principal component analysis and an extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator under some regularity conditions, and compare it with other estimation methods using Monte Carlo simulations. Finally, we demonstrate the proposed method by empirically analyzing two real data sets.

Extreme quantile estimation for partial functional linear regression models with heavy-tailed distributions.

In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy-tailed distributions. The conventional quantile regression estimators are often unstable at the extreme tails due to data sparsity, especially for heavy-tailed distributions. We first estimate the slope function and the partially linear coefficient using a functional quantile regression based on functional principal component analysis, which is a robust alternative to the ordinary least squares regression. The extreme conditional quantiles are then estimated by using a new extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator and illustrate its finite sample performance by simulation studies and an empirical analysis of diffusion tensor imaging data from a cognitive disorder study.

Dans cet article, un nouvel estimateur de quantiles conditionnels extrêmes est élaboré dans le cadre de modèles de régression linéaire fonctionnelle partielle avec des distributions à queues lourdes. Il est bien connu que la rareté des observations dans les ailes extrêmes de distributions à queues lourdes rend souvent les estimateurs de régression quantile usuels instables. Pour parer à la non robustesse des moindres carrés classiques, les auteurs ont commencé par estimer la fonction de pente et le coefficient partiellement linéaire d'une régression quantile en ayant recours à une approche basée sur l'analyse en composantes principales fonctionnelles. Ensuite, ils ont estimé les quantiles conditionnels extrêmes à l'aide d'une nouvelle technique d'extrapolation issue de la théorie des valeurs extrêmes. En plus d'établir la normalité asymptotique de l'estimateur proposé, les auteurs illustrent ses bonnes performances à distance finie par le biais d'une étude de simulation et une mise en oeuvre pratique sur les données d'imagerie de diffusion par tenseurs provenant d'une étude portant sur des troubles cognitifs.

Production of gas-releasing electrolyte-replenishing Ah-scale zinc metal pouch cells with aqueous gel electrolyte.

Aqueous zinc batteries are ideal candidates for grid-scale energy storage because of their safety and low-cost aspects. However, the production of large-format aqueous Zn batteries is hindered by electrolyte consumption, hydrogen gas evolution and accumulation, and Zn dendrites growth. To circumvent these issues, here we propose an "open" pouch cell design for large-format production of aqueous Zn batteries, which can release hydrogen gas and allow the refilling of the electrolyte components consumed during cell cycling. The cell uses a gel electrolyte containing crosslinked kappa (k)-carrageenan and chitosan. It bonds water molecules and hinders their side reaction with Zn, preventing electrolyte leakage and fast evaporation. As a proof-of-concept, we report the assembly and testing of a Zn | |ZnxV2O5·nH2O multi-layer "open" pouch cell using the carrageenan/chitosan gel electrolyte, which delivers an initial discharge capacity of 0.9 Ah and 84% capacity retention after 200 cycles at 200 mA g‒1, 370 kPa and 25 °C.

Specificity of mRNA Folding and Its Association with Evolutionarily Adaptive mRNA Secondary Structures.

The secondary structure is a fundamental feature of both non-coding RNAs (ncRNAs) and messenger RNAs (mRNAs). However, our understanding of the secondary structures of mRNAs, especially those of the coding regions, remains elusive, likely due to translation and the lack of RNA-binding proteins that sustain the consensus structure like those binding to ncRNAs. Indeed, mRNAs have recently been found to adopt diverse alternative structures, but the overall functional significance remains untested. We hereby approach this problem by estimating the folding specificity, i.e., the probability that a fragment of an mRNA folds back to the same partner once refolded. We show that the folding specificity of mRNAs is lower than that of ncRNAs and exhibits moderate evolutionary conservation. Notably, we find that specific rather than alternative folding is likely evolutionarily adaptive since specific folding is frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the ability to modulate ribosome movement as one potential functional advantage provided by specific folding. Our findings reveal a novel facet of the RNA structurome with important functional and evolutionary implications and indicate a potential method for distinguishing the mRNA secondary structures maintained by natural selection from molecular noise.

Simple and efficient algorithm for the roundness error from polar coordinate measurement data.

Evaluation conditions of the minimum circumscribed circle and maximum inscribed circle in Cartesian coordinates are transformed into those in polar coordinates. According to the radius of the measured points, the candidate points for evaluating the minimum circumscribed circle and maximum inscribed circle are divided into three cases which are solved with the corresponding algorithms. Several examples have been used to validate the validity of the proposed algorithm.

An improved algorithm for evaluation of the minimum circumscribed circle and maximum inscribed circle based on the local minimax radius.

An improved algorithm for evaluation of the minimum circumscribed circle and maximum inscribed circle is proposed in this paper. The candidate points for the minimum circumscribed circle and maximum inscribed circle satisfying the acute triangle are determined based on the local minimax radius in different regions. The more suitable region division method for the maximum inscribed circle is proposed. These simple algorithms are verified to be useful for determining the minimum circumscribed circle and maximum inscribed circle.