Negative Binomial Models for Longitudinal and Sparse Data

Longitudinal count data such as traffic flows data and email data are sometimes over-dispersed and sparse with an exceeded number of zeros, which are often challenging to be modeled. In this dissertation, I make solid contributions to the statistical modeling of longitudinal and sparse longitudinal responses with applications to traffic flows data and email data

Smoothing regression and impact measures for accidents of traffic flows

Traffic pattern identification and accident evaluation are essential for improving traffic planning, road safety, and traffic management. In this paper, we establish classification and regression models to characterize the relationship between traffic flows and different time points and identify different patterns of traffic flows by a negative binomial model with smoothing splines. It provides mean response curves and Bayesian credible bands for traffic flows, a single index, and the log-likelihood difference, for traffic flow pattern recognition. We further propose an impact measure for evaluating the influence of accidents on traffic flows based on the fitted negative binomial model. The proposed method has been successfully applied to real-world traffic flows, and it can be used for improving traffic management.</p

Trace Pursuit: A General Framework for Model-Free Variable Selection

<p>We propose trace pursuit for model-free variable selection under the sufficient dimension-reduction paradigm. Two distinct algorithms are proposed: stepwise trace pursuit and forward trace pursuit. Stepwise trace pursuit achieves selection consistency with fixed <i>p</i>. Forward trace pursuit can serve as an initial screening step to speed up the computation in the case of ultrahigh dimensionality. The screening consistency property of forward trace pursuit based on sliced inverse regression is established. Finite sample performances of trace pursuit and other model-free variable selection methods are compared through numerical studies. Supplementary materials for this article are available online.</p

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The full text of this article can be freely accessed on the publisher's website

A Trigamma-free Approach for Computing Information Matrices Related to Trigamma Function

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Endoscopy-assisted versus open tissue expander placement in plastic and reconstructive surgery: a meta-analysis

Tissue expansion can be used to overcome challenges due to tissue deficiency in plastic and reconstructive surgery; however, the long expansion process is often accompanied by numerous complications. This meta-analysis aimed to determine whether endoscopy-assisted expander placement could decrease complications and shorten treatment time. This study followed the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and was registered in PROSPERO (CRD42021226116). A literature search was performed in eight databases from their inception dates up to 25 August 2021, to identify clinical studies on endoscopy-assisted and/or open tissue expander placement in plastic and reconstructive surgery. Seven studies met the inclusion criteria. In seven studies, 194 underwent endoscopy-assisted expander placement, and 565 underwent open expander placement. The overall complication rate in the endoscopy-assisted group was significantly lower than that in the open group (risk difference (RD) −0.28, 95% confidence interval (CI), −0.38, −0.18, p p I2 = 0%). The endoscopy-assisted group had shorter surgery time, hospital stay and time to full expansion (weighted mean difference (WMD), −13.97 min, −16.88 h, −27.54 days; 95% CI, −15.85, −12.08 min, −24.36, −9.40 h, −38.85, −16.24 days; both p Abbreviations: CI: confidence interval; CNKI: China National Knowledge Infrastructure Database; CSTJ, China Science and Technology Journal Database; NOS: the Newcastle–Ottawa Scale; PRISMA: preferred reporting items for systematic reviews and meta-analyses; RCT: randomized controlled trial; RoB: the cochrane risk-of-bias; RD: risk difference; WMD: weighted mean difference; SE: standard error; SND: standard normal deviate</p

Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman–Rubin Convergence Diagnostics

The determination of the solvation free energy of ions and molecules holds profound importance across a spectrum of applications spanning chemistry, biology, energy storage, and the environment. Molecular dynamics simulations are powerful tools for computing this critical parameter. Nevertheless, the accurate and efficient calculation of the solvation free energy becomes a formidable endeavor when dealing with complex systems characterized by potent Coulombic interactions and sluggish ion dynamics and, consequently, slow transition across various metastable states. In the present study, we expose limitations stemming from the conventional calculation of the statistical inefficiency g in the thermodynamic integration method, a factor that can hinder the determination of convergence of the solvation free energy and its associated uncertainty. Instead, we propose a robust scheme based on Gelman–Rubin convergence diagnostics. We leverage this improved estimation of uncertainties to introduce an innovative accelerated thermodynamic integration method based on the Gaussian Process regression. This methodology is applied to the calculation of the solvation free energy of trivalent rare-earth elements immersed in ionic liquids, a scenario in which the aforementioned challenges render standard approaches ineffective. The proposed method proves to be effective in computing solvation free energy in situations where traditional thermodynamic integration methods fall short

Molecular Structure and Dynamics of Ionic Liquids in a Rigid-Rod Polyanion-Based Ion Gel

The recent fabrication of liquid crystalline ion gels featuring rigid-rod polyanions aligned within room-temperature ionic liquids (RTILs) opens up exciting new avenues for engineering ion conducting materials. These gels exhibit an unusual combination of properties including high ionic conductivity, distinct transport anisotropy, and widely tunable elastic modulus. Using molecular simulations, we study the structure and dynamics of the ions in an ion gel consisting of rigid-rod polyanions and [C2mim]­[TfO] RTILs. We show that the ion distribution in the interstitial space between polymer rods exhibits the hallmarks of the RTIL structure near charged surfaces; i.e., cations (C2mim+) and anions (TfO–) form alternating layers around the polymer rods and the charge on the rod is overscreened by the ionic layer surrounding it. The distinct ordering of ions suggests the formation of a long-range “electrostatic network” in the ion gel, which may contribute to its mechanical cohesion and high modulus. The dynamics of both C2mim+ and TfO– ions slow down due to the fact that some C2mim+ ions become associated with the sulfonate groups of the polymer rod on nanosecond time scales, which hinders the dynamics of all ions in the gel. C2mim+ and TfO– ion diffusion in the gel are only 2–10 times slower than in bulk RTILs, which is still much faster than, e.g., Li ions in typical ion conducting polymers. This fast ion transport combined with strong mechanical cohesion open up exciting opportunities for application of these gels in electrochemical devices including Li-metal batteries

Pseudogene fms-related tyrosine kinase 1 pseudogene 1 (FLT1P1) cooperates with RNA binding protein dyskeratosis congenita 1 (DKC1) to restrain trophoblast cell proliferation and angiogenesis by targeting fms-related tyrosine kinase 1 (FLT1) in preeclampsia

In preeclampsia (PE), preexistent maternal endothelial dysfunction leads to impaired placentation and vascular maladaptation. Long noncoding RNAs (lncRNAs) have been shown to participate in the placentation process. LncRNA fms-related tyrosine kinase 1 pseudogene 1 (FLT1P1) was previously reported to be upregulated in PE. In this study, we verified the effect of FLT1P1 and its cognate gene FLT1 on trophoblast cell proliferation and angiogenesis by using Cell Counting Kit-8 (CCK-8) assay, tube formation assay, and western blot analysis. Their binding to RNA binding protein dyskeratosis congenita 1 (DKC1) was validated by conducting RNA immunoprecipitation (RIP) and RNA pulldown assays. In this study, knockdown of FLT1P1 or FLT1 was found to promote cell proliferation and angiogenesis in trophoblasts. In addition, FLT1P1 recruited DKC1 to stabilize FLT1. Importantly, silencing FLT1P1 or DKC1 decreased the stability of FLT1. Rescue assays revealed that FLT1 overexpression reversed the effect of silenced FLT1P1. Overall, FLT1P1 cooperates with DKC1 to restrain trophoblast cell proliferation and angiogenesis by targeting FLT1.</p