BRAIN MENINGES SURFACE RECONSTRUCTION: APPLICATION TO LONGITUDINAL STUDY OF NORMAL AGING

The cranial meninges are membranes enveloping the brain. The space between two of these membranes contains cerebrospinal fluid. Changes in the meninges have been associated with many neurodegenerative diseases. It is of interest to study how the volumes of this space change with respect to normal aging. In this work, we propose to combine convolutional neural networks (CNNs) with nested topology-preserving geometric deformable models (NTGDMs) to reconstruct meningeal surfaces from magnetic resonance (MR) images. We first use CNNs to predict implicit representations of these surfaces then refine them with NTGDMs to achieve sub-voxel accuracy while maintaining spherical topology and the correct anatomical ordering. MR contrast harmonization is used to match the contrasts between training and testing images. We applied our algorithm to a subset of healthy subjects from the Baltimore Longitudinal Study of Aging for demonstration purposes and conducted longitudinal statistical analysis of the intracranial volume (ICV) and subarachnoid space (SAS) volume. We found a statistically significant decrease in the ICV and an increase in the SAS volume with respect to normal aging. Additionally, we conducted a preliminary study on 5 subjects, in which we assigned region labels to the meninges—using a fast marching algorithm from cortical labels—and calculated the thickness of the meningeal layers. In the future, we hope to apply the algorithms to larger datasets to further study the regional thickness changes in the meninges

Efficient robust control of mixed platoon for improving fuel economy and ride comfort

The emergence of connected and automated vehicle technology has improved the operational efficiency of mixed traffic systems. This paper studies a two-tier trajectory optimization problem for mixed platooning to improve fuel efficiency, ride comfort, and operational safety during vehicle operations. The proposed model follows a two-tier control logic to plan the trajectory of platooning vehicles with three objectives, including minimizing fuel consumption, maximizing ride comfort, and enhancing the anti-disturbance performance of the platoon. The first is the planning tier, which aims to design the optimal trajectory for Connected and Automated Vehicles (CAVs) based on the optimal fuel consumption and comfort and obtain the expected acceleration curve of CAV. The second is the control tier, which aims to ensure the safe operation of platooning vehicles in the presence of uncertain disturbances in real time. Specifically, we propose a robust tube MPC control method, which dynamically adjusts the CAV acceleration according to the reference trajectory obtained by the planning tier to resist the effects of uncertain disturbances, and the tracking behaviour of Human-Driven Vehicles (HDVs) is offline solved by the robust optimal velocity model. Finally, we design simulation experiments to verify the effectiveness of the proposed two-tier optimization framework. The experimental results show the effectiveness and advantages of the two-tier framework in terms of fuel economy, ride comfort, and robustness against different noise disturbances

Joint optimization of platoon control and resource scheduling in cooperative vehicle-infrastructure system

Vehicle platooning technology is essential in achieving group consensus, on-road safety, and fuel-saving. Meanwhile, Vehicle-to-Infrastructure (V2I) communication significantly facilitates the development of connected vehicles. However, the coupled effects of the longitudinal vehicle’s mobility, platoon control and V2I communication may result in a low reliable communication network between the platoon vehicle and the roadside unit, there is a tradeoff between the platoon control and communication reliability. In this paper, we investigate a biobjective joint optimization problem where the first objective is to maximize the success probability of data transmission (communication reliability) and the second objective function is to minimize the traffic oscillation flow. The vehicle’s mobility state of the platoon vehicle affects the channel capacity and transmission performance. In this context, we deeply explore the relationship between control signals and resource scheduling and theoretically deduce a closed-form expression of the optimal communication reliability objective. Through this closed expression, we transform the bi-objective model into a single objective MPC model by using ϵ-constraint method. We design an efficient algorithm for solving the joint optimization model and prove the convergence. To verify the effectiveness of the proposed method, we finally evaluate the spacing error, speed error, and resource scheduling of platooning vehicles through simulation experiments in two experimental scenarios. The results show that the proposed control-communication co-design can improve the platoon control performance while satisfying the high reliability of V2I communications

Rapid Brain Meninges Surface Reconstruction with Layer Topology Guarantee

The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying volume differences between patients with neurodegenerative diseases and normal aging subjects. In this work, we use convolutional neural networks (CNNs) to reconstruct surfaces representing meningeal layer boundaries from magnetic resonance (MR) images. We first use the CNNs to predict the signed distance functions (SDFs) representing these surfaces while preserving their anatomical ordering. The marching cubes algorithm is then used to generate continuous surface representations; both the subarachnoid space (SAS) and the intracranial volume (ICV) are computed from these surfaces. The proposed method is compared to a state-of-the-art deformable model-based reconstruction method, and we show that our method can reconstruct smoother and more accurate surfaces using less computation time. Finally, we conduct experiments with volumetric analysis on both subjects with multiple sclerosis and healthy controls. For healthy and MS subjects, ICVs and SAS volumes are found to be significantly correlated to sex (p<0.01) and age (p<0.03) changes, respectively.Comment: ISBI 2023 Ora

Structure and Luminescence Properties of Eu3+-Doped Cubic Mesoporous Silica Thin Films

Eu3+ ions-doped cubic mesoporous silica thin films with a thickness of about 205 nm were prepared on silicon and glass substrates using triblock copolymer as a structure-directing agent using sol–gel spin-coating and calcination processes. X-ray diffraction and transmission electron microscopy analysis show that the mesoporous silica thin films have a highly ordered body-centered cubic mesoporous structure. High Eu3+ ion loading and high temperature calcination do not destroy the ordered cubic mesoporous structure of the mesoporous silica thin films. Photoluminescence spectra show two characteristic emission peaks corresponding to the transitions of5D0-7F1 and 5D0-7F2 of Eu3+ ions located in low symmetry sites in mesoporous silica thin films. With the Eu/Si molar ratio increasing to 3.41%, the luminescence intensity of the Eu3+ ions-doped mesoporous silica thin films increases linearly with increasing Eu3+ concentration

BRAIN MENINGES SURFACE RECONSTRUCTION: APPLICATION TO LONGITUDINAL STUDY OF NORMAL AGING

The cranial meninges are membranes enveloping the brain. The space between two of these membranes contains cerebrospinal fluid. Changes in the meninges have been associated with many neurodegenerative diseases. It is of interest to study how the volumes of this space change with respect to normal aging. In this work, we propose to combine convolutional neural networks (CNNs) with nested topology-preserving geometric deformable models (NTGDMs) to reconstruct meningeal surfaces from magnetic resonance (MR) images. We first use CNNs to predict implicit representations of these surfaces then refine them with NTGDMs to achieve sub-voxel accuracy while maintaining spherical topology and the correct anatomical ordering. MR contrast harmonization is used to match the contrasts between training and testing images. We applied our algorithm to a subset of healthy subjects from the Baltimore Longitudinal Study of Aging for demonstration purposes and conducted longitudinal statistical analysis of the intracranial volume (ICV) and subarachnoid space (SAS) volume. We found a statistically significant decrease in the ICV and an increase in the SAS volume with respect to normal aging. Additionally, we conducted a preliminary study on 5 subjects, in which we assigned region labels to the meninges—using a fast marching algorithm from cortical labels—and calculated the thickness of the meningeal layers. In the future, we hope to apply the algorithms to larger datasets to further study the regional thickness changes in the meninges

Isotopic effect on the dynamics of the H/D plus LiH/LiD reactions Isotopic effect in the H plus LiH system

The H/D + LiH/LiD (v= 0, j = 0) -> H-2/HD/D-2 + Li reactions are studied using the time-dependent wave packet (TDWP) and quasi-classical trajectory (QCT) methods on a ground state potential energy surface (PES). Integral cross sections and rate constants are calculated. The present quantum and classical integral cross sections are in good agreement with each other. The total integral cross sections and rate constants are found to be in reasonable agreement with the available literature results. We compare the dynamics among different isotopic variants of the reactions: the integral cross section of the D+LiH reaction is largest among the four reactions, and the rate constant of the H + LiH reaction is the largest one. We also analyze the state-to-state rate constants in detail, and find that not only the products are preferentially formed in their excited rovibrational states, but also the favored final state varies with temperature. Besides, the favored final states of the title reactions are different with each other because of the isotopic effect. (c) 2016 Elsevier B.V. All rights reserved

Preparation and characterization of floating porous graphite carbon monoliths produced from biomass and its application

Herein, a new floating porous graphite carbon monolith (FCM) was prepared using the graphite powder and peanut shells as the carbon skeleton and using FAC and sepiolite as the swelling agent. The multi-hierarchical porous FCMs were obtained by two-step acid activation method. The effects of the addition of biomass and phosphoric acid on the physical properties and pore structure of the prepared material were investigated. The FCM was combined with codoped titania to develop a new floating photocatalysts. The results showed an increase in the amount of biomass materials during FCM preparation increased the ratio of mesoporous structure in the products. In addition, a high micropore volume ratio and the strongest adsorption effect were achieved by optimizing the phosphoric acid impregnation ratio. After process optimization, the densities of the prepared FCMs ranged between 0.75 and 0.89 g/cm3, and the specific surface area and diameter range of the large pores of the material were 104.5 m2/g and 3-50 μm, respectively. Moreover, the new floating catalysts displayed the excellent photocatalytic properties and recyclability performance

Essential Role of Non-Coding RNAs in Enterovirus Infection: From Basic Mechanisms to Clinical Prospects

Enteroviruses (EVs) are common RNA viruses that can cause various types of human diseases and conditions such as hand, foot, and mouth disease (HFMD), myocarditis, meningitis, sepsis, and respiratory disorders. Although EV infections in most patients are generally mild and self-limiting, a small number of young children can develop serious complications such as encephalitis, acute flaccid paralysis, myocarditis, and cardiorespiratory failure, resulting in fatalities. Established evidence has suggested that certain non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs) are involved in the occurrence and progression of many human diseases. Recently, the involvement of ncRNAs in the course of EV infection has been reported. Herein, the authors focus on recent advances in the understanding of ncRNAs in EV infection from basic viral pathogenesis to clinical prospects, providing a reference basis and new ideas for disease prevention and research directions

Downregulation of lncRNA-HOXA11-AS modulates proliferation and stemness in Glioma cells

Abstract Background Glioma stem cells (GSCs) represent a subpopulation of cells within glioma that are characterized by chemotherapy resistance and tumor recurrence. GSCs are therefore important therapeutic target for glioma therapy. Long non-coding RNAs (lncRNAs) have been shown to regulate important functions in cancer. HOXA11-AS is one such lncRNA and has been shown to regulate cell proliferation via promotion of cell cycle progression in glioblastoma (GBM) cells. However, the specific roles of HOXA11-AS in GSCs remain unclear. Methods Here we investigated the role of HOXA11-AS in driving GSC stemness properties via sphere-forming and protein chip assays. Results Gain-of-function as well as loss-of-function results showed that the HOXA11-AS maybe a critical modulator in GBM recurrence as demonstrated by cell sphere-forming ability. Furthermore, we showed that induced expression of HOXA11-AS does increase the levels of stemness-related transcription factors (Oct4/Sox17/Sox2) in U87MG cells. In vivo xenograft experiments using the HOXA11-AS knockdown U87MG cells revealed that downregulation of HOXA11-AS could strongly inhibit tumor growth. Furthermore, we found that HOXA11-AS knockdown decreased the expression of cancer stemness markers in vivo. Conclusions Collectively, these data suggests that HOXA11-AS is involved in GSC stemness and supports its clinical significance as a important therapeutic target in glioma