Verification for Different Contrail Parameterizations Based on Integrated Satellite Observation and ECMWF Reanalysis Data

Aviation induced cloud termed contrail plays a more and more important role in the climate change, which makes a significant contribution to anthropogenic climate forcing through impacting the coverage of cirrus in the intersection of troposphere and stratosphere. In this paper, we propose one novel automatic contrail detecting method based on Himawari-8 stationary satellite imagery and two kinds of potential contrail coverage (PCC1 and PCC2) from contrail parameterization in ECHAM4 and HadGEM2. In addition, we propose one new climatological index called contrail occurrence and persistence (COP). According to the algorithm identification (AI) and artificial visual inspection (AVI), COP measured from Himawari-8 stationary satellite imagery is related to upper tropospheric relative humidity over ice (RHI) computed with the ECMWF reanalysis data by simple linear regression. Similarly, we compared the linear correlation between COP and PCCs fractions and found that PCC1 has better correspondence with COP than PCC2

DEVELOPMENT OF ΒETA-LACTOGLOBULIN BASED PARTICLES AS COLLOIDAL STABILIZERS AND EVALUATION OF THEIR PERFORMANCE ON INTERFACES

Beta-lactoglobulin (Blg) is a major whey protein in bovine milk. The desirable functional properties of Blg make it a versatile material, which has been processed into various types of colloidal systems such as nanoparticles, microgels and emulsions. This dissertation first developed several stable colloidal systems using native Blg molecules or denatured Blg aggregates as stabilizers. The study then elucidated the stabilization mechanism by characterizing Blg microgels adsorption on the interface. Firstly, novel selenium nanoparticles were developed using Blg as a stabilizer. The synthesized Blg-selenium nanoparticles were stable at pH 2.5-3.5 and 6.5-8.5 at 4ºC for 30 days as a result of electrostatic repulsions. Furthermore, the cell toxicity of selenium nanoparticles was significantly lower than that of sodium selenite on both cancerous and non-cancerous cells, implying their potential uses as anti-cancer medicines. The second part of this study was to stabilize a novel water-in-water (W/W) emulsion system using self-assembled Blg microgels. The microstructure and stability of the W/W emulsion were investigated under different environmental conditions. Microgels accumulating at the liquid-liquid interface led to a stable emulsion at pH 3 to 5. When pH was increased above the pI of the microgels, the emulsion was destabilized because the microgels tended to stay in the continuous phase (i.e., dextran) rather than the interface. In addition to electrostatic interactions, interfacial tension and hydrophobic attraction between microgels and two polymer phases were investigated to better understand the driving force for particles’ accumulation at the interface. Lastly, we proposed a new method to study the interfacial properties of Blg microgel. Quartz crystal microbalance with dissipation (QCM-D) was employed to investigate adsorption behavior of Blg microgels on a hydrophobic solid surface, which was hypothesized to mimic the oil-water interface. Coupling with atomic force microscopy (AFM), QCM-D showed the ability to characterize the microgels adsorption efficiency and viscoelasticity of adsorbed layer on the solid surface. The application of QCM-D and AFM enabled us to generate insights into the fundamental behavior of soft particles at a solid-liquid interface

Predictive PDF control in shaping of molecular weight distribution based-on a new modelling Algorithm

The aims of this work are to develop an efficient modeling method for establishing dynamic output probability density function (PDF) models using measurement data and to investigate predictive control strategies for controlling the full shape of output PDF rather than the key moments. Using the rational square-root (RSR) B-spline approximation, a new modeling algorithm is proposed in which the actual weights are used instead of the pseudo weights in the weights dynamic model. This replacement can reduce computational load effectively in data-based modeling of a high-dimensional output PDF model. The use of the actual weights in modeling and control has been verified by stability analysis. A predictive PDF model is then constructed, based on which predictive control algorithms are established with the purpose to drive the output PDF towards the desired target PDF over the control process. An analytical solution is obtained for the non-constrained predictive PDF control. For the constrained predictive control, the optimal solution is achieved via solving a constrained nonlinear optimization problem. The integrated method of data-based modeling and predictive PDF control is applied to closed-loop control of molecular weight distribution (MWD) in an exemplar styrene polymerization process, through which the modeling efficiency and the merits of predictive control over standard PDF control are demonstrated and discussed

Molecular Pathogenesis of Gastric Adenocarcinoma

The incidence and mortality of gastric cancer (GC) rank top five and top three, respectively, among cancers around the world. It is an intricate malignancy caused by the reciprocity of intrinsically genetic, environmental, and host-related elements. The silent property, advanced clinical characterization, and potential heterogeneity have made GC a thorny disease with a high death rate. The increasing knowledge of the abundant genetic abnormalities regarding GC will definitely elongate the patients’ survival. Scientists have been working hard to discover the myths beneath gastric tumorigenesis: novel biomarkers have been established, and cell transduction cascades have been well described. The study grouping GC into four molecular subtypes by The Cancer Genome Atlas (TCGA) broadens our horizon of GC etiologies. Knowledge regarding to the sophisticated networks in tumor microenvironment also bring new insights into the mechanisms assist GC development. In the future, people will strive for translating more research achievements into clinical utility. Successful translational medicine will lead to new methods for early GC diagnosis and precise medical strategies for individuals

IMPLEMENTATION OF MOTION ESTIMATION BASED ON HETEROGENEOUS PARALLEL COMPUTING SYSTEM WITH OPENC

International audienceHeterogeneous computing system increases the performance of parallel computing in many domain of general purpose computing with CPU, GPU and other accelerators. Open Computing Language (OpenCL) is the first open, royaltyfree standard for heterogenous computing on multi hardware platforms. In this paper, we propose a parallel Motion Estimation (ME) algorithm implemented using OpenCL and present several optimization strategies applied in our OpenCL implementation of the motion estimation. In the same time, we implement the proposed algorithm on our heterogeneous computing system which contains one CPU and one GPU, and propose one method to determine the balance to distribute the workload in heterogeneous computing system with OpenCL. According to experiments, our motion estimator with achieves 100 to 150 speed-up compared with its implementation with C code executed by single CPU core and our proposed method obtains obviously enhancement of performance in based on our heterogeneous computing system

An analysis on the sensibility of casing vibration signal and its application to aero-hydraulic pump

Aero-hydraulic pump is a central part of hydraulic system in an aircraft. Acceleration sensors are installed in the axis, tangential and vertical direction for identifying the weak imbalance fault, and meanwhile analysis is made for the sensibility of weak imbalance fault from different direction acceleration signal. The result shows that the signal from vertical acceleration sensor is the most sensitive and the one from axis acceleration sensor is the least sensitive to identify and diagnose weak imbalance fault of aero-hydraulic pump

Implementation of Stereo Matching Using High Level Compiler for Parallel Computing Acceleration

International audienceHeterogeneous computing system increases the performance of parallel computing in many domain of general purpose computing with CPU, GPU and other accelerators. With Hardware developments, the software developments like Compute Unified Device Architecture(CUDA) and Open Computing Language (OpenCL) try to offer a simple and visualized tool for parallel computing. But it turn out to be more difficult than programming on CPU platform for optimization of performance. For one kind of parallel computing application, there are different configuration and parameters for various hardware platforms. In this paper, we apply the Hybrid Multi-cores Parallel Programming(HMPP) to automatic-generates tunable code for GPU platform and show the result of implementation of Stereo Matching with detailed comparison with C code version and manual CUDA version. The experimental results show that the default and optimized HMPP have the approximative 1 compared with CUDA implementation. And the HMPP workbench can greatly reduce the time of application development using parallel computing device

C2G2: Controllable Co-speech Gesture Generation with Latent Diffusion Model

Co-speech gesture generation is crucial for automatic digital avatar animation. However, existing methods suffer from issues such as unstable training and temporal inconsistency, particularly in generating high-fidelity and comprehensive gestures. Additionally, these methods lack effective control over speaker identity and temporal editing of the generated gestures. Focusing on capturing temporal latent information and applying practical controlling, we propose a Controllable Co-speech Gesture Generation framework, named C2G2. Specifically, we propose a two-stage temporal dependency enhancement strategy motivated by latent diffusion models. We further introduce two key features to C2G2, namely a speaker-specific decoder to generate speaker-related real-length skeletons and a repainting strategy for flexible gesture generation/editing. Extensive experiments on benchmark gesture datasets verify the effectiveness of our proposed C2G2 compared with several state-of-the-art baselines. The link of the project demo page can be found at https://c2g2-gesture.github.io/c2_gestureComment: 12 pages, 6 figures, 7 table