Research and Application of 3D Simulation Technology for Water Resources Digital Twin Platform

The physical simulation software and digital twin technology play a very important role in building a digital twin platform for water resources, which provides the necessary support to realize digital mapping and intelligent simulation of water resources production and operation. In order to promote the coordinated and efficient operation of different types of water modeling and the intelligence of watershed and water project governance processes, this project will carry out the research and application of process architecture and core technologies for water 3D simulation. The results of this project will provide the theoretical basis and technical support for the development of digital twin technology in the field of water resources in China and contribute to the development of water resources in China

Parallel Graph Connectivity in Log Diameter Rounds

We study graph connectivity problem in MPC model. On an undirected graph with $n$ nodes and $m$ edges, $O(\log n)$ round connectivity algorithms have been known for over 35 years. However, no algorithms with better complexity bounds were known. In this work, we give fully scalable, faster algorithms for the connectivity problem, by parameterizing the time complexity as a function of the diameter of the graph. Our main result is a $O(\log D \log\log_{m/n} n)$ time connectivity algorithm for diameter-$D$ graphs, using $\Theta(m)$ total memory. If our algorithm can use more memory, it can terminate in fewer rounds, and there is no lower bound on the memory per processor. We extend our results to related graph problems such as spanning forest, finding a DFS sequence, exact/approximate minimum spanning forest, and bottleneck spanning forest. We also show that achieving similar bounds for reachability in directed graphs would imply faster boolean matrix multiplication algorithms. We introduce several new algorithmic ideas. We describe a general technique called double exponential speed problem size reduction which roughly means that if we can use total memory $N$ to reduce a problem from size $n$ to $n/k$, for $k=(N/n)^{\Theta(1)}$ in one phase, then we can solve the problem in $O(\log\log_{N/n} n)$ phases. In order to achieve this fast reduction for graph connectivity, we use a multistep algorithm. One key step is a carefully constructed truncated broadcasting scheme where each node broadcasts neighbor sets to its neighbors in a way that limits the size of the resulting neighbor sets. Another key step is random leader contraction, where we choose a smaller set of leaders than many previous works do

A Joint Statistical and Dynamical Assessment of Atmospheric Response to North Pacific Oceanic Variability in CCSM3

ABSTRACT Atmospheric response to North Pacific oceanic variability is assessed in Community Climate System Model, version 3 (CCSM3) using two statistical methods and one dynamical method. All methods identify an equivalent barotropic low response to a warmer sea surface temperature (SST) anomaly in the Kuroshio Extension region (KOE) during early-midwinter. While all three methods capture the major features of the response, the generalized equilibrium feedback assessment method (GEFA) isolates the impact of KOE SST from a complex context, and thus makes itself an excellent choice for similar practice

Prevention of post-surgical abdominal adhesions by a novel biodegradable thermosensitive PECE hydrogel.

<p>Abstract</p> <p>Background</p> <p>Post-operative peritoneal adhesions are common and serious complications for modern medicine. We aim to prevent post-surgical adhesions using biodegradable and thermosensitive poly(ethylene glycol)-poly(ε-caprolactone)-poly(ethylene glycol) (PEG-PCL-PEG, PECE) hydrogel. In this work, we investigated the effect of PECE hydrogel on preventing post-surgical abdominal adhesions in mouse and rat models.</p> <p>Results</p> <p>The PECE hydrogel in sol state could be transformed into gel in less than 20 s at 37°C. In addition, the PECE hydrogel could be easily adhered to the damaged peritoneal surfaces, and be gradually degraded and absorbed by the body within 14 days along with the healing of peritoneal wounds. A notable efficacy of the PECE hydrogel in preventing peritoneal adhesions was demonstrated in the animal models. In contrast, all untreated animals developed adhesions requiring sharp dissection. Furthermore, no significant histopathological changes were observed in main organs of the hydrogel-treated animals.</p> <p>Conclusion</p> <p>Our results suggested that the thermosensitive PECE hydrogel was an effective, safe, and convenient agent on preventing post-surgical intro-abdominal adhesions.</p

Prevalence of porcine circovirus-like agent P1 in Jiangsu, China

Recently, we identified a novel porcine circovirus type 2-like agent P1 isolate from swine. The present study represents the first survey of P1 prevalence in swine herds from Jiangsu, China, by using PCR targeting the complete genome of P1. Prevalences of 50% and 19% were found among 6 herds and 248 animals, respectively. The results indicate a high prevalence of P1 in China pig populations

Design and Control of an Omnidirectional Mobile Wall-Climbing Robot

Omnidirectional mobile wall-climbing robots have better motion performance than traditional wall-climbing robots. However, there are still challenges in designing and controlling omnidirectional mobile wall-climbing robots, which can attach to non-ferromagnetic surfaces. In this paper, we design a novel wall-climbing robot, establish the robot&rsquo;s dynamics model, and propose a nonlinear model predictive control (NMPC)-based trajectory tracking control algorithm. Compared against state-of-the-art, the contribution is threefold: First, the combination of three-wheeled omnidirectional locomotion and non-contact negative pressure air chamber adhesion achieves omnidirectional locomotion on non-ferromagnetic vertical surfaces. Second, the critical slip state has been employed as an acceleration constraint condition, which could improve the maximum linear acceleration and the angular acceleration by 164.71% and 22.07% on average, respectively. Last, an NMPC-based trajectory tracking control algorithm is proposed. According to the simulation experiment results, the tracking accuracy is higher than the traditional PID controller

Forecast of Ionospheric TEC Maps Using ConvGRU Deep Learning Over China

In this article, we propose a convolutional gated recurrent unit (ConvGRU) deep learning method to forecast ionospheric total electron content (TEC) over China based on the regional ionospheric maps (RIMs) from 2015 to 2018. First, we use Global Navigation Satellite System observations from the Crustal Movement Observation Network of China to generate the RIMs of China (CRIMs). Second, we use the CRIMs of 2015&#x2013;2017 as the training set to predict the ionospheric TEC over China in 2018. Finally, comparative experiments are carried out with ConvLSTM, International Reference Ionosphere (IRI), and Center for Orbit Determination in Europe&#x0027;s (CODE&#x0027;s) 1-day predicted Global Ionospheric Map (C1PG) released by CODE. In addition, we add geomagnetic indices (ap, Kp, and Dst) and solar activity index (F10.7) as the training set to analyze the prediction accuracy of the model (using -A if there are no indices, and -B if there are indices). The results illustrate that the prediction accuracy of ConvLSTM-B and ConvGRU-B models are improved on both geomagnetic storm and quiet days, and the improvement is more obvious on geomagnetic storm days. Furthermore, the root mean square error (RMSE) of the ConvGRU-B model decreases by 28&#x0025;, 22.4&#x0025;, and 5.9&#x0025; compared to that of the ConvGRU-A, IRI-2016, and ConvLSTM-B models during geomagnetic storm days, respectively. For the prediction accuracy of a certain grid point, the RMSE of the ConvGRU-B model decreases by 23&#x0025;, 32.6&#x0025;, and 19.3&#x0025; during geomagnetic quiet days and 24.4&#x0025;, 30.6&#x0025;, and 15.7&#x0025; during geomagnetic storm days compared to that of the ConvGRU-A, IRI-2016, and ConvLSTM-B models, respectively. For the forecast accuracy of TEC in different seasons, the performance of the ConvGRU-B model is also better than that of the ConvLSTM-B model in 2018. These results show that the ConvGRU-B model has competitive performance in RIMs prediction over China during the geomagnetic quiet and storm days

Factors influencing the immunogenicity of influenza vaccines

Annual vaccination is the best prevention of influenza. However, the immunogenicity of influenza vaccines varies among different populations. It is important to fully identify the factors that may affect the immunogenicity of the vaccines to provide best protection for vaccine recipients. This paper reviews the factors that may influence the immunogenicity of influenza vaccines from the aspects of vaccine factors, adjuvants, individual factors, repeated vaccination, and genetic factors. The confirmed or hypothesized molecular mechanisms of these factors have also been briefly summarized