Experimental and simulation study on nonlinear pitch control of Seagull underwater glider

1008-1015The Seagull underwater glider, developed by the Shanghai Jiao Tong University, is designed as a test-bed glider for the development and validation of various algorithms to enhance the glider’s long-term autonomy. In this paper, an adaptive backstepping control (ABC) method is proposed for the nonlinear pitch control of the underwater glider gliding in the vertical plane. The linear quadratic regulator (LQR) control and proportional-integral-derivative (PID) control are applied and evaluated with the ABC method to control a glider in saw-tooth motion. Simulation results demonstrate inherent effectiveness and superiority of the LQR or PID based method. According to Lyapunov stability theory, the ABC control scheme is derived to ensure the tracking errors asymptotically converge to zero. The ABC controller has been implemented on Seagull underwater glider, and verified in field experiments in the Qiandao Lake, Zhejiang

Dynamic modeling and optimal control of a positive buoyancy diving autonomous vehicle

The positive buoyancy diving autonomous vehicle combines the features of an Unmanned Surface Vessel (USV) and an Autonomous Underwater Vehicle (AUV) for marine measurement and monitoring. It can also be used to study reasonable and efficient positive buoyancy diving techniques for underwater robots. In order to study the optimization of low power consumption and high efficiency cruise motion of the positive buoyancy diving vehicle, its dynamic modeling has been established. The optimal cruising speed for low energy consumption of the positive buoyancy diving vehicle is determined by numerical simulation. The Linear Quadratic Regulator (LQR) controller is designed to optimize the dynamic error and the actuator energy consumption of the vehicle in order to achieve the optimal fixed depth tracking control of the positive buoyancy diving vehicle. The results demonstrate that the LQR controller has better performance than PID, and the system adjustment time of the LQR controller is reduced by approximately 56% relative to PID. The motion optimization control method proposed can improve the endurance of the positive buoyancy diving vehicle, and has a certain application value

Developing an Active Canopy Sensor-Based Integrated Precision Rice Management System for Improving Grain Yield and Quality, Nitrogen Use Efficiency, and Lodging Resistance

Active crop sensor-based precision nitrogen (N) management can significantly improve N use efficiency but generally does not increase crop yield. The objective of this research was to develop and evaluate an active canopy sensor-based precision rice management system in terms of grain yield and quality, N use efficiency, and lodging resistance as compared with farmer practice, regional optimum rice management system recommended by the extension service, and a chlorophyll meter-based precision rice management system. Two field experiments were conducted from 2011 to 2013 at Jiansanjiang Experiment Station of China Agricultural University in Heilongjiang, China, involving four rice management systems and two varieties (Kongyu 131 and Longjing 21). The results indicated that the canopy sensor-based precision rice management system significantly increased rice grain yield (by 9.4–13.5%) over the farmer practice while improving N use efficiency, grain quality, and lodging resistance. Compared with the already optimized regional optimum rice management system, in the cool weather year of 2011, the developed system decreased the N rate applied in Kongyu 131 by 12% and improved N use efficiency without inducing yield loss. In the warm weather year of 2013, the canopy sensor-based management system recommended an 8% higher N rate to be applied in Longjing 21 than the regional optimum rice management, which improved rice panicle number per unit area and eventually led to increased grain yield by over 10% and improved N use efficiency. More studies are needed to further test the developed active canopy sensor-based precision rice management system under more diverse on-farm conditions and further improve it using unmanned aerial vehicle or satellite remote sensing technologies for large-scale applications.publishedVersio

Gas Sensitivity of In0.3Ga0.7As Surface QDs Coupled to Multilayer Buried QDs

AbstractA detailed analysis of the electrical response of In0.3Ga0.7As surface quantum dots (SQDs) coupled to 5-layer buried quantum dots (BQDs) is carried out as a function of ethanol and acetone concentration while temperature-dependent photoluminescence (PL) spectra are also analyzed. The coupling structure is grown by solid source molecular beam epitaxy. Carrier transport from BQDs to SQDs is confirmed by the temperature-dependent PL spectra. The importance of the surface states for the sensing application is once more highlighted. The results show that not only the exposure to the target gas but also the illumination affect the electrical response of the coupling sample strongly. In the ethanol atmosphere and under the illumination, the sheet resistance of the coupling structure decays by 50% while it remains nearly constant for the reference structure with only the 5-layer BQDs but not the SQDs. The strong dependence of the electrical response on the gas concentration makes SQDs very suitable for the development of integrated micrometer-sized gas sensor devices

Serum CIRP increases the risk of acute kidney injury after cardiac surgery

IntroductionAcute kidney injury (AKI) is a frequent perioperative complication. The underlying mechanisms of cardiac surgery-associated AKI are still not completely elucidated. Cold-induced RNA-binding protein (CIRP) has been subsequently found to be regulated by various stress conditions. During cardiac surgery and cardiopulmonary bypass (CPB), the host is subjected to hypothermia and inadequate organ perfusion, resulting in an upregulation of CIRP secretion. The aim of this study is to evaluate the role of elevated extracellular CIRP level as a contributing factor in the development of AKI.MethodsA total of 292 patients who underwent cardiac surgery were retrospectively enrolled and their serum samples were collected preoperative and postoperative. Demographic data, intraoperative data, in-hospital outcomes, and the occurrence of AKI were also collected for the patients. The correlation between CIRP and intraoperative procedures, as well as its association with postoperative outcomes were analyzed.ResultsIn multivariable analysis, higher ΔCIRP (p = 0.036) and body mass index (p = 0.015) were independent risk factors for postoperative AKI. Meanwhile, patients with postoperative AKI exhibited lower survival rate in 2-year follow-up (p = 0.008). Compared to off-pump coronary artery bypass grafting surgery, patients who underwent on-pump coronary artery bypass grafting, valve surgery, aortic dissection and other surgery showed higher ΔCIRP, measuring 1,093, 666, 914 and 258 pg/mL, respectively (p < 0.001). The levels of ΔCIRP were significantly higher in patients who underwent CPB compared to those who did not (793.0 ± 648.7 vs. 149.5 ± 289.1 pg/mL, p < 0.001). Correlation analysis revealed a positive correlation between ΔCIRP levels and the duration of CPB (r = 0.502, p < 0.001). Patients with higher CIRP levels are at greater risk of postoperative AKI (OR: 1.67, p = 0.032), especially the stage 2–3 AKI (OR: 2.11, p = 0.037).ConclusionCIRP secretion increases with prolonged CPB time after cardiac surgery, and CIRP secretion is positively correlated with the duration of CPB. Cardiac surgeries with CPB exhibited significantly higher levels of CIRP compared to non-CPB surgeries. Elevation of CIRP level is an independent risk factor for the incidence of AKI, especially the severe AKI, and were associated with adverse in-hospital outcomes

Application of different watershed units to debris flow susceptibility mapping: A case study of Northeast China

The main purpose of this study was to compare two types of watershed units divided by the hydrological analysis method (HWUs) and mean curvature method (CWUs) for debris flow susceptibility mapping (DFSM) in Northeast China. Firstly, a debris flow inventory map consisting of 129 debris flows and 129 non-debris flows was randomly divided into a ratio of 70% and 30% for training and testing. Secondly, 13 influencing factors were selected and the correlations between these factors and the debris flows were determined by frequency ration analysis. Then, two types of watershed units (HWUs and CWUs) were divided and logistic regression (LR), multilayer perceptron (MLP), classification and regression tree (CART) and Bayesian network (BN) were selected as the evaluation models. Finally, the predictive capabilities of the models were verified using the predictive accuracy (ACC), the Kappa coefficient and the area under the receiver operating characteristic curve (AUC). The mean AUC, ACC and Kappa of four models (LR, MLP, CART and BN) in the training stage were 0.977, 0.931, and 0.861, respectively, for the HWUs, while 0.961, 0.905, and 0.810, respectively, for the CWUs; in the testing stage, were 0.904, 0.818, and 0.635, respectively, for the HWUs, while 0.883, 0.800, and 0.601, respectively, for the CWUs, which showed that HWU model has a higher debris flow prediction performance compared with the CWU model. The CWU-based model can reflect the spatial distribution probability of debris flows in the study area overall and can be used as an alternative model

QCR7 affects the virulence of Candida albicans and the uptake of multiple carbon sources present in different host niches

BackgroundCandida albicans is a commensal yeast that may cause life-threatening infections. Studies have shown that the cytochrome b-c1 complex subunit 7 gene (QCR7) of C. albicans encodes a protein that forms a component of the mitochondrial electron transport chain complex III, making it an important target for studying the virulence of this yeast. However, to the best of our knowledge, the functions of QCR7 have not yet been characterized.MethodsA QCR7 knockout strain was constructed using SN152, and BALb/c mice were used as model animals to determine the role of QCR7 in the virulence of C. albicans. Subsequently, the effects of QCR7 on mitochondrial functions and use of carbon sources were investigated. Next, its mutant biofilm formation and hyphal growth maintenance were compared with those of the wild type. Furthermore, the transcriptome of the qcr7Δ/Δ mutant was compared with that of the WT strain to explore pathogenic mechanisms.ResultsDefective QCR7 reduced recruitment of inflammatory cells and attenuated the virulence of C. albicans infection in vivo. Furthermore, the mutant influenced the use of multiple alternative carbon sources that exist in several host niches (GlcNAc, lactic acid, and amino acid, etc.). Moreover, it led to mitochondrial dysfunction. Furthermore, the QCR7 knockout strain showed defects in biofilm formation or the maintenance of filamentous growth. The overexpression of cell-surface-associated genes (HWP1, YWP1, XOG1, and SAP6) can restore defective virulence phenotypes and the carbon-source utilization of qcr7Δ/Δ.ConclusionThis study provides new insights into the mitochondria-based metabolism of C. albicans, accounting for its virulence and the use of variable carbon sources that promote C. albicans to colonize host niches

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe