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For the autonomous surface vehicle (ASV) planning problem, an enhanced A* method incorporating encrypted memory database for ASV efficient local path planning is proposed. Considering the current various path planning problems mostly use methods with high time complexity, such as neural networks, we select the A* algorithm with low time complexity as the basis. To speed up the path planning rate and further improve the real-time and realistic algorithm, this paper modifies the heuristic function of the A* algorithm by combining the motion mode of ASV. In response to the problem that the target point is far from the detection, we improve the target point design mechanism and create a new temporary target point within the detection range. In addition, the algorithm incorporates a memory database, which can record commonly used waters or retain the environmental path of navigated waters as a priori information. When the same waters are reencountered, the memory database information can be read directly to complete the navigation. Moreover, the memory database is encrypted to prevent information leakage. Finally, a simulation environment is built to verify the effectiveness of the proposed algorithm by comparison with some existing algorithms.

Seed production is critical for watermelon production, which mostly involves first-generation hybrid varieties. However, watermelon hybrid seed production currently requires complex procedures, including artificial isolation and pollination. Therefore, the development and use of a male-sterile system to generate watermelon hybrids can simplify the process. The scarcity of male-sterile watermelon germplasm resources necessitates the use of molecular breeding methods. Unfortunately, the genes responsible for male sterility in watermelon have not been cloned. Thus, the genetic basis of the male sterility remains unknown. In this study, two DNA pools derived from male-sterile and normal plants in the F2 population were used for whole-genome resequencing. The Illumina high-throughput sequencing resulted in 62.99 Gbp clean reads, with a Q30 of 80% after filtering. On the basis of the SNP index association algorithm, eight candidate regions (0.32 Mb) related to specific traits were detected on chromosome 6. Expression pattern analyses and watermelon transformation studies generated preliminary evidence that Cla006625 encodes a pollen-specific leucine-rich repeat protein (ClaPEX1) influencing the male sterility of watermelon. The identification and use of genic male sterility genes will promote watermelon male sterility research and lay the foundation for the efficient application of seed production technology.

Fractured horizontal wells have been widely used to develop unconventional oil and gas reservoirs. In previous studies, most studies on the transient pressure behavior of multistage horizontal wells were based on the assumption of single porosity medium, in which the coupling relationship of natural fractures and artificial fractures was not taken into account or artificial fractures were assumed to be infinitely conductive. In this paper, the fracture is finite conductive, which means that there is flow resistance in the fracture. Based on point-source method and superposition principle, a transient model for multistage fractured horizontal wells, which considers the couple of fracture flow and reservoir seepage, is built and solved with the Laplace transformation. The transient pressure behavior in multistage fractured horizontal wells is discussed, and effects of influence factors are analyzed. The result of this article can be used to identify the response characteristic of fracture conductivity to pressure and pressure differential and provide theoretical basis for effective development of tight oil reservoirs. The findings of this study can help for better understanding of transient pressure behavior of multistage fractured horizontal wells with finite conductivity in tight oil reservoirs.

This paper proposes a new trajectory tracking scheme for the constrained nonlinear underwater vehicle-manipulator system (UVMS). For overcoming the unmodeled uncertainties, external disturbances, and constraints of control inputs in the operation of UVMS, a modified constrained H∞ controller with a basic computed-torque controller (CTC) and a new designed nonlinear disturbance observer (NDO) are proposed. The CTC gives the nominal model-based control. The NDO is designed based on the system dynamics and used to online provide the estimation of the lumped disturbances. However, the designed NDO is an observer of biased estimation, i.e., it has a blind domain of disturbance estimation which cannot be rejected. In order to reject the biased estimation, the modified constrained H∞ controller is designed but with new features. To the best of our knowledge, the conventional H∞ robust controller is generally designed by calculating the Riccati equation offline and ignoring the constraints of control inputs made by the physical actuators, which are poor in handling the time-varying environment. In order to solve these issues, the modified constrained H∞ robust controller online optimized by grey wolf optimizer (GWO) is designed to ensure the control system has a compensation of the biased estimation, a satisfied constrained control input, and a fast calculation. In this paper, we modify the prior method of offline calculating the Riccati equation of the conventional H∞ robust controller to be an online optimization scheme and proposed a new constrained evaluation function. The new constrained evaluation function is online optimized by the GWO, which can both find out the constrained suboptimal control actions and compensate the biased estimation of the NDO for the UVMS. The whole system stability is proved. The effectiveness of the fast online calculation, tracking accuracy, and lumped disturbances rejection is shown by a series of UVMS simulations.

Abstract Background/aims ErbB3 is an oncogene which has proliferation and metastasis promotion effects by several signaling pathways. However, the individual expression difference regulated by miRNA was almost still unknown. We focused on the miRNAs associated SNPs in the 3′-UTR of ErbB3 to investigate the further relationship of the SNPs with miRNAs among Chinese gastric cancer (GC) patients. Methods We performed case–control study including 851 GC patients and 799 cancer-free controls. Genotyping, real-time PCR assay, cell transfection, the dual luciferase reporter assay, western-blot, cell proliferation and trans-well based cell invasion assay were used to investigate the effects of the SNP on ErbB3 expression. Moreover, a 5-years-overall survival and relapse free survival were investigated between different genotypes. Results We found that patients suffering from Helicobacter pylori (Hp.) infection indicated to be the susceptible population by comparing with controls. Besides, SNP rs3202538 (G/T) in ErbB3 3′-UTR was involved in the occurrence of GC by acting as tumor risk factors. SNP rs3202538 (G/T) could be regulated by both miR-204 and miR-211 which caused an upregulation of ErbB3 in patients. Furthermore, the carriers of T genotype was related to the significantly high expression of ErbB3, and to big tumor size, poor differentiation as well as the high probability of metastasis. Both miR-211 and miR-204 can significantly decrease cell proliferation, metastasis as well as downstream AKT activation through G but not T allele of ErbB3 3′UTR. Moreover, the SNP of G/T was associated with shorter survival of post-surgery GC patients with 5 years of follow up study. Conclusion In conclusion, our findings have shown that the SNP rs3202538 (G/T) in ErbB3 3′-UTR acted as promotion factors in the GC development through disrupting the regulatory role of miR-204 and miR-211 in ErbB3 expression.

It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorithms for USV path planning, the rapidly-exploring random tree (RRT) is popular due to its simple structure, high speed and ease of modification. However, it also has some obvious drawbacks and problems. Designed to perfect defects of the basic RRT and improve the performance of USVs, an enhanced algorithm of path planning is proposed in this study, called the adaptive hybrid dynamic stepsize and target attractive force-RRT(AHDSTAF-RRT). The ability to pass through a narrow area and the forward speed in open areas of USVs are improved by adopting the AHDSTAF-RRT in comparison to the basic RRT algorithm. The improved algorithm is also applied to an actual gulf map for simulation experiments, and the experimental data is collected and organized. Simulation experiments show that the proposed AHDSTAF-RRT in this paper outperforms several existing RRT algorithms, both in terms of path length and calculating speed.

Autophagy has been shown to be protective against drug and alcohol-induced liver injury. CYP2E1 plays a role in the toxicity of ethanol, carcinogens and certain drugs. Inhibition of autophagy increased ethanol-toxicity and accumulation of fat in wild type and CYP2E1 knockin mice but not in CYP2E1 knockout mice as well as in HepG2 cells expressing CYP2E1 (E47 cells) but not HepG2 cells lacking CYP2E1 (C34 cells). The goal of the current study was to evaluate whether modulation of autophagy can affect CYP2E1-dependent cytotoxicity in the E47 cells. The agents used to promote CYP2E1 –dependent toxicity were a polyunsaturated fatty acid, arachidonic acid (AA), buthionine sulfoximine (BSO), which depletes GSH, and CCl4, which is metabolized to the CCl3 radical. These three agents produced a decrease in E47 cell viability which was enhanced upon inhibition of autophagy by 3-methyladenine (3-MA) or Atg 7 siRNA. Toxicity was lowered by rapamycin which increased autophagy and was much lower to the C34 cells which do not express CYP2E1. Toxicity was mainly necrotic and was associated with an increase in reactive oxygen production and oxidative stress; 3-MA increased while rapamycin blunted the oxidative stress. The enhanced toxicity and ROS formation produced when autophagy was inhibited was prevented by the antioxidant N-Acetyl cysteine. AA, BSO and CCl4 produced mitochondrial dysfunction, lowered cellular ATP levels and elevated mitochondrial production of ROS. This mitochondrial dysfunction was enhanced by inhibition of autophagy with 3-MA but decreased when autophagy was increased by rapamycin. The mitogen activated protein kinases p38 MAPK and JNK were activated by AA especially when autophagy was inhibited and chemical inhibitors of p38 MAPK and JNK lowered the elevated toxicity of AA produced by 3-MA. These results show that autophagy was protective against the toxicity produced by several agents known to be activated by CYP2E1. Since CYP2E1 plays an important role in the toxicity of ethanol, drugs and carcinogens and is activated under various pathophysiological conditions such as diabetes, NASH and obesity, attempts to stimulate autophagy may be beneficial in preventing/lowering CYP2E1/ethanol liver injury.

Application of phosphorus (P) fertilizers to P-deficient soils can also result in P accumulation. In this study, soil P status and P uptake by apple trees were investigated in 5-, 10-, and 15-year-old orchards in the semi-arid Loess Plateau, China, and subset soils with different soil P statuses (14-90 Olsen-P mg kg(-1)) were selected to evaluate the characteristic P adsorption. Due to the low P-use efficiency (4-6%), total soil P increased from 540 mg kg(-1) to 904 mg kg(-1), Olsen-P ranged from 3.4 mg kg(-1) to 30.7 mg kg(-1), and CaCl2-P increased from less than 0.1 mg kg(-1) to 0.66 mg kg(-1) under continuous P fertilization. The P sorption isotherms for each apple orchard were found to fit the Langmuir isotherm model (R2 = 0.91-0.98). K (binding energy) and Qm (P sorption maximum) decreased, whereas DPS (degree of phosphorus sorption) increased with increasing P concentration. CaCl2-P increased significantly with the increase of Olsen-P, especially above the change point of 46.1 mg kg(-1). Application of surplus P could result in P enrichment in P-deficient soil which has high P fixation capacity, thus posing a significant environmental risk.

A robot-based three-dimensional (3D) measurement system is presented. In the presented system, a structured light vision sensor is mounted on the arm of an industrial robot. Measurement accuracy is one of the most important aspects of any 3D measurement system. To improve the measuring accuracy of the structured light vision sensor, a novel sensor calibration approach is proposed to improve the calibration accuracy. The approach is based on a number of fixed concentric circles manufactured in a calibration target. The concentric circle is employed to determine the real projected centres of the circles. Then, a calibration point generation procedure is used with the help of the calibrated robot. When enough calibration points are ready, the radial alignment constraint (RAC) method is adopted to calibrate the camera model. A multilayer perceptron neural network (MLPNN) is then employed to identify the calibration residuals after the application of the RAC method. Therefore, the hybrid pinhole model and the MLPNN are used to represent the real camera model. Using a standard ball to validate the effectiveness of the presented technique, the experimental results demonstrate that the proposed novel calibration approach can achieve a highly accurate model of the structured light vision sensor.

In the title compound, C13H15N3O3, the dihedral angle between the benzene and pyrazole rings is 7.7 (1)° and the O—C—C—N torsion angle of the side chain is 74.1 (2)°. In the crystal, molecules are linked by O—H...O, N—H...O and N—H...N hydrogen bonds.

The mechanisms by which alcohol causes cell injury are not clear. A major mechanism is the role of lipid peroxidation and oxidative stress in alcohol toxicity. Many pathways have been suggested to play a role in how alcohol induces oxidative stress. Considerable attention has been given to alcohol elevated production of lipopolysaccharide (LPS) and TNFα and to alcohol induction of CYP2E1. These two pathways are not exclusive of each other; however, interactions between them, have not been extensively evaluated. Increased oxidative stress from induction of CYP2E1 sensitizes hepatocytes to LPS and TNFα toxicity and oxidants, activation of inducible nitric oxide synthase and p38 and JNK MAP kinases, and mitochondrial dysfunction are downstream mediators of this CYP2E1-LPS/TNFα-potentiated hepatotoxicity. This paper will summarize studies showing potentiated interactions between these two risk factors in promoting liver injury and the mechanisms involved including activation of the mitogen-activated kinase kinase kinase ASK-1. Decreasing either cytosolic or mitochondrial thioredoxin in HepG2 cells expressing CYP2E1 causes loss of cell viability and elevated oxidative stress via an ASK-1/JNK-dependent mechanism. We hypothesize that similar interactions occur as a result of ethanol induction of CYP2E1 and TNFα.

The environmental pollution caused by various sources has escalated the climate crisis making the need to establish reliable, intelligent, and persistent environmental monitoring solutions more crucial than ever. Mobile sensing systems are a popular platform due to their cost-effectiveness and adaptability. However, in practice, operation environments demand highly intelligent and robust systems that can cope with an environment's changing dynamics. To achieve this reinforcement learning has become a popular tool as it facilitates the training of intelligent and robust sensing agents that can handle unknown and extreme conditions. In this paper, a framework that formulates active sensing as a reinforcement learning problem is proposed. This framework allows unification with multiple essential environmental monitoring tasks and algorithms such as coverage, patrolling, source seeking, exploration and search and rescue. The unified framework represents a step towards bridging the divide between theoretical advancements in reinforcement learning and real-world applications in environmental monitoring. A critical review of the literature in this field is carried out and it is found that despite the potential of reinforcement learning for environmental active sensing applications there is still a lack of practical implementation and most work remains in the simulation phase. It is also noted that despite the consensus that, multi-agent systems are crucial to fully realize the potential of active sensing there is a lack of research in this area. [ABSTRACT FROM AUTHOR]