Mechanical Behavior Analysis and Testing of Marine Riser in Deepwater Drilling

In this chapter, the mechanical model and control equation have been established to analyse the mechanical behaviour of marine riser in working condition. The control equation has been solved by weighted residual method, and the analysis model has been verified by finite element method (FEM) in ABAQUS framework. Based on this, the deformation and stress distribution of the marine riser have been acquired. Then, a simulation experimental system has been introduced, and the system composition, functions and operational approach of the experimental setup have been stated in detail. After that, a tubular sample has been manufactured to simulate the marine riser, and the simulation experiments have been carried out based on this setup, where the experimental procedures, key aspects, difficult points of the experiment and its corresponding solutions have been elaborated. At last, the strain value of the specimen has been measured successfully after the experiment, and the stress state of the specimen has been obtained based on the analysis

Simulating the water content and temperature changes in an experimental embankment using meteorological data

International audienceAn experimental embankment was constructed in Rouen, France. The construction was completed in December 2004. The first objective of this experiment is to investigate the influence of climatic changes on the soil response such as changes in water content and temperature as well as the induced vertical and horizontal displacements; and the second objective is to investigate the soil response under water flooding from the base of embankment. In this study, the changes in temperature, volumetric water content and suction along the central axis have been analysed using a one-dimensional model and based on the meteorological data obtained in the field. Comparisons made between the measurements and simulations have shown the relevance of the method adopted, provided that suitable boundary conditions and soil parameters are taken into consideration. Moreover, both the simulation and field monitoring showed that climatic effects are limited to a shallow depth, which results from the low permeability of the compacted fill

Sliding Mode Control (SMC) of Image‐Based Visual Servoing for a 6DOF Manipulator

The accuracy and stability are two fundamental concerns of the visual servoing control system. This chapter presents a sliding mode controller for image‐based visual servoing (IBVS) which can increase the accuracy of 6DOF robotic system with guaranteed stability. The proposed controller combines proportional derivative (PD) control with sliding mode control (SMC) for a 6DOF manipulator. Compared with conventional proportional or SMC controller, this approach owns faster convergence and better disturbance rejection ability. Both simulation and experimental results show that the proposed controller can increase the accuracy and robustness of a 6DOF robotic system

Octreotide ameliorates hypoxia/reoxygenation-induced cerebral infarction by inhibiting oxidative stress, inflammation and apoptosis, and via inhibition of TLR4/MyD88/NF-κB signaling pathway

Purpose: To explore the effects of octreotide (OCT) on oxidative stress, inflammation and apoptosis in hypoxia/reoxygenation (H/R)-induced cerebral infarction.Methods: The in vitro model of cerebral infarction was established by treating N2A cells with hypoxia for 4 h and reoxygenation for 24 h. The viability of N2A cells was determined by CCK-8 assay. The cells were divided into 3 groups: control group, H/R group, and H/R+OCT group. The cells in H/R+OCT group were pretreated with OCT (60 ng/mL) before H/R treatment. The oxidative stress of N2A cells were assessed by determining the levels of superoxide dismutase (SOD), glutathione peroxidase (GSHPx), catalase (CAT), reactive oxygen species (ROS) and malondialdehyde (MDA). Inflammation of N2A cells was evaluated by evaluating the levels of TNF-α, IL-1β, IL-6, and IL-8, while the apoptosis of N2A cells was assessed by flow cytometry. Western blot analysis was used to determine the expression of Bcl-2, Bax, TLR4, MyD88, and NF-κB.Results: Octreotide treatment significantly reduced the level of oxidative stress. The inflammation of N2A cells caused by hypoxia/reoxygenation was inhibited by treatment with octreotide. Apoptosis of N2A cells was also inhibited by octreotide treatment. Hypoxia/reoxygenation activated TLR4/MyD88/NF-κB signaling pathway, while octreotide inhibits the activation of this pathway.Conclusion: The results reveal that octreotide inhibits hypoxia/reoxygenation-induced oxidative stress,as well as the inflammation, and apoptosis of N2A cells by inhibiting TLR4/MyD88/NF-κB signaling pathway. Thus, these findings may provide new insights into the treatment of cerebral infarction

Venlafaxine inhibits neuronal apoptosis in a depression rat model via ERK1/ERK2 pathway

Purpose: To investigate the effects and mechanism of action of venlafaxine on neuronal apoptosis of depressed rats. Methods: Rats were randomly divided into normal control (NC) group, depressed rats (depression) group or venlafaxine-treatment group. Changes in body weight and sucrose preference ratio were recorded and behaviors in open field test (OFT) were observed in each group. Pathological changes in and the apoptosis rate of the cerebral neurons, and the activity of extracellular signal-regulated kinase 1 (ERK1)/ERK2 pathway were observed under a microscope. Results: At weeks 2 and 4, the body weight and water consumption of rats in depression group dropped below those of rats in NC group. On the other hand, at week 2, the body weight and water consumption of rats in venlafaxine-treatment group were significantly higher than those of rats in depression group (p < 0.05). Besides, depression group had randomly arranged neuron cells and a thinner cell layer, while venlafaxine-treatment group had a relatively regular hippocampal neural cell arrangement and a thicker cell layer. Moreover, cell apoptosis rate was higher in depression group than in that NC group, and lower in venlafaxine-treatment group than that in depression group (p < 0.05). Finally, the protein expressions of phosphorylated (p)-ERK1 and p-ERK2 were significantly higher in depression group than those in NC group (p<0.05), and distinctly lower in venlafaxine-treatment group than those in depression group (p <0.05). Conclusion: By suppressing the activity of ERK1/ERK2 pathway, venlafaxine relieves the symptoms of depression and repairs neuronal injuries in rats, thereby suppressing neuronal apoptosis. Thus, these findings provide a novel approach for the development of new antidepressants

Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

Artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS). In this study, a novel artificial fish swarm algorithm (NAFSA) that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost) of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification

Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation

Pipeline leakage or explosion has caused huge economic losses, polluted the environments and threatened the safety of civilian’s lives and assets, which even caused negative influences to the society greatly. Fortunately, pipeline inspection gauge (PIG) could accomplish the pipeline defect (corrosions, cracks, grooves, etc.) inspection effectively and meanwhile to localize these defects precisely by navigation sensors. The results are utilized for pipeline integrity management (PIM) and pipeline geographic information system construction. Generally, the urban underground pipeline presents with small-diameter and complicated-distribution properties, which are of great challenges for the pipeline defects positioning by PIG. This chapter focuses on in-depth research of the high-precision positioning method for small-diameter PIG navigation. In the beginning, the problems and system errors statement of MEMS SINS-based PIG are analyzed step by step. Then, the pipeline junction (PJ) identification method based on fast orthogonal search (FOS) is studied. After that, a PIG positioning system that comprises of micro-inertial/AGM/odometer/PJ is proposed, and also the application mechanism of extended Kalman filter and its smoothing technology on PIG navigation system is researched to improve the overall positioning precision for the small-diameter PIG. Finally, the proposed methods and research conclusions are verified by the indoor wheel robot simulation platform

PCAS – a precomputed proteome annotation database resource

BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome. PCAS is available at CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified