Field Experimental Study on Corrosion Mechanism of Well Lai 14-9

Casing corrosion is serious and the injection efficiency is considerably low due to high injecting water corrosion in Well Lai 14-9. Casing corrosion mechanism is retrieved through SEM observation, energy spectrum analysis, XRD analysis spectrum, TGA analysis of corrosion fouling. The results show casing corrosion mechanism varies with depths; casing corrosion is the result of the combined action of carbon dioxide, dissolved oxygen, sulfate-reducing bacteria and high salinity. To extend the life of casing, appropriate casing protection measures should be adopted, which can reduces the cost of production of the oilfield.Key words: Corrosion mechanism; Fouling; SEM observation; XRD analysis spectrum; TGA analysi

SoccerDB: A Large-Scale Database for Comprehensive Video Understanding

Soccer videos can serve as a perfect research object for video understanding because soccer games are played under well-defined rules while complex and intriguing enough for researchers to study. In this paper, we propose a new soccer video database named SoccerDB, comprising 171,191 video segments from 346 high-quality soccer games. The database contains 702,096 bounding boxes, 37,709 essential event labels with time boundary and 17,115 highlight annotations for object detection, action recognition, temporal action localization, and highlight detection tasks. To our knowledge, it is the largest database for comprehensive sports video understanding on various aspects. We further survey a collection of strong baselines on SoccerDB, which have demonstrated state-of-the-art performances on independent tasks. Our evaluation suggests that we can benefit significantly when jointly considering the inner correlations among those tasks. We believe the release of SoccerDB will tremendously advance researches around comprehensive video understanding. {\itshape Our dataset and code published on https://github.com/newsdata/SoccerDB.}Comment: accepted by MM2020 sports worksho

Vibration characteristics of the impeller at multi-conditions in mixed-flow pump under the action of fluid-structure interaction

In this study, the flow field and impeller structure response in the mixed-flow pump are cooperative solved based on the bidirectional synchronization solving method, to study the vibration characteristics of the mixed-flow pump impeller rotor under the fluid-structure interaction. The pressure distributions of blade surface in the mixed-flow pump under different flow rate conditions were compared, and the deformation, equivalent stress distribution and natural vibration frequency of impeller blade under static force load were studied. Meanwhile, the deformation of impeller blade and coupling stress distribution was analyzed based on bidirectional fluid-structure interaction. The results show that the deformation of impeller blade increases from hub to rim, and the maximum deformation occurs at the rim of the blade. The stress distribution of impeller blade in the circumferential direction is symmetrical, and the maximum equivalent stress occurs at the blade outlet edge near the hub. The maximum deformation position and the stress concentration location are basically consistent before and after coupling calculation, but the maximum deformation value increases and the maximum equivalent stress value decreases under the fluid-structure interaction. The influence of water pressure on the strength and frequency of vibration is very limited. With the increase of flow rate, the maximum equivalent stress of impeller decreases and the total deformation increases gradually. The results of this research provide reference basis for the structure design and reliability analysis of the mixed-flow pump

RGD Peptide-Grafted Graphene Oxide as a New Biomimetic Nanointerface for Impedance-Monitoring Cell Behaviors

A new biomimetic nanointerface was constructed by facile grafting the bioactive arginylglycylaspartic acid (RGD) peptide on the graphene oxide (GO) surface through carbodiimide and N-hydroxysuccinimide coupling amidation reaction. The formed RGD-GO nanocomposites own unique two-dimensional structure and desirable electrochemical performance. The linked RGD peptides could improve GO’s biocompatibility and support the adhesion and proliferation of human periodontal ligament fibroblasts (HPLFs) on RGD-GO biofilm surface. Furthermore the biologically active RGD-GO nanocomposites were demonstrated as a potential biomimetic nanointerface for monitoring cell biobehaviors by electrochemical impedance spectroscopy (EIS). By analysis of the data obtained from equivalent circuit-fitting impedance spectroscopy, the information related to cell membrane capacitance, cell-cell gap resistance, and cell-electrode interface gap resistance in the process of cell adhesion and proliferation could be obtained. Besides, this proposed impedance-based cell sensor could be used to assess the inhibition effect of the lipopolysaccharide (LPS) on the HPLFs proliferation. Findings from this work suggested that RGD peptide functionalized GO nanomaterials may be not only applied in dental tissue engineering but also used as a sensor interface for electrochemical detection and analysis of cell behaviors in vitro

LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification

Extreme Multi-label text Classification (XMC) is a task of finding the most relevant labels from a large label set. Nowadays deep learning-based methods have shown significant success in XMC. However, the existing methods (e.g., AttentionXML and X-Transformer etc) still suffer from 1) combining several models to train and predict for one dataset, and 2) sampling negative labels statically during the process of training label ranking model, which reduces both the efficiency and accuracy of the model. To address the above problems, we proposed LightXML, which adopts end-to-end training and dynamic negative labels sampling. In LightXML, we use generative cooperative networks to recall and rank labels, in which label recalling part generates negative and positive labels, and label ranking part distinguishes positive labels from these labels. Through these networks, negative labels are sampled dynamically during label ranking part training by feeding with the same text representation. Extensive experiments show that LightXML outperforms state-of-the-art methods in five extreme multi-label datasets with much smaller model size and lower computational complexity. In particular, on the Amazon dataset with 670K labels, LightXML can reduce the model size up to 72% compared to AttentionXML

Mitigating bias from intermittent measurement of time-dependent covariates in failure time analysis

This is the peer reviewed version of the following article: Shu Jiang, Richard J. Cook and Leilei Zeng, Mitigating bias from intermittent measurement of time-dependent covariates in failure time analysis, Statistics in Medicine (2020), 39 (13): 1833–1845 which has been published in final form at https://doi.org/10.1002/sim.8517. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.Cox regression models are routinely fitted to examine the association between time-dependent markers and a failure time when analyzing data from clinical registries. Typically, the marker values are measured periodically at clinic visits with the recorded value carried forward until the next assessment. We examine the asymptotic behavior of estimators from Cox regression models under this observation and data handling scheme when the true relationship is based on a Cox model using the current value of the marker. Specifically, we explore the impact of the marker process dynamics, the clinic visit intensity, and the marginal failure rate on the limiting value of the estimator of the marker effect from the Cox model. We also illustrate how a joint multistate model that accommodates intermittent observation of the time-varyingmarker can be formulated. Simulation studies demonstrate that the finite sample performance of the naive estimator aligns with the asymptotic results and shows good performance of the estimators from the joint model. We apply both methods to data from a study of bone markers and their effect on the development of skeletal complications in metastatic cancer.This research was supported by Discovery Grants from the Natural Sciences and Engineering Research Council of Canada to R.J.C. (RGPIN 155849 and RGPIN 04207) and L.Z. (RGPIN 115928) and from the Canadian Institutes for Health Research to R.J.C. (FRN 13887). R.J.C. is a Faculty of Mathematics Research Chair, University of Waterloo

Complex emulsions for shape control based on mass transfer and phase separation

Complex emulsions are used to fabricate new morphologies of multiple Janus droplets, evolving from non-engulfing to complete engulfing core/shell configuration. The produced droplets contain an aqueous phase of dextran (DEX) solution and an oil phase, which is mixed with ethoxylated trimethylolpropane triacrylate (ETPTA) and poly(ethylene glycol) diacrylate (PEGDA). The PEGDA in the oil phase is transferred into the aqueous phase to form complex morphologies due to the phase separation of PEGDA and DEX. The effects are investigated including the ratio of oil to aqueous phase, the content of initial PEGDA, DEX and surfactants, and the type of surfactants. DEX/PEGDA-ETPTA core/shell-single phase Janus droplets are formed with an increasing engulfed oil droplet into the aqueous droplet while the ratio of oil to aqueous phase increases or the initial PEGDA content increases. The high DEX content leads to the DEX-PEGDA-ETPTA doublet Janus. The use of surfactants polyglycerol polyricinoleate (PGPR) and Span 80 results in the formation of DEX/PEGDA/ETPTA single core/double shell and DEX/PEGDA-ETPTA core/shell-single phase Janus droplets, respectively. These complex emulsions are utilized to fabricate solid particles of complex shapes. This method contributes to new material design underpinned by mass transfer and phase separation, which can be extended to other complex emulsion systems

Metabolic Interaction of the Active Constituents of Coptis chinensis

Coptis chinensis is commonly used in traditional Chinese medicine. The study investigated metabolic interaction of the active constituents (berberine, coptisine, palmatine, and jatrorrhizine) of Coptis chinensis in human liver microsomes. After incubation of the four constituents of Coptis chinensis in HLMs, the metabolism of the four constituents was observed by HPLC. The in vitro inhibition experiment between the active constituents was conducted, and IC50 value was estimated. Coptisine exhibited inhibitions against the formation of the two metabolites of berberine with IC50 values of 6.5 and 8.3 μM, respectively. Palmatine and jatrorrhizine showed the weaker inhibitory effect on the formation of the metabolites of berberine. Berberine showed a weak inhibitory effect on the production of coptisine metabolite with an IC50 value of 115 μM, and palmatine and jatrorrhizine had little inhibitory effect on the formation of coptisine metabolite. Berberine, coptisine, and jatrorrhizine showed no inhibitory effect on the generation of palmatine metabolite (IC50 > 200 μM). The findings suggested that there are different degrees of metabolic interaction between the four components. Coptisine showed the strongest inhibition toward berberine metabolism