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Doxorubicin, sold under the brand name Adriamycin among others, is an important drug for cancer therapy; however, its use is limited by its cardiotoxicity. Ginsenoside Rg2 is extracted from Panax ginseng C.A.Mey., Araliaceae, which is believed to have cardioprotective properties. However, to date, there have been no reports on whether ginsenoside Rg2 could protect cardiomyocytes against doxorubicin. In this study, we investigated the action and the underlying mechanisms of cardioprotection of ginsenoside Rg2 upon doxorubicin treatment. Cell counting kit-8 was used to determine cell viability; in addition, terminal deoxynucleotidyl transferase–mediated dUTP nick-end labeling staining was used to detect apoptotic cells. Western blotting was used to investigate the relevant pathways. LY294002, a phosphatidylinositol 3-kinase inhibitor, was also used in this study. Ginsenoside Rg2 significantly (p < 0.01) neutralized cardiomyocyte apoptosis induced by doxorubicin in a dose-dependent manner, but this effect was blocked by LY294002. Furthermore, ginsenoside Rg2 upregulated protein kinase B phosphorylation through the phosphatidylinositol 3-kinase/protein kinase B pathway and inhibited p53 expression. These results suggest that ginsenoside Rg2 could attenuate doxorubicin-induced cardiomyocyte apoptosis via the phosphatidylinositol 3-kinase/protein kinase B pathway. Graphical abstract

Stroke patients with autonomic dysfunction are more likely to develop cardiac problems, which have been linked to lower functional outcomes and increased mortality. In this study, heart rate variability (HRV) detection paired with the Clinical Feature Scale will be utilized to elucidate the immediate impact of manual acupuncture on autonomic dysfunction of varying severity in the convalescence stroke phase. This is a randomized, single-blind, controlled clinical trial approach. At a ratio of 1:1, 60 appropriate patients will be randomly randomized into either the experimental or control group. On the basis of symptomatic treatment drugs, the experimental group will additionally undertake acupuncture therapy 3 times a week for 4 weeks, for a total of 12 times. Primary outcomes include 24-hour HRV and 60-minute HRV detection at week 4 compared with baseline. The secondary outcome is the score of clinical feature scale at week 4 compared with the baseline. Adverse events and safety indices will be recorded throughout the experiment. The SPSS V.25.0 statistical program was applied for analysis, and measurement data were expressed as mean ± SD.

In response to the shortcomings of cobalt-rich cathodes, iron-based perovskite oxides appear as promising alternatives for solid oxide fuel cells (SOFCs). However, their inferior electrochemical performance at reduced temperatures (

In over 30 years, the forms of public legal education activities have become increasingly rich. However, with the technology refresh, the traditional public legal education model characterized by one-way communication has gradually become out of touch, which can not adapt to the return of the people’s subjectivity and meet the personalized needs of different groups of people. As an important part of advancing the Rule of Law in China, public legal education should be timely innovated with the help of new technology. By combining the knowledge graph technology in the era of artificial intelligence with the work of public legal education, this paper studies how to use the knowledge graph technology to build public legal education network platform, introduce customized legal education content, and establish a sound mechanism for intelligent public legal education work, so that users can complete the important transformation from the object of legal education to the subject of law learning. This will enrich the theoretical research results of public legal education.

The emergence of machine vision has promoted the automation of defect detection (DD) in the industrial field. Therefore, scholars at home and abroad have carried out a lot of research and exploration on the traditional visual DD method of mechanical design products. At the same time, this method has been widely used in the field of modern manufacturing due to its noncontact and fast detection speed. The traditional visual detection method is to use cameras, computers, and other equipment instead of people to detect the detected objects, although this method improves the production efficiency to a certain extent. However, this detection method is greatly affected by light, has a certain false detection rate, and has poor adaptability. The intelligent detection method based on deep learning developed on the basis of traditional vision is a further optimization of traditional visual detection methods. The rapid development of deep learning makes the advantages of visual DD more obvious.

The effect of exopolysaccharide (EPS) produced by Weissella confusa QS813 on the hydration, water distribution, rheology and microstructure of wheat gluten during freeze–thaw cycles (FTC) was investigated. Addition of EPS increased the water content of fresh gluten and delayed the dehydration of gluten during FTC. Low field-nuclear magnetic resonance showed that the presence of EPS reduced the mobility of both confined and bulk water in the fresh gluten matrix. Proton distribution changes in gluten during FTC indicated that deterioration of the gluten network was attributable to ice recrystallization of capillary confined water and bulk water. The presence of EPS effectively reduced the release of bulk water and retarded the redistribution of confined water induced by FTC. Dynamic oscillatory studies indicated that the presence of EPS induced a softening effect on the fresh gluten. FTC significantly decreased the rheological parameters, storage modulus (G′) and loss modulus (G″), of all gluten samples. Gluten with higher concentrations of EPS (above 0.5%) exhibited a delayed decrease in G′ and G″ and maintained a constant tanδ value after FTC. Laser scanning confocal microscope and scanning electron microscope revealed that EPS maintained the structural integrity of gluten during FTC, suggesting an inhibitory effect on the recrystallization of ice crystals. These results in the present study indicated that the bacterial dextran is a promising cryoprotectant for the frozen dough industry.

Relative permeability is a concept used to convey the reduction in flow capability due to the presence of multiple mobile fluids. The study of the mechanism and characteristics of discontinuous flow in multiphase flow have great significance in reservoir engineering, geotechnical engineering, biomedical engineering, chemical engineering. In this article, considering the oil/water micro-distribution characteristic in the ultra-high water cut stage and the self-similar fractal characteristics of porous media, an analytical model of relative permeability curve in porous media with discontinuous phase is derived based on capillary bundle model. The new expression contains the characteristic parameters of both porous media and fluid in it. The accuracy of the model is verified by fitting the available experimental data and comparing with other similar models. By changing the value of each parameter (the length ratio of oil drops to water drops, the radius of oil drops, the ratio of oil-water viscosity, fractal dimension for pore size, tortuosity fractal dimension) in the new mathematical analysis model, the influence of each parameter on the characteristics of relative permeability curve has been investigated, thus help reveal the law of two-phase seepage in the porous media of the ultra-high water cut period.

BackgroundDrug abuse has many negative effects not only on individuals but also on society. Nowadays, researchers pay a lot of attention to the quality of life of drug-dependent persons. However, there are few scales available to measure the quality of life of people with substance-abuse disorders. A quality of life scale for patients with drug addiction/dependence (QLICD-DA) developed in China according to their actual situation could be used to measure the quality of life of drug abusers. It has good validity and reliability and is sensitive to the quality of life of drug-dependent persons. MethodsWe selected 192 drug-dependent persons as participants and they all completed the general information questionnaire and the QLICD-DA. We used a t-test to compare the scores of the quality of life of the participants with the norm in different domains, then we used one-way ANOVA to screen for variables. A stepwise regression method was applied to explore the influencing factors of the quality of life of the participants.ResultsThe quality of life of the participants was lower than the norm in the physiological domain, psychological domain, social domain, and common general domain, and the differences were statistically significant (p

Background Drug abuse has many negative effects not only on individuals but also on society. Nowadays, researchers pay a lot of attention to quality of life of drug addicts. However, there are few scales available to measure quality of life of drug addicts. The scale QLICD-DA (quality of life instrument for chronic diseases-drug addition) developed by modular approach could be used to measure quality of life of drug addicts with good validity, reliability and sensitivity. Objective This study is aimed to understand the quality of life status and influencing factors in drug addicts by suitable sensitively scale, with the hypothesis of the quality of life in drug addicts being different from that of other peoples and possibly being influenced by many factors. Methods By cluster random sampling method, 192 drug addicts at Kunming compulsory drug rehabilitation center were recruited to take part in the investigation. All participants completed the general information questionnaire and the scale QLICD-DA. We used a t-test to compare the scores of the quality of life of the participants with the norm (QOL scores from 1953 patients of 10 chronic diseases). A stepwise regression method was applied to explore the influencing factors of the quality of life in drug addicts. Results 192 participants ranged in age from 19 to 59 with an average age of 34.86. Most of them were male (70.3%), high school education level (67.7%) and of Han nationality (82.8%). The quality of life of drug addicts was lower than the norm in the physical domain, psychological domain, social domain, and general module, and the differences were statistically significant (p p = 0.006) and specific module (p = 0.019). Past family atmosphere and the mode of drug abuse were the influencing factors in the general module (p = 0.027, p = 0.037). Conclusion The quality of life of drug addicts was worse than that of patients with other chronic diseases, and the influencing factors of the quality of life of drug abusers were sex, mode of drug abuse, and past family atmosphere.

Developing low-cost, efficient, and durable cobalt-free perovskite oxides for oxygen reduction reaction at intermediate-to-low temperatures is crucial to enhance the viability of solid oxide fuel cells (SOFCs), a promising ingredient for establishing a more sustainable future. Herein, a highly active and robust cobalt-free perovskite Ba

Productivity behavior change systems help us reduce our time on unproductive activities. However, is that time actually saved, or is it just redirected to other unproductive activities? We report an experiment using HabitLab, a behavior change browser extension and phone application, that manipulated the frequency of interventions on a focal goal and measured the effects on time spent on other applications and platforms. We find that, when intervention frequency increases on the focal goal, time spent on other applications is held constant or even reduced. Likewise, we find that time is not redistributed across platforms from browser to mobile phone or vice versa. These results suggest that any conservation of procrastination effect is minimal, and that behavior change designers may target individual productivity goals without causing substantial negative second-order effects.

Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus (PHEB) has become one of the most popular powertrains due to its alterable operating modes, excellent fuel economy and strong adaptability for driving cycles. Nevertheless, for configuring the PHEB with single-shaft series-parallel powertrain in the development stage, it still faces greater challenge than other configurations when choosing and matching the main component parameters. Motivated by this issue, a comprehensive multi-objectives optimization strategy based on Genetic Algorithm (GA) is developed for the PHEB with the typical powertrain. First, considering repeatability and regularity of bus route, the methods of off-line data processing and mathematical statistics are adopted, to obtain a representative driving cycle, which could well reflect the general characteristic of the real-world bus route. Then, the economical optimization objective is defined, which is consist of manufacturing costs of the key components and energy consumption, and combined with the dynamical optimization objective, a multi-objective optimization function is put forward. Meanwhile, GA algorithm is used to optimize the parameters, for the optimal components combination of the novel series-parallel powertrain. Finally, a comparison with the prototype is carried out to verify the performance of the optimized powertrain along driving cycles. Simulation results indicate that the parameters of powertrain components obtained by the proposed comprehensive multi-objectives optimization strategy might get better fuel economy, meanwhile ensure the dynamic performance of PHEB. In contrast to the original, the costs declined by 18%. Hence, the strategy would provide a theoretical guidance on parameter selection for PHEB manufacturers.

© Chinese Mechanical Engineering Society and Springer-Verlag Berlin Heidelberg 2016. Since the main power source of hybrid electric vehicle (HEV) is supplied by the power battery, the predicted performance of power battery, especially the state-of-charge (SOC) estimation has attracted great attention in the area of HEV. However, the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected. A variable structure extended kalman filter (VSEKF)-based estimation method, which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition, is presented. First, the general lower-order battery equivalent circuit model (GLM), which includes column accumulation model, open circuit voltage model and the SOC output model, is established, and the off-line and online model parameters are calculated with hybrid pulse power characteristics (HPPC) test data. Next, a VSEKF estimation method of SOC, which integrates the ampere-hour (Ah) integration method and the extended Kalman filter (EKF) method, is executed with different adaptive weighting coefficients, which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes. According to the experimental analysis, the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV. The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method. In Summary, the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system, which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method. The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

An Al2O3-supported core–shell-structured PdO@SiO2 catalyst was rationally synthesized for lean-CH4 oxidation with outstanding water-tolerance and sinter-resistance properties. PdO@SiO2 works two parts in promoting the hydrothermally catalytic performance. Firstly, the core–shell configurations with maximized interface and intimate contact bring out the strong metal-support interaction, which leads to the benign oxidation–reduction property and the higher desorption rate of OH–/H2O over the PdO active centres; secondly, the SiO2 shells could isolate PdO nanoparticles from each other and protect them from agglomeration especially at high temperature (>600 °C). As a result, PdO@SiO2/Al2O3 exhibits a 90% CH4 conversion at 380 °C, a low Ea value as 54.0 ± 1.6 kJ/mol and an enhanced hydrothermal stability at 800 °C for 10 h. Such an interface-promoted core–shell-structured catalyst design strategy sheds some light on the stabilization and application of Pd-based catalysts.

Conventional water flooding method becomes ineffective facing low and ultra-low permeability oilfields, and the recovery rate of the non water harvesting period is only about 20%. Most residual oil is trapped in the reservoir and cannot be recovered. The conversion of injection well into production ones is used on some scale at home and abroad as a technique of oilfield adjustment, stimulation and EOR. Yet, problems like the optimum converting time, microscopic stimulation mechanisms, etc., have not been clearly studied. The optimum time for reverse displacement can be acquired through forward and reverse displacement experiments of man-made cores with different permeability. Then, based on CT scanning technology an analysis is made of the processes of the forward displacement (till the converting time point) and the reverse displacement (till the end). According to the information of pores and water-oil distribution extracted from the CT graphs, water flooding characteristics and the change in residual oil distribution in different layers and at different displacement stages can be recognized. With the process of forward water injection, the residual oil in the core behave as types of discontinuous phases, including film flow, blob flow, slug flow, multi-pore flow, etc., the total volume fraction of which increases with the displacement continuing. During the reverse displacement, in contrast, the former dispersed residual oil gradually gathered in cluster that is comparatively more recognizable. Meanwhile, the amount of multi-pore flow ascend, which is most obvious. These factors made part of the residual oil better displaced. By above analysis, a reasonable microscopic explanation of the stimulation technology by converting injection wells into production ones. The article concisely and directly uncovered the microscopic mechanism of the reverse displacement to enhance oil recovery. Based on the study and taking other influential factors of development into account, instructions can be made on further EOR process of low and ultra-low permeability oilfield at lower costs and with higher efficiency, which is one of the top concerns for most low permeability oilfields.

Energy optimization control for a parallel hybrid electric system with automated mechanical transmission (AMT) can be divided into two steps in this paper. First, the AMT shift is not optimized and the optimal torque distribution strategy is proposed to minimize the powertrain equivalent specific fuel consumption by considering the power conversion efficiency, which distributes the vehicle single torque request into separate torque requests for the internal combustion engine (ICE) and the electric motor (EM). The distribution results are expressed in a table format and can be found from the simple process of looking up the table using the vehicle torque request, the ICE speed, and the battery state of charge (SOC). Then, the AMT shift control is suggested to maximize the powertrain system efficiency and optimizes the speed as the basis for the above-mentioned torque distribution, in which the ICE efficiency, the EM efficiency, and the battery efficiency are all explicitly taken into account. The AMT optimal shift control law and the EM optimal torque are essentially look-up-table-based control according to the ICE power, the EM power, the vehicle velocity, and the battery SOC after offline calculations. Simulation results reveal that potential fuel economy improvement has been achieved by using the energy optimization control.

The power distribution is proposed to determine the target operating points of the system components as the basis for maximal the efficiency of the overall system for a power split dual electric machine hybrid electric bus. The coordinated control is constructed on the basis of the power distribution. The basic coordinated control is implemented to satisfy the driver's power demand, in which both the dynamic characteristics of the engine and the dual electric machine are explicitly taken into account. Moreover, the improved coordinated control is suggested to suppress engine dynamic operation and rich fuel injection.

This is the second part of the two-part paper to illustrate the control system design and multi-energy strategy, it is the key to fulfill the fuel economy target for ISG hybrid bus. Based on a hierarchical structure, the control system is developed with the HCU (hybrid control unit) as the central controller to coordinate the motor, engine and CAN communication protocol. The multi-energy control strategy is consisted of the auxiliary strategy and the main strategy. The first one includes the finite state machine which decides the turning-point from one state to another state and the 2-quad tree of expert system which is adopted to realize the automatic start/stop function; the last one is called as the torque distribution strategy that satisfies the drive demand as well as implements the optimal torque distribution by fuzzy method. The parallel regenerative brake strategy and self-adaptive SOC balance strategy are all cooperated into the fuzzy based torque distribution strategy. The road tests are done to test the performance of ISG power-train and to validate the functions of the control system. The result shows that the fuel economy is 25% better than the traditional bus.