Antitumor effect of salidroside on mice bearing HepA hepatocellular carcinoma

Salidroside, a phenylpropanoid glycoside extracted from Rhodiola rosea L., has antiproliferative effects on tumour cells in mice. However it’s antitumor mechanism remains largely unknown. In this study, 4 groups of mice bearing hepatocarcinoma cells were given treatment with vehicle alone, cyclophosphamide (25 mg/kg, i.p.) and salidroside, either 100 or 200 mg/kg (p.o.) for 14 days. The morphology of tumour specimens was analysed by transmission electron microscopy. Apoptotic cells in sections of mouse tumour tissue were analysed using an in situ apoptosis kit. The expression of Bcl-2, Bax and caspase 3 mRNA were examined with RT-PCR. The results showed that the tumour weights in groups 100 or 200 mg/kg/day of salidroside were reduced significantly (45.34 and 52.48% respectively), compared to vehicle groups. Salidroside increased apoptotic cells index, e.g. in 200 mg/kg group, it was four times higher compared to the control group. Even more, treatment with salidroside decreased Bcl-2 mRNA expression and increased Bax and caspase 3 mRNA expressions. These indicated that the antitumor mechanism of salidroside may induce tumour cell apoptosis in mice by triggering the mitochondrial-dependent pathway and activation of caspase 3

Energy Consumption Estimation for Electric Buses Based on a Physical and Data-Driven Fusion Model

The energy consumption of electric vehicles is closely related to the problems of charging station planning and vehicle route optimization. However, due to various factors, such as vehicle performance, driving habits and environmental conditions, it is difficult to estimate vehicle energy consumption accurately. In this work, a physical and data-driven fusion model was designed for electric bus energy consumption estimation. The basic energy consumption of the electric bus was modeled by a simplified physical model. The effects of rolling drag, brake consumption and air-conditioning consumption are considered in the model. Taking into account the fluctuation in energy consumption caused by multiple factors, a CatBoost decision tree model was constructed. Finally, a fusion model was built. Based on the analysis of electric bus data on the big data platform, the performance of the energy consumption model was verified. The results show that the model has high accuracy with an average relative error of 6.1%. The fusion model provides a powerful tool for the optimization of the energy consumption of electric buses, vehicle scheduling and the rational layout of charging facilities

Battery Pack State of Health Prediction Based on the Electric Vehicle Management Platform Data

In electric vehicle technologies, the state of health prediction and safety assessment of battery packs are key issues to be solved. In this paper, the battery system data collected on the electric vehicle data management platform is used to model the corresponding state of health of the electric vehicle during charging and discharging processes. The increment in capacity in the same voltage range is used as the battery state of health indicator. In order to improve the modeling accuracy, the influence of ambient temperature on the capacity performance of the battery pack is considered. A temperature correction coefficient is added to the battery state of health model. Finally, a double exponential function is used to describe the process of battery health decline. Additionally, for the case where the amount of data is relatively small, model migration is also applied in the method. Particle swarm optimization algorithm is used to calibrate the model parameters. Based on the migration battery pack model and parameter identification method, the proposed method can obtain accurate battery pack SOH prediction result. The method is simple and easy to perform on the electric vehicle data management platform

Evaluating Social Performance of Construction Projects: An Empirical Study

The concept of sustainable development is gaining increasing popularity in construction industry. Previous studies have prioritized on the sustainable performance of construction projects from perspectives of economy and environment, social performance of construction projects has not drawn much attention. Social performance of construction projects refers to the extent which the projects meet the needs of current and future generations. Therefore, social performance of construction projects is critical for project success as well as social sustainability. However, a systematic framework for evaluating social performance of construction projects is absent. At the same time, existing methods are time-consuming and subject to certain degree of subjectivity. To overcome these limitations, the fuzzy analytical hierarchy process (FAHP) method is introduced in this paper to evaluate social performance of construction projects. A real-world hospital redevelopment project was employed as an empirical study to develop the systematic framework for social performance evaluation using FAHP method. By analyzing previous studies and the hospital redevelopment project, a systematic framework with 18 indicators of five dimensions (i.e., socio-economy development, socio-environment development, social flexibility, public service development, and environment and resource conservation) was developed. Social performance of two proposed schemes for hospital redevelopment project were evaluated using the FAHP approach. Results show Scheme 2 has a relative higher social performance sore than that of Scheme 1 and the hospital redevelopment project would improve socio-economy development, socio-environment development, social flexibility, and public service development, while it brings challenges to environment and resource conservation. More seriously, results indicate the hospital project may threaten healthcare and disease prevention of the local communities. Therefore, more measures should be taken to improve social performance of the hospital redevelopment project. The empirical study shows the proposed framework using FAHP method is viable for conducting social performance evaluation of construction projects, which could be helpful to improve social performance, reduce negative social impacts, and contribute to the social sustainability of construction projects

Effects of flow regimes on the interaction between granular flow and flexible barrier

Flexible barriers are widely used to mitigate granular flows. In practice, flow regimes may keep changing along a flow path after the initiation of granular flows. The effects of flow regimes should be considered in the design of flexible barriers to intercept granular flow. In this study, flow regimes are divided into three types: dilute flow; dense flow; and quasistatic flow. The impact mechanisms of dense granular flows and dilute granular flows against flexible barriers are investigated using flume tests and the discrete element method. Influences of the ratio of the average particle size to the mesh size of a flexible barrier and particle segregation on the interaction between the flexible barrier and the granular flow are revealed. Differences of the impact mechanisms between rockfall and granular flow are compared. Results show that the impact force of dense granular flow against a flexible barrier will not increase linearly with the average particle size. The tensile force of the bottom cable is usually the maximum tensile force among all cables of the flexible barrier. Particle segregation will lead to increase in impact force of dense flows and tensile force of the upper cables. Impact force of the dilute granular flow increases with the average particle size. Different from the failure of a flexible barrier under the impact of the dense flow, the middle and upper cables are easier to break. Based on these findings, a useful reference for the future design of flexible barriers was proposed

Experimental and Theoretical Research on Bending Behavior of Photovoltaic Panels with a Special Boundary Condition

Currently, the photovoltaic (PV) panels widely manufactured on market are composed of stiff front and back layers and the solar cells embedded in a soft polymeric interlayer. The wind and snow pressure are the usual loads to which working PV panels need to face, and it needs the panels keep undamaged under those pressure when they generate electricity. Therefore, an accurate and systematic research on bending behavior of PV panels is important and necessary. In this paper, classical lamination theory (CLT) considering soft interlayer is applied to build governing equations of the solar panel. A Rayleigh–Rita method is modified to solve the governing equations and calculate the static deformation of the PV panel. Different from many previous researches only analyzing simply supported boundary condition for four edges, a special boundary condition which consists of two opposite edges simply supported and the others two free is studied in this paper. A closed form solution is derived out and used to do the numerical calculation. The corresponding bending experiments of PV panels are completed. Comparing the numerical results with experiment results, the accuracy of the analytical solutions are verified

Mechanical analysis of photovoltaic panels with various boundary condition

The photovoltaic (PV) panels currently existed on market are laminated plate structures, which are composed of two stiff glass skins and a soft interlayer. Some panels are installed on the buildings and integrated as the components of the structures, such as wall and roof. In different locations, the installations of PV panels are different and the boundary conditions are not always simply supported. In this paper, the bending behaviour of PV panels with various boundary conditions is analysed and the influence of boundary condition is studied carefully. The Kirchhoff theory is adopted to build governing equations of PV panels under static force. A Rayleigh-Rita method is modified to solve the governing equations and calculate the static deformation and stress. Different boundary conditions usually require different assumptions of the deflection function, but a modified general function is developed in here to solve that problem. A theoretical solution is derived out and used to do the numerical calculation. The bending experiments of PV panels with two boundary conditions are used to verify the accuracy of the proposed solutions. Finally, the influence of different boundary condition is stated by comparing the numerical results and some guides for the PV panel installation are proposed

An angular normalization method for temperature vegetation dryness index (TVDI) in monitoring agricultural drought

International audienc

Quantification of host proteomic responses to genotype 4 hepatitis E virus replication facilitated by pregnancy serum

Abstract Background Hepatitis E virus (HEV) infection is a common cause of acute hepatitis worldwide and causes approximately 30% case fatality rate among pregnant women. Pregnancy serum (PS), which contains a high concentration of estradiol, facilitates HEV replication in vitro through the suppression of the PI3K–AKT–mTOR and cAMPK–PKA–CREB signaling pathways. However, the proteomics of the complex host responses to HEV infection, especially how PS facilitates viral replication, remains unclear. Methods In this study, the differences in the proteomics of HEV-infected HepG2 cells supplemented with fetal bovine serum (FBS) from those of HEV-infected HepG2 cells supplemented with serum from women in their third trimester of pregnancy were quantified by using isobaric tags for relative and absolute quantification technology. Results A total of 1511 proteins were identified, among which 548 were defined as differentially expressed proteins (DEPs). HEV-infected cells supplemented with PS exhibited the most significant changes at the protein level. A total of 328 DEPs, including 66 up-regulated and 262 down-regulated proteins, were identified in HEV-infected cells supplemented with FBS, whereas 264 DEPs, including 201 up-regulated and 63 down-regulated proteins, were found in HEV-infected cells supplemented with PS. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that in HEV-infected cells, PS supplementation adjusted more host genes and signaling pathways than FBS supplementation. The DEPs involved in virus–host interaction participated in complex interactions, especially a large number of immune-related protein emerged in HEV-infected cells supplemented with PS. Three significant or interesting proteins, including filamin-A, thioredoxin, and cytochrome c, in HEV-infected cells were functionally verified. Conclusions The results of this study provide new and comprehensive insight for exploring virus–host interactions and will benefit future studies on the pathogenesis of HEV in pregnant women