Green Tea Polyphenols Prevent Early Vascular Aging Induced by High-Fat Diet via Promoting Autophagy in Young Adult Rats

Objective Epidemiology studies indicate that green tea polyphenols(GTP)perform a protective effect on cardiovascular diseases,but the underlying mechanisms are complex.The present study aimed to investigate the effect of GTP on high-fat diets(HFD)induced-early vascular aging.Methods Six-week young adult Wistar rats were fed with standard chow or HFD in the presence and absence of GTP(200 mg/kg body weight)for 18 weeks.In vitro experiment,human umbilical vascular endothelial cells(HUVECs)were treated with palmitic acid(PA)and GTP.Results The results showed that GTP alleviated the disorganized arterial wall and the increased intima-media thickness induced by HFD.In addition,the vascular oxidative injury was suppressed following GTP treatment.Furthermore,GTP elevated the ratio of LC3-II/LC3-I and suppressed expression of p62/SQSTM1,and restored SIRT3 expression in the aorta of HFD rats.Consistently,in cultured HUVECs,GTP inhibited cell senescence indicated by SA-β-gal and promoted endothelial autophagy compared with the PA treatment group.The activity of SIRT3 was specifically inhibited by 3-TYP,and the protective effect of GTP was consequently abolished.Conclusion The findings indicated that GTP protected against early vascular senescence in young HFD rats via ameliorating oxidative injury and promoting autophagy which was partially regulated by the SIRT3 pathway.

Effect of oxide interactions on chromium speciation transformation during simulated municipal solid waste incineration

Chromium released during municipal solid waste incineration(MSWI)is toxic and carcinogenic.The removal of chromium from simulated MSWI flue gas by four sorbents(CaO,bamboo charcoal(BC),powdered activated carbon(PAC),and Al_(2)O_(3))and the effects of four oxides(SiO_(2),Al_(2)O_(3),Fe_(2)O_(3),and CaO)on chromium speciation transformationwere investigated.The results showed that the removal rates of total Cr by the four sorbents were Al_(2)O_(3)<CaO<PAC<BC,while the removal rates of Cr(Ⅵ)by the four sorbents were Al_(2)O_(3)<PAC<BC<CaO.CaO had a strong oxidizing effect on Cr(Ⅲ),while BC and PAC had a better-reducing effect on Cr(Ⅵ).SiO_(2)was better for the reduction of Na_(2)CrO_(4)and K_(2)CrO_(4)above 1000℃due to its strong acidity,and the addition of CaO significantly inhibited the reduction of Cr(Ⅵ).MgCrO_(4)decomposed above 700℃to form MgCr_(2)O_(4),and the reaction between MgCrO_(4)and oxides also existed in the form of a more stable trivalent spinel.Furthermore,when investigating the effect of oxides on the oxidation of Cr(Ⅲ)in CrC_(l3),it was discovered that CaO promoted the conversion of Cr(Ⅲ)to Cr(Ⅵ),while the presence of chlorine caused chromium to exist in the form of Cr(V),and increasing the content of CaO and extending the heating time facilitated the oxidation of Cr(Ⅲ).In addition,silicate,aluminate,and ferrite were generated after the addition of SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),which reduced the alkalinity of CaO and had an important role in inhibiting the oxidation of Cr(Ⅲ).The acidic oxides can not only promote the reduction of Cr(Ⅵ)but also have an inhibitory effect on the oxidation of Cr(Ⅲ)ascribed to alkali metals/alkaline earth metals,and the proportion of acidic oxides can be increased moderately to reduce the generation of harmful substances in the hazardous solid waste heat treatment.

UCat: heterogeneous memory management for unikernels

Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-based VMs in a single physical server. In such a cloud computing platform, main memory is the primary bottleneck resource for high-density application deployment. Recently, non-volatile memory (NVM) technologies has become increasingly popular in cloud data centers because they can offer extremely large memory capacity at a low expense. However, there still remain many challenges to utilize NVMs for unikernel-based VMs, such as the difficulty of heterogeneous memory allocation and high performance overhead of address translations.In this paper, we present UCat, a heterogeneous memory management mechanism that support multi-grained memory allocation for unikernels. We propose front-end/back-end cooperative address space mapping to expose the host memory heterogeneity to unikernels. UCat exploits large pages to reduce the cost of two-layer address translation in virtualization environments, and leverages slab allocation to reduce memory waste due to internal memory fragmentation. We implement UCat based on a popular unikernel--OSv and conduct extensive experiments to evaluate its efficiency. Experimental results show that UCat can reduce the memory consumption of unikernels by 50% and TLB miss rate by 41%, and improve the throughput of real-world benchmarks such as memslap and YCSB by up to 18.5% and 14.8%, respectively.

Deep reinforcement learning for shared control of mobile robots

Shared control of mobile robots integrates manual input with auxiliary autonomous controllers to improve the overall system performance.However,prior work that seeks to find the optimal shared control ratio needs an accurate human model,which is usually challenging to obtain.In this study,the authors develop an extended Twin Delayed Deep Deterministic Policy Gradient(DDPG)(TD3X)-based shared control framework that learns to assist a human operator in teleoperating mobile robots optimally.The robot's states,shared control ratio in the previous time step,and human's control input is used as inputs to the reinforcement learning(RL)agent,which then outputs the optimal shared control ratio between human input and autonomous controllers without knowing the human model.Noisy softmax policies are developed to make the TD3X algorithm feasible under the constraint of a shared control ratio.Furthermore,to accelerate the training process and protect the robot,a navigation demonstration policy and a safety guard are developed.A neural network(NN)structure is developed to maintain the correlation of sensor readings among heterogeneous input data and improve the learning speed.In addition,an extended DAGGER(DAGGERX)human agent is developed for training the RL agent to reduce human workload.Robot simulations and experiments with humans in the loop are conducted.The results show that the DAGGERX human agent can simulate real human inputs in the worst-case scenarios with a mean square error of 0.0039.Compared to the original TD3 agent,the TD3X-based shared control system decreased the average collision number from 387.3 to 44.4 in a simplistic environment and 394.2 to 171.2 in a more complex environment.The maximum average return increased from 1043 to 1187 with a faster converge speed in the simplistic environment,while the performance is equally good in the complex environment because of the use of an advanced human agent.In the human subject tests,participants'average perceived workload was significantly lower in shared control than that in exclusively manual control(26.90 vs.40.07,p=0.013).