Mesoporous silica SBA-15 supported iron and cobalt catalysts (Fe–Co/SBA-15) were prepared and used in the electrochemical (EC) enhanced heterogeneous activation of peroxydisulfate (PDS, S2O82−) ...process for the removal of Orange II. The effects of some important reaction parameters such as initial pH, current density, PDS concentration and dosage of Fe–Co/SBA-15 catalysts were investigated. The results showed that the decolorization efficiency was not significantly affected by the initial pH value, and it did increase with the higher PDS concentration, current density and Fe–Co/SBA-15 dosage. Both the sulfate radical (SO4·−) and the hydroxyl radical (OH) are considered as the primary reactive oxidants for the Orange II decolorization. The Fe–Co/SBA-15 catalyst maintained its high activity during repeated batch experiments. The intermediate products were identified by GC–MS analysis and a plausible degradation pathway is proposed accordingly. The removal efficiencies of chemical oxygen demand (COD) and total organic carbon (TOC) were 52.1% and 31.9%, respectively after 60 min of reaction time but reached 82.9% and 51.5%, respectively when the reaction time was extended to 24 h. Toxicity tests with activated sludge indicated that the toxicity of the solution increased during the first 30 min and then decreased as the oxidation proceeded.
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•Fe–Co/SBA-15 was fabricated and utilized in EC enhanced heterogeneous activation of PDS.•The effect of reaction parameters for the decolorization of Orange II was evaluated.•Possible reaction mechanism and the stability of Fe–Co/SBA-15 were investigated.•Main intermediates were determined and a plausible degradation pathway was proposed.•The toxicity of Orange II was eliminated after 24 h treatment.
•A novel electro/Fe3O4/PDS process was employed to degrade Acid Orange 7 in water.•The effect of operating parameters on the degradation was investigated.•The surface properties of Fe3O4 before and ...after reaction was investigated by XPS.•A plausible degradation pathway of Acid Orange 7 was proposed.
The decolorization of C. I. Acid Orange 7 (AO7) in aqueous solution by Fe3O4 activated peroxydisulfate (PDS) oxidation in an electrochemical reactor (EC/Fe3O4/PDS process) was performed in this study. Various parameters were investigated to optimize the process, including initial pH, current density, PDS concentration and Fe3O4 dosage. The stability of Fe3O4 particles was observed by recycle experiments. The X-ray photoelectron spectroscopy (XPS) was applied to investigate the surface properties of Fe3O4 before and after reaction. GC–MS analysis was employed to identify the intermediate products and a plausible degradation pathway of AO7 was proposed. The change of acute toxicity during the treatment was investigated by activated sludge inhibition test. The TOC removal efficiency was 30.0% in a 90min reaction.
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► Na
2S
2O
8 was activated by magnetite and ultrasound for the degradation of tetracycline. ► The presence of different types of radical scavengers would inhibit the degradation rate. ...► The oxidation mechanism on the surface of the heterogeneous catalyst is scarce.
The removal of tetracycline by magnetite (Fe
3O
4) activated peroxydisulfate (Na
2S
2O
8) in the presence of ultrasound irradiation has been performed in this study. The effects of Na
2S
2O
8 concentration, Fe
3O
4 addition, ultrasonic power, initial concentration and initial pH on the degradation of tetracycline were investigated. The results showed that tetracycline removal rate increased with the increase of Fe
3O
4 dosage, but decreased with the increase of initial pH and initial tetracycline concentration. With the optimum values of Na
2S
2O
8 concentration and ultrasound power, the highest degradation rate can be achieved. The scavenging effect was examined by using ethanol,
tert-butyl alcohol and 1,4-benzoquinone to evaluate the roles of sulfate radicals, hydroxyl radicals and superoxide radicals. The results indicated that sulfate radicals and the hydroxyl radicals played important roles in the degradation of tetracycline by Fe
3O
4/Na
2S
2O
8/US process.
Autonomous planning robotic contact-rich manipulation has long been a challenging problem. Automatic peeling of glass substrates of LCD flat panel displays is a typical contact-rich manipulation ...task, which requires extremely high safe handling through the manipulation process. To this end of peeling glass substrates automatically, the system model is established from data and is used for the online planning of the robot motion in this paper. A simulation environment is designed to pretrain the process model with deep learning-based neural network structure to avoid expensive and time-consuming collection of real-time data. Then, an online learning algorithm is introduced to tune the pretrained model according to the real-time data from the peeling process experiments to cover the uncertainties of the real process. Finally, an Online Learning Model Predictive Path Integral (OL-MPPI) algorithm is proposed for the optimal trajectory planning of the robot. The performance of our algorithm was validated through glass substrate peeling tasks of experiments.
The 12 May 2008 Wenchuan earthquake （Ms=8.0） struck on the Longmen Shan foreland thrust zone. The event took place within the context of long-term uplift of the Longmen Shan range as a result of the ...extensive eastward-extrusion of crustal materials from the Tibetan plateau against the rheologically strong crust of the Sichuan Basin. The Longmen Shan range is charac- terized by a Pre-Sinian crystalline complex constrained by the Maoxian-Wenchuan-Kangding ductile detach- ment at the western margin and the Yingxiu-Beichuan- Luding ductile thrust at the eastern margin. The Long- men Shan uplift was initiated by intracontinental sub- duction between the Songpan-Ganzi terrane and the Yangtze block during the Pre-Cenozoic. The uplift rate was increased considerably by the collision between the Indian and Eurasian plates since -50 Ma. The Wenchuan earthquake resulted in two major NE-strik- ing coseismic ruptures （i.e., the -275 km long Yingxiu- Beichuan-Qingchuan fault and the -100 km long Anx- ian-Guanxian fault）. Field investigations combined with focal solutions and seismic reflection profiles suggest that the coseismic ruptures are steeply dipping close-to- pure reverse or right reverse oblique slip faults in the -15 km thick upper crust. These faults are unfavorably oriented for frictional slip in the horizontally compres- sional regime, so that they need a long recurrence interval to accumulate the tectonic stress and fluid pres- sure to critically high levels for the formation of strong earthquakes at a given locality. It is also found that all the large earthquakes （Ms〉7.0） occurred in the fault zones across which the horizontal movement velocities measured by the GPS are markedly low （〈3 mm/yr）. The faults, which constitute the northeastern fronts of the enlarging Tibetan plateau against the strong Sichuan Basin, Ala Shan and Ordos blocks, are very destructive, although their average recurrence intervals are generally long.
Bimetallic Fe-Co/GAC （granular activated carbon） was prepared and used as heterogeneous catalyst in the ultrasound enhanced heterogeneous activation of peroxydisulfate （PS, S2O8 2-） process. The ...effect of initial pH, PS concentration, catalyst addition and stirring rate on the decolorization of Acid Orange 7 （AO7） was investigated. The results showed that the decolorization efficiency increased with an increase in PS concentration from 0.3 to 0.5 g/L and an increase in catalyst amount from 0.5 to 0.8 g/L. But further increase in PS concentration and catalyst addition would result in an unpronounced increase in decolorization efficiency. In the range of 300 to 900 r/min, stirring rate had little effect on AO7 decolorization. The catalyst stability was evaluated by measuring decolorization efficiency for four successive cycles.
Magnetic multi-walled carbon nanotubes were prepared as magnetic solid-phase extraction (MSPE) adsorbent for the enrichment of six heterocyclic pesticides in environmental water samples, including ...imidacloprid, triadimefon, fipronil, flusilazole, chlorfenapyr and fenpyroximate. Then six heterocyclic pesticides were separated and determined by high-performance liquid chromatography-diode-array detector (HPLC-DAD). Major factors influencing MSPE efficiency, including the dose of mag-multi-walled carbon nanotubes (mag-MWCNTs), extraction time, solution pH, salt concentration, type and volume of eluent and desorption time were investigated. Under the optimized conditions, the enrichment factor of the method reached to 250. The linearity was achieved within 0.05-10.0 μg/L for imidacloprid and chlorfenapyr, 0.10-10.0 μg/L for fipronil, flusilazole, triadimefon and fenpyroximate. Limits of detection were in the range of 0.01-0.03 μg/L. Good precision at three spiked levels were 1.1-11.2% (intra-day) and 1.7-11.0% (inter-day) with relative standard deviation of peak area, respectively. The developed method was utilized to analyze tap water, river water and reservoir water samples and recoveries at three spiked concentration levels ranged from 72.2% to 107.5%. The method was proved to be a convenient, rapid and practical method for sensitive determination of heterocyclic pesticides.
Tool wear monitoring is of great significance for the development of manufacturing systems and intelligent manufacturing. Online tool condition monitoring is a crucial technology for cost reduction, ...quality improvement, and manufacturing intelligence in modern manufacturing. However, it remains a difficult problem to monitor the status of tools online, in real-time and accurately in the industry. In the research status of mainstream technology, the convolution neural network may be a good solution to this problem, based on the appropriate sensor system and correct signal processing methods. Therefore, this paper outlines the state-of-the-art systems encountered in the open access literature, focusing on information collection, feature selection–extraction technologies based on deep convolutional neural networks, and monitoring network architecture and modeling methods. Based on typical cases, this paper focuses on the application of the convolution neural network in tool wear monitoring. From the application results, it is feasible and reliable to apply convolution neural networks in tool wear monitoring. Additionally, it can improve the prediction accuracy, which is of great significance for the future development of technology. This paper can be a guide for the researchers and manufacturers in the area of tool wear monitoring for explaining the latest trends and requirements.
There are 9.9 million new cases of dementia in the world every year. Short-term conversion rate from mild cognitive impairment (MCI) to dementia is between 20% and 40%, but long-term in 5–10 years ...ranges from 60% to 100%. It is particularly important to prevent or prolong the development of MCI into dementia. Both auriculotherapy and vagus nerve stimulation are effective on improving cognitive functions. However, there is no double blinded randomized clinical trial to support the effectiveness of transcutaneous electrical stimulation of auricular acupoints in patients with MCI.
This randomized controlled trial involved patients with MCI, aged from 55 to 75 years old. Patients were randomly allocated to transcutaneous auricular vagus nerve stimulation (taVNS) group or sham taVNS group. In the taVNS group, two auricular acupoints were stimulated, including heart (concha, CO15) and kidney (CO10), which are in the distribution of vagus nerve. While in the sham taVNS group, two other auricular acupoints were stimulated, including elbow (scaphoid fossa, SF3) and shoulder (SF4,5), which are out of the distribution of vagus nerve. The primary outcome was the Montreal cognitive assessment-basic, MOCA-B. The secondary outcomes included auditory verbal learning test-HuaShan version (AVLT-H), shape trails test A&B (STT-A&B), animal fluence test (AFT), Boston naming test (BNT), Pittsburgh sleep quality index (PSQI), rapid eye movement sleep behavior disorder screening questionnaire (RBDSQ), Epworth sleepiness scale (ESS) and functional activities questionnaire (FAQ). These outcome measures were taken at baseline, 24 weeks later.
After 24 weeks of intervention, the data of 52 patients were intended for analysis. After intervention, there was significant difference in the overall scores of MoCA-B between taVNS group and sham taVNS group (p = 0.033 < 0.05). In taVNS group, compared with before intervention, the overall scores of MOCA-B increased significantly after intervention (p < 0.001). As for N5 and N7, the two sub-indicators of AVLT-H, in taVNS group, compared with before intervention, both N5 and N7 increased significantly after intervention (both ps < 0.001). As for STTB, in taVNS group, compared with before intervention, STTB was significantly reduced after intervention (p = 0.016). For BNT, in taVNS group, compared with before intervention, BNT increased significantly after intervention (p < 0.001). In taVNS group, compared with before intervention, PSQI, RBDSQ, ESS and FAQ decreased significantly after intervention (p = 0.002, 0.025, <0.001, 0.006 respectively). 1 patient with a history of tympanic membrane perforation in taVNS group was reported with mild adverse reactions which disappeared a week after termination of taVNS. The intervention of taVNS is effective on increasing the overall scores of MoCA-B, N5 and N7.
The clinical trial demonstrated that taVNS can improve cognitive performance in patients with MCI. This inexpensive, effective and innovative method can be recommended as a therapy for more patients with MCI in the prevention or prolonging of its development into dementia, but it is still required to be further investigated.
http://www.chictr.org.cn. (ID: ChiCTR2000038868)
•It is particularly important to prevent or prolong its development of mild cognitive impairment (MCI) into Alzheimer's Disease (AD).•It is the first randomized controlled trial worldwide for taVNS to manage MCI.•Both vagus nerve stimulation and auriculotherapy are effective in improving cognitive functions.•It demonstrates that taVNS can improve cognitive performance in patients with MCI.
Autonomous learning of robotic skills seems to be more natural and more practical than engineered skills, analogous to the learning process of human individuals. Policy gradient methods are a type of ...reinforcement learning technique which have great potential in solving robot skills learning problems. However, policy gradient methods require too many instances of robot online interaction with the environment in order to learn a good policy, which means lower efficiency of the learning process and a higher likelihood of damage to both the robot and the environment. In this paper, we propose a two-phase (imitation phase and practice phase) framework for efficient learning of robot walking skills, in which we pay more attention to the quality of skill learning and sample efficiency at the same time. The training starts with what we call the first stage or the imitation phase of learning, updating the parameters of the policy network in a supervised learning manner. The training set used in the policy network learning is composed of the experienced trajectories output by the iterative linear Gaussian controller. This paper also refers to these trajectories as near-optimal experiences. In the second stage, or the practice phase, the experiences for policy network learning are collected directly from online interactions, and the policy network parameters are updated with model-free reinforcement learning. The experiences from both stages are stored in the weighted replay buffer, and they are arranged in order according to the experience scoring algorithm proposed in this paper. The proposed framework is tested on a biped robot walking task in a MATLAB simulation environment. The results show that the sample efficiency of the proposed framework is much higher than ordinary policy gradient algorithms. The algorithm proposed in this paper achieved the highest cumulative reward, and the robot learned better walking skills autonomously. In addition, the weighted replay buffer method can be made as a general module for other model-free reinforcement learning algorithms. Our framework provides a new way to combine model-based reinforcement learning with model-free reinforcement learning to efficiently update the policy network parameters in the process of robot skills learning.
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