Photo Fenton RAFT Polymerization of (Meth)Acrylates in DMSO Sensitized by Methylene Blue.

A novel open-to-air photo RAFT polymerization of a series of acrylate and methacrylate monomers mediated by matching chain transfer agent irradiated by far-red light in DMSO is reported. Hydroxyl radical (•OH) generated from methylene blue (MB) sensitized decomposition of H O via photo-Fenton like-reaction is used for polymerization initiation. The "living/control" characteristic is evidenced by kinetic study, in which a pseudo first order curve and linearly increases of molecular weight with the increase of monomer conversion are observed.

A multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data.

As an indispensable part of large Computer Numerical Control machine tool, rolling bearing faults diagnosis is particularly important. However, due to the imbalanced distribution and partially missing of collected monitoring data, such diagnostic issue generally emerging in manufacturing industry is still hardly to be solved. Thus, a multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data is formulated in this paper.

Proteolysis modification targeting protein corona affects ultrasound-induced membrane homeostasis of saccharomyces cerevisiae: Analysis of lipid relative contributions on membrane properties.

Introduction: Protein corona (PCN) adsorbed on the surface of nanoparticles has brought new research perspectives for the interaction between nanoparticles and microorganisms. In this study, the responses of ' membrane lipid composition, the average length of the fatty acyl chains and the average number of unsaturation of fatty acids to ultrasound combined with nano-FeO@PCN with time-limited proteolysis (nano-FeO@TLP-PCN) was investigated.

Methods: Lipidomic data was obtained using Ultra-high performance liquid chromatography coupled with a Q-Exactive plus mass spectrometer.

Biomechanical behavior analysis of four types of short implants with different placement depths using the finite element method.

Statement Of Problem: The clinical application of short implants has been increasing. However, studies on the marginal bone loss of short implants are sparse, and clinicians often choose short implants based on their own experience rather than on scientific information.

Purpose: The purpose of this finite element analysis study was to evaluate the microstrain-stress distribution in the peri-implant bone and implant components for 4 types of short implants at different placement depths of platform switching.

Pathways to carbon neutrality: how do government corruption and resource misallocation affect carbon emissions?

The government corruption and resource misallocation are important factors that inhibit economic transformation and environmental governance. Using a study sample of 30 provinces in China, this study employs the spatial econometric methods and threshold model to investigate the relationship between regional corruption, resource misallocation, and CO2 emission. The results show that there is a clear spatial dependence and correlation of CO2 emissions.

Proteolysis Degree of Protein Corona Affect Ultrasound-Induced Sublethal Effects on : Transcriptomics Analysis and Adaptive Regulation of Membrane Homeostasis.

Protein corona (PC) adsorbed on the surface of nanoparticles brings new research perspectives on the interaction between nanoparticles and fermentative microorganisms. Herein, the proteolysis of wheat PC adsorbed on a nano-Se surface using cell-free protease extract from was conducted. The proteolysis caused monotonic changes of ζ-potentials and surface hydrophobicity of PC.

Price competition and blockchain technology adoption strategies of agents on the digital platform.

The rise of digital platforms intensifies the price competition among agents. Agents often use low price strategies to attract consumers. However, the low-price strategy is often filled with false information and consumers perceive the non-truthfulness of the price information.

Railway accident prediction strategy based on ensemble learning.

Railway accident prediction is of great significance for establishing an early warning mechanism and preventing the occurrences of accidents. Safety agencies rely on prediction models to design railroad risk management strategies. Based on historical railway accident data, an ensemble learning strategy for accident prediction is proposed.

A statistical study of railway safety in China and Japan 1990-2020.

Safety is the precondition and guarantee of railway development. However, due to equipment failure, poor management, misoperation and so on, accidents on the railway occur from time to time. China and Japan, as leading countries in Railway Technology in the world, have done a lot of work in accident prevention and safety.

An implant-supported overdenture for a mandibular defect after tumor resection guided by 3-dimensional finite element analysis: A clinical report.

This clinical report describes the rehabilitation of a mandibular defect after tumor resection with an implant-supported overdenture and the attachment selection as guided by 3-dimensional finite element analysis. Autologous bone grafting was declined by the patient who demanded the restoration of lateral appearance and mastication function. Three implants were placed based on the condition of the bone, and a satisfactory definitive prosthesis was provided that corresponded with the results of the finite element analysis.

Multi-model train state estimation based on multi-sensor parallel fusion filtering.

Accurately determining a train's state is essential for passenger safety, operation efficiency, and maintenance. However, the actual operation state of a train is composed of a variety of modes and is disturbed by several known or unknown factors, for which an accurate estimator is required. Hence, in this paper, a train multi-mode model considering the actual operation environment is established, and a train state estimation method based on multi-sensor parallel fusion filter is proposed.

Fault Diagnosis of Brake Train Based on Multi-Sensor Data Fusion.

In this paper, a fault diagnosis method is proposed based on multi-sensor fusion information for a single fault and composite fault of train braking systems. Firstly, the single mass model of the train brake is established based on operating environment. Then, the pre-allocation and linear-weighted summation criterion are proposed to fuse the monitoring data.

Pansharpening of WorldView-2 Data via Graph Regularized Sparse Coding and Adaptive Coupled Dictionary.

The spectral mismatch between a multispectral (MS) image and its corresponding panchromatic (PAN) image affects the pansharpening quality, especially for WorldView-2 data. To handle this problem, a pansharpening method based on graph regularized sparse coding (GRSC) and adaptive coupled dictionary is proposed in this paper. Firstly, the pansharpening process is divided into three tasks according to the degree of correlation among the MS and PAN channels and the relative spectral response of WorldView-2 sensor.

Theacrine, a Potent Antidepressant Purine Alkaloid from a Special Chinese Tea, Promotes Adult Hippocampal Neurogenesis in Stressed Mice.

Daily intake of tea has been known to relate to a low risk of depression. In this study, we report that a special variety of tea in China, var. (), possesses antidepressant effects but with less adverse effects as compared to traditional tea .

Computational Methods and Online Resources for Identification of piRNA-Related Molecules.

piRNAs are a class of small non-coding RNA molecules, which interact with the PIWI family and have many important and diverse biological functions. The present review is aimed to provide guidelines and contribute to piRNA research. We focused on the four types of identification models on piRNA-related molecules, including piRNA, piRNA cluster, piRNA target, and disease-related piRNA.

An efficient and global interactive optimization methodology for path planning with multiple routing constraints.

Path planning problem is attracting wide attention in autonomous system and process industry system. The existed research mainly focuses on finding the shortest path from the source vertex to the termination vertex under loose constraints of vertex and edge. However, in realistic, the constraints such as specified vertexes, specified paths, forbidden paths and forbidden vertexes have to be considered, which makes the existing algorithms inefficient even infeasible.

Early warning model for passenger disturbance due to flight delays.

Disruptive behavior by passengers delayed at airport terminals not only affects personal safety but also reduces civil aviation efficiency and passenger satisfaction. This study investigated the causal mechanisms of disruptive behavior by delayed passengers in three aspects: environmental, managerial, and personal. Data on flight delays at Shenzhen Airport in 2018 were collected and analyzed.

Identification and characterization of N9-methyltransferase involved in converting caffeine into non-stimulatory theacrine in tea.

Caffeine is a major component of xanthine alkaloids and commonly consumed in many popular beverages. Due to its occasional side effects, reduction of caffeine in a natural way is of great importance and economic significance. Recent studies reveal that caffeine can be converted into non-stimulatory theacrine in the rare tea plant Camellia assamica var.

The joint effect of ultrasound and magnetic FeO nanoparticles on the yield of 2,6-dimethoxy-ρ-benzoquinone from fermented wheat germ: Comparison of evolutionary algorithms and interactive analysis of paired-factors.

2,6-Dimethoxy-ρ-benzoquinone (DMBQ) is a potential anti-tumor substance found in the fermented wheat germ. In this study, ultrasound and FeO nanoparticles were used to improve the DMBQ yield. An artificial neural network (ANN) embedded separately with the back-propagation algorithm (BP), genetic algorithm (GA), particle swarm optimized algorithm (PSO), ant colony optimized algorithm (ACO), GA-ACO, GA-PSO and PSO-ACO, were used to establish the relationship between 11 factors and DMBQ yield.

Delivery of plasmid DNA to shrimp hemocytes by Infectious hypodermal and hematopoietic necrosis virus (IHHNV) nanoparticles expressed from a baculovirus insect cell system.

Virus-like particles (VLPs) are potential containers for delivery of therapeutic agents at the nanoscale. In this study, the capsid protein of Infectious hypodermal and hematopoietic necrosis virus (IHHNV) was expressed in a baculovirus insect cell system. The 37-kDa recombinant protein containing the hexahistidine residues (His Tag) at N-terminal was purified using immobilized metal affinity chromatography (IMAC) and assembled into VLPs with a diameter of 23 ± 3 nm analyzed by transmission electron microscopy.

Deep model integrated with data correlation analysis for multiple intermittent faults diagnosis.

Currently, single fault diagnosis has received mass concern, and the related research achievements are remarkable. However, because of the mutual interaction of subsystems and the coupling of faults characteristics, the diagnosis of multiple intermittent faults commonly existing in industrial systems is still an intractable problem. In order to solve the problem, an improved Constrained Sparse Autoencoder integrated with Correlation Analysis (CA-CSAE) is proposed, further, a diagnosis scheme for multiple intermittent faults is formulated in this paper.

Strategy for Fault Diagnosis on Train Plug Doors Using Audio Sensors.

As the only entry/exit for passengers getting on and off a train, the train plug door is of great importance to keep train operation safe and reliable. As signal processing technologies develop rapidly, taking the easy acquisition advantages of sound signals, a novel fault diagnosis method for train plug doors using multi-scale normalized permutation entropy (MNPE) and an improved particle swarm optimization based multi-class support vector machine (IPSO-MSVM) is proposed. Firstly, sound samples are collected using high-precision audio sensor.