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Nucleic acid methylations are important genetic and epigenetic biomarkers. The formation and removal of these markers is related to either methylation or demethylation. In this review, we focus on the demethylation or oxidative modification that is mediated by the 2-oxoglutarate (2-OG)/Fe(II)-dependent AlkB/TET family enzymes. In the catalytic process, most enzymes oxidize 2-OG to succinate, in the meantime oxidizing methyl to hydroxymethyl, leaving formaldehyde and generating demethylated base. The AlkB enzyme from Escherichia coli has nine human homologs (ALKBH1-8 and FTO) and the TET family includes three members, TET1 to 3. Among them, some enzymes have been carefully studied, but for certain enzymes, few studies have been carried out. This review focuses on the kinetic properties of those 2-OG/Fe(II)-dependent enzymes and their alkyl substrates. We also provide some discussions on the future directions of this field.

As a power output unit, Induction Motor (IM) is widely used in Electric Vehicles (EV) due to its unique advantages of higher power density and better torque ability. With more complicated motor controller system, there are some hardware and software failures which bring some risks including EV unexpected acceleration or deceleration, therefore it is necessary to build high-accuracy torque estimation and safety control strategy. Firstly, hazard and safety concept are analyzed to make sure function safety goals and levels for IM system. Secondly, a novel method of high-accuracy torque estimation is proposed based on a rotor dynamic and composite flux linkage observer. Then, fault diagnosis and handling mechanisms of motor torque are designed to avoid hazards when it is a significant difference between motor estimation torque and vehicle requested torque. Finally, power test and Hardware in Loop (HIL) bench are configured to verify torque estimation accuracy and fault protection mechanisms rationality by comparing test results and injecting related faults. Experiment result shows that motor torque accuracy is within ±5 Nm and fault protection mechanisms can bring motor to safety state promptly.

In order to characterize the quality characteristics of three varieties of mango (Tainong, Xiangya and Jinhuang), the main quality indexes of mango was determined and a comprehensive scoring model of main quality of mango was established by principal component analysis (PCA). The volatile flavor compounds of mango were analyzed by HS-SPME-GC-MS technology, and its quality and processing characteristics were evaluated comprehensively. The results showed that the content of soluble solids, total sugar and sugar acid ratio of Jinhuang were the highest, which were 19%, 24.18 mg/g and 10.86 respectively; The contents of VC and total phenol in Tainong were the highest, which were 9.52 mg/100 g and 1.03 mg/g respectively; The results of PCA analysis showed that the comprehensive score of Tainong was the highest, indicating that its comprehensive quality was the best, followed by Jinhuang, and the comprehensive score of Xiangya was the lowest. A total of 116 volatile compounds were detected from three mangoes by HS-SPME-GC-MS, mainly including olefins, phenols and aldehydes. The volatile compounds of Tainong and Xiangya were mainly olefins, with relative contents of 45.52% and 58.12% respectively. The volatile compounds of Jinhuang were mainly phenols, with relative contents of 56.88%. Fifteen key flavor compounds were identified from three mango varieties by the analysis of relative activity value (ROAV). Among them, (E,Z)-2,6-nonadienal contributed the most to the aroma in Tainong and Xiangya, 3-hexenal contributed the most to the aroma in Jinhuang; Tainong had citrus and sweet aroma, Xiangya had cucumber flavor, and Jinhuang had special wood flavor, which was mainly contributed by 2,4-di-tert-butylphenol. Comprehensive analysis showed that Tainong and Xiangya were suitable for deep processing, while Jinhuang was more suitable for fresh food.

Abstract Background The study looks at a changed in consumer’s eating and purchasing habits during COVID-19 period. There are several modes of transmission but transmission through food as being speculated is one area that has not been confirmed through research. The study, therefore, looks at how speculations about COVID-19 spreading through food has affected consumers' eating and purchasing habits. This study through probit model analysed how consumers' eating and purchasing habits have been influenced. Results The result shows that age, gender and education have negatively influenced consumer’s eating and purchasing habits during the COVID-19 pandemic compared to pre-pandemic period. The preference for imported food items, preference for frozen food, been infected or knowing someone who has been infected by the virus, and been infected through agricultural source or knowing someone who has been infected by the COVID-19 through agricultural source have negatively affected consumers' eating and purchasing habits compared to pre-pandemic period. The result, however, suggests that consumers who trust in the cold-chain food systems ability to limit the spread of the COVID-19 still maintain a positive eating and purchasing habits. Conclusions The study provides evidence on the impact of COVID-19 on consumer’s eating and purchasing habits. Therefore, there is the need to institute proper sanitary measures, especially at cold-chain food systems to help curb the spread and also boost consumers’ confidence.

This study aims to determine the sources of indoor particulate matter at the Potala Palace Museum in Tibet, China, and evaluate the potential hazards of these pollutants for cultural relics. Long-term monitoring of indoor and outdoor suspended particulate matter concentrations was conducted, and sediment particle samples were collected. The chemical composition of the deposited particles was determined using X-ray fluorescence analysis (XRF). The outdoor suspended particulate concentration was much lower than that indoors; the indoor PM1-10 concentration was much higher than that outdoors and was less affected by outdoor sources. The sources of indoor deposited particles in the high-plateau museum can be classified into four categories: soil dust brought in by tourists from the outdoors, incense ash, pollution from human activities, and ores. Based on data analysis and discussion, proper ventilation can dilute indoor suspended particulate matter, and the installation of air conditioning systems can control temperature and humidity at 20 °C and about 45–60%, respectively, and reduce the fluctuation value, so as to promote particle deposition and better protect the museum’s cultural relics.

Motor as well as its controller plays an important role in driving electric vehicle. As sole power device, it is closely related with actual torque accuracy to make sure security during EV driving. Due to complex controlling system for motor, there are some random failures of hardware and software which can bring a series of unexpected risks for EV acceleration or deceleration. A novel method based on motor parameters feature is proposed to estimate motor torque based on parameters feature extraction for three-phase of volts and currents. Additionally, Quality Factor ( QF ) and confidence coefficient are also adopted to judge whether motor estimation torque is reasonable or not and motor failure torque is limited to be output by setting fault flag in controller software. Finally, test bench is built to analyze torque accuracy compared with actual test value and verify security control strategy at failure modes, test results show that estimation torque accuracy is within ±5 Nm which is compared with actual test torque and motor system can effectively come into security state from failure state by security control strategy which is proposed in this paper.

The study looks at the factors that influence vegetable farmers' compliance to pesticide application guidelines and regulation. Compliance is measured by looking at whether vegetable farmers follow pesticide use regulations and guidelines or otherwise. To help achieve this objective, vegetable growing communities in Yunnan province were purposively selected for the study. Six hundred and thirty-two (632) vegetable farmers were selected through a systematic random sampling technique. The result shows that the number of years spent in schooling, quality driven motives, commercial oriented production, knowledge and experience in pesticide application, government supervision and extension support have positive statistical significance on compliance to pesticide guidelines and regulations. The result, however, reveals that vegetable farmers driven by quantity are less likely to comply with the pesticide use guidelines and regulations. The interactive effect of quantity and quality driven motives shows a positive significant effect on compliance. Programs and projects geared towards sensitizing farmers especially, vegetable farmers on correct usage of pesticide should be of concern to policy makers.Here we show for the first that interaction between quantity driven motive and quality driven motive has a positive effect on compliance with pesticide use guidelines and regulations.

According to the United Nations (UN), about 70% of the world’s population projected to live in urban areas by 2050. Therefore, cities are experiencing an enormous urban transition the world has ever seen, accounting for 80% of global carbon dioxide emissions, consuming over two-thirds of the world’s energy, and producing 1.3 billion tons of waste per year. Leaders, governments, architects, urban designers, developers, planners and business leaders need to make decisions and find solutions for how billions of urbanites will live in the future. Therefore, future cities will require new design principles to face their urban challenges and problems such as pollution, poverty, poor environment, land use management, green-house gas emissions and socio-economic and environmental risks. In this context, the case study area of this paper will be El Raval district, which is in a medieval quarter of Barcelona. This area considered as one of the oldest and a significant part of the city that contains many heritage buildings and unique traditional urban context going back to hundreds of years. The district has an influx of immigrants, which has transformed its label from an industrial neighbourhood into a residential one and low rents that have attracted many people of low income, making it a vibrant and multicultural community. Therefore, the main aim of this paper is to address the implementation of innovative solutions, advanced technologies, ICT and IoT that might enhance people participation in the urban design processes and respond to urban futures challenges. The result of this research will lead to creating a platform to resolve the conflicting values of architectural heritage and smart cities principles, sourcing new sustainable technologies and the integration of the smart infrastructure systems.DOI: https://doi.org/10.20365/disegnarecon.23.2019.14

The actual power capacity of permanent magnet synchronous machine for electric vehicles is usually limited by rotor temperature, and rotor overheating is one of the major reasons for permanent magnet synchronous machine failure. Therefore, an approach of rotor temperature estimation is proposed to improve motor peak power utilization and protect permanent magnet synchronous machine from serious demagnetization due to thermal damage. A real-time iterative algorithm is provided based on the equivalent thermal model for rotor temperature. First, the heat generating principle of each part as well as the power flow transferring of the motor system is analyzed. Second, rotor temperature model is built based on the conservation of energy loss from the stator and real-time superposition of temperature variation rate for the rotor. Finally, the motor performance test bench is built to validate the proposed algorithm and numerical models are also constructed to simplify estimation parameters for rotor temperature model. The algorithm accuracy is improved and verified by optimizing control parameters with given environment temperature and power load. The experimental result shows that the maximum error between actual test value and estimation value is within ±10°C, and it meets the requirement of algorithm accuracy and also benefits on system performance and manufacture cost efficiently.