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Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.

The voltage level of a coal mine power grid directly affects the starting and normal operation of the electric motor, but the current grid monitoring system cannot use real-time grid structure parameters and power flow distribution data to conduct early warning research on the running status and voltage level of the power grid, so it cannot eliminate hidden danger in the operation of the power grid. Therefore, it is necessary to accurately and effectively evaluate the voltage safety level of the coal mine power grid. In this paper, an improved AHP-FCE method is proposed to evaluate the voltage safety level of a coal mine power grid. By replacing the comparison judgment matrix with the interval judgment matrix, the objectivity of the weight vector is improved while retaining expert subjectivity. According to the real-time power flow distribution data of the power grid monitoring system, the current voltage safety level of the power grid is evaluated. The results show that the improved AHP-FCE method can accurately evaluate the current grid voltage level, analyze the voltage development trend, give early warnings regarding coal mine grid voltage operation, and improve the monitoring function of the power monitoring system.

As a result of population growth, an emerging middle-class, and a more health-conscious society concerned with overconsumption of fats and carbohydrates, dietary protein intake is on the rise. To address this rapid change in the food market, and the subsequent high demand for protein products, agriculture, aquaculture, and the food industry have been working actively in recent years to increase protein product output from both production and processing aspects. Dietary proteins derived from animal sources are of the highest quality, containing well-balanced profiles of essential amino acids that generally exceed those of other food sources. However, as a result of studies highlighting low production efficiency (e.g., feed to food conversion) and significant environmental impacts, together with the negative health impacts associated with the dietary intake of some animal products, especially red meats, the consumption of animal proteins has been remaining steady or even declining over the past few decades. To fill this gap, researchers and product development specialists at all levels have been working closely to discover new sources of protein, such as plant-based ingredients. In this regard, microalgae have been recognized as strategic crops, which, due to their vast biological diversity, have distinctive phenotypic traits and interactions with the environment in the production of biomass and protein, offering possibilities of production of large quantities of microalgal protein through manipulating growing systems and conditions and bioengineering technologies. Despite this, microalgae remain underexploited crops and research into their nutritional values and health benefits is in its infancy. In fact, only a small handful of microalgal species are being produced at a commercial scale for use as human food or protein supplements. This review is intended to provide an overview on microalgal protein content, its impact by environmental factors, its protein quality, and its associated evaluation methods. We also attempt to present the current challenges and future research directions, with a hope to enhance the research, product development, and commercialization, and ultimately meet the rapidly increasing market demand for high-quality protein products.

Background: Previous studies demonstrated a significant association between the albumin–globulin ratio (AGR) and various types of cancers. The aim of this study was to evaluate the prognostic value of preoperative AGR in patients with early-stage non-small cell lung cancer (NSCLC). Methods: Patients diagnosed as NSCLC in a single center between January 1, 2014 and February 29, 2016 were retrospectively reviewed. AGR was defined as the ratio between the serum albumin level and the serum globulin level. Receiver operating characteristics analysis was performed to determine optimal cutoff values. Overall survival (OS) and disease-free survival (DFS) were clinical outcomes of our study. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors, and the Kaplan–Meier method was used to estimate survival curves. Results: A total of 279 early stage NSCLC patients were enrolled in our study with the median follow-up of 39 months (range 1–56 months). The statistical analyses manifested that the age (hazard ratio (HR)=1.045, 95% confidence interval (95% CI): 1.010–1.081, P=0.011) and AGR

Multiple signal classification (MUSIC) algorithm is a promising method in guided wave based structural health monitoring (SHM) area because of its directional scanning ability and easy arrangement of the sensor array. However, since composite structures are anisotropic , guided waves have different velocities along different directions, i.e. propagation anisotropy. For different scanning positions of the monitoring area in MUSIC algorithm, the directions from the scanning position to the sensor array are different. Even for the same scanning position, the directions from the scanning position to each element in the sensor array are also different. If a fixed velocity is used in MUSIC algorithm, there must exist sensor phase errors in steering vectors of MUSIC algorithm caused by structural anisotropy, as well as the sensor position error, resulting in the localization error . To reduce the localization error caused by sensor phase errors, an anisotropy compensated MUSIC algorithm is proposed, which could compensate different kinds of sensor phase errors jointly and improve the localization precision and reliability of MUSIC algorithm. The proposed method is verified on a reinforced composite panel with one T-stiffener. Experimental results show that the proposed method can realize damage localization with an obviously improved accuracy.