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Abstract:The effect of urbanization on the urban thermal environment (UTE) has attracted increasing research attention for its significant relationship to local climatic change and habitat comfort. Using quantitative thermal remote sensing and spatial statistics methods, here we analyze four Landsat TM/ETM+ images of Guangzhou in South China acquired respectively on 13 October 1990, 2 January 2000, 23 November 2005, and 2 January 2009, to investigate the spatiotemporal variations in the land surface temperature (LST) over five land use/land cover (LULC) types and over different urban/rural zones. The emphases of this study are placed on the urban heat island (UHI) intensity and the relationships among LST, the normalized difference built-up index (NDBI), and the normalized difference vegetation index (NDVI). Results show that: (1) the UHI effect existed obviously over the period from 1990 to 2009 and high temperature anomalies were closely associated with built-up land and densely populated and heavily industrialized districts; (2) the UHI intensities represented by the mean LST difference between the urban OPEN ACCESSRemote Sens. 2012, 4 2034 downtown area and the suburban area were on average 0.88, 0.49, 0.90 and 1.16 K on the four dates, at the 99.99% confidence level; and (3) LST is related positively with NDBI and negatively with NDVI. The spatiotemporal variation of UTE of Guangzhou could be attributed to rapid urbanization, especially to the expanding built-up and developing land, declining vegetation coverage, and strengthening of anthropogenic and industrial activities which generate increasing amounts of waste heat. This study provides useful information for understanding the local climatic and environment changes that occur during rapid urbanization.

The coronavirus disease 2019 (COVID-19) epidemic has had a crucial influence on people’s lives and socio-economic development. An understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic on multiple scales could benefit the control of the outbreak. Therefore, we used spatial autocorrelation and Spearman’s rank correlation methods to investigate these two topics, respectively. The COVID-19 epidemic data reported publicly and relevant open data in Hubei province were analyzed. The results showed that (1) at both prefecture and county levels, the global spatial autocorrelation was extremely significant for the cumulative confirmed COVID-19 cases (CCC) in Hubei province from 30 January to 18 February 2020. Further, (2) at both levels, the significant hotspots and cluster/outlier areas were observed solely in Wuhan city and most of its districts/sub-cities from 30 January to 18 February 2020. (3) At the prefecture level in Hubei province, the number of CCC had a positive and extremely significant correlation (p < 0.01) with the registered population (RGP), resident population (RSP), Baidu migration index (BMI), regional gross domestic production (GDP), and total retail sales of consumer goods (TRS), respectively, from 29 January to 18 February 2020 and had a negative and significant correlation (p < 0.05) with minimum elevation (MINE) from 2 February to 18 February 2020, but no association with the land area (LA), population density (PD), maximum elevation (MAXE), mean elevation (MNE), and range of elevation (RAE) from 23 January to 18 February 2020. (4) At the county level, the number of CCC in Hubei province had a positive and extremely significant correlation (p < 0.01) with PD, RGP, RSP, GDP, and TRS, respectively, from 27 January to 18 February 2020, and was negatively associated with MINE, MAXE, MNE, and RAE, respectively, from 26 January to 18 February 2020, and negatively associated with LA from 30 January to 18 February 2020. It suggested that (1) the COVID-19 epidemics at both levels in Hubei province had evident characteristics of significant global spatial autocorrelations and significant centralized high-risk outbreaks. (2) The COVID-19 epidemics were significantly associated with the natural factors, such as LA, MAXE, MNE, and RAE, -only at the county level, not at the prefecture level, from 2 February to 18 February 2020. (3) The COVID-19 epidemics were significantly related to the socioeconomic factors, such as RGP, RSP, TRS, and GDP, at both levels from 26 January to 18 February 2020. It is desired that this study enrich our understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic and benefit classified prevention and control of the COVID-19 epidemic for policymakers.

Silver telluride nanowires have been synthesized by the composite-hydroxide-mediated (CHM) method at temperatures of 180−225 °C. The products were single-crystalline nanowires and monoclinic phase Ag2Te with a high purity. The reversible structural phase transition from monoclinic structure (β-Ag2Te) to face-centered cubic structure (α-Ag2Te) around 148/133 °C was observed during the heating/cooling process. The latent heat of the phase transition was calculated. The electrical resistance and thermal emf versus temperature were for the first time investigated on the Ag2Te nanowires. Abrupt changes of conductivity and Seebeck coefficient around the phase transition temperature were observed. The maximum Seebeck coefficient is ∼170 and ∼160 μV K−1 during the heating and cooling process, respectively, indicating a promising one-dimensional thermoelectric material as a building block to construct nanodevices.

Based on the 1960-2009 meteorological data from 559 stations across China, the urbanization effect on the diurnal temperature range (DTR) was evaluated in this study. Different roles of urbanization were specially detected under solar dimming and solar brightening. During the solar dimming time, both urban and rural stations showed decreasing trends in maximum temperature (T max ) because of decreased radiation, suggesting that the dimming effects are not only evident in urban areas but also in rural areas. However, minimum temperature (T min ) increased more substantially in urban areas than in rural areas during the dimming period, resulting in a greater decrease in the DTR in the urban areas. When the radiation reversed from dimming to brightening, the change in the DTR became different. The T max increased faster in rural areas, suggesting that the brightening could be much stronger in rural areas than in urban areas. Similar trends of T min between urban and rural areas appeared during the brightening period. The urban DTR continued to show a decreasing trend because of the urbanization effect, while the rural DTR presented an increasing trend. The remarkable DTR difference in the urban and rural areas showed a significant urbanization effect in the solar brightening time.

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Highly sensitive and stretchable strain sensors have attracted considerable attention due to their promising applications in human motion detection, soft robot, wearable electronics, etc. However, there is still a trade-off between high sensitivity and high stretchability. Here, we reported a stretchable strain sensor by sandwiching reduced graphene oxide (RGO)-coated polystyrene microspheres (PS@RGO) and silver nanowires (AgNWs) conductive hybrids in an elastic polydimethylsiloxane (PDMS) matrix. Due to the synergistic effect of PS@RGO and AgNWs, the PDMS/PS@RGO/ AgNWs/PDMS sensor exhibits a high initial electrical conductivity of 8791 S m −1 , wide working range of 0−230%, large gauge factor of 11 at 0−60% of strain and 47 at 100%−230% of strain with a high linear coefficient of 0.9594 and 0.9947, respectively, low limit of detection (LOD) of 1% of strain, and excellent long-term stability over 1000 stretching/releasing cycles under 50% strain. Furthermore, the strain sensor has been demonstrated in detecting human body motion and fan rotation with high stretchability and stability, showing potential application in intelligent robot and Internet of things.