Remote sensing and social sensing data reveal scale-dependent and system-specific strengths of urban heat island determinants

Urban natural surfaces and non-surface human activities are key factors determining the urban heat island (UHI), but their relative importance remains highly controversial and may vary at different spatial scales and focal urban systems. However, systematic studies on the scale-dependency system-specificity remain largely lacking. Here, we selected 32 major Chinese cities as cases and used Landsat 8 images to retrieve land surface temperature (LST) and quantify natural surface variables using point of interest (POI) data as a measure of the human activity variable and using multiple regression and relative weight analysis to study the contribution and relative importance of these factors to LST at a range of grain sizes (0.25–5 km) and spatial extents (20–60 km). We revealed that the contributions and relative importance of natural surfaces and human activities are largely scale-dependent and system-specific. Natural surfaces, especially vegetation cover, are often the most important UHI determinants for a majority of scales, but the importance of non-surface human activities is increasingly pronounced at a coarser spatial scale with respect to both grain and spatial extent. The scaling relations of the UHI determinants and their relative importance were mostly linear-like at the city-collective level, but highly diverse across individual cities, so reducing non-surface heat emissions could be the most effective measure in particular cases, especially at relatively large spatial scales. This study advances the understanding of UHI formation mechanisms and highlights the complexity of the scale issue underpinning the UHI effect

Metal Emulsion-Based Synthesis, Characterization, and Properties of Sn-Based Microsphere Phase Change Materials

A comparative study of the metal emulsion-based synthesis of Sn-based materials in two different types of molten salts (namely LiCl–KCl–CsCl and LiNO3-NaNO3-KNO3 eutectics) is presented, and the properties of Sn, Sn-Cu and Sn-Cu-Zn microsphere phase change materials prepared in chloride salts are evaluated by differential scanning calorimetry (DSC) to understand the effect of element doping. Despite a high ultrasonic power (e.g., 600 W or above) being required for dispersing liquid Sn in the chloride system, well-shaped Sn microspheres with a relatively narrow size range, e.g., about 1 to 15 µm or several micrometers to around 30 µm, can be prepared by adjusting the ultrasonic power (840–1080 W), sonication time (5–10 min) and the volume ratio of salts to metal (25:1–200:1). Such a method can be extended to the synthesis of Sn-based alloy microspheres, e.g., Sn-Cu and Sn-Cu-Zn microspheres. In the nitrate system, however, a very low ultrasonic power (e.g., 12 W) can be used to disperse liquid Sn, and the particles obtained are much smaller. At low ultrasonic power (e.g., 12 W), the particle size is generally less than 10 or 4 µm when the sonication time reaches 2 or 5 min, and at high ultrasonic power, it is typically in the range of hundreds of nanometers to 2 µm, regardless of the change in ultrasonic power (480–1080 W), irradiation time (5–10 min), or volume ratio of salts to metal (25:1–1000:1). In addition, the appearance of a SnO phase in the products prepared under different conditions hints at the occurrence of a reaction between Sn droplets and O2 in situ generated by the ultrasound-induced decomposition of nitrates, and such an interfacial reaction is believed to be responsible for these differences observed in two different molten salt systems. A DSC study of Sn, Sn-Cu, and Sn-Cu-Zn microspheres encapsulated in SiO2 reveals that Cu (0.3–0.9 wt.%) or Cu-Zn (0.9 wt.% Cu and 0.6% Zn) doping can raise the onset freezing temperature and thus suppress the undercooling of Sn, but a broad freezing peak observed in these doped microspheres, along with a still much higher undercooling compared to those of reported Sn-Cu or Sn-Cu-Zn solders, suggests the existence of a size effect, and that a low temperature is still needed for totally releasing latent heat. Since the chloride salts can be recycled by means of the evaporation of water and are stable at high temperature, our results indicate that the LiCl–KCl–CsCl salt-based metal emulsion method might also serve as an environmentally friendly method for the synthesis of other metals and their alloy microspheres

Undercooling, Thermal Stability, and Application in Exothermic Catalytic Reaction of SiO₂ Encapsulated SnZnCu Microspheres

SiO2 encapsulated SnZnCu microspheres (several micrometers to about 30 μm in diameter) with very low undercooling, narrow freezing/melting range, and high thermal cycling stability have been produced and used as the temperature stabilizer of the packed bed in highly exothermic Fischer–Tropsch reaction. The core–shell structured SnZnCu@SiO2 microspheres are prepared in a two-step way, namely SnZnCu microspheres are firstly produced via a molten LiCl–KCl–CsCl eutectic-based metal emulsion method, and then a sol–gel approach is employed to coat them with a uniform, anti-leakage SiO2 layer. It is found that raising the amount of Zn to 4.0 at.% is critical for achieving a very low undercooling (0.04Cux@SiO2 vs. about 84 °C for Sn@SiO2) and a narrow freezing/melting peak width, and both undercooling and peak width are almost unchanged as the Cu content (x) increases from 1.5 to 3.0 at.%. However, their thermal cycling stability depends positively on the amount of Cu and can be remarkably improved when 3.0 at.% Cu is added. The results also show that low undercooling and narrow freezing/melting peak width are associated with the formation of Sn–Zn–Cu ternary eutectic and metastable phase Cu5Zn8, and poor thermal cycling stability of SnZn0.04Cux@SiO2 microspheres with low Cu content is related to the decomposition of Cu5Zn8 during thermal cycling. By embedding thermally stable SnZn0.04Cu0.03@SiO2 microspheres into the Co/SiO2 catalyst for Fischer–Tropsch synthesis, the temperature gradient in the catalyst bed can be significantly reduced by suppressing the formation of hot spots or thermal runaway and thus rapid deactivation of Co catalyst that occurs in the SnZn0.04Cux@SiO2-absent Co/SiO2 catalyst can be avoided

Improved Feature Learning: A Maximum-Average-Out Deep Neural Network for the Game Go

Computer game-playing programs based on deep reinforcement learning have surpassed the performance of even the best human players. However, the huge analysis space of such neural networks and their numerous parameters require extensive computing power. Hence, in this study, we aimed to increase the network learning efficiency by modifying the neural network structure, which should reduce the number of learning iterations and the required computing power. A convolutional neural network with a maximum-average-out (MAO) unit structure based on piecewise function thinking is proposed, through which features can be effectively learned and the expression ability of hidden layer features can be enhanced. To verify the performance of the MAO structure, we compared it with the ResNet18 network by applying them both to the framework of AlphaGo Zero, which was developed for playing the game Go. The two network structures were trained from scratch using a low-cost server environment. MAO unit won eight out of ten games against the ResNet18 network. The superior performance of the MAO unit compared with the ResNet18 network is significant for the further development of game algorithms that require less computing power than those currently in use

IEEE Access Special Section: Security Analytics and Intelligence for Cyber Physical Systems

A Cyber Physical System (CPS) is a smart network system with actuators, embedded sensors, and processors to interact with the physical world by guaranteeing the performance and supporting real-time operations of safety critical applications. These systems drive innovation and are a source of competitive advantage in today's challenging world. By observing the behavior of physical processes and activating actions, CPS can alter its behavior to make the physical environment perform better and more accurately. By definition, CPS basically has two major components including cyber systems and physical processes. Examples of CPS include autonomous transportation systems, robotics systems, medical monitoring, automatic pilot avionics, and smart grids. Advances in CPS will empower scalability, capability, usability, and adaptability, which will go beyond the simple systems of today. At the same time, CPS has also increased cybersecurity risks and attack surfaces. Cyber attackers can harm such systems from multiple sources while hiding their identities. As a result of sophisticated threat matrices, insufficient knowledge about threat patterns, and industrial network automation, CPS has become extremely insecure. Since such infrastructure is networked, attacks can be prompted easily without much human participation from remote locations, thereby making CPS more vulnerable to sophisticated cyber-attacks. In turn, large-scale data centers managing a huge volume of CPS data become vulnerable to cyber-attacks. To secure CPS, the role of security analytics and intelligence is significant. It brings together huge amounts of data to create threat patterns, which can be used to prevent cyber-attacks in a timely fashion. The primary objective of this Special Section in IEEE A CCESS is to collect a complementary and diverse set of articles, which demonstrate up-to-date information and innovative developments in the domain of security analytics and intelligence for CPS.Non peer reviewe

Decoupling of soil carbon mineralization and microbial community composition across a climate gradient on the Tibetan Plateau

Soil microbes drive soil organic carbon (SOC) mineralization. Because microbial groups differ in metabolic efficiency and respond differently to temperature variation, it is reasonable to expect a close association of SOC mineralization and its temperature sensitivity (Q10 which is defined as the factor of the change of soil carbon mineralization induced by 10 °C temperature increase) with microbial community diversity and composition. However, these relations have rarely been tested. Here, we conducted an incubation experiment to assess the temperature responses of microbial α diversity and the relative abundance of microbial r- and K-strategists in soils from a wide range of ecosystems across a climate gradient in the southeast Tibet. The results indicated that the instantaneous α diversity and the relative abundance of r- and K-strategists are significantly (P < 0.05) influenced by temperature, but these microbial variables are poor predictors of SOC mineralization measured at the same time. Rather, microbial community diversity and the relative abundance of r- and K-strategists of fresh soils showed consistent and significant (P < 0.05) effects on both SOC mineralization and Q10 at different incubation stages. Importantly, path analysis indicated that microbial α diversity and r- and K-strategists exerts no independent effects on SOC mineralization and Q10 when variation in climate, SOC chemistry, physical protection, and edaphic properties are accounted for. Together, our results suggest that while soil microbial community diversity and composition are a strong proxy of SOC quality and availability, they are not a fundamental determinant of SOC mineralization and Q10

Additional file 1 of Undetectable off-target effects induced by FokI catalytic domain in mouse embryos

Additional file 1. Supplementary figures S1-S11 and tables S1-S4