Energy-effective offloading scheme in UAV-assisted C-RAN system

In this paper, we aim to minimize the total power of all the Internet of Things devices (IoTDs) by jointly optimizing user association, computation capacity, transmit power, and the location of unmanned aerial vehicles (UAVs) in an UAV-assisted cloud radio access network (C-RAN). In order to solve this non-convex problem, we propose an effective algorithm by solving four subproblems iteratively. For the user association and the computation capacity subproblems, the non-convex constraints are relaxed and the optimal solutions are obtained. For the transmit power control and the location planning subproblems, successive convex approximation (SCA) technique is used to transform the non-convex constraints into convex ones. Moreover, to obtain the suboptimal solutions, slack variables are also introduced to deal with the feasibility-check problems. The simulation results demonstrate that the proposed algorithm can greatly reduce the total power consumption of IoTDs

Vertical Interface Induced Dielectric Relaxation in Nanocomposite (BaTiO3)1-x:(Sm2O3)x Thin Films

Vertical interfaces in vertically aligned nanocomposite thin films have been approved to be an effective method to manipulate functionalities. However, several challenges with regard to the understanding on the physical process underlying the manipulation still remain. In this work, because of the ordered interfaces and large interfacial area, heteroepitaxial (BaTiO(3))(1-x):(Sm(2)O(3))(x) thin films have been fabricated and used as a model system to investigate the relationship between vertical interfaces and dielectric properties. Due to a relatively large strain generated at the interfaces, vertical interfaces between BaTiO(3) and Sm(2)O(3) are revealed to become the sinks to attract oxygen vacancies. The movement of oxygen vacancies is confined at the interfaces and hampered by the misfit dislocations, which contributed to a relaxation behavior in (BaTiO(3))(1-x):(Sm(2)O(3))(x) thin films. This work represents an approach to further understand that how interfaces influence on dielectric properties in oxide thin films

Face mask integrated with flexible and wearable manganite oxide respiration sensor

Face masks are key personal protective equipment for reducing exposure to viruses and other environmental hazards such as air pollution. Integrating flexible and wearable sensors into face masks can provide valuable insights into personal and public health. The advantages that a breath-monitoring face mask requires, including multi-functional sensing ability and continuous, long-term dynamic breathing process monitoring, have been underdeveloped to date. Here, we design an effective human breath monitoring face mask based on a flexible La0.7Sr0.3MnO3 (LSMO)/Mica respiration sensor. The sensor’s capabilities and systematic measurements are investigated under two application scenes, namely clinical monitoring mode and daily monitoring mode, to monitor, recognise, and analyse different human breath status, i.e., cough, normal breath, and deep breath. This sensing system exhibits super-stability and multi-modal capabilities in continuous and long-time monitoring of the human breath. We determine that during monitoring human breath, thermal diffusion in LSMO is responsible for the change of resistance in flexible LSMO/Mica sensor. Both simulated and experimental results demonstrate good discernibility of the flexible LSMO/Mica sensor operating at different breath status. Our work opens a route for the design of novel flexible and wearable electronic devices

Formulating and Performance of Quick Drying Fog Seal Material

 A new fog seal material was formulated with asphalt rejuvenator, alcohol and co-solvent. The new material provides a quick drying performance and could be used for airport runways and elevated highways. Properties of the rejuvenator used in the fog seal materials were analyzed firstly by several instruments, and its functional groups were calculated. Then, the functional groups were used in the group-contribution method and Hansen solubility parameters theory to screen out a suitable co-solvent, which should have a better solubility in alcohol. Experimental results showed that the co-solvent N-Methyl-2-Pyrrolidone could greatly improve the solubility of the rejuvenator in alcohol. Ternary phase diagram was used to optimize the formula of the fog seal material. At last, the prepared material was evaluated and showed good performances of fast drying, stability and regeneration of aged asphalt

Formulating and Performance of Quick Drying Fog Seal Material

 A new fog seal material was formulated with asphalt rejuvenator, alcohol and co-solvent. The new material provides a quick drying performance and could be used for airport runways and elevated highways. Properties of the rejuvenator used in the fog seal materials were analyzed firstly by several instruments, and its functional groups were calculated. Then, the functional groups were used in the group-contribution method and Hansen solubility parameters theory to screen out a suitable co-solvent, which should have a better solubility in alcohol. Experimental results showed that the co-solvent N-Methyl-2-Pyrrolidone could greatly improve the solubility of the rejuvenator in alcohol. Ternary phase diagram was used to optimize the formula of the fog seal material. At last, the prepared material was evaluated and showed good performances of fast drying, stability and regeneration of aged asphalt

Identification of Hydraulic Connection Points between Different Confined Aquifers in the Liyazhuang Coal Mine

Water inrush from coal seam floors is one major geological obstacle hindering safe and efficient production activities in mines. Determining the source of water inrush can facilitate its prediction and guide decisions regarding measures for prevention and control. The process of identifying the location of hidden hydraulic contact points in different confined aquifers forms the basis of hydrogeological explorations. It is also the basis for categorizing mine areas prone to water inrush and making qualitative decisions regarding the prevention and control of water inrush. In this study, the positions of hidden hydraulic contact points between the Ordovician Fengfeng and Shangmajiagou formations in the basement of the Liyazhuang coal mine were determined using numerical simulations of the flow fields. First, each node of the finite element grid was considered as a water inrush point to determine the water level at other nodes. Subsequently, the error between measured and simulated water levels, determined based on the flow fields, was determined using the least squares method. The node with the minimum error was then considered as the hidden hydraulic contact point. The simulation results for the flow field indicate a distance of 5000 m between the hydraulic connection and the water inrush points located between the peak formation and the Majiagou aquifer in the Liyazhuang coal mine. Furthermore, the hydraulic relationship between them is poor. Observational data of water inrush from the floor of the No. 2 coal seam and the water level of the confined aquifer in the Liyazhuang coal mine, including the water quality test data of different Ordovician ash aquifers, show that the source of water inrush from the floor of the No. 2 coal seam is the aquifer of the Fengfeng Formation. This finding is consistent with the results of the numerical simulations of the flow field. The results demonstrate that, in mining areas subjected to high pressures, numerical simulations of the flow field can serve as an effective tool for determining the location of hidden hydraulic contact points

Mapping the Geothermal System Using AMT and MT in the Mapamyum (QP) Field, Lake Manasarovar, Southwestern Tibet

Southwestern Tibet plays a crucial role in the protection of the ecological environment and biodiversity of Southern Asia but lacks energy in terms of both power and fuel. The widely distributed geothermal resources in this region could be considered as potential alternative sources of power and heat. However, most of the known geothermal fields in Southwestern Tibet are poorly prospected and currently almost no geothermal energy is exploited. Here we present a case study mapping the Mapamyum (QP) geothermal field of Southwestern Tibet using audio magnetotellurics (AMT) and magnetotellurics (MT) methods. AMT in the frequency range 11.5–11,500 Hz was used to map the upper part of this geothermal reservoir to a depth of 1000 m, and MT in the frequency range 0.001–320 Hz was used to map the heat source, thermal fluid path, and lower part of the geothermal reservoir to a depth greater than 1000 m. Data from 1300 MT and 680 AMT stations were acquired around the geothermal field. Bostick conversion with electromagnetic array profiling (EMAP) filtering and nonlinear conjugate gradient inversion (NLCGI) was used for data inversion. The AMT and MT results presented here elucidate the geoelectric structure of the QP geothermal field, and provide a background for understanding the reservoir, the thermal fluid path, and the heat source of the geothermal system. We identified a low resistivity anomaly characterized by resistivity in the range of 1–8 Ω∙m at a depth greater than 7 km. This feature was interpreted as a potential reflection of the partially melted magma in the upper crust, which might correlate to mantle upwelling along the Karakorum fault. It is likely that the magma is the heat source of the QP geothermal system, and potentially provides new geophysical evidence to understand the occurrence of the partially melted magmas in the upper crust in Southwestern Tibet

R-YOLO: A YOLO-Based Method for Arbitrary-Oriented Target Detection in High-Resolution Remote Sensing Images

In view of the existence of remote sensing images with large variations in spatial resolution, small and dense objects, and the inability to determine the direction of motion, all these components make object detection from remote sensing images very challenging. In this paper, we propose a single-stage detection network based on YOLOv5. This method introduces the MS Transformer module at the end of the feature extraction network of the original network to enhance the feature extraction capability of the network model and integrates the Convolutional Block Attention Model (CBAM) to find the attention area in dense scenes. In addition, the YOLOv5 target detection network is improved by incorporating a rotation angle approach from the a priori frame design and the bounding box regression formulation to make it suitable for rotating frame-based detection scenarios. Finally, the weighted combination of the two difficult sample mining methods is used to improve the focal loss function, so as to improve the detection accuracy. The average accuracy of the test results of the improved algorithm on the DOTA data set is 77.01%, which is higher than the previous detection algorithm. Compared with the average detection accuracy of YOLOv5, the average detection accuracy is improved by 8.83%. The experimental results show that the algorithm has higher detection accuracy than other algorithms in remote sensing scenes