Multicell Edge Coverage Enhancement Using Mobile UAV-Relay

Unmanned aerial vehicle (UAV)-assisted communication is a promising technology in future wireless communication networks. UAVs can not only help offload data traffic from ground base stations (GBSs) but also improve the Quality of Service (QoS) of cell-edge users (CEUs). In this article, we consider the enhancement of cell-edge communications through a mobile relay, i.e., UAV, in multicell networks. During each transmission period, GBSs first send data to the UAV, and then the UAV forwards its received data to CEUs according to a certain association strategy. In order to maximize the sum rate of all CEUs, we jointly optimize the UAV mobility management, including trajectory, velocity, and acceleration, and association strategy of CEUs to the UAV, subject to minimum rate requirements of CEUs, mobility constraints of the UAV, and causal buffer constraints in practice. To address the mixed-integer nonconvex problem, we transform it into two convex subproblems by applying tight bounds and relaxations. An iterative algorithm is proposed to solve the two subproblems in an alternating manner. Numerical results show that the proposed algorithm achieves higher rates of CEUs as compared with the existing benchmark schemes

Importance of Mitochondrial-Related Genes in Dilated Cardiomyopathy Based on Bioinformatics Analysis

We designed this study to identify potential key protein interaction networks, genes, and correlated pathways in dilated cardiomyopathy (DCM) via bioinformatics methods. We selected the GSE3586 microarray dataset, consisting of 15 dilated cardiomyopathic heart biopsy samples and 13 nonfailing heart biopsy samples. Initially, the GSE3586 dataset was downloaded and was analyzed with the limma package to identify differentially expressed genes (DEGs). A total of 172 DEGs consisting of 162 upregulated genes and ten downregulated genes in DCM were selected by the criterion of adjusted Pvalues less than 0.01 and the log2-fold change of 0.6 or greater. Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to view the biological processes, cellular components, molecular function, and KEGG pathways of the DEGs. Next, protein-protein interactions were constructed, and the hub protein modules were identified. Then we selected the key genes DLD , UQCRC2 , DLAT , SUCLA2 , ATP5A1 , PRDX3 , FH , SDHD , and NDUFV1 , which are involved in a wide range of biological activities, such as the citrate cycle, oxidation-reduction processes and cellular respiration, and energy derivation by oxidation of organic compounds in mitochondria. Finally, we found that currently there are no related gene-targeting drugs after exploring the predicted interactions between key genes and drugs, and transcription factors. In conclusion, our study provides greater understanding of the pathogenesis and underlying molecular mechanisms in DCM. This contributes to the exploration of potential gene therapy targets

Synthesis of Hierarchical CoO Nano/Microstructures as Anode Materials for Lithium-Ion Batteries

Hierarchical CoO nano/microstructures are synthesized via a hydrothermal method and a subsequent annealed process. When evaluated for use in lithium-ion batteries, hierarchical CoO nano/microstructures show a high initial discharge capacity of 1370 mAh/g and a high reversible capacity of 1148 mAh/g over 20 cycles at a current density of 100 mA/g. Superior rate performance with coulombic efficiency of about 100% upon galvanostatic cycling is also revealed. The excellent electrochemical properties of hierarchical CoO nano/microstructures make it a promising alternative anode material for high power lithium-ion batteries applications

How to Identify Future Priority Areas for Urban Development: An Approach of Urban Construction Land Suitability in Ecological Sensitive Areas

The suitability of urban construction land (SUCL) is key to the appropriate utilization of land resources and represents an important foundation for regional exploration and land management. This study explores the SUCL conceptual framework by considering the theory of human-land relationships. The upper reaches of the Yangtze River were studied, a typical ecologically-sensitive area of China. The spatial pattern and control of the SUCL were determined using the improved entropy method. The results show that an area of 91 × 104 km2 was categorized as prohibited or restricted, and these categories account for 28.61% and 50.66% of the total area, respectively. Priority areas and suitable areas are mainly located in the Chengdu Plain, the urban agglomeration of southern Sichuan Province, Chongqing, and the economic corridor in the west, and the surrounding cities of Guiyang and Kunming. SUCL hotspots feature obvious spatial heterogeneity and are concentrated in Sichuan Basin and Guizhou Plateau. The SUCL is obviously constrained by the physical geography of this region. In addition, towns affected by the pole–axis effect have stronger suitability for development and construction. These findings will be very useful for land managers as they provide relevant information about urban development in mountainous areas

EFAFN: An Efficient Feature Adaptive Fusion Network with Facial Feature for Multimodal Sarcasm Detection

Sarcasm often manifests itself in some implicit language and exaggerated expressions. For instance, an elongated word, a sarcastic phrase, or a change of tone. Most research on sarcasm detection has recently been based on text and image information. In this paper, we argue that most image data input to the sarcasm detection model is redundant, for example, complex background information and foreground information irrelevant to sarcasm detection. Since facial details contain emotional changes and social characteristics, we should pay more attention to the image data of the face area. We, therefore, treat text, audio, and face images as three modalities and propose a multimodal deep-learning model to tackle this problem. Our model extracts the text, audio, and image features of face regions and then uses our proposed feature fusion strategy to fuse these three modal features into one feature vector for classification. To enhance the model’s generalization ability, we use the IMGAUG image enhancement tool to augment the public sarcasm detection dataset MUStARD. Experiments show that although using a simple supervised method is effective, using a feature fusion strategy and image features from face regions can further improve the F1 score from 72.5% to 79.0%

Incorporating Rarity and Accessibility Factors into the Cultural Ecosystem Services Assessment in Mountainous Areas: A Case Study in the Upper Reaches of the Minjiang River

Cultural ecosystem services (CES) are not only a key source for supporting the development of economy but also maintain the ecological security in mountainous areas. However, there are limited numbers of studies that focus on establishing the assessment model for the CES at a regional scale. We combined the topographic factors and accessibility factors to quantify the distribution of CES and tested the approach with data on road and topography in the upper reaches of the Minjiang River. The results showed that the areas with high CES were located in the southwestern part of the study area, where it was convenient traffic and rare topography. Results from our approach were likely to support the development of local tourism industry because the distribution of CES was consistent with current hotspots for scenic spots. Meanwhile, we found that the area with high rarity and low accessibility should improve accessibility in order to enhance the capacity of CES. The assumptions applied in our approach highlighted the impacts of complex topography on CES, which could be suitable for the area with a lack of data. Moreover, our approach provided an effective way to assess CES for creating management strategies and enhancing capacity in mountainous areas

Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China

Risk assessment lays a foundation for disaster risk reduction management, especially in relation to climate change. Intensified extreme weather and climate events driven by climate change may increase related disaster susceptibility. This may interact with exposed and vulnerable socioeconomic systems to aggravate the impacts and impede progress towards regional development. In this study, debris flow risk under climate change was assessed by an integrated debris flow mechanism model and an inclusive socioeconomic status evaluation. We implemented the method for a debris flow-prone area in the eastern part of the Qinghai-Tibet Plateau, China. Based on the analysis of three general circulation models (GCMs)—Beijing Climate Center Climate System Model version 1 (BCC_CSM), model for Interdisciplinary Research on Climate- Earth System, version 5 (MIROC5, and the Community Climate System Model version 4 (CCSM4)—the water–soil process model was applied to assess debris flow susceptibility. For the vulnerability evaluation, an index system established from the categories of bearing elements was analyzed by principle component analysis (PCA) methods. Our results showed that 432 to 1106 watersheds (accounting for 23% to 52% of the study area) were identified as debris-flow watersheds, although extreme rainfall would occur in most of the area from 2007 to 2060. The distributions of debris flow watersheds were concentrated in the north and transition zones of the study area. Additionally, the result of the index and PCA suggested that most areas had relatively low socioeconomic scores and such areas were considered as high-vulnerability human systems (accounts for 91%). Further analysis found that population density, road density, and gross domestic production made great contributions to vulnerability reduction. For practical mitigation strategies, we suggested that the enhancement of road density may be the most efficient risk reduction strategy