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The accurate estimation of a 3D human pose is of great importance in many fields, such as human–computer interaction, motion recognition and automatic driving. In view of the difficulty of obtaining 3D ground truth labels for a dataset of 3D pose estimation techniques, we take 2D images as the research object in this paper, and propose a self-supervised 3D pose estimation model called Pose ResNet. ResNet50 is used as the basic network for extract features. First, a convolutional block attention module (CBAM) was introduced to refine selection of significant pixels. Then, a waterfall atrous spatial pooling (WASP) module is used to capture multi-scale contextual information from the extracted features to increase the receptive field. Finally, the features are input into a deconvolution network to acquire the volume heat map, which is later processed by a soft argmax function to obtain the coordinates of the joints. In addition to the two learning strategies of transfer learning and synthetic occlusion, a self-supervised training method is also used in this model, in which the 3D labels are constructed by the epipolar geometry transformation to supervise the training of the network. Without the need for 3D ground truths for the dataset, accurate estimation of the 3D human pose can be realized from a single 2D image. The results show that the mean per joint position error (MPJPE) is 74.6 mm without the need for 3D ground truth labels. Compared with other approaches, the proposed method achieves better results. [ABSTRACT FROM AUTHOR]

The millimeter wave self-backhaul network (mW-SBN) is one of the key solutions in 5G small cell backhaul. However, a lot of new challenges will be faced when the routing protocol of mW-SBN is designed, due to the dynamic traffic requirement and the directional transmission. To solve the problem well, the remaining bandwidth is described in the paper firstly, which plays a key role in the process of the path discovery. Secondly, a remaining bandwidth based multi-path routing (RBMR) protocol is proposed for the mW-SBN, which is mainly composed of the interaction of the remaining bandwidth information between adjacent nodes, the source route discovery that meets the data backhaul bandwidth requirements and the effective maintenance of the routing table. Thirdly, the upper limit of the number of multi-path is analyzed indirectly. Finally, the proposed protocol is simulated and compared. The simulation results show that RBMR protocol has greater gain than the three variations, i.e. remaining bandwidth based single-path routing (RBSR), non-remaining bandwidth based multi-path routing (NBMR) and non-remaining bandwidth based single-path routing (NBSR), in terms of network average throughput, routing overhead and packet loss rate. [ABSTRACT FROM AUTHOR]

Highlights • The satellite remote sensing data is used to estimate energy consumption in China. • Spatial-temporal geographically-weighted regression models are developed. • The models simulate accurately the energy consumption of provinces in China. Abstract Delay in publication of energy statistics prevents a timely assessment of progress towards meeting targets for energy saving and emission reduction in China. This makes it difficult to meet the requirements to rapidly monitor and evaluate energy consumption for each province. In this study, an alternative approach is provided to estimate the energy consumption by using satellite remote sensing data. We develop spatio-temporal geographically weighted regression models to simulate energy consumption of provinces in China based on the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) global stable night-time light data. The models simulate China's energy consumption accurately with the goodness of fit higher than 99%. Generally, the national average annual energy consumption is 2.8 billion tonnes of coal equivalent in China between 2000 and 2013, which is close to the actual value with errors smaller than 0.1%. From both temporal and spatial dimensions, the relative errors are smaller than 5.5% at the provincial level. Therefore, the use of satellite night-time light data provides a useful reference in monitoring and assessing provincial energy consumption in China. [ABSTRACT FROM AUTHOR]

With the rapid development of machine learning, artificial intelligence (AI) has drawn much more attention. Under this circumstances, abstract strategy games, such as chess, checkers and Go, have been a fascinating problem of AI research. Most of the existing state-of-the-art Go programs used deep neural network technology, like convolutional neural networks (CNNs). However, CNNs require multiple iterations to optimize weights and spend a lot of training time. Therefore, in this paper, in order to solve the above shortcomings, we propose a new learning algorithm ECNN, which integrates CNNs with extreme learning machine (ELM). We remove pooling layers of CNNs and insert ELM layers between convolutional layers. The newly added ELM layers will be updated in back-propagation process, and they accelerate the convergence of weights in CNNs. Therefore, our ECNN can reduce the training time of CNNs. Further, we propose ECNN-Go algorithm, which applies ECNN to Go game. Because of the advantage of ECNN, ECNN-Go algorithm has the fast learning speed to make move prediction in Go game. Finally, the experimental results show the efficiency and accuracy of ECNN algorithm and demonstrate the strength of ECNN-Go. [ABSTRACT FROM AUTHOR]

The microscopic properties and superfluidity of the inner crust in neutron stars are investigated in the framework of the relativistic mean field(RMF) model and BCS theory. The Wigner-Seitz(W-S) cell of inner crust is composed of neutron-rich nuclei immersed in a sea of dilute, homogeneous neutron gas. The pairing properties of nucleons in the W-S cells are treated in BCS theory with Gogny interaction. In this work, we emphasize on the choice of the boundary conditions in the RMF approach and superfluidity of the inner crust. Three kinds of boundary conditions are suggested. The properties of the W-S cells with the three kinds of boundary conditions are investigated. The neutron density distributions in the RMF and Hartree-Fock-Bogoliubov(HFB) models are compared. [ABSTRACT FROM AUTHOR]

Flying ad hoc network is widely used in many military and civilian scenarios. Compared with mobile ad hoc network and vehicular ad hoc network, flying ad hoc network holds some special characteristics such as high mobility, long-distance communication, and sparse node-deployment, which cause an important challenge in the design of routing protocols. In this article, a velocity-aware and stability-estimation–based multi-path routing protocol is proposed for flying ad hoc network. The protocol is mainly composed of two important parts, which are the routing discovery mechanism and routing maintenance mechanism. In routing discovery process, the routing discovery request packet only can be forwarded by the reliable node, which is decided by the calculation of co-direction degree, then the routing overhead is reduced at some extent. Noticeably, the correlation of the survival duration between adjacent links is fully considered, which is very important to the path stability criteria. In routing maintenance progress, a path similarity and path remaining survival duration–based multi-path selection mechanism is proposed. The performance superiority of velocity-aware and stability-estimation–based multi-path routing protocol is also demonstrated by extensive simulations. The results show that velocity-aware and stability-estimation–based multi-path routing protocol is much better than other existing protocols in terms of network throughput, average delay of data transmission, routing overhead, and the convergence time of the routing discovery. [ABSTRACT FROM AUTHOR]

Melanoma is an aggressive malignant tumor with a poor prognosis. Vemurafenib (PLX4032, vem) is applied to specifically treat BRAF V600E‐mutated melanoma patients. However, prolonged usage of vem makes patients resistant to the drug and finally leads to clinical failure. We previously tested the combination regimen of tubulin inhibitor VERU‐111 with vem, as well as USP14 selective inhibitor b‐AP15 in combination with vem, both of which have showed profound therapeutic effects in overcoming vem resistance in vitro and in vivo. Most importantly, we discovered that vem‐resistant melanoma cell lines highly expressed E3 ligase SKP2 and DUB enzyme USP14, and we have demonstrated that USP14 directly interacts and stabilizes SKP2, which contributes to vem resistance. These works give us a clue that USP14 might be a promising target to overcome vem resistance in melanoma. MitoCur‐1 is a curcumin derivative, which was originally designed to specifically target tumor mitochondria inducing redox imbalance, thereby promoting tumor cell death. In this study, we have demonstrated that it can work as a novel USP14 inhibitor, and thus bears great potential in providing an anti‐tumor effect and sensitizing vem‐resistant cells by inducing ferroptosis in melanoma. Application of MitoCur‐1 dramatically induces USP14 inhibition and inactivation of GPX4 enzyme, meanwhile, increases the depletion of GSH and decreases SLC7A11 expression level. As a result, ferrous iron‐dependent lipid ROS accumulated in the cell, inducing ferroptosis, thus sensitizes the vem‐resistant melanoma cell. Interestingly, overexpression of USP14 antagonized all the ferroptosis cascade events induced by MitoCur‐1, therefore, we conclude that MitoCur‐1 induces ferroptosis through inhibition of USP14. We believe that by inhibition of USP14, vem resistance can be reversed and will finally benefit melanoma patients in future. [ABSTRACT FROM AUTHOR]

Background: An increasing number of systematic reviews (SRs) in the environmental field have been published in recent years as a result of the global concern about the health impacts of air pollution and temperature. However, no study has assessed and compared the methodological and reporting quality of SRs on the health effects of air pollutants and extreme temperatures. This study aims to assess and compare the methodological and reporting quality of SRs on the health effects of ambient air pollutants and extreme temperatures. Methods: PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, and Epistemonikos databases were searched. Two researchers screened the literature and extracted information independently. The methodological quality of the SRs was assessed through A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2). The reporting quality was assessed through Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA). Results: We identified 405 SRs (286 for air pollution, 108 for temperature, and 11 for the synergistic effects). The methodological and reporting quality of the included SRs were suboptimal, with major deficiencies in protocol registration. The methodological quality of SRs of air pollutants was better than that of temperature, especially in terms of satisfactory explanations for any heterogeneity (69.6% v. 45.4%). The reporting quality of SRs of air pollution was better than temperature, however, adherence to the reporting of the assessment results of risk of bias in all SRs (53.5% v. 34.3%) was inadequate. Conclusions: Methodological and reporting quality of SRs on the health effect of air pollutants were higher than those of temperatures. However, deficiencies in protocol registration and the assessment of risk of bias remain an issue for both pollutants and temperatures. In addition, developing a risk-of-bias assessment tool applicable to the temperature field may improve the quality of SRs. [ABSTRACT FROM AUTHOR]

We review a large body of predictions obtained within the framework of relativistic meson theory together with the Dirac-Brueckner-Hartree-Fock approach to nuclear matter and finite nuclei. The success of this method has been largely related to its ability to take into account important three-body effects. Therefore, the overarching theme of this paper is the interpretation of the so-called 'Dirac effects' as an effective three-nucleon force. We address the equation of state (EoS) of isospin symmetric and asymmetric nucleonic matter and related issues, ranging from proton and neutron density distributions to momentum distributions and short-range correlations. A central part of the discussion is devoted to the optical model potential for nucleon-nucleus scattering. We also take the opportunity to explore similarities and differences with predictions based on the increasingly popular chiral effective field theory. [ABSTRACT FROM AUTHOR]

To address the dangerous driving behaviors prevalent among current car drivers, it is necessary to provide real-time, accurate warning and correction of driver's driving behaviors in a small, movable, and enclosed space. In this paper, we propose a method for detecting dangerous behaviors based on frequency-modulated continuous-wave radar (mm-DSF). The highly packaged millimeter-wave radar chip has good in-vehicle emotion recognition capability. The acquired millimeter-wave differential frequency signal is Fourier-transformed to obtain the intermediate frequency signal. The physiological decomposition of the local micro-Doppler feature spectrum of the target action is then used as the eigenvalue. Matrix signal intensity and clutter filtering are performed by analyzing the signal echo model of the input channel. The signal classification is based on the estimation and variety of the feature vectors of the target key actions using a modified and optimized level fusion method of the SlowFast dual-channel network. Nine typical risky driving behaviors were set up by the Dula Hazard Questionnaire and TEIQue-SF, and the accuracy of the classification results of the self-built dataset was analyzed to verify the high robustness of the method. The recognition accuracy of this method increased by 1.97% compared with the traditional method. [ABSTRACT FROM AUTHOR]

The positioning of indoor electronic devices is an essential part of human–computer interaction, and the accuracy of positioning affects the level of user experience. Most existing methods for RF-based device localization choose to ignore or remove the impact of multipath effects. However, exploiting the multipath effect caused by the complex indoor environment helps to improve the model's localization accuracy. In response to this question, this paper proposes a multipath-assisted localization (MAL) model based on millimeter-wave radar to achieve the localization of indoor electronic devices. The model fully considers the help of the multipath effect when describing the characteristics of the reflected signal and precisely locates the target position by using the MAL area formed by the reflected signal. At the same time, for the situation where the radar in the traditional Single-Input Single-Output (SISO) mode cannot obtain the 3D spatial position information of the target, the advantage of the MAL model is that the 3D information of the target can be obtained after the mining process of the multipath effect. Furthermore, based on the original hardware, it can achieve a breakthrough in angular resolution. Experiments show that our proposed MAL model enables the millimeter-wave multipath positioning model to achieve a 3D positioning error within 15 cm. [ABSTRACT FROM AUTHOR]

Currently, researchers have mainly focused on the role of the tissues of the posterior segment of the eyes in the development of myopia. However, the ciliary body, an anterior ocular tissue that contracts to initiate the process of accommodation, may also play an important role in the progression of myopia due to the increased demand for near work. In the present study, we established a lens-induced myopia (LIM) animal model in guinea pigs and investigated the molecular changes in the ciliary body associated with the development of myopia based on RNA sequencing. As a result, 871 differentially expressed (DE) mRNAs and 19 DE lncRNAs were identified in the ciliary body between the LIM group and the normal control group. In addition, the lncRNA-mRNA co-expression analysis was performed to explore the target genes of lncRNAs, which were mainly enriched in the Rap1 signaling pathway, cytokine-cytokine receptor interaction, and complement and coagulation cascades pathways based on the functional enrichment analysis. Among the target genes of lncRNAs, three hub genes, including Ctnnb1 , Pik3r1, and Itgb1 , were found to be involved in the Rap1 signaling pathway. Interestingly, two crucial genes, Grk1 and Pde6a , which are mainly expressed in retinal photoreceptors, were enriched in visual perception in the ciliary body in functional analysis and were verified to be expressed in the ciliary body. These findings indicate the molecular pathogenetic role of the ciliary body in myopia and provide new insights into the underlying mechanism of myopia development. Further studies are needed to explore the specific contributions of these identified lncRNAs and mRNAs to the development of myopia. • RNA-seq revealed molecular pathogenetic role of the ciliary body in myopia. • Ctnnb1, Pik3r1, and Itgb1 were confirmed hub genes in the development of myopia. • Ctnnb1, Pik3r1, and Itgb1 were involved in the Rap1 signaling pathway in myopia. [ABSTRACT FROM AUTHOR]

In pharmaceutical warehousing operations, a scientific and reasonable medicine and shelf matching strategy can improve medicine shelving efficiency and manual work efficiency. However, the traditional matching strategy has the problems of static matching and low matching efficiency, so this paper proposes the matching algorithm for drugs and shelves based on the fuzzy analytic hierarchy process and Bayesian convolutional neural network (FAHP-BCNN). First, we propose a drug-shelf matching degree model and discuss the influence of the dynamic matching process on the matching results by studying two parts: the attribute matching degree and the dynamic matching influence degree. Secondly, this paper quantitatively assessed the importance of the two matches by means of the fuzzy analytic hierarchy process. Finally, we mapped the massive matching information onto Bayesian convolutional neural network nodes, constructed a dynamic matching network model, and obtained competitive matching strategies and results. The experimental results show that the FAHP-BCNN algorithm exhibits better matching results in all three scenarios with different quantity ratios of drugs and shelf matching. Compared with the fixed cargo matching strategy of the ABC classification method, the FAHP-BCNN algorithm shows excellent performance in both the manual walking distance index and fatigue index. In summary, the drug-shelf matching algorithm based on FAHP-BCNN is effective and can provide theoretical support for pharmaceutical warehousing enterprises to perform drug-shelf matching. [ABSTRACT FROM AUTHOR]

Highlights • Both production- and consumption-based emissions in Shanghai declined in recent years. • Production-based emissions declined due to changes in the economic structure and energy mix. • Consumption-based emissions declined due to changes in consumption patterns and interregional emission flows. Abstract Carbon emissions are strongly related to economic development. China has entered a new phase of economic development – “New Normal” – in which large-scale and multidimensional changes are occurring in the economic structure. This study aims to estimate the carbon implications of these changes in the economic structure at the city level. We compiled a multiregional input-output (MRIO) model for China and used an environmentally extended input-output analysis (EEIOA) to estimate CO 2 emissions in Shanghai from both production and consumption perspectives. We found that consumption-based CO 2 emissions were more than 30% higher than production-based emissions in Shanghai. In recent years, both production- and consumption-based CO 2 emissions in Shanghai declined because of changes in China’s economic development mode. The production-based emissions declined mainly due to changes in the production structure and energy mix, while the consumption-based emissions declined mainly due to changes in consumption patterns and domestic interregional emission flows. [ABSTRACT FROM AUTHOR]