The problem of subcarrier, bit and power allocation for an OFDM based cognitive radio system in which one or more spectrum holes exist between multiple primary user (PU) frequency bands is studied. ...The cognitive radio user is able to use any portion of the frequency band as long as it does not interfere unduly with the PUs' transmissions. We formulate the resource allocation as a multidimensional knapsack problem and propose a low-complexity, greedy max-min algorithm to solve it. The proposed algorithm is simple to implement and simulation results show that its performance is very close to (within 0.3% of) the optimal solution.
The background in image of remote sensing is often complicated and changeable, and the edge of cloud and its shadow is irregular. In the traditional method, the bright part of the background is easy ...to be misjudged as cloud, while the dark part is easy to be misjudged as cloud shadow. Moreover, the edge information of the extracted cloud and its shadow is rough, and it is easy to miss the judgment for the thin cloud part and the light cloud shadow part. In order to solve the above problems, a strip pooling channel spatial attention network is proposed. In this work, the strip pooling residual network is used as the backbone network to obtain the feature of cloud and its shadow. The strip pooling residual network can obtain more accurate local position information of cloud and its shadow, which can improve the accuracy of edge segmentation. Channel attention and spatial attention combine shallow spatial information with deep context information, so that cloud and its shadow can be accurately segmented from the background. The experimental results demonstrate that method in our work can acquire more accurate segmentation edge than existing methods, hence it is practical in accurate cloud and its shadow segmentation.
•The strip pool residual neural network is used as the backbone network to obtain the feature of clouds and cloud shadows.•The strip pool residual network can improve the accuracy of edge segmentation.•Channel attention and spatial attention combine shallow location information with deep semantic information.
The China-Nepal Highway is a vital land route in the Kush-Himalayan region. The occurrence of mountain hazards in this area is a matter of serious concern. Thus, it is of great importance to perform ...hazard assessments in a more accurate and real-time way. Based on temporal and spatial sensor data, this study tries to use data-driven algorithms to predict landslide susceptibility. Ten landslide instability factors were prepared, including elevation, slope angle, slope aspect, plan curvature, vegetation index, built-up index, stream power, lithology, precipitation intensity, and cumulative precipitation index. Four machine learning algorithms, namely decision tree (DT), support vector machines (SVM), Back Propagation neural network (BPNN), and Long Short Term Memory (LSTM) are implemented, and their final prediction accuracies are compared. The experimental results showed that the prediction accuracies of BPNN, SVM, DT, and LSTM in the test areas are 62.0%, 72.9%, 60.4%, and 81.2%, respectively. LSTM outperformed the other three models due to its capability to learn time series with long temporal dependencies. It indicates that the dynamic change course of geological and geographic parameters is an important indicator in reflecting landslide susceptibility.
•Attentional change detection network based on Siamese U-shaped structure is proposed.•Multi-scale Convolution Residual Module is proposed.•Three new modules are proposed to extract effective ...features.
Remote sensing image change detection is an essential aspect of remote sensing technology application. Existing change detection algorithms based on deep learning do not distinguish between changed and unchanged areas explicitly, resulting in serious loss of edge detail information during detection. Therefore, a new attentional change detection network based on Siamese U-shaped structure (SUACDNet) is proposed in this paper. In the feature encoding stage, three branches are introduced between the Siamese structure to focus on the global information, difference information and similarity information of bitemporal images respectively. In the feature decoding stage, an U-shaped structure is constructed for upsampling and recovery layer by layer. Multi-scale Convolution Residual Module (MCRM) is a new convolution structure designed for multi-scale feature extraction in the network. In addition, this work also proposes three auxiliary modules to optimize the network, namely Spatial Attention Module (SAM), Feature Fusion Module (FFM) and Cross-scale Global Context Semantic Information Aggregation Module (CGCAM), making the network more sensitive to the changed area while filtering out the background noise. Comparative experiments on three datasets show that our method is superior to the existing methods.
•A variable order fractional accumulation generating operator is proposed.•A variable order derivative is introduced into a grey model.•The effect of the new model is better than that of similar ...competitive models.•The new model can be used to predict problems with variable order characteristics.
The use of constant order differential equations to describe the evolution of complex systems is often unable to describe some of the changing characteristics of the systems accurately. Variable order fractional derivatives provide us with new tools to solve such problems. In this paper, the accumulation and derivative orders of the classic grey model are expanded from constants to functions, and a variable order fractional grey model is established to describe the evolution process of complex systems. Firstly, this paper defines the variable order fractional accumulation generation sequence. On the basis of this sequence, a variable order fractional derivative grey model is established, the parameters of the model are estimated using the least square method, and the quantum particle swarm optimization algorithm is used to solve the order of fractional derivative and accumulation. Sadik transform and Laplace transform are adopted to obtain the analytical solution of the new model. Lastly, the effectiveness of the new model is verified through four cases. Compared with other models, the variable order fractional model can describe the development process of complex systems more accurately.
The study was designed to explore the relationships among character strengths, strengths use, future self-continuity and subjective well-being. A total of 225 undergraduates completed ...paper-and-pencil questionnaires assessing character strengths, strengths use, future self-continuity, and subjective well-being. Results suggested several character strengths were correlated with subjective well-being and the strongest correlations were found for hope, curiosity, zest, perseverance and love. All character strengths were significantly correlated with strengths use. Strengths use and future self-continuity were robustly correlated with subjective well-being. The mediation analysis showed that strengths use mediates the relationship between character strengths and subjective well-being, and specifically, the indirect effects of strengths use varies from different character strengths. The moderated mediator suggested that future self-continuity moderated the mediation of strengths use because future self-continuity moderates the effect of strengths use on subjective well-being. Furthermore, the indirect effect of strengths use was stronger with high level of future self-continuity than those with low level of future self-continuity. The present findings make a contribution to understand the underlying mechanisms involving in character strengths are associated with higher level of well-being. Additionally, the findings expand knowledge about future self-continuity and its relation to strengths use and subjective well-being among undergraduates, having significant implications in the educational context.
•Water yield in Yellow River basin (YRB) showed an increasing trend during 2000, 2010 and 2019.•The contribution of land use/land cover change to water yield is lower than of precipitation in ...YRB.•Land greening in YRB resulted in benefits for water yield in recent years.•The contribution of turning green to water yield is various in different geomorphic units of YRB.
Understanding the impacts of climate and land use/land cover (LULC) changes on water yield has great importance for water resource management and policy development, especially in arid and semi-arid areas. However, it is unclear whether land greening under the human land management is beneficial to the water yield of different geomorphic units under the unique climate models. Here, we used InVEST model to estimate the water yield of the Yellow River Basin (YRB) in 2000, 2010 and 2019 and selected different scenarios to analyse the contribution of LULC changes to water yield. The results showed that the water yield of the YRB increased during the study period. The mean depth of water yield (MDWY) of grassland, cultivated land, shrubland and forest decreased in turn, while the annual MDWY of each type increased. Cultivated land and grassland were the main contribution types of water yield in the YRB accounting for about 84% of the total, and the annual water yield of LULC types covered by vegetation increased except for cultivated land. The annual water yield of the Qinghai Tibet Plateau (region Ⅰ) and the Loess Plateau (region III) in the YRB accounted for more than 80% of the total YRB water yield and showed an interannual increasing trend with part of the Mongolia Plateau (region Ⅱ) in the basin. The contribution of LULC to water yield in the whole YRB was small compared with that of precipitation, but LULC changes resulted in benefits for water yield in recent years, especially in region III that is controlled by a warm-temperate semi-arid continental climate and region I that is controlled by a plateau cold climate. However, in region Ⅱ, which is controlled by a mid-temperate semi-arid continental climate, revegetation further weakened the water yield ecosystem service. The results can provide references for land use management to enhance water yield under the background of global climate change.
Abstract
STUDY QUESTION
What is the role of the programmed cell death-1 (PD-1)/PD-1 ligand-1 (PD-L1) axis in macrophage polarization during early pregnancy?
SUMMARY ANSWER
PD-1 signaling is a major ...regulator of macrophage differentiation and function, and it is critical for the success of a pregnancy.
WHAT IS KNOWN ALREADY
The predominance of decidual macrophages (DMs) with an M2 phenotype is an important contributor to maternal-fetal tolerance during early pregnancy.
STUDY DESIGN, SIZE, DURATION
Twenty-four women with recurrent miscarriage (RM) and 70 women undergoing elective termination of an early normal pregnancy (NP) were included. Twelve female CBA/J, four male DBA/2, and four male BALB/c mice were included and mating carried out. The 12 CBA/J pregnant mice were then categorized into three groups of four mice: healthy control group CBA/J×BALB/c, abortion-prone pregnant group CBA/J×DBA/2 and normal pregnancies CBA/J×BALB/c treated with anti-PD-1 monoclonal antibodies.
PARTICIPANTS/MATERIALS, SETTING, METHODS
The profile of DMs, and the expression of PD-1 and PD-L1 in DMs from women with NP and RM were measured by flow cytometry. PD-L1 expression in human villi was determined by quantitative RT-PCR (qRT-PCR) and western blot. An in vitro model consisting of peripheral CD14+ monocytes isolated from women with NP was used. The profile of differentiated macrophages and their phagocytotic activity were then measured by flow cytometry. The mRNA levels of genes potentially underlying macrophage polarization modulated by PD-1 signaling were determined by qRT-PCR. Twelve pregnant mice were included in our in vivo model and underwent different treatment. The embryo resorption rate, and macrophage profile as well as PD-1 expression in murine spleens and uterus were analyzed by flow cytometry.
MAIN RESULTS AND THE ROLE OF CHANCE
Compared with NP, women with RM had elevated percentages of M1 DMs (P < 0.01), and reduced frequencies of M2 DMs (P < 0.05), as well as decreased PD-1 protein expression (P < 0.05) in the DMs. In addition, decreased mRNA and protein levels of PD-L1 expression in placental villi were observed in women with RM (P < 0.001). Using in vitro experiments, compared to the control group, we found that PD-1 activation by recombinant human (rh) PD-L1 Fc (human PD-L1 fused to the Fc region of human IgG1) drove the differentiation of macrophages with immuno-modulatory characteristics (P < 0.01). However, PD-1 blockade promoted dominance of the M1 phenotype (P < 0.01). PD-1 polarized macrophages showed enhanced phagocytic activity (P < 0.01), which was decreased with PD-1 blockade (P < 0.001). Furthermore, PD-1 blockade promoted the expression of pro-inflammatory cytokines and interferon regulatory factor (IRF) 5 (P < 0.05), while IRF4 expression was inhibited (P < 0.05). In addition, PD-1 blockade promoted macrophage glycolysis (P < 0.01) and inhibited fatty acid oxidation (P < 0.05). The mRNA expression levels of both phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin and mitogen-activated protein kinase/extracellular signal-regulated kinase/extracellular signal-regulated kinase were upregulated (P < 0.05) with PD-1 blockade during DM metabolic reprogramming. Moreover, in vivo mice data showed that PD-1 blockade or deficiency was associated with decreased M2 percentages at the maternal-fetal interface (P < 0.05) and embryo loss (P < 0.05).
LARGE SCALE DATA
N/A.
LIMITATIONS, REASONS FOR CAUTION
Whether the changes in DM polarization seen in miscarriage tissues are a cause or consequence of the demise of the pregnancy still requires further investigation. In addition, conducting metabolite analysis is required to further measure bioenergetic profiles.
WIDER IMPLICATIONS OF THE FINDINGS
This is the first study on the role of the PD-1/PD-L1 axis in macrophage polarization during early pregnancy; such exploration enhances our understanding of the physiology of early pregnancy. Our study also indicates that targeting the PD-1 pathway may represent a novel therapeutic strategy to prevent pregnancy loss.
STUDY FUNDING/COMPETING INTEREST(S)
This study was supported by the National Nature Science Foundation of China (No. 81671490) and Integrated Innovative Team for Major Human Diseases Program of Tongji Medical College, HUST (No. 5001519002). None of the authors has any conflict of interest to declare.
We describe a compact radial cavity power divider based on the substrate integrated waveguide (SIW) technology in this paper. The equivalent-circuit model is used to analyze the multiport structure, ...and a design procedure is also established for the structure. An eight-way C-band SIW power divider with low insertion loss is designed, fabricated, and measured. Good agreement between simulated and measured results is found for the pro posed power divider. The measured minimum insertion loss of the eight-way power divider is approximately 0.2 dB and return loss is approximately 30 dB at 5.25 GHz. The measured 15-dB return-loss bandwidth is found to be approximately 500 MHz, and its 1-dB insertion-loss bandwidth is approximately 1.2 GHz. Furthermore, the isolations between the output ports of the eight-way power divider are also discussed.
We study the resource-allocation problem in a multiuser orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) system using a cross-layer approach. The goal is to provide ...satisfactory quality of service (QoS) to both real-time and non-real-time applications, despite the rapid variations in available resources caused by the activities of the primary users. The dynamic nature of the available spectrum gives rise to two resource allocation issues: 1) problem feasibility and 2) false urgency. To solve the problem-feasibility issue, which arises when resources are insufficient to meet all user QoS requirements, we adopt a goal-programming approach. The false-urgency issue that was caused by variations in available system resources is effectively avoided by a proposed rate-requirement calculation mechanism based on the status of the packets in queue and system resource availability. Simulation results show that the proposed cross-layer resource-allocation algorithm for CR systems performs better than existing algorithms that were designed for multiuser OFDM systems.
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