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In optical interconnection field, inconsistent coupling behaviors of TE and TM modes may cause abnormal operation. Therefore, it is very significant to implement a polarization-independent directional coupler. In this paper, a hybrid-plasmonic-waveguide-based polarization-independent directional coupler has been proposed. Since the energy of the hybrid plasmonic waveguides for TE and TM modes is distributed in different layers, we manage to achieve polarization independence by adjusting the material properties and dimensions of the corresponding layer. We optimize the parameters of our proposed directional coupler such as radius of silicon waveguide layer, height of silica waveguide layer, and the distance between the two waveguides, etc. Then performance of the directional coupler has been evaluated. It is worth mentioning that the length of the coupling section is only 4.25μm. Meanwhile, the polarization-dependent loss is only 0.393 dB, and the maximum coupling efficiency of TE and TM modes can reach 86.4% and 94.6%, respectively. Besides, the coupling efficiency of TM mode remains above 90% over the entire C-band, while the coupling efficiency also keeps at least 80% for TE mode. Finally, the manufacture process for the proposed directional coupler has been discussed. In brief, the improved polarization-independent directional coupler features small size, low energy loss, good polarization-independent characteristics, and wavelength insensitivity simultaneously. Compared to the other counterparts ever proposed, our proposed coupler can provide a perfect trade-off between device size and loss, which shows important potential applications in the fields of PIC and optical interconnection.

Photonic polymer coatings that can adaptively respond to the constant changes of surrounding environments are of profound significance for diverse applications such as optical sensors, information encryption, and adaptive camouflage. Here, we report the fabrication of humidity-driven color-changing photonic polymer coatings on the basis of judiciously designed hydrogen-bonded three-dimensional (3D) blue phase liquid crystal networks. Thanks to the inherent self-assembled 3D photonic nanostructures and tough covalent bonding between the polymers and substrate surfaces, the resulting polymer coatings are found to exhibit vivid structural colors, and humidity-driven reversible color changes across the visible spectrum of light can be achieved upon breaking the hydrogen bonds and subsequent conversion into a hygroscopic polymer coating. As the proof-of-concept applications, we demonstrate the information encryption, inkjet-printable photonic patterns, bioinspired adaptive camouflage, and colorimetric humidity sensor with such promising humidity-driven color-changing photonic polymer coatings. The results disclosed herein are expected to provide new insights into the development of stimuli-responsive advanced functional materials with tailorable 3D photonic nanostructures toward technological applications ranging from sensing, display, anticounterfeiting, and biomimetic camouflage.

To develop a predictive model and scoring system to enhance the diagnostic efficiency for coronavirus disease 2019 (COVID-19). From January 19 to February 6, 2020, 88 confirmed COVID-19 patients presenting with pneumonia and 80 non-COVID-19 patients suffering from pneumonia of other origins were retrospectively enrolled. Clinical data and laboratory results were collected. CT features and scores were evaluated at the segmental level according to the lesions’ position, attenuation, and form. Scores were calculated based on the size of the pneumonia lesion, which graded at the range of 1 to 4. Air bronchogram, tree-in-bud sign, crazy-paving pattern, subpleural curvilinear line, bronchiectasis, air space, pleural effusion, and mediastinal and/or hilar lymphadenopathy were also evaluated. Multivariate logistic regression analysis showed that history of exposure (β = 3.095, odds ratio (OR) = 22.088), leukocyte count (β = − 1.495, OR = 0.224), number of segments with peripheral lesions (β = 1.604, OR = 1.604), and crazy-paving pattern (β = 2.836, OR = 2.836) were used for establishing the predictive model to identify COVID-19-positive patients (p

The battery industry has been growing fast because of strong demand from electric vehicle and power storage applications.Laser welding is a key process in battery manufacturing. To control the production quality, the industry has a great desire for defect inspection of automated laser welding. Recently, Convolutional Neural Networks (CNNs) have been applied with great success for detection, recognition, and classification. In this paper, using transfer learning theory and pre-training approach in Visual Geometry Group (VGG) model, we proposed the optimized VGG model to improve the efficiency of defect classification. Our model was applied on an industrial computer with images taken from a battery manufacturing production line and achieved a testing accuracy of 99.87%. The main contributions of this study are as follows: (1) Proved that the optimized VGG model, which was trained on a large image database, can be used for the defect classification of laser welding. (2) Demonstrated that the pre-trained VGG model has small model size, lower fault positive rate, shorter training time, and prediction time, so, it is more suitable for quality inspection in an industrial environment. Additionally, we visualized the convolutional layer and max-pooling layer to make it easy to view and optimize the model.

Multiple cropping index (MCI) is the ratio of total sown area and cropland area in a region, which represents the regional time intensity of planting crops. Multiple cropping systems have effectively improved the utilization efficiency and production of cropland by increasing cropping frequency in one year. Meanwhile, it has also significantly altered biogeochemical cycles. Therefore, exploring the spatio-temporal dynamics of multiple cropping intensity is of great significance for ensuring food and ecological security. In this study, MCI of Huang-Huai-Hai agricultural region with intensive cropping practices was extracted based on a cropping intensity mapping algorithm using MODIS Enhanced Vegetation Index (EVI) time series at 500-m spatial resolution and 8-day time intervals. Then the physical characteristics and landscape pattern of MCI trends were analyzed from 2000–2012. Results showed that MCI in Huang-Huai-Hai agricultural region has increased from 152% to 156% in the 12 years. Topography is a primary factor in determining the spatial pattern dynamics of MCI, which is more stable in hilly area than in plain area. An increase from 158% to 164% of MCI occurred in plain area while there was almost no change in hilly area with single cropping. The most active region of MCI change was the intersection zone between the hilly area and plain area. In spatial patterns, landscape of multiple cropping systems tended to be homogenized reflected by a reduction in the degree of fragmentation and an increase in the degree of concentration of cropland with the same cropping system.

3D photonic nanostructures with intrinsic chirality have recently entered the research limelight due to their fundamental importance and potential technological applications. Blue‐phase liquid crystals (BPLCs) with chiral cubic nanostructures are an inventive example of 3D chiral photonic nanostructures. The inherently self‐organized 3D chiral nanostructures give rise to a complete photonic bandgap, which results in the selective reflection of circularly polarized light in all three dimensions. Herein, a comprehensive review of the state‐of‐the‐art of BPLCs and their potential applications is presented. First, the history and fundamentals of BPLCs are introduced. Then, the recent endeavors in the design, synthesis, and properties of BPLCs such as lattice orientation control with different techniques, photonic bandgap tuning with external fields, and fabrication of free‐standing BPLC polymer films are summarized. Finally, a discussion of the future challenges and potential applications of BPLCs is provided. It is believed that this review would stimulate innovative ideas for the design and engineering of novel chiral nanostructured materials for advanced photonic systems with tailorable functionalities.

Population geography (PopGeo), although a sub-discipline of human geography, should have been well developed in China in light of its national population size and unique demographic issues, regional socio-economic development, and biophysical differences. Yet it typically lags behind the development of its parent disciplines, especially demography and geography. Specifically, PopGeo in Chinese higher education is still at a low level in terms of the three major aspects of disciplinary development: academic majors for higher education, academic conferences, and journals. The research content of PopGeo in China has focused on the growth, composition, change, distribution, and carrying capacity of population at the meso- and macro-spatial scales. As the most populated country in the world, questions about how and why the population changes, where the population settles and migrates to, its maximum carrying capacity, and how to guide sound development of population matter to society and the economy, are always important topics in the PopGeo studies in China. In contrast, some new population phenomena such as human space–time behaviors (commuting, remittances, and friends’ interaction), popular in the scientific community abroad, are not fully investigated at the micro-level. Presently, PopGeo in China may face both challenges and opportunities because of the adjustment of fertility policies and implementation of national new urbanization plans at the national level. It is this occasion that calls for a state-of-the-art review of the development of PopGeo since the 1980s, the turning point of an increasing number of PopGeo studies in China. We aim to reveal the current status of PopGeo in China to the world, and shed light on its further study.

The COVID-19 pandemic has triggered concerns about the global food crisis, thus identification of food security risks constitutes an important basis for responding to the influence of the pandemic. In this study, the influence path of the pandemic on food security was analyzed first. Then, the risk nodes of the trade network of countries along the Belt and Road were identified by complex network analysis. Further, food security risks were comprehensively assessed, and dominant risk types were systematically determined by using a four-dimensional integrated food security risk assessment model. According to the results: (1) The COVID-19 pandemic adds to the uncertainty of food security, lowers the efficiency and stability of international trade, highlights the importance of domestic supply, and exposes the vulnerability of external dependence. (2) The Main Cereals Trade Network (MCTN) presents typical scale-free features in the Belt and Road, and core countries significantly affect the stable service of the network. However, as spreading of COVID-19, these countries may pose potential risks to the global food market in the future, by disrupting MCTN. (3) The possession of cereals less than 200 kg/per in 19 countries along the Belt and Road, nine countries have an external dependence of above 90%, and eight countries have an import concentration of above 90%. With the pandemic, 27 countries’ Food Security Risks Indices (FSRI) increase over 1.5 times. (4) Roughly 25%, 40%, and 15% of the countries are dominated by the pandemic risk, dual risks, and compound risks, respectively. About half a number of the countries shows very high or high FSRI level. Specifically, seven countries are dominated by the compound risk. Ten countries are dominated by the domestic supply risk and the pandemic risk. Six countries are dominated by the domestic supply risk and the import concentration risk.

Wind velocity distribution and the vortex around the wind turbine present a significant challenge in the development of straight-bladed vertical axis wind turbines (VAWTs). This paper is intended to investigate influence of tip vortex on wind turbine wake by Computational Fluid Dynamics (CFD) simulations. In this study, the number of blades is two and the airfoil is a NACA0021 with chord length of c = 0.265 m. To capture the tip vortex characteristics, the velocity fields are investigated by the Q-criterion iso-surface (Q = 100) with shear-stress transport (SST) k-ω turbulence model at different tip speed ratios (TSRs). Then, mean velocity, velocity deficit and torque coefficient acting on the blade in the different spanwise positions are compared. The wind velocities obtained by CFD simulations are also compared with the experimental data from wind tunnel experiments. As a result, we can state that the wind velocity curves calculated by CFD simulations are consistent with Laser Doppler Velocity (LDV) measurements. The distribution of the vortex structure along the spanwise direction is more complex at a lower TSR and the tip vortex has a longer dissipation distance at a high TSR. In addition, the mean wind velocity shows a large value near the blade tip and a small value near the blade due to the vortex effect.

Climate change affects regional agricultural development, but a quantitative assessment of large-scale impacts remains difficult. Northwest China has experienced considerable climate change during the last 40 years, and this study uses GIS technology to evaluate the impacts of that change on the agricultural water balance. Results show that over the last 40 years the climate has transitioned from a warm-dry to a warm-wet pattern in the northwestern area of Northwest China, while exhibiting a pattern of increasing aridity in other parts of the region since the 1980s. Through analysis of the spatio-temporal distribution of agricultural water balance using water cycle models that include climatic, crop and cropland layers, we found that the climate warming in the northwestern area of the region has led to a notable reduction in the agricultural water deficit. This reduction, however, still cannot significantly alleviate the water deficit. Finally, we argue that to make agricultural development sustainable in this area, both hard and soft approaches are needed to bring about efficient use of the limited water resources.