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Elaborated optical and thermal modulatory systems are of great importance to the survival and evolution of organisms in nature. Inspired by these natural intelligent systems, researchers have made great efforts for developing stretchable polymers and exploring their applications in fields of communication, dynamic camouflage, thermal management, and others. Herein, an up‐to‐date account of the advancements in bioinspired stretchable polymers for dynamic optical and thermal regulation is provided. First, stretchable polymers for dynamic structural colors are presented, including cholesteric liquid crystal elastomers, photonic crystal elastomers, and emerging photonic polymers. Then stretchable polymers for dynamic infrared emissivity are introduced, which are achieved by stretch‐induced wrinkled‐flat surface or stretch‐induced cracked surface. Third, stretchable polymers for dynamic thermal management are discussed, focusing on tunable solar transmittance and dynamic radiative cooling. Moreover, the perspectives on the opportunities and challenges for future research directions of bioinspired stretchable polymers are presented at the end.

Abstract Smart chiral liquid crystal elastomers are a class of soft photonic crystals with periodic nanostructures. There are two kinds of chiral liquid crystal elastomers with structural colors: cholesteric liquid crystal elastomers with a one‐dimensional helical nanostructure and blue‐phase liquid crystal elastomers with a three‐dimensional photonic crystal nanostructure. The self‐assembled nanostructure of chiral liquid crystal elastomers can be dynamically controlled under external stimulation, and the reflected color can be adjusted throughout the visible light range. Along with the development of innovative material systems and cutting‐edge manufacturing technologies, researchers have proposed diverse strategies to design and synthesize chiral liquid crystal elastomers and have thoroughly investigated their properties and potential applications. Here, we provide a systematic review of the progress in the design and fabrication of smart chiral liquid crystal elastomers, focusing on the cholesteric liquid crystal elastomers via surface‐enforced alignment, bar coating, 3D printing, anisotropic deswelling methods as well as the three‐dimensional self‐assembly of blue‐phase liquid crystal elastomers without additional alignment. Smart chiral liquid crystal elastomers are able to respond quickly to external stimuli and have a wide range of applications in areas such as adaptive optics, color‐changing camouflage, soft robotics, and information encryption. This review concludes with a perspective on the opportunities and challenges for the future development of smart chiral liquid crystal elastomers.

Abstract Background Contrast-induced encephalopathy (CIE) is considered as an uncommon complication following cardiac catheterization. Due to the varied manifestations, CIE has no formal diagnostic criteria. In fact, the incidence of CIE may be greatly underestimated because of the difficulty in its differential diagnosis with other cerebrovascular complications. Thus, making a flow diagram according to patients’ clinical symptoms and examinations after cardiac catheterization to help clinicians diagnose CIE is important and needed. Case presentation In this report, we describe a case of probable CIE in a 66-year-old Chinese man with hypertension who underwent cardiac catheterization with stents placement in the bifurcation lesion, during which 80 ml iopromide contrast was used. About 2 h following the procedure, the patient lost his consciousness suddenly and suffered from a status epilepticus. Malignant arrhythmias were not found through continuous electrocardiogram monitoring, but mild ST-segment elevation was displayed in leads I and aVL. The echocardiography, plasma glucose and electrolyte levels were normal. Emergency re-angiography with percutaneous transluminal coronary angioplasty was performed in the culprit lesion, which involved 60 ml iopromide contrast. However, the patient remained unconsciousness and epilepticus. Non-contrast computed tomography (CT) of the head showed cortical and subarachnoid enhancement as well as prolonged retention of contrast media in the middle cerebral artery. With supportive treatment of intravenous hydration, sedative and dehydrant, the patient recovered 3 h later and finally discharged without any neurological deficits. Conclusions CIE is an acute reversible encephalopathy induced by contrast media. It is exceptionally challenging to make the diagnosis of CIE following cardiac catheterization since there is a lack of consensus on the definition of CIE. Via this case we reviewed the related literatures, through which a flow diagram of the differential diagnosis and clinical decision making was given, which could help to differentiate CIE from other neurological complications following cardiac catheterization.

Abstract In the wave of the Internet era created by computer and communication technology, flexible sensors play an important role in accurately collecting information owing to their excellent flexibility, ductility, freeform bending or folding, and versatile structural shapes. By endowing elastomeric polymers with conductivity, researchers have recently devoted extensive efforts toward developing high‐performance flexible sensors based on elastomeric conductive layers and exploring their potential applications in diverse fields ranging from project manufacturing to daily life. This review reports the recent advancements in elastomeric polymers used to make conductive layers, as well as the relationships between elastomeric polymers and the performance and application of flexible sensors are comprehensively summarized. First, the principles and methods for using elastomeric polymers to construct conductive layers are provided. Then, the fundamental design, unique properties, and underlying mechanisms in different flexible sensors (pressure/strain, temperature, humidity) and their related applications are revealed. Finally, this review concludes with a perspective on the challenges and future directions of high‐performance flexible sensors.

Under a background of uncoordinated economic development and the ecological environment, quantifying the ecological effect brought by land resource changes, have become research key and hotspots. To explore land use change and its impact on ecosystem service value (ESV), the land use change analysis method, ecosystem service evaluation model, flow direction analysis model and two-dimensional graph theory clustering method were used to analyze the profit and loss of ESV in Qiqihar in 2010 and 2020 and the division of ecological function areas with counties as units. The results show that: 1) The land use change in Qiqihar city is more obvious, Among them, the area of cultivated land, wetland, construction land and other increases, Woodland, grassland, water area decreased, The changed land area accounts for 30.95% of the total area; 2) The ESV in Qiqihar city increased by 869 million yuan, The sum of the value of cultivated land and wetland exceeded 70.0% of the ESV, is the main source of ESV in Qiqihar city; 3) Not all land-use shifts are conducive to ESV growth. The increase of ESV mainly comes from the flow of cultivated land and grassland to the wetland; Conversion of woodlands, water area, wetlands to other types causes ESV loss, the most loss is the conversion of wetlands to cultivated land; 4) Qiqihar city is divided into the central wetland ecological conservation area, the western characteristic agriculture and dotted wetland ecological function area, and the northeast agricultural ecological environment construction functional area. Three policies were proposed to improve ESV:(1) give play to the radiation role of wetland nature reserves; (2) popularize the black land protection technology model; and (3) prevent and control agricultural non-point source pollution and promote clean agriculture.

In this study, we have investigated the evolution process and dynamic characteristics of a multi-pulse regime in an erbium-doped fiber ring laser based on a single-mode fiber–graded-index multimode fiber–single-mode fiber (SMF-GIMF-SMF) structure as an optical modulator. By utilizing the excellent nonlinear optical absorption of the SMF-GIMF-SMF (SMS) device with a modulation depth of ~8.68%, stable single-pulse mode locking at the frequency of 9.84 MHz can be readily observed at low pump power. In addition, the single-pulse operation can evolve into a multiple-pulse regime on account of the peak-power-clamping effect via suitably raising the pump power and carefully regulating the polarization state. Further, the single-shot temporal evolution of multiple pulses is monitored, indicating that this state shows unique and interesting temporal characteristics with variable pulse separations and inconsistent pulse intensities, which, as far as we know, is the first such observation in ultrafast fiber lasers. Additionally, this study, based on the time-stretch dispersive Fourier transformation method, suggests that these multiple pulses consist of chaotic wave envelopes with erratic intensities and changeable pulse energy. We believe that these findings have profound implications for revealing fascinating nonlinear pulse dynamics in ultrafast fiber optics.

Approximately 1 billion people worldwide currently inhabit slum areas. The UN Sustainable Development Goal (SDG 11.1) underscores the imperative of upgrading all slums by 2030 to ensure adequate housing for everyone. Geo-locations of slums help local governments with upgrading slums and alleviating urban poverty. Remote sensing (RS) technology, with its excellent Earth observation capabilities, can play an important role in slum mapping. Deep learning (DL)-based RS information extraction methods have attracted a lot of attention. Currently, DL-based slum mapping studies typically uses three optical bands to adapt to existing models, neglecting essential geo-scientific information, such as spectral and textural characteristics, which are beneficial for slum mapping. Inspired by the geoscience-aware DL paradigm, we propose the Geoscience-Aware Network for slum mapping (GASlumNet), aiming to improve slum mapping accuracies via incorporating the DL model with geoscientific prior knowledge. GASlumNet employs a two-stream architecture, combining ConvNeXt and UNet. One stream concentrates on optical feature representation, while the other emphasizes geo-scientific features. Further, the feature-level and decision-level fusion mechanisms are applied to optimize deep features and enhance model performance. We used Jilin-1 Spectrum 01 and Sentinel-2 images to perform experiments in Mumbai, India. The results demonstrate that GASlumNet achieves higher slum mapping accuracy than the comparison models, with an intersection over union (IoU) of 58.41%. Specifically, GASlumNet improves the IoU by 4.60~5.97% over the baseline models, i.e., UNet and ConvNeXt-UNet, which exclusively utilize optical bands. Furthermore, GASlumNet enhances the IoU by 10.97% compared to FuseNet, a model that combines optical bands and geo-scientific features. Our method presents a new technical solution to achieve accurate slum mapping, offering potential benefits for regional and global slum mapping and upgrading initiatives.

We report a compact, tunable, self-starting, all-fiber laser-based asynchronous optical sampling (ASOPS) system. Two Er-doped fiber oscillators were used as the pulsed-laser source, whose repetition rate could be set at 100 MHz with a tuning range of 1.25 MHz through a fiber delay line. By employing phase-locked and temperature control loops, the repetition rate offset of the two lasers was stabilized with 7.13 × 10−11 fractional instability at an average time of 1 s. Its capabilities in the terahertz regime were demonstrated by terahertz time-domain spectroscopy, achieving a spectral bandwidth of 3 THz with a dynamic range of 30 dB. The large range of repetition rate adjustment in our ASOPS system has the potential to be a powerful tool in the terahertz regime.

The main purpose of this study is to analyze the main influencing factors of the landslide in the coal mine area and, on this basis, establish the sensitivity zoning model of the landslide. Considering the difficulty to obtain the expected results by using machine learning under the condition of lacking data, the typical landslide is used as the data basis, that is, the Fenxi coal mine and Xishan Bujiu coal mine are selected as the coal mining landslide points. Various factors, such as goaf, land subsidence, slope structure, formation lithology, and various indicators are used as input data sources, and artificial neural network (ANN) datasets are used for training to establish a pre-training model. Using the pre-training model, the mining landslide sensitivity evaluation model based on transfer learning is established. In order to demonstrate the performance of transfer learning more intuitively, the neural network is introduced to evaluate the evaluation model. The test results show that transfer learning can achieve a transfer effect higher than 0.95, and the regional distributions of highest landslide sensitivity calculated based on self-transfer learning, direct push transfer learning, and inductive transfer learning are 31.33, 35.50, and 33.75%, respectively, which further deduced that inductive transfer learning can be used for evaluating an LSP model.

The food supply–demand balance is a perpetual concern for many countries, especially developing countries, such as Uzbekistan. Using the land resource carrying capacity model, here, food supply and demand for the cereals and calories in Uzbekistan during 1995–2020 were revealed. Despite increased demand for cereals and calories, unstable crop production has led to volatile growth patterns. The carrying capacity of cropland resources under Uzbekistan’s consumption standard shifted from overload to surplus and then to balance. Moreover, the carrying capacity of cropland resources under the healthy diet standard moved from balance to surplus in the past 25-years. Additionally, the calorific equivalent land resource carrying capacity under Uzbekistan’s consumption standard fluctuated, with the carrying state shifting from balance to surplus, and the healthy diet standard still in overload. These findings can help guide sustainable production and consumption strategies in Uzbekistan and other countries by analyzing the consumption structure and changes in supply and demand relationships.

Nepal is one of the least developed countries in the world, with more than 80% of the population engaged in agricultural production and more than two-fifths of the population still living below the poverty line. Ensuring food security has always been a key national policy in Nepal. Using a nutrient conversion model and an improved resource carrying capacity model as well as statistical data and household questionnaires, an analysis framework for food supply balance is developed in this study, which quantitatively analyzes the balance of food supply and demand in Nepal from the perspectives of food and calories during the period 2000–2020. Nepal’s agricultural production and consumption have increased significantly, and the diet has been relatively stable over the past two decades. The diet structure is stable and homogeneous, with plant products occupying the absolute position in overall dietary consumption. The supply of food and calories varies widely from region to region. Although the increasing supply level at the national scale can meet the needs of the current population, the food self-sufficiency level cannot meet the needs of the local population development at the county level due to the influence of population, geographical location, and land resources. We found that the agricultural environment in Nepal is fragile. The government can improve agricultural production capacity by adjusting the agricultural structure, improving the efficiency of agricultural resources, improving the cross-regional flow of agricultural products, and improving international food trade channels. The food supply and demand balance framework provided a reference for achieving balance between the supply and demand of food and calories in a resource-carrying land and provides a scientific basis for Nepal to achieve zero hunger under the framework of the Sustainable Development Goals. Furthermore, development of policies in order to increase agricultural productivity will be critical for improving food security in agricultural countries such as Nepal.

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.

Lightweight alloys produced by pressurized castings suffer from flow-induced microstructural segregation due to the migration of externally solidified crystals (ESCs). Although some qualitative research has been carried out on ESCs migration, quantitative prediction of it is still demanded. In this respect, an ESCs migration model based on hydrodynamics and the rheological behaviour of semi-solid metals (SSMs) is proposed to estimate flow-induced microstructural segregation. By employing the model, a plug flow region having a decisive influence on ESCs migration is observed according to the flow simulation of yield-pseudoplastic SSMs. Good agreement between the experimental data and the simulation results is obtained, suggesting that such flow-induced microstructural segregation is controllable by manipulating process parameters such as solid fraction, cavity size and filling velocity. A real-time in situ synchrotron X-ray radiography experiment is carried out to reveal the nature of ESCs migration and provide evidence for the hypothesized flow-induced ESCs migration mechanism. A semi-empirical solid fraction-related rheological (SFR) model capable of relating rheological parameters with solid fraction of SSMs is also proposed, enabling the optimization of process parameters.

Abstract The performance of 33 Coupled Model Intercomparison Project 5 (CMIP5) general circulation models (GCMs) in temperature simulations in the Tibetan Plateau (TP) was comprehensively assessed by an improved score‐based and multiple‐criteria method using data collected from 1961 to 2005. Future temperatures were also simulated based on a multimodel ensemble coupled with the Delta downscaling method for near‐term (2006–2050) and long‐term (2051–2095) projections under Representative Concentration Pathways (RCP, scenarios RCP4.5 and RCP8.5). Our results demonstrated that all the GCMs evaluated in our study could capture the seasonal temperature patterns. However, most GCMs tended to underestimate temperatures by an average of −2.0°C. All the GCMs could effectively simulate temporal distribution, with a mean correlation coefficient of 0.997. However, they did not perform well in reproducing spatial distribution. Different assessment criteria lead to inconsistent results; however, the improved rank score method with multiple criteria provided a robust assessment of GCMs performance. MPI‐ESM‐LR, CMCC‐CMS, and GFDL‐ESM 2M showed a better temperature simulation performance compared to the other GCMs that we have assessed. Topographic correction could effectively enhance spatial distribution simulation; however, this increased temperature underestimation. Future temperatures were projected to increase by 1.4°C and 1.6°C in near‐term, and by 2.4°C and 4.0°C in long‐term under RCP4.5 and RCP8.5 scenarios, respectively. High temperatures mainly occurring in the southeastern end of the Himalayas, as well as the northern and southeastern margins of the TP. The results are expected to provide valuable information on climate change and its impact on hydrology, ecology, and socioeconomics of the TP.

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.

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.

The complex roles of the steroid hormone brassinosteroids (BRs) in many different yield- and stress-related traits make it difficult to utilize the hormones for crop improvement. Here, we show that SERK2 as a BR signaling component is a potentially useful candidate for BR manipulation in rice. We generated multiple mutant alleles of SERK2 by CRISPR/Cas9 editing and show that knockout of SERK2 results in a compact structure accompanied with increased grain size. SERK2 is localized on plasma membrane and can interact with OsBRI1, the BR receptor, suggesting its conserved role as co-receptor in BR signaling. Consistently, the mutant has impaired BR sensitivity compared to wild type. Notably, the mutant is highly sensitive to salt stress as evaluated by plant survival rate as well as transcriptome analysis, whereas has slightly increased sensitivity to ABA, the stress hormone. By contrast, overexpression of SERK2 significantly enhances grain size and salt stress resistance, importantly, without affecting plant architecture. Furthermore, while salt suppresses SERK2 transcription, the protein is greatly induced by salt stress. Taken together, we propose that the adverse condition induces SERK2 accumulation to enhance early BR signaling on plasma membrane in favor of the anti-stress response. Our results illustrate the great potentials of specific BR components such as SERK2 for crop improvement by utilizing flexible strategies.

Tibet constitutes a major part of the Qinghai–Tibet Plateau (QTP) and is a typical ethnic minority (e.g., Tibetan) and ecologically fragile area in the world. Land resources are one of the most important foundations of food production, and Tibet’s increasingly multi-type food demands are putting new pressure on land resources. However, there is still debate on how many people can be supported with the food production in Tibet. Investigating the land carrying capacity (LCC) in Tibet is very important for maintaining food security and formulating sustainable land management and utilization. Based on an analysis of the unique characteristics of the local farming, pastoral production, and dietary consumption, the spatio-temporal patterns of theLCC in Tibet in 2000–2019 were quantitatively assessed against the grain demands and calorie requirements at three different standards of living (i.e., basic prosperity, comprehensive moderate prosperity, and affluence). The dietary consumption was characterized by the high consumption of grains and meat products, and the low consumption of fruits and vegetables. The LCC in Tibet has continued to increase. The LCC in approximately 60% of the counties increased, with the high-LCC counties concentrated mainly in the Yarlung Zangbo River—Nyangqu River—Lhasa River area, and municipal districts and pastoral counties generally experiencing a low LCC. The load on land resources (LoL) in Tibet exhibited the characteristic of overall balance with local overloads and increasing tensions. More than 50% of the counties experienced population overload, mainly in municipal districts and pastoral counties. Food surplus was mainly found in farming counties, while the food production in pastoral counties was generally unable to meet the calorie demand. Considering the important role of land use in maintaining regional food security and ecological security, the conversion of grassland to cultivated land, the occupation of cultivated land, and the phenomenon of cultivated land was used to non grain should be avoided. Trans-regional transport of food should be strengthened to meet the calorie needs in population overload areas in the future. Our study provides a perspective for evaluating the pressure of land resources. The result can provide a reference for realizing the balance of grain and calorie supply–demand and lay a foundation for formulating sustainable land use policies in the QPT.

Since the outbreak of the coronavirus disease 2019 (COVID-19), political and academic circles have focused significant attention on stopping the chain of COVID-19 transmission. In particular outbreaks related to cold chain food (CCF) have been reported, and there remains a possibility that CCF can be a carrier. Based on CCF consumption and trade matrix data, here, the “source” of COVID-19 transmission through CCF was analyzed using a complex network analysis method, informing the construction of a risk assessment model reflecting internal and external transmission dynamics. The model included the COVID-19 risk index, CCF consumption level, urbanization level, CCF trade quantity, and others. The risk level of COVID-19 transmission by CCF and the dominant risk types were analyzed at national and global scales as well as at the community level. The results were as follows. (1) The global CCF trade network is typically dominated by six core countries in six main communities, such as Indonesia, Argentina, Ukraine, Netherlands, and the USA. These locations are one of the highest sources of risk for COVID-19 transmission. (2) The risk of COVID-19 transmission by CCF in specific trade communities is higher than the global average, with the Netherlands–Germany community being at the highest level. There are eight European countries (i.e., Netherlands, Germany, Belgium, France, Spain, Britain, Italy, and Poland) and three American countries (namely the USA, Mexico, and Brazil) facing a very high level of COVID-19 transmission risk by CCF. (3) Of the countries, 62% are dominated by internal diffusion and 23% by external input risk. The countries with high comprehensive transmission risk mainly experience risks from external inputs. This study provides methods for tracing the source of virus transmission and provides a policy reference for preventing the chain of COVID-19 transmission by CCF and maintaining the security of the global food supply chain.

Exploring how urban form affects the Particulate Matter 2.5 (PM2.5) concentration could help to find environmentally friendly urbanization. According to the definition of geography, this paper constructs a comprehensive urban form evaluation index system applicable to many aspects. Four urban form metrics, as well as road density and five control variables are selected. Based on 2015 data on China’s 340 prefecture-level cities, the spatial regression model and geographically weighted regression model were used to explore the relationship between the urban form evaluation index system and PM2.5 pollution. The main results show that the spatial distribution of PM2.5 in China follows an increasing trend from northwest to southeast. Urban form indicators such as AI, LPI, PLAND, LSI and road density were all significantly related to PM2.5 concentrations. More compact urban construction, lower fragmentation of urban land, and lower density of the road network are conducive factors for improving air quality conditions. In addition, affected by seasonal changes, the correlation between urban form and PM2.5 concentration in spring and winter is higher than that in summer and winter. This study confirmed that a reasonable urban planning strategies are very important for improving air quality.

The release of global gridded population datasets, including the Gridded Population of the World (GPW), Global Human Settlement Population Grid (GHS-POP), WorldPop, and LandScan, have greatly facilitated cross-comparison for ongoing research related to anthropogenic impacts. However, little attention is paid to the consistency and discrepancy of these gridded products in the regions with rapid changes in local population, e.g., Mainland Southeast Asia (MSEA), where the countries have experienced fast population growth since the 1950s. This awkward situation is unsurprisingly aggravated because of national scarce demographics and incomplete census counts, which further limits their appropriate usage. Thus, comparative analyses of them become the priority of their better application. Here, the consistency and discrepancy of the four common global gridded population datasets were cross-compared by combing the 2015 provincial population statistics (census and yearbooks) via error-comparison based statistical methods. The results showed that: (1) the LandScan performs the best both in spatial accuracy and estimated errors, then followed by the WorldPop, GHS-POP, and GPW in MSEA. (2) Provincial differences in estimated errors indicated that the LandScan better reveals the spatial pattern of population density in Thailand and Vietnam, while the WorldPop performs slightly better in Myanmar and Laos, and both fit well in Cambodia. (3) Substantial errors among the four gridded datasets normally occur in the provincial units with larger population density (over 610 persons/km2) and a rapid population growth rate (greater than 1.54%), respectively. The new findings in MSEA indicated that future usage of these datasets should pay attention to the estimated population in the areas characterized by high population density and rapid population growth.

International food trade is an integral part of the food system, and the COVID-19 pandemic has exposed the fragility of external food supplies. Based on the perspective of cereals trade networks (CTN), the pandemic risk is combined with the trade intensity between countries, and an assessment model of cereals external supply risk is constructed that includes external dependence index (EDI), import concentration, and risk of COVID-19 from import countries index (RICI). The results show that: (1) the global main CTN have typical scale-free characteristics, and seven communities are detected under the influence of the core countries; (2) about 60%, 50%, and 70% of countries face risks of medium and above (high and very high) external dependence, concentration of imports, and COVID-19 in the country of origin, respectively. Under the influence of the pandemic, the risk of global external cereal supply index (RECSI) has increased by 65%, and the USA-CAN communities show the highest risk index; (3) the countries with a very high risk are mainly the Pacific island countries and the Latin American and African countries. In addition, Japan, Mexico, South Korea, and 80% of the net food-importing developing countries are at high or very high RECSI levels. Approximately 50% of countries belong to the compound risk type, and many export countries belong to the RICI risk type; (4) global external food supply is subjected to multiple potential threats such as trade interruption, “price crisis”, and “payment dilemma”. The geographical proximity of community members and the geographical proximity of the pandemic risk is superimposed, increasing the regional risk of external food supply; and (5) this study confirms that the food-exporting countries should avoid the adoption of food export restriction measures and can prevent potential external supply risks from the dimensions of maintaining global food liquidity and promoting diversification of import sources. We believe that our assessment model of cereals external supply risk comprises a useful method for investigations regarding the international CTN or global food crisis under the background of the pandemic.

Spatial data of regional populations are indispensable in studying the impact of human activities on resource utilization and the ecological environment. Because the differences between datasets and their spatial distribution are still unclear, this has become a puzzle in data selection and application. This study is based on four mainstream spatialized population datasets: the History Database of the Global Environment version 3.2.000 (HYDE), Gridded Population of the World version 4 (GPWv4), Global Human Settlement Layer (GHSL), and WorldPop. In view of possible influences of geographical factors, this study analyzes the differences in accuracy of population estimation by computing relative errors and population spatial distribution consistency in different regions by comparing datasets pixel by pixel. The results demonstrate the following: (1) Source data, spatialization methods, and case area features affect the precision of datasets. As the main data source is statistical data and the spatialization method maintains the population in the administrative region, the populations of GPWv4 and GHSL are closest to the statistical data value. (2) The application of remote sensing, mobile communication, and other geospatial data makes the datasets more accurate in the United Kingdom, with rich information, and the absolute value of relative errors is less than 4%. In the Tibet Autonomous Region of China, where data are hard to obtain, the four datasets have larger relative errors. However, the area where the four datasets are completely consistent is as high as 84.73% in Tibet, while in the UK it is only 66.76%. (3) The areas where the spatial patterns of the four datasets are completely consistent are mainly distributed in areas with low population density, or with developed urbanization and concentrated population distribution. Areas where the datasets have poor consistency are mainly distributed in medium population density areas with high urbanization levels. Therefore, in such areas, a more careful assessment should be made during the data application process, and more emphasis should be placed on improving data accuracy when using spatialization methods.

Crop production potential is an index used to evaluate crop productivity capacity in one region. The spatial production potential can help give the maximum value of crop yield and visually clarify the prospects of agricultural development. The DSSAT (Decision Support System for Agrotechnology Transfer) model has been used in crop growth analysis, but spatial simulation and analysis at high resolution have not been widely performed for exact crop planting locations. In this study, the light-temperature production potential of winter wheat was simulated with the DSSAT model in the winter wheat planting area, extracted according to Remote Sensing (RS) image data in the Jing-Jin-Ji (JJJ) region. To obtain the precise study area, a Decision Tree (DT) classification was used to extract the winter wheat planting area. Geographic Information System (GIS) technology was used to process spatial data and provide a map of the spatial distribution of the production potential. The production potential of winter wheat was estimated in batches with the DSSAT model. The results showed that the light-temperature production potential is between 4238 and 10,774 kg/ha in JJJ. The production potential in the central part of the planting area is higher than that in the south and north in JJJ due to the influences of light and temperature. These results can be useful for crop model simulation users and decision makers in JJJ.

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.

Effects of underlying uniform current on the nonlinear hydroelastic waves generated due to an infinite floating plate are studied analytically, under the hypotheses that the fluid is homogeneous, incompressible, and inviscid. For the case of irrotational motion, the Laplace equation is the governing equation, with the boundary conditions expressing a balance among the hydrodynamics, the uniform current, and elastic force. It is found that the convergent series solutions, obtained by the homotopy analysis method (HAM), consist of the nonlinear hydroelastic wave profile and the velocity potential. The impacts of important physical parameters are discussed in detail. With the increment of the following current intensity, we find that the amplitudes of the hydroelastic waves decrease very slightly, while the opposing current produces the opposite effect on the hydroelastic waves. Furthermore, the amplitudes of waves increase very obviously for higher opposing current speed but reduce very slightly for higher following current speed. A larger amplitude of the incident wave increases the hydroelastic wave deflections for both opposing and following current, while for Young’s modulus of the plate there is the opposite effect.

In this study, the performance of 33 Coupled Model Intercomparison Project 5 (CMIP5) global climate models (GCMs) in simulating precipitation over the Tibetan Plateau (TP) was assessed using data from 1961 to 2005 by an improved score-based method, which adopts multiple criteria to achieve a comprehensive evaluation. The future precipitation change was also estimated based on the Delta method by selecting the submultiple model ensemble (SMME) in the near-term (2006−2050) and far future (2051−2095) periods under Representative Concentration Pathways (RCP) scenarios RCP4.5 and RCP8.5. The results showed that most GCMs can reasonably simulate the precipitation pattern of an annual cycle; however, all GCMs overestimated the precipitation over TP, especially in spring and summer. The GCMs generally provide good simulations of the temporal characteristics of precipitation, while they did not perform as well in reproducing its spatial distributions. Different assessment criteria lead to inconsistent results; however, the improved rank score method, which adopts multiple criteria, provided a robust assessment of GCMs performance. The future annual precipitation was projected to increase by ~6% in the near-term with respect to the period 1961−2005, whereas increases of 12.3% and 16.7% are expected in the far future under RCP4.5 and RCP8.5 scenarios, respectively. Similar spatial distributions of future precipitation changes can be seen in the near-term and far future periods under the two scenarios, and indicate that the most predominant increases occurred in the north of TP. The results of this study are expected to provide valuable information on climate change, and for water resources and agricultural management in TP.

The blade pitch angle has a significant influence on the aerodynamic characteristics of horizontal axis wind turbines. However, few research results have revealed its impact on the straight-bladed vertical axis wind turbine (Sb-VAWT). In this paper, wind tunnel experiments and CFD simulations were performed at the Sb-VAWT to investigate the effect of different blade pitch angles on the pressure distribution on the blade surface, the torque coefficient, and the power coefficient. In this study, the airfoil type was NACA0021 with two blades. The Sb-VAWT had a rotor radius of 1.0 m with a spanwise length of 1.2 m. The simulations were based on the k-ω Shear Stress Transport (SST) turbulence model and the wind tunnel experiments were carried out using a high-speed multiport pressure device. As a result, it was found that the maximum pressure difference on the blade surface was obtained at the blade pitch angle of β = 6° in the upstream region. However, the maximum pressure coefficient was shown at the blade pitch angle of β = 8° in the downstream region. The torque coefficient acting on a single blade reached its maximum value at the blade pitch angle of β = 6°. As the tip speed ratio increased, the power coefficient became higher and reached the optimum level. Subsequently, further increase of the tip speed ratio only led to a quick reversion of the power coefficient. In addition, the results from CFD simulations had also a good agreement with the results from the wind tunnel experiments. As a result, the blade pitch angle did not have a significant influence on the aerodynamic characteristics of the Sb-VAWT.

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.

In the title compound, [Sm(C9I3O6)(C3H7NO)3]n, the SmIII atom is coordinated by nine O atoms, viz. six carboxylate O atoms from three 2,4,6-triiodobenzene-1,3,5-tricarboxylate (I3BTC) ligands and three O atoms from three N,N-dimethylformamide (DMF) molecules. Each I3BTC ligand bridges three SmIII atoms, generating a three-dimensional metal-organic framework structure. The asymmetric unit contains one SmIII ion and one I3BTC anion, both situated on a threefold axis, and one DMF molecule in a general position.