Identifying the uneven distribution of health and education services in China using open geospatial data

Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.

正电子湮没谱表征热处理工艺对聚碳酸酯力学性能的影响

考察了退火和淬火2种热处理方法所用的不同热处理温度和时间对聚碳酸酯力学性能的影响,并采用正电子湮没谱分析经过不同热处理工艺后聚碳酸酯内部自由体积的含量。结果表明,在玻璃化转变温度附近及以上进行一定时间的淬火可通过增大内部自由体积含量和尺寸来显著改善聚碳酸酯的韧性,降低材料的屈服强度和弯曲强度,提高缺口冲击强度和拉伸强度。在玻璃化转变温度以下,淬火不能改变材料内部的自由体积,不能提高材料的韧性。退火只能降低材料内部自由体积的含量和尺寸,但不受温度和时间的影响,且材料的拉伸强度、断裂伸长率和缺口冲击强度大幅降低。

相对分子质量和退火处理对聚碳酸酯力/热性能的影响

文中研究了不同相对分子质量聚碳酸酯在经历退火处理后力学性能和热性能的变化,深入分析了相对分子质量和退火处理的影响机制。结果表明,高分子量聚碳酸酯未退火状态下抗拉伸断裂性能和冲击性能更优,相对分子质量降低和退火处理会提升拉伸强度与弯曲性能。光弹应力分析显示,高分子量未退火聚碳酸酯的残余应力高,冲击断面表现为韧性断裂,对应冲击强度高。动态力学热分析和差示扫描量热法研究发现,随着相对分子质量增大,聚碳酸酯的玻璃化转变温度升高,链段运动更加趋于弹性响应。

厚壁结构聚碳酸酯制品注射成型的典型缺陷与控制

采用单因素多水平的试验方法,考察了注射成型工艺对厚壁结构聚碳酸酯制品的典型缺陷(表观缺陷、几何收缩和残余应力)的影响,工艺条件包括模具温度、注射速度、保压时间、保压压力和冷却时间。通过制品表观质量、收缩状态和应力分布的表征,分析了不同缺陷的变化规律。结果表明,表观缺陷中的真空泡在模具温度120℃以上、保压时间20 s、冷却时间60 s时基本不存在,而表面气痕在注射速度低于5 mm/s时完全消除。随着保压压力、保压时间和模具温度的增加,制品几何收缩显著降低,尺寸精度和几何变形得到有效控制。制品的残余应力受成型工艺的影响,但退火处理的影响更加明显,也是降低残余应力的有效手段。

注射成型后期热处理对聚碳酸酯性能的影响

考察了退火方式和退火工艺对聚碳酸酯(PC)残余应力和拉伸性能的影响。光弹法定量分析结果表明,退火能够显著降低PC的残余应力,残余应力随退火温度升高和退火时间延长而减小。但退火温度越高,退火温度和退火时间对PC残余应力影响差异性逐渐减弱。拉伸测试结果表明,130℃4 h退火工艺下,开模取件后立即退火使PC拉伸强度提高5.5%,而完全冷却后退火则使PC拉伸强度降低8.7%。综合分析表明,退火消除的流动残余应力将降低PC的拉伸强度,而退火消除的热残余应力则会提高PC的拉伸强度,退火过程中拉伸强度的变化,是流动残余应力和热残余应力偶合作用变化的结果。

Thermoacoustic-reflected focusing lens based on acoustic Bessel-like beam with phase manipulation

We report the realization of broadband reflected acoustic focusing lenses based on thermoacoustic phased arrays of Bessel-like beams, in which the units of phase manipulation are composed of three rigid insulated boundaries and a thermal insulation film in air with different temperatures. Based on these units, we realize a reflected focusing lens which can focus reflected acoustic energy on a line, and its fractional bandwidth can reach about 0.29. In addition, we discuss the influences of the base angle of Bessel-like beam, the number of basic unit, and the variation of unit temperature on focusing performances in details. Furthermore, the reflected focusing lens for the cylindrical acoustic wave based on the Bessel-like beam is also demonstrated. The proposed focusing lens has the advantages of a broad working bandwidth, large focus size,and high robustness, which may provide possibilities for the design and application of acoustic lenses.

Ultra-broadband acoustic ventilation barrier based on multi-cavity resonators

The numerical simulations and experimental results of an ultra-broadband acoustic ventilation barrier composed of periodic unit cells are reported in this paper.Based on multiple mechanisms,including sound absorption by eigenmodes of the unit cell and sound reflection by a plate structure on upper surface of the unit cell,a single-layer ventilation barrier with broadband sound reduction is designed,and its working bandwidth can reach about 1560 Hz.The experimental results accord well with the simulation results.Furthermore,two types of three-layer ventilation barriers are designed and demonstrated by using the unit cells with different values of a(the length of the hollow square region)and w(the width of the channel between the adjacent cavities),and the bandwidths of both ventilation barriers can increase to 3160 Hz and 3230 Hz,respectively.The designed barrier structures have the advantages of ultra-broadband sound reduction and ventilation,which paves the way to designing high-performance ventilation barriers for the applications in environmental protection and architectural acoustics.

Steady-State Visual Evoked Potential (SSVEP) in a New Paradigm Containing Dynamic Fixation Points

Steady-state visual evoked potential(SSVEP)has become a powerful tool for Brain Computer Interface(BCI)because of its high signal-tonoise ratio,high information transmission rate,and minimal user training.At present,the edge information of each region cannot be identified in spatial coding based on SSVEP-BCI technology,and the user experience is poor.To solve this problem,this paper designed a new paradigm to explore the relationship between the fixation point position of continuous sliding and the correlation coefficient ratio in the dualfrequency case.Firstly,the standard sinusoidal signal was employed to simulate the Electroencephalogram(EEG)signal,which verified the reliability of characterizing the amplitude variation of test signal by correlation coefficient.Then,the relationship between the amplitude response of SSVEP and the distance between the fixation point and the stimulus in the horizontal direction was tested by Canonical Correlation Analysis(CCA)and Filter bank CCA(FBCCA).Finally,the experimental data were offline analyzed under the condition of continuous sliding of the fixation point.It is feasible and reasonable to detect the amplitude change of frequency component in SSVEP by utilizing the spatial coding method in this paper to improve the extraction accuracy of spatial information.

Ultra-broadband asymmetric acoustic transmission with single transmitted beam

We report both experimentally and numerically that ultra-broadband asymmetric acoustic transmission is realized by a brass plate and a right triangle reflector immersed in water. This exotic phenomenon arises from the asymmetric excitation of the leaky asymmetric zero-order Lamb mode in the brass plate induced by the incident angle of external bulk waves. The results show that the bandwidth of the asymmetric acoustic transmission could reach 2000 k Hz, and the positive transmitted wave is only a single acoustic beam. The device has the advantages of ultra-broadband, single transmitted beam,and simpler structure, which has great potential applications in ultrasonic devices.

Progress of big geodata

The rapid growth of big geodata has been facilitated by the development of sensing technologies,such as mobile location,Earth observation,and other sensor networks,as well as by the continuous expansion of their application fields[1–3].In essence,big geodata is a large-scale coverage sample set involving time,space,and attribute dimensions for geographical phenomena[2].

Influence of surface charges on the emission polarization properties of single CdSe/CdS dot-in-rods

We report an experimental investigation of the influence of surface charges on the emission polarization properties of single CdSe/CdS dot-in-rods(DRs),which is important for their polarization-based practical applications.By covering the single DRs with N-type semiconductor indium tin oxide(ITO)nanoparticles,the surface of single DRs is charged by ITO through interracial electron transfer.This is confirmed by the experimental observations of the reduced photoluminescence intensities and lifetimes as well as the suppressing blinking.It is found that the full width at half maximum of histogram of polarization degrees of the single DRs is broadened from 0.24(on glass)to 0.41(in ITO).In order to explain the exprimental results,the band-edge exciton fine structure of single DRs is calculated by taking into account the sample parameters,the emission polarization,and the surface charges.The calculation results show that the level ordering of the emitting states determines the polarization degrees tending to increase or decrease under the influence of surface electrons.The surface electrons can induce an increase in the spacing between the emitting levels to change the populations and thus change the polarization degrees.In addition,different numbers of surface electrons may randomly distribute on the long CdSe/CdS rods,leading to the heterogeneous influences on the single DRs causing the broadening of polarization degrees also.

First wetland mapping at 10-m spatial resolution in South America using multi-source and multi-feature remote sensing data

Wetland degradation has been accelerating in recent years globally. Accurate information on the geographic distribution and categories of wetlands is essential for their conservation and management. Despite being the world′s fourth largest continent, South America has limited research on wetland mapping, and there is currently no available map that provides comprehensive information on wetland distribution and categories in the region. To address this issue, we used Sentinel-1, Sentinel-2 and SRTM data, developed a sample collection method and a wetland mapping method with a collection of multi-source features such as optical features, polarization features and shape features for South American wetlands. We produced a 10-m resolution wetland map based on the Google Earth Engine(GEE) platform. Our Level-1 wetland cover map accurately captured six wetland sub-categories with an overall accuracy of 96.24% and a kappa coefficient of 0.8649, while our Level-2 water cover map included five sub-categories with an overall accuracy of 97.23% and a kappa coefficient of0.9368. The results show that the total area of existing wetlands in South America is approximately 1,737,000 km~2, which is6.8% of the total land area. Among the ten wetland categories, shallow sea had the largest area(960,527.4 km~2), while aquaculture ponds had the smallest area 1513.6 km~2. Swamp had the second largest area(306,240.1 km~2). Brazil, Argentina,Venezuela, Bolivia, and Colombia were found to have the largest wetland areas, with Brazil and Colombia having the most diverse wetland categories. This product can serve as baseline data for subsequent monitoring, management, and conservation of South American wetlands.

Exploiting multi-channels deep convolutional neural networks for multivariate time series classification

Time series classification is related to many dif- ferent domains, such as health informatics, finance, and bioinformatics. Due to its broad applications, researchers have developed many algorithms for this kind of tasks, e.g., multivariate time series classification. Among the classifi- cation algorithms, k-nearest neighbor （k-NN） classification （particularly 1-NN） combined with dynamic time warping （DTW） achieves the state of the art performance. The defi- ciency is that when the data set grows large, the time con- sumption of 1-NN with DTW will be very expensive. In con- trast to 1-NN with DTW, it is more efficient but less ef- fective for feature-based classification methods since their performance usually depends on the quality of hand-crafted features. In this paper, we aim to improve the performance of traditional feature-based approaches through the feature learning techniques. Specifically, we propose a novel deep learning framework, multi-channels deep convolutional neu- ral networks （MC-DCNN）, for multivariate time series classi- fication. This model first learns features from individual uni- variate time series in each channel, and combines information from all channels as feature representation at the final layer. Then, the learnt features are applied into a multilayer percep- tron （MLP） for classification. Finally, the extensive experi- ments on real-world data sets show that our model is not only more efficient than the state of the art but also competitive in accuracy. This study implies that feature learning is worth to be investigated for the problem of time series classification.

In-situ fabricated anisotropic halide perovskite nanocrystals in polyvinylalcohol nanofibers: Shape tuning and polarized emission

We report an in-situ fabrication of halide perovskite (CH3NH3PbX3,CH3NH3 =methylammonium,MA,X =Cl,Br,I) nanocrystals in polyvinylalcohol (PVA) nanofibers (MAPbX3@PVA nanofibers) through electrospinning a perovskite precursor solution.With the content of the precursors increased,the resulting MAPbBr3 nanocrystals in PVA matrix changed the shape from ellipsoidal to pearl-like,and finely into rods-like.Optimized MAPbBr3@PVA nanofibers show strong polarized emission with the photoluminescence quantum yield of up to 72%.We reveal correlations between the shape of in-situ fabricated perovskite nanocrystals and the polarization degree of their emission by comparing experimental data from the single nanofiber measurements with theoretical calculations.Polarized emission of MAPbBr3@PVA nanofibers can be attributed to the dielectric confinement and quantum confinement effects.Moreover,nanofibers can be efficiently aligned by using parallel positioned conductor strips with an air gap as collector.A polarization ratio of 0.42 was achieved for the films of well-aligned MAPbBr3@PVA nanofibers with a macroscale size of 0.5 cm × 2 cm,which allows potential applications in displays,lasers,waveguides,etc.

中国社会经济与环境协调发展的可持续减贫模式

过去几十年里,中国在贫困地区实施了大量的减贫措施,贫困地区的基础设施和居民的生活水平得到了极大地改善.中国的贫困地区与生态保护区和脆弱区高度重叠,而贫困地区社会经济发展与环境之间的协调关系仍然没有得到充分认识.本研究提出了一个包含社会经济和生态环境维度的区县水平指标体系,揭示了贫困地区社会经济和环境的时空变化模式,并评估了它们之间的协调发展关系.研究表明,2000-2020年,中国贫困地区社会经济和环境的协调发展指数得到了加强.同时,在社会经济指数以58.4%的增长率实现增长的同时,环境指数也有明显改善,增长率为19.6%.贫困地区在社会经济发展方面与非贫困地区仍然有较大差距,但贫困地区在环境指数方面表现较好.得益于中国的地理多样性,本文确定了有利有效性、持续性、周期性和有限有效性四种减贫模式,可以为世界其他地区在应对减贫和环境保护方面的挑战提供参考.

Leveraging proficiency and preference for online Karaoke recommendation

Recently,many online Karaoke(KTV)platforms have been released,where music lovers sing songs on these platforms.In the meantime,the system automatically evaluates user proficiency according to their singing behavior.Recommending approximate songs to users can initialize singers5 participation and improve users,loyalty to these platforms.However,this is not an easy task due to the unique characteristics of these platforms.First,since users may be not achieving high scores evaluated by the system on their favorite songs,how to balance user preferences with user proficiency on singing for song recommendation is still open.Second,the sparsity of the user-song interaction behavior may greatly impact the recommendation task.To solve the above two challenges,in this paper,we propose an informationfused song recommendation model by considering the unique characteristics of the singing data.Specifically,we first devise a pseudo-rating matrix by combing users’singing behavior and the system evaluations,thus users'preferences and proficiency are leveraged.Then we mitigate the data sparsity problem by fusing users*and songs'rich information in the matrix factorization process of the pseudo-rating matrix.Finally,extensive experimental results on a real-world dataset show the effectiveness of our proposed model.

Advance of research on modern soil phytolith

Phytolith study is a new branch of micropaleontology with an increasingly important role in geology, archaeology, and plant taxonomy. Phytoliths have several advantages considering their characteristics of small particle size, high production, wide distribution, anti-decomposition, in situ deposition, distinctive morphologies, and element sequestrating capacity. Phytolith assemblages in modem soil have been found to be closely related to modem vegetation types and climate conditions, which forms the basis for the quantitative study of paleoecology, paleoclimate, and bio-geochemical cycles. At present, phytolith studies generally focus on the following four aspects： （1） Morphology： about 260 unduplicated types of phytoliths have been identified in modem soil, of which 110 types are from grasses, 50 types from ferns, woody plants and other angiosperms, whereas the origin plants of the remaining 100 types are still under investigation. （2） Soil phytolith assemblages and vegetation： phytolith assemblages from the topsoil have been used to distinguish surface vegetation types including different forests and grasslands over a typical region. This model has been applied to restore past vegetation conditions and monitor the dynamic evolution of specific vegetation types at different temporal and spatial scales. （3） Soil phytolith assemblages and climate： quantitative and semi-quantitative relationships between phytolith assemblages and a series of climate parameters, such as annual mean temperature, annual mean precipitation and altitude, have been established through mathematical analysis. In this manner, quantitative reconstruction of paleoclimatic parameters has been achieved through the phytolith-climate transfer function model. （4） Soil phytolith and its sequestered elements： in this topic, the content of soil PhytOC （Phytolith-occluded Organic Carbon） and the importance of PhytOC in the bio-geochemical cycle have been the focus. The study of modem soil phytoliths has provided new approaches and many successful cases for solving specific problems in various fields, such as Earth science and archaeology. This study analyzed existing issues in addition to the abovementioned significant progresses, and provides directions for future research on modem soil phytoliths.

Research on automatic spraying of single-walled carbon nanotubes and detection of spraying effects

Single-walled carbon nanotubes(SWNTs)have been introduced as compliant electrodes for dielectric elastomers(DEs)due to fault tolerance.To acquire a better electrostrictive strain and longer lifetime,it is essential to obtain a certain and uniform width of the SWNT electrode.To ensure uniform width manually,a small flux and longer time are necessary.Moreover,it is difficult to control the width of the electrode for the randomness of manual spraying.Therefore,a new type of automatic spraying process is presented in this paper.The width and homogeneity of the electrode can be easily controlled by certain parameters of the process.Two methods for detecting the homogeneity of the electrode are introduced in this paper:Measurement of surface resistance and luminosity.The coefficient of variation(CV)values detected by the two methods are virtually equal and less than 8%,which shows the feasibility of the detection method and homogeneity of automatic spraying.The speed of automatic spraying is 102 mm^(2)/s,which is higher than that of manual spraying.The spraying process and the method used to detect homogeneity in this paper provide a reference for the relevant processes.