Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Synergistic interaction of perovskite oxides and N-doped graphene in versatile electrocatalyst

Abstract: Multifunctional electrocatalysts with high catalytic activity and durability are needed for environmentally clean energy technologies such as water-splitting devices and metal–air batteries. Herein, we investigate a new catalyst, P-3G, consisting of a cation-ordered perovskite (PrBa0.5Sr0.5)0.95Co1.5Fe0.5O5+δ (PBSCF) and 3D porous N-doped graphene (3DNG). This new type of composite electrocatalyst simultaneously exhibited outstanding multifunctional catalytic activities and excellent stabilities for the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER). A possible mechanism for the synergistic effects between perovskite oxides and 3DNG on ORR, OER and HER was firstly proposed by DFT calculations. The electrocatalytic activity of P-3G appeared to have great potential for a rechargeable Zn–air battery system. The operating voltage differences between the charge and discharge (Δη) of P-3G and Pt/C–IrO2 after 110 cycles were 0.63 V and 0.87 V, respectively, indicating the substantial durability of P-3G. Moreover, a water-splitting device using P-3G efficiently produced H2 and O2 gases at rates of 0.859 μL s−1 and 0.417 μL s−1, respectively. This study highlights extended applications of coupled perovskite oxides/carbon materials as versatile electrocatalysts for ORR, OER, and HER and unveils the cause of synergistic interactions between oxide and carbon by DFT calculation.

Multilabel Remote Sensing Image Retrieval Based on Fully Convolutional Network

Abstract: Conventional remote sensing image retrieval (RSIR) system usually performs single-label retrieval where each image is annotated by a single label representing the most significant semantic content of the image. In this scenario, however, the scene complexity of remote sensing images is ignored, where an image might have multiple classes (i.e., multiple labels), resulting in poor retrieval performance. We therefore propose a novel multilabel RSIR approach based on fully convolutional network (FCN). Specifically, FCN is first trained to predict segmentation map of each image in the considered image archive. We then obtain multilabel vector and extract region convolutional features of each image based on its segmentation map. The extracted region features are finally used to perform region-based multilabel retrieval. The experimental results show that our approach achieves state-of-the-art performance in contrast to handcrafted and convolutional neural network features.

Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China

Abstract: . Aerosol pollution in eastern China is an unfortunate consequence of the region's rapid economic and industrial growth. Here, sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify the aerosols based on size and absorption. Bimodal size distributions were found throughout the year, but larger volumes and effective radii of fine-mode particles occurred in June and September due to hygroscopic growth and/or cloud processing. Increases in the fine-mode particles in June and September caused AOD 440 nm > 1.00 at most sites, and annual mean AOD 440 nm values of 0.71–0.76 were found at the urban sites and 0.68 at the rural site. Unlike northern China, the AOD 440 nm was lower in July and August ( ∼ 0.40–0.60) than in January and February (0.71–0.89) due to particle dispersion associated with subtropical anticyclones in summer. Low volumes and large bandwidths of both fine-mode and coarse-mode aerosol size distributions occurred in July and August because of biomass burning. Single-scattering albedos at 440 nm (SSA 440 nm) from 0.91 to 0.94 indicated particles with relatively strong to moderate absorption. Strongly absorbing particles from biomass burning with a significant SSA wavelength dependence were found in July and August at most sites, while coarse particles in March to May were mineral dust. Absorbing aerosols were distributed more or less homogeneously throughout the region with absorption aerosol optical depths at 440 nm ∼ 0.04–0.06, but inter-site differences in the absorption Angstrom exponent indicate a degree of spatial heterogeneity in particle composition. The annual mean DARF was − 93 ± 44 to − 79 ± 39 W m −2 at the Earth's surface and ∼ − 40 W m −2 at the top of the atmosphere (for the solar zenith angle range of 50 to 80 ∘ ) under cloud-free conditions. The fine mode composed a major contribution of the absorbing particles in the classification scheme based on SSA, fine-mode fraction and extinction Angstrom exponent. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing algorithms.

A constrained differential evolution algorithm to solve UAV path planning in disaster scenarios

Abstract: Disasters have caused significant losses to humans in the past decades. It is essential to learn about the disaster situation so that rescue works can be conducted as soon as possible. Unmanned aerial vehicle (UAV) is a very useful and effective tool to improve the capacity of disaster situational awareness for responders. In the paper, UAV path planning is modelled as the optimization problem, in which fitness functions include travelling distance and risk of UAV, three constraints involve the height of UAV, angle of UAV, and limited UAV slope. An adaptive selection mutation constrained differential evolution algorithm is put forward to solve the problem. In the proposed algorithm, individuals are selected depending on their fitness values and constraint violations. The better the individual is, the higher the chosen probability it has. These selected individuals are used to make mutation, and the algorithm searches around the best individual among the selected individuals. The well-designed mechanism improves the exploitation and maintains the exploration. The experimental results have indicated that the proposed algorithm is competitive compared with the state-of-art algorithms, which makes it more suitable in the disaster scenario.

Waste cooking oil as an energy resource: Review of Chinese policies

Abstract: Converting waste cooking oil into biofuel represents a three-win solution, dealing simultaneously with food security, pollution, and energy security. In this paper, we encode the policy documents of waste cooking oil refining biofuel in China based on content analysis, and explore the related policies from the two dimensions as basic policy tools and enterprises supply chain. Research indicates the weak institution coordination of policy issuing entities. Also, the findings show that tools of regulatory control and goal planning are overused. Policies of government procurement, outsourcing and biofuel consumption are relatively scarce. Generally, government focuses more on formulating policies from the strategic, administrative and regulatory aspects, while less on market-oriented initiatives as funding input and financial support.