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.

Fine particulate matter (PM 2.5) in China at a city level

Abstract: This study presents one of the first long term datasets including a statistical summary of PM2.5 concentrations obtained from one-year monitoring in 190 cities in China. We found only 25 out of 190 cities could meet the National Ambient Air Quality Standards of China, and the population-weighted mean of PM2.5 in Chinese cities are 61 μg/m3, ~3 times as high as global population-weighted mean, highlighting a high health risk. PM2.5 concentrations are generally higher in north than in south regions due to relative large PM emissions and unfavorable meteorological conditions for pollution dispersion. A remarkable seasonal variability of PM2.5 is observed with the highest during the winter and the lowest during the summer. Due to the enhanced contributions from dust particles and open biomass burning, high PM2.5 abundances are also found in the spring (in Northwest and West Central China) and autumn (in East China), respectively. In addition, we found the lowest and highest PM2.5 often occurs in the afternoon and evening hours, respectively, associated with daily variation of the boundary layer depth and anthropogenic emissions. The diurnal distribution of the PM2.5-to-CO ratio consistently displays a pronounced peak during the afternoon periods, reflecting a significant contribution of secondary PM formation.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images

Abstract: Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by 1) the large number of nuclei and the size of high resolution digitized pathology images, and 2) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of “Deep Learning” strategies for classification and analysis of big image data. Histopathology, given its size and complexity, represents an excellent use case for application of deep learning strategies. In this paper, a Stacked Sparse Autoencoder (SSAE), an instance of a deep learning strategy, is presented for efficient nuclei detection on high-resolution histopathological images of breast cancer. The SSAE learns high-level features from just pixel intensities alone in order to identify distinguishing features of nuclei. A sliding window operation is applied to each image in order to represent image patches via high-level features obtained via the auto-encoder, which are then subsequently fed to a classifier which categorizes each image patch as nuclear or non-nuclear. Across a cohort of 500 histopathological images (2200 $\times$ 2200) and approximately 3500 manually segmented individual nuclei serving as the groundtruth, SSAE was shown to have an improved F-measure 84.49% and an average area under Precision-Recall curve (AveP) 78.83%. The SSAE approach also out-performed nine other state of the art nuclear detection strategies.

Novel MOF‐Derived Co@N‐C Bifunctional Catalysts for Highly Efficient Zn–Air Batteries and Water Splitting

Abstract: Metal-organic frameworks (MOFs) and MOF-derived materials have recently attracted considerable interest as alternatives to noble-metal electrocatalysts. Herein, the rational design and synthesis of a new class of Co@N-C materials (C-MOF-C2-T) from a pair of enantiotopic chiral 3D MOFs by pyrolysis at temperature T is reported. The newly developed C-MOF-C2-900 with a unique 3D hierarchical rodlike structure, consisting of homogeneously distributed cobalt nanoparticles encapsulated by partially graphitized N-doped carbon rings along the rod length, exhibits higher electrocatalytic activities for oxygen reduction and oxygen evolution reactions (ORR and OER) than that of commercial Pt/C and RuO2 , respectively. Primary Zn-air batteries based on C-MOF-900 for the oxygen reduction reaction (ORR) operated at a discharge potential of 1.30 V with a specific capacity of 741 mA h gZn-1 under 10 mA cm-2 . Rechargeable Zn-air batteries based on C-MOF-C2-900 as an ORR and OER bifunctional catalyst exhibit initial charge and discharge potentials at 1.81 and 1.28 V (2 mA cm-2 ), along with an excellent cycling stability with no increase in polarization even after 120 h - outperform their counterparts based on noble-metal-based air electrodes. The resultant rechargeable Zn-air batteries are used to efficiently power electrochemical water-splitting systems, demonstrating promising potential as integrated green energy systems for practical applications.

Decontamination of Bisphenol A from Aqueous Solution by Graphene Adsorption

Abstract: The decontamination of bisphenol A (BPA) from aqueous solution by graphene adsorption was investigated. The maximum adsorption capacity (qm) of graphene for BPA obtained from a Langmuir isotherm was 182 mg/g at 302.15 K, which was among the highest values of BPA adsorption compared with other carbonaceous adsorbents according to the literature. Both π–π interactions and hydrogen bonds might be responsible for the adsorption of BPA on graphene, and the excellent adsorption capacity of graphene was due to its unique sp2-hybridized single-atom-layer structure. Therefore, graphene could be regarded as a promising adsorbent for BPA removal in water treatment. The kinetics and isotherm data can be well described by the pseudo-second-order kinetic model and the Langmuir isotherm, respectively. The thermodynamic studies indicated that the adsorption reaction was a spontaneous and exothermic process. Besides, the presence of NaCl in the solution could facilitate the adsorption process, whereas the alkaline pH rang...