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| 1 | Satellite-observed trends in the Arctic sea ice concentration for the period 1979–2016显示文摘Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ). | WANG Yunhe BI Haibo HUANG Haijun LIU Yanxia LIU Yilin LIANG Xi FU Min ZHANG Zehua | 2019 | Journal of Oceanology and Limnology2019，37，1： | 7 |
| 2 | Green‑Solvent Processed Blade‑Coating Organic Solar Cells with an Efficiency Approaching 19%Enabled by Alkyl‑Tailored Acceptors显示文摘Power-conversion-efficiencies(PCEs)of organic solar cells(OSCs)in laboratory,normally processed by spin-coating technology with toxic halogenated solvents,have reached over 19%.However,there is usually a marked PCE drop when the bladecoating and/or green-solvents toward large-scale printing are used instead,which hampers the practical development of OSCs.Here,a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused endgroup.Thanks to the N-alkyl engineering,NIR-absorbing YR-SeNF series show different crystallinity,packing patterns,and miscibility with polymeric donor.The studies exhibit that the molecular packing,crystallinity,and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains,providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YRSeNF-based OSCs.As a result,a record-high PCE approaching 19%is achieved in the blade-coating OSCs fabricated from a greensolvent o-xylene with high-boiling point.Notably,ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep>80%of the initial PCEs for even over 400 h.Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs,which paves a way for industrial development. | Hairui Bai Ruijie Ma Wenyan Su Top Archie Dela Pea Tengfei Li Lingxiao Tang Jie Yang Bin Hu Yilin Wang Zhaozhao Bi Yueling Su Qi Wei Qiang Wu Yuwei Duan Yuxiang Li Jiaying Wu Zicheng Ding Xunfan Liao Yinjuan Huang Chao Gao Guanghao Lu Mingjie Li Weiguo Zhu Gang Li Qunping Fan Wei Ma | 2023 | Nano-Micro Letters2023，15，12： | 1 |
| 3 | Arctic sea ice thickness changes in terms of sea ice age显示文摘In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite(ICESat)-based results show a thickness reduction over perennial sea ice(ice that survives at least one melt season with an age of no less than 2 year) up to approximately 0.5–1.0 m and 0.6–0.8 m(depending on ice age) during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980 s, there is a clear thickness drop of roughly 0.50 m in 2010 s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water(primarily via albedo feedback) in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness. | BI Haibo FU Min SUN Ke LIU Yilin XU Xiuli HUANG Haijun | 2016 | Acta Oceanologica Sinica2016，35，10： | 1 |
| 4 | Big Data Audit of Banks Based on Fuzzy Set Theory to Evaluate Risk Level显示文摘The arrival of big data era has brought new opportunities and challenges to the development of various industries in China.The explosive growth of commercial bank data has brought great pressure on internal audit.The key audit of key products limited to key business areas can no longer meet the needs.It is difficult to find abnormal and exceptional risks only by sampling analysis and static analysis.Exploring the organic integration and business processing methods between big data and bank internal audit,Internal audit work can protect the stable and sustainable development of banks under the new situation.Therefore,based on fuzzy set theory,this paper determines the membership degree of audit data through membership function,and judges the risk level of audit data,and builds a risk level evaluation system.The main features of this paper are as follows.First,it analyzes the necessity of transformation of the bank auditing in the big data environment.The second is to combine the determination of the membership function in the fuzzy set theory with the bank audit analysis,and use the model to calculate the corresponding parameters,thus establishing a risk level assessment system.The third is to propose audit risk assessment recommendations,hoping to help bank audit risk management in the big data environment.There are some shortcomings in this paper.First,the amount of data acquired is not large enough.Second,due to the lack of author’knowledge,there are still some deficiencies in the analysis of audit risk of commercial banks. | Yilin Bi Yuxin Ouyang Guang Sun Peng Guo Jianjun Zhang Yijun Ai | 2020 | Journal on Big Data2020，2，1： | 0 |
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