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| 1 | Extended Range(10–30 Days) Heavy Rain Forecasting Study Based on a Nonlinear Cross-Prediction Error Model显示文摘Extended range(10–30 d) heavy rain forecasting is difficult but performs an important function in disaster prevention and mitigation. In this paper,a nonlinear cross prediction error(NCPE) algorithm that combines nonlinear dynamics and statistical methods is proposed. The method is based on phase space reconstruction of chaotic single-variable time series of precipitable water and is tested in 100 global cases of heavy rain. First,nonlinear relative dynamic error for local attractor pairs is calculated at different stages of the heavy rain process,after which the local change characteristics of the attractors are analyzed. Second,the eigen-peak is defined as a prediction indicator based on an error threshold of about 1.5,and is then used to analyze the forecasting validity period. The results reveal that the prediction indicator features regarded as eigenpeaks for heavy rain extreme weather are all reflected consistently,without failure,based on the NCPE model; the prediction validity periods for 1–2 d,3–9 d and 10–30 d are 4,22 and 74 cases,respectively,without false alarm or omission. The NCPE model developed allows accurate forecasting of heavy rain over an extended range of 10–30 d and has the potential to be used to explore the mechanisms involved in the development of heavy rain according to a segmentation scale. This novel method provides new insights into extended range forecasting and atmospheric predictability,and also allows the creation of multi-variable chaotic extreme weather prediction models based on high spatiotemporal resolution data. | XIA Zhiye CHEN Hongbin XU Lisheng WANG Yongqian | 2015 | Advances in Atmospheric Sciences2015，32，12： | 4 |
| 2 | Improving the Antibacterial Property of Chitosan Hydrogel Wound Dressing with Licorice Polysaccharide显示文摘A series of hydrogels with different ratios of chitosan and licorice polysaccharide(LP)were prepared by crosslinking to different concentrations of genipin(gp).They were characterized by FTIR(Fourier transform infrared spectroscopy),SEM(Scanning electron microscope),swelling ratio,rheological measurements,degradation with time,cytotoxicity,and antibacterial efficacy.Results show that the hydrogels have porous structures.With an increase in LP content,the swelling rate grows in the early stage of immersion in buffer and drops later.The swelling ratio ranged from 986%to 1677%,and stiffness varied from 777 Pa to 1792 Pa.The addition of LP reduced the mechanical strength and delayed gelation and degradation of the hydrogels.However,the most important discovery was that gp increases the viability of NIH 3T3 cells from 94%to 137%,and LP raises the bacteriostatic efficacy from 51%to 78%.Hydrogels synthesized from 1%genipin,3%chitosan,and 4%licorice polysaccharide showed the best antibacterial and fibroblast proliferation promoting activities.They exhibited moderate swelling and degradation rates over time,while being more suitable to affect healing of chronic wound infections.These results provide a new strategy to improve the antibacterial effectiveness and cyto-compatibility of chitosan hydrogels with water soluble active LPs from Glycyrrhiza that derive from traditional Chinese medicine. | Haiwei Ren Li Wang Hui Bao Yunya Xia Dada Xu Weijie Zhang Zhiye Wang | 2020 | Journal of Renewable Materials2020，8，10： | 2 |
| 3 | Error Sensitivity Analysis in 10–30-Day Extended Range Forecasting by Using a Nonlinear Cross-Prediction Error Model显示文摘Extended range forecasting of 10–30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error(NCPE) model, and their stability in the prediction validity period in 10–30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small(10^(–6)–10^(–2)), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10^(–1)–2(i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10^(–2)–10^(–1), both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect(m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water. | zhiye xia lisheng xu hongbin chen yongqian wang jinbao liu wenlan feng | 2017 | Journal of Meteorological Research2017，31，3： | 1 |
| 4 | Design of a Water Environment Monitoring System Based on Wireless Sensor Networks 显示文摘 | Peng Jiang Hongbo Xia Zhiye He Zheming Wang | 2009 | Sensors2009，，： | 1 |
| 5 | Design of a water environment monitoring system based on wireless sensor networks显示文摘 | Jiang Peng Xia Hongbo He Zhiye | 2009 | Sensors2009，9，8： | 1 |
| 6 | Anticarin-β shows a promising antiosteosarcoma effect by specifically inhibiting CCT4 to impair proteostasis显示文摘Unlike healthy, non-transformed cells, the proteostasis network of cancer cells is taxed to produce proteins involved in tumor development. Cancer cells have a higher dependency on molecular chaperones to maintain proteostasis. The chaperonin T-complex protein ring complex(TRiC) contains eight paralogous subunits(CCT1-8), and assists the folding of as many as 10% of cytosolic proteome.TRiC is essential for the progression of some cancers, but the roles of TRiC subunits in osteosarcoma remain to be explored. Here, we show that CCT4/TRiC is significantly correlated in human osteosarcoma,and plays a critical role in osteosarcoma cell survival. We identify a compound anticarin-β that can specifically bind to and inhibit CCT4. Anticarin-β shows higher selectivity in cancer cells than in normal cells. Mechanistically, anticarin-β potently impedes CCT4-mediated STAT3 maturation. Anticarin-β displays remarkable antitumor efficacy in orthotopic and patient-derived xenograft models of osteosarcoma.Collectively, our data uncover a key role of CCT4 in osteosarcoma, and propose a promising treatment strategy for osteosarcoma by disrupting CCT4 and proteostasis. | Gan Wang Min Zhang Ping Meng Chengbo Long Xiaodong Luo Xingwei Yang Yunfei Wang Zhiye Zhang James Mwangi Peter Muiruri Kamau Zhi Daic Zunfu Ke Yi Zhang Wenlin Chen Xudong Zhao Fei Ge Qiumin Lv Mingqiang Rong Dongsheng Li Yang Jin Xia Sheng Ren Lai | 2022 | Acta Pharmaceutica Sinica B2022，12，5： | 1 |
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