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| 1 | Status and distribution changes of the endangered Green Peafowl (Pavo muticus) in China over the past three decades (1990s-2017)显示文摘Background: Understanding the changes in population dynamics, including demographics, distribution and threats, is essential for species status assessing. The endangered Green Peafowl(Pavo muticus) has experienced sharp population declines and distribution range diminishing both in China and Southeast Asia. Field population surveys have not been conducted in China since the 1990 s, which hindered conservation planning and decision-making.Methods: With interview and line transects methods, we figured out the population and distribution changes of Green Peafowl across its historical ranges over the past three decades in China during 2014-2017.Results: The Green Peafowl once habituated in 54 counties in China. Nearly 60% of the distribution counties were lost in the past three decades, with the left 22 counties distributed in central, southern and western Yunnan, SW China. Population decrease detected in all distribution areas except for Shuangbai and Xinping county where more than 60% of the total population is located. Only about 30% of the former bird population were recorded with the same interviewing method as 20 years ago. Three birds, 1 carcass, 6 calls and 12 footprints were detected along the 865 km line transects, indic-ating extremely low encounter rate of Green Peafowl in field. Sharp decreases in flock sizes were also detected, from 820 birds per flock in the 1990 s to 3-5 birds at present. Poaching and habitat conversion are two widespread and long-lasting threats, while poisoning caused mortality in the past and hydropower construction affect regional population's survival. Large flocks of 18–27 birds were discovered in the field, which increases our confidence of population recovery of this endangered pheasant in China.Conclusions: Only interviewed bird number and counts based on line transects were presented in this study, without further population estimation due to limitation of the data sets. Although the actual population of this cryptic bird must be underestimated, dramatic population declines and distribution concentrations of the endangered Green Peafowl occurred over the past 30 years in China undoubtedly. | Dejun Kong Fei Wu Pengfei Shan Jianyun Gao Dao Yan Weixiong Luo Xiaojun Yang | 2018 | Avian Research2018，9，2： | 12 |
| 2 | Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies显示文摘Background:Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperpla-sia,the positive rate for malignancy identification during biopsy is low,thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt.Here,we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning.Methods:An endoscopic images-based nasopharyngeal malignancy detection model(eNPM-DM)consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation.Briefly,a total of 28,966 qualified images were collected.Among these images,27,536 biopsy-proven images from 7951 individuals obtained from January 1st,2008,to December 31st,2016,were split into the training,validation and test sets at a ratio of 7:1:2 using simple randomiza-tion.Additionally,1430 images obtained from January 1st,2017,to March 31st,2017,were used as a prospective test set to compare the performance of the established model against oncologist evaluation.The dice similarity coef-ficient(DSC)was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images,by comparing automatic segmentation with manual segmenta-tion performed by the experts.Results:All images were histopathologically confirmed,and included 5713(19.7%)normal control,19,107(66.0%)nasopharyngeal carcinoma(NPC),335(1.2%)NPC and 3811(13.2%)benign diseases.The eNPM-DM attained an overall accuracy of 88.7%(95%confidence interval(CI)87.8%-89.5%)in detecting malignancies in the test set.In the prospective comparison phase,eNPM-DM outperformed the experts:the overall accuracy was 88.0%(95%CI 86.1%-89.6%)vs.80.5%(95%CI 77.0%-84.0%).The eNPM-DM required less time(40 s vs.110.0±5.8 min)and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background,with an average DSC of 0.78±0.24 and 0.75±0.26 in the test and prospective test sets,respectively.Conclusions:The eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant,and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images. | Chaofeng Li Bingzhong Jing Liangru Ke Bin Li Weixiong Xia Caisheng He Chaonan Qian Chong Zhao Haiqiang Mai Mingyuan Chen Kajia Cao Haoyuan Mo Ling Guo Qiuyan Chen Linquan Tang Wenze Qiu Yahui Yu Hu Liang Xinjun Huang Guoying Liu Wangzhong Li Lin Wang Rui Sun Xiong Zou Shanshan Guo Peiyu Huang Donghua Luo Fang Qiu Yishan Wu Yijun Hua Kuiyuan Liu Shuhui Lv Jingjing Miao Yanqun Xiang Ying Sun Xiang Guo Xing Lv | 2018 | Cancer Communications2018，38，1： | 9 |
| 3 | The Role of OsMSH5 in Crossover Formation during Rice Meiosis显示文摘MSH5,傻瓜相当或相同的事物家庭的一个成熟分裂特定的成员,在开始发育的酵母,老鼠, Caenorhabditis elegans,和 Arabidopsis 为再结合的正常水平被要求。这里,我们报导它的米饭相当或相同的事物的鉴定和描述, OsMSH5,并且在米饭表明它的功能成熟分裂。五独立 Osmsh5 异种展出了正常植物的生长和严重绝育。当交叉频率极大地被归结为观察了在那中的约 10% 个时, synaptonemal 建筑群很好在 Osmsh5 被安装野类型,导致相应不分离和完全的无菌的显型。OsMSH5 主要在圆锥花序被表示。Immunofluorescence 研究显示 OsMSH5 chromosomal 本地化限于早 meiotic 前期我。OsMSH5 能在 Oszip4, Osmer3,和 hei10 被装载到 meiotic 染色体上。然而,那些 ZMM 蛋白质不能当 OsMSH5 不在时通常是局部性的。而且,剩余 chiasmata 被显示在 zmm 异种之中最不经常,包括 Osmer3, Oszip4, hei10,和 Osmsh5。一起拿,我们建议 OsMSH5 工作在一级转线路的 OsZIP4, OsMER3,和 HEI10 在上游形成。 | Qiong Luo Ding Tang MO Wang Weixiong Luo Lei Zhang Baoxiang Qin Yi Shen Kejian Wang Yafei Li Zhukuan Cheng | 2013 | Molecular Plant2013，6，3： | 5 |
| 4 | The efficacy and safety of nimodipine in acute ischemic stroke patients with mild cognitive impairment: a double-blind, randomized,placebo-controlled trial显示文摘Nimodipine might be effective in subcortical vascular dementia(VaD). Its benefit in preventing further cognitive decline in patients with acute ischemic stroke(AIS) and vascular mild cognitive impairment(VaMCI) remains to be established. In this multicenter, double-blind trial, we randomly assigned 654 eligible patients to nimodipine 30 mg three times a day or placebo. The primary outcome was any cognitive decline defined by the changes on the Mini-Mental State Examination(DMMSE à3) or vascular AD assessment scale cognitive subscale(DADAS-cog ! 4) at 6 months. Secondary outcomes included any distribution shift of DADAS-cog, DMMSE or cognitive improvement defined by DADAS-cog à2, or DMMSE ! 0. The primary outcome in the nimodipine group and placebo group were similar for DMMSE à3(4.18% and 7.22%, respectively, P = 0.15) and DADAS-cog ! 4(8.36% and 8.93% respectively,P = 0.88). The distribution shift of DADAS-cog and DMMSE differed significantly between the two groups(P = 0.03 and P = 0.05 respectively). Cognitive improvement occurred in 55.4% in the nimodipine group and 43.6% in the placebo group measured by DADAS-cog à2(Odds Ratio, 1.54; 95% confidence interval[CI] 1.10–2.14, P < 0.01) or 84.0% and 74.6% respectively by DMMSE ! 0(Odds Ratio, 1.79; 95% CI 1.18–2.70, P < 0.01). Nimodipine was associated with better cognitive function in the memory domain. The adverse events rate was similar in two groups. This study is registered with ClinicalTrials.gov,NCT01220622. Nimodipine did not show benefit to prevent cognitive decline in AIS patients with VaMCI, but improved cognition moderately, especially measured in the memory domain. | Huaguang Zheng Yilong Wang Anxin Wang Hao Li David Wang Xingquan Zhao Penglian Wang Haipeng Shen Lijun Zuo Yuesong Pan Zixiao Li Xia Meng Xianwei Wang Weixiong Shi Yi Ju Liping Liu Kehui Dong Chunxue Wang Rubo Sui Rong Xue Xiaoping Pan Xiaoyua Niu Benyan Luo Yi Sui Huali Wang Tao Feng Yongjun Wang | 2019 | Science Bulletin2019，64，2： | 5 |
| 5 | Coding Scheme for Ka Band Fixed Satellite Communication System显示文摘 | Wang Aihua Luo Weixiong | 2002 | Journal of Beijing Instiute of Technology2002，11，2： | 1 |
| 6 | Polarized spectroscopy of Er 3+ ions in YAl 3 (BO 3 ) 4 crystal显示文摘 | Weixiong You Yanfu Lin Yujin Chen Zundu Luo Yidong Huang | 2005 | Optical Materials2005，，： | 1 |
| 7 | Ce^(3+) doped BaLu_(2)Al_(2)Ga_(2)SiO_(12)——A novel blue-light excitable cyan-emitting phosphor with ultra-high quantum efficiency and excellent stability for full-spectrum white LEDs显示文摘It is well known that cyan-emitting phosphors play a very important role in full-spectrum white LEDs.A large number of cyan-emitting phosphors have been reported in the past few years,however,most of them can only be effectively excited by near-ultraviolet light.There are very few cyan-emitting phosphors that can be intensively excited by blue light(440 and 470 nm).Here,a novel blue-light excitable cyan-emitting phosphor BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)with excellent performance is reported.The cyan phosphor has a cubic structure in space group Ia3^(-)d with a=1.205379(3)nm,which can be easily obtained through a solid-state reaction pathway.The emission peak of the cyan phosphor is located at 500 nm and its internal quantum efficiency is as high as 90.01%when excited at 455 nm at 25℃.The cyan phosphor exhibits superior resistance against thermal quenching of luminescence,and its intensity at 125℃is as strong as 92.14%of the intensity at room temperature.Meanwhile,it also shows an outstanding resistance against water,where its luminescence intensity is hardly changed after being immersed in pure water for 528 h.The white LED lamp prepared by employing the obtained BaLu_(1.95)-Ce_(0.05)Al_(2)Ga_(2)SiO_(12)as cyan phosphor displays remarkable optical properties with CCT=4441 K,Ra=93.7,CRI=90.4 and CIE 1931(x,y)as(x=0.3648,y=0.3752).The experimental results demonstrate that BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)is a promising cyan-emitting phosphor with great application potential in full-spectrum white LEDs. | Mingzhang Liang Jianfei Xu Yaochun Qiang Haojian Kang Lulu Zhang Jie Chen Chun Liu Xianbi Luo Ying Li Jingjing Zhang Liqing Ouyang Weixiong You Xinyu Ye | 2021 | Journal of Rare Earths2021，39，9： | 0 |
| 8 | Optimizing energy efficiency of CNN-based object detection with dynamic voltage and frequency scaling显示文摘On the one hand,accelerating convolution neural networks(CNNs)on FPGAs requires ever increasing high energy efficiency in the edge computing paradigm.On the other hand,unlike normal digital algorithms,CNNs maintain their high robustness even with limited timing errors.By taking advantage of this unique feature,we propose to use dynamic voltage and frequency scaling(DVFS)to further optimize the energy efficiency for CNNs.First,we have developed a DVFS framework on FPGAs.Second,we apply the DVFS to SkyNet,a state-of-the-art neural network targeting on object detection.Third,we analyze the impact of DVFS on CNNs in terms of performance,power,energy efficiency and accuracy.Compared to the state-of-the-art,experimental results show that we have achieved 38%improvement in energy efficiency without any loss in accuracy.Results also show that we can achieve 47%improvement in energy efficiency if we allow 0.11%relaxation in accuracy. | Weixiong Jiang Heng Yu Jiale Zhang Jiaxuan Wu Shaobo Luo Yajun Ha | 2020 | Journal of Semiconductors2020，41，2： | 0 |
| 9 | 基于内镜图像深度学习的鼻咽恶性肿瘤检测模型的建立与验证显示文摘背景与目的由于鼻咽部解剖位置隐匿且腺体增生频发,活检时恶性肿瘤的阳性率较低,从而导致初诊时鼻咽恶性肿瘤确诊延时或漏诊。本文旨在建立一种人工智能工具——基于深度学习的内镜检查,来检测鼻咽恶性肿瘤。方法建立了一种基于内镜图像的鼻咽恶性肿瘤检测模型(endoscopic imagesbased nasopharyngeal malignancies detection model,eNPM-DM),该模型由基于空间结构的全卷积网络构成,采用单独训练集和验证集对分类和分割进行微调。总共收集了28,966张合格图像。其中,自2008年1月1日至2016年12月31日,从7951例个体中获得了27,536张经活检证实的图像,按照7∶1∶2的比例随机分为训练、验证和测试集。此外,将2017年1月1日到2017年3月31日获得的1430张图像纳入预测集,用以对建立模型的性能与肿瘤专家的评价进行比较。以鼻咽镜图像为背景,对自动分割和专家手工分割进行比较,采用dice相似系数(dice similarity coefficient,DSC)评价eNPM-DM从鼻咽部内镜图像的背景中自动分割出恶性肿瘤区域的效率。结果所有图像经过病理组织学验证,包括正常对照5713(19.7%)例、鼻咽癌(nasopharyngeal carcinoma,NPC)19,107(66.0%)例、其他恶性肿瘤335(1.2%)例和3811(13.2%)例良性病变。在测试集中,eNPM-DM检测恶性肿瘤的总准确率达88.7%[95%置信区间(confidence interval,CI):87.8%–89.5%]。在预测比较阶段,eNPM-DM表现优于专家:总准确率分别为88.0%(95%CI:86.1%–89.6%)和80.5%(95%CI:77.0%–84.0%)。eNPM-DM耗时更短(40 s vs. 110.0±5.8 min),且从背景中自动分割出鼻咽恶性肿瘤区域方面表现优秀,测试集和预测集中的平均DSC分别为0.78±0.24和0.75±0.26。结论 eNPM-DM在鼻咽肿块良性/恶性诊断分类方面优于肿瘤学家评估,并且实现了从鼻咽内镜图像背景中对恶性区域自动分割。 | Chaofeng Li Bingzhong Jing Liangru Ke Bin Li Weixiong Xia Caisheng He Chaonan Qian Chong Zhao Haiqiang Mai Mingyuan Chen Kajia Cao Haoyuan Mo Ling Guo Qiuyan Chen Linquan Tang Wenze Qiu Yahui Yu Hu Liang Xinjun Huang Guoying Liu Wangzhong Li Lin Wang Rui Sun Xiong Zou Shanshan Guo Peiyu Huang Donghua Luo Fang Qiu Yishan Wu Yijun Hua Kuiyuan Liu Shuhui Lv Jingjing Miao Yanqun Xiang Ying Sun Xiang Guo Xing Lv | 2019 | 癌症2019，38，7： | 0 |
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