| 1 |
Qiu_M_2005 |
Antibody responses to individual proteins of SARS coronavirus and their neutralization activities |
Qiu, Maofeng; Shi, Yuling; Guo, Zhaobiao; Chen, Zeliang; He, Rongqiao; Chen, Runsheng; Zhou, Dongsheng; Dai, Erhei; Wang, Xiaoyi; Si, Bingyin; Song, Yajun; Li, Jingxiang; Yang, Ling; Wang, Jin; Wang, Hongxia; Pang, Xin; Zhai, Junhui; Du, Zongmin; Liu, Ying; Zhang, Yong; Li, Linhai; Wang, Jian; Sun, Bing; Yang, Ruifu |
2005 |
2005-05-31 |
PMC |
Y |
PMC7110836 |
15878679.0 |
10.1016/j.micinf.2005.02.006 |
nc82a70n |
0.829400 |
Okda_2017, Hu_W_2013 |
Li_S_2016, Zhao_2005 |
| 2 |
Lee_H_2010 |
Production of specific antibodies against SARS-coronavirus nucleocapsid protein without cross reactivity with human coronaviruses 229E and OC43 |
Lee, Hyun-Kyoung; Lee, Byoung-Hee; Seok, Seung-Hyeok; Baek, Min-Won; Lee, Hui-Young; Kim, Dong-Jae; Na, Yi-Rang; Noh, Kyoung-Jin; Park, Sung-Hoon; Kumar, Dutta Noton; Kariwa, Hiroaki; Nakauchi, Mina; Heo, Suk-Jin; Park, Jae-Hak |
2010 |
2010-05-11 |
PMC |
N |
PMC2873818 |
20458159.0 |
10.4142/jvs.2<IP_ADDRESS> |
95kpbpj5 |
0.689685 |
|
Elshabrawy_2012, Saijo_2005 |
| 3 |
Wang_2003 |
Assessment of Immunoreactive Synthetic Peptides from the Structural Proteins of Severe Acute Respiratory Syndrome Coronavirus |
Wang, Jingqiang; Wen, Jie; Li, Jingxiang; Yin, Jianning; Zhu, Qingyu; Wang, Hao; Yang, Yongkui; Qin, E’de; You, Bo; Li, Wei; Li, Xiaolei; Huang, Shengyong; Yang, Ruifu; Zhang, Xumin; Yang, Ling; Zhang, Ting; Yin, Ye; Cui, Xiaodai; Tang, Xiangjun; Wang, Luoping; He, Bo; Ma, Lianhua; Lei, Tingting; Zeng, Changqing; Fang, Jianqiu; Yu, Jun; Wang, Jian; Yang, Huanming; West, Matthew B; Bhatnagar, Aruni; Lu, Youyong; Xu, Ningzhi; Liu, Siqi |
2003 |
2003-12-01 |
PMC |
N |
PMC7108193 |
14633869.0 |
10.1373/clinchem.2003.023184 |
gm99cadh |
0.687632 |
Okda_2017 |
Li_S_2016, Qiu_M_2005, Liu_S_2006 |
| 4 |
LIN_Y_2003 |
Identification of an epitope of SARS-coronavirus nucleocapsid protein |
LIN, Ying; SHEN, Xu; YANG, Rui Fu; LI, Yi Xue; JI, Yong Yong; HE, You Yu; SHI, Mu De; LU, Wei; SHI, Tie Liu; WANG, Jin; WANG, Hong Xia; JIANG, Hua Liang; SHEN, Jian Hua; XIE, You Hua; WANG, Yuan; PEI, Gang; SHEN, Bei Fen; WU, Jia Rui; SUN, Bing |
2003 |
2003-06-23 |
PMC |
N |
PMC7091728 |
12862314.0 |
10.1038/sj.cr.7290158 |
rbtyu4cu |
0.664525 |
Okda_2017, Hu_W_2013, Andoh_2015 |
Li_S_2016, Zhao_2005, Liu_S_2006, Shi_S_2006 |
| 5 |
Zhao_2005 |
Development and evaluation of an enzyme-linked immunosorbent assay for detection of antibodies against the spike protein of SARS-coronavirus |
Zhao, Jincun; Wang, Wei; Wang, Guang-Fa; Li, Yonghua; Zhuang, Hui; Xu, Xiaoyuan; Ren, Furong; Zhao, Zhendong; Gao, Xiao-Ming |
2005 |
2005-05-31 |
PMC |
N |
PMC7108335 |
15797360.0 |
10.1016/j.jcv.2004.09.024 |
srenbxa7 |
0.663216 |
Lee_H_2010, Okda_2017, Chan_2004, Hu_W_2013, Czerny_1989 |
Saijo_2005, Chirnside_1995 |
| 6 |
Chen_2004 |
Antigenicity Analysis of Different Regions of the Severe Acute Respiratory Syndrome Coronavirus Nucleocapsid Protein |
Chen, Zeliang; Pei, Decui; Jiang, Lingxiao; Song, Yajun; Wang, Jin; Wang, Hongxia; Zhou, Dongsheng; Zhai, Junhui; Du, Zongmin; Li, Bei; Qiu, Maofeng; Han, Yanping; Guo, Zhaobiao; Yang, Ruifu |
2004 |
2004-06-01 |
PMC |
N |
PMC7108132 |
15054081.0 |
10.1373/clinchem.2004.031096 |
4krkj8sq |
0.641380 |
Okda_2017 |
Li_S_2016, Das_D_2006 |
| 7 |
Chang_2004 |
Antibody detection of SARS-CoV spike and nucleocapsid protein |
Chang, Mau-Sun; Lu, Yen-Ta; Ho, Shin-Tsung; Wu, Chao-Chih; Wei, Tsai-Yin; Chen, Chia-Ju; Hsu, Yun-Ting; Chu, Po-Chen; Chen, Ching-Hsin; Chu, Jien-Ming; Jan, Ya-Lin; Hung, Chia-Chien; Fan, Chi-Chen; Yang, Yuh-Cheng |
2004 |
2004-02-20 |
PMC |
N |
PMC7111193 |
14751221.0 |
10.1016/j.bbrc.2003.12.195 |
lob26ih1 |
0.639539 |
Lee_H_2010, Hu_W_2013 |
Poh_C_2020, Saijo_2005 |
| 8 |
Kammila_2008 |
A rapid point of care immunoswab assay for SARS-CoV detection |
Kammila, Sriram; Das, Dipankar; Bhatnagar, Pravin K.; Sunwoo, Hoon H.; Zayas-Zamora, Gustavo; King, Malcolm; Suresh, Mavanur R. |
2008 |
2008-09-30 |
None |
N |
PMC2678951 |
18620761.0 |
10.1016/j.jviromet.2008.05.023 |
xl2u8asv |
0.638996 |
Hu_W_2013, Lee_H_2010, Wrammert_2011 |
Saijo_2005, Saijo_2007, Xue_G_2013 |
| 9 |
Shin_2007 |
Antigenic characterization of severe acute respiratory syndrome-coronavirus nucleocapsid protein expressed in insect cells: The effect of phosphorylation on immunoreactivity and specificity |
Shin, Gu-Choul; Chung, Yoon-Seok; Kim, In-Soo; Cho, Hae-Wol; Kang, Chun |
2007 |
2007-07-31 |
PMC |
N |
PMC7114200 |
17499376.0 |
10.1016/j.virusres.2007.03.019 |
c4w3ct50 |
0.620127 |
|
Li_S_2016, Ren_A_2004, Shi_S_2006 |
| 10 |
Li_S_2016 |
The Epitope Study on the SARS-CoV Nucleocapsid Protein |
Li, Shuting; Lin, Liang; Wang, Hao; Yin, Jianning; Ren, Yan; Zhao, Zhe; Wen, Jie; Zhou, Cuiqi; Zhang, Xumin; Li, Xiaolei; Wang, Jingqiang; Zhou, Zhengfeng; Liu, Jinxiu; Shao, Jianmin; Lei, Tingting; Fang, Jianqiu; Xu, Ningzhi; Liu, Siqi |
2016 |
2016-11-28 |
None |
N |
PMC5172353 |
15629032.0 |
10.1016/s1672-0229(03)01025-8 |
9ne5iwny |
0.610418 |
Okda_2017, Hu_W_2013 |
Liu_S_2006, Zhao_2005, LIN_Y_2003 |
| 11 |
Woo_P_2004 |
Relative rates of non-pneumonic SARS coronavirus infection and SARS coronavirus pneumonia |
Woo, Patrick CY; Lau, Susanna KP; Tsoi, Hoi-wah; Chan, Kwok-hung; Wong, Beatrice HL; Che, Xiao-yan; Tam, Victoria KP; Tam, Sidney CF; Cheng, Vincent CC; Hung, Ivan FN; Wong, Samson SY; Zheng, Bo-jian; Guan, Yi; Yuen, Kwok-yung |
2004 |
2004-03-13 |
PMC |
N |
PMC7112439 |
15031027.0 |
10.1016/s0140-6736(04)15729-2 |
ctx39vhi |
0.599228 |
Lee_H_2010, Che_X_2005 |
Saijo_2005 |
| 12 |
Giménez_2008 |
Development of an Enzyme-Linked Immunosorbent Assay-Based Test with a Cocktail of Nucleocapsid and Spike Proteins for Detection of Severe Acute Respiratory Syndrome-Associated Coronavirus-Specific Antibody |
Giménez, Luis G.; Rojas, Jose; Rojas, Almudena; Mendoza, Joaquín; Camacho, Ana G. |
2008 |
2008-11-26 |
None |
N |
PMC2643541 |
19038782.0 |
10.1128/cvi.00252-08 |
pt3k01vx |
0.580656 |
Okda_2017, Nagesha_2001, Hu_W_2013, Elia_2003, Shenyang_2007 |
Saijo_2005, Abdelwahab_2015 |
| 13 |
Liang_2013 |
Immunoreactivity characterisation of the three structural regions of the human coronavirus OC43 nucleocapsid protein by Western blot: Implications for the diagnosis of coronavirus infection |
Liang, Fang-Ying; Lin, Leng-Chieh; Ying, Tsung-Ho; Yao, Chen-Wen; Tang, Tswen-Kei; Chen, Yi-Wen; Hou, Ming-Hon |
2013 |
2013-02-28 |
None |
N |
PMC7112824 |
23174159.0 |
10.1016/j.jviromet.2012.11.009 |
nb8mfh7z |
0.570033 |
Okda_2017, Lee_H_2010 |
Xing_2009, Xue_G_2013 |
| 14 |
Ren_A_2004 |
Expression, Purification and Sublocalization of SARS-CoV Nucleocapsid Protein in Insect Cells |
Ren, Ai-Xia; Xie, You-Hua; Kong, Yu-Ying; Yang, Guan-Zhen; Zhang, Yao-Zhou; Wang, Yuan; Wu, Xiang-Fu |
2004 |
2004-11-23 |
PMC |
N |
PMC7110235 |
15514849.0 |
10.1093/abbs/36.11.754 |
nb5ckbfs |
0.555485 |
|
Loa_C_2004, Li_S_2016, Eshaghi_2005 |
| 15 |
Guo_J_2004 |
SARS corona virus peptides recognized by antibodies in the sera of convalescent cases |
Guo, Jian-Ping; Petric, Martin; Campbell, William; McGeer, Patrick L |
2004 |
2004-07-01 |
PMC |
N |
PMC7125913 |
15207612.0 |
10.1016/j.virol.2004.04.017 |
29ih5c9v |
0.532753 |
Hu_W_2013, Wrammert_2011 |
Poh_C_2020, Li_S_2016, Elshabrawy_2012 |
| 16 |
Yu_S_2005 |
Retrospective Serological Investigation of Severe Acute Respiratory Syndrome Coronavirus Antibodies in Recruits from Mainland China |
Yu, Sumeng; Qiu, Maofeng; Chen, Zeliang; Ye, Xiaobo; Gao, Yaling; Wei, Aimin; Wang, Xiaoyi; Yang, Ling; Wang, Jin; Wen, Jie; Song, Yajun; Pei, Decui; Dai, Erhei; Guo, Zhaobiao; Cao, Cheng; Wang, Jian; Yang, Ruifu |
2005 |
2005-04-01 |
None |
N |
PMC1074388 |
15817766.0 |
10.1128/cdli.12.4.552-554.2005 |
vpblnie6 |
0.532352 |
Lee_H_2010 |
WANG_2016 |
| 17 |
Shichijo_2004 |
Assessment of synthetic peptides of severe acute respiratory syndrome coronavirus recognized by long‐lasting immunity |
Shichijo, S.; Keicho, N.; Long, H.T.; Quy, T.; Phi, N.C.; Ha, L.D.; Ban, V.V.; Itoyama, S.; Hu, C.‐J.; Komatsu, N.; Kirikae, T.; Kirikae, F.; Shirasawa, S.; Kaji, M.; Fukuda, T.; Sata, M.; Kuratsuji, T.; Itoh, K.; Sasazuki, T. |
2004 |
2004-10-20 |
PMC |
N |
PMC7169720 |
15496204.0 |
10.1111/j.1399-0039.2004.00314.x |
xys0g8b8 |
0.530278 |
Okda_2017, de_Alwis_2011, Hu_W_2013, Wrammert_2011, Mitsuki_2008 |
|
| 18 |
Das_D_2010 |
Development, Characterization, and Application of Monoclonal Antibodies against Severe Acute Respiratory Syndrome Coronavirus Nucleocapsid Protein |
Das, Dipankar; Kammila, Sriram; Suresh, Mavanur R. |
2010 |
2010-10-06 |
None |
N |
PMC3008203 |
20926700.0 |
10.1128/cvi.00293-10 |
yofywc53 |
0.527315 |
Lee_H_2010, Okda_2017, Hu_W_2013, Paton_1991 |
Elshabrawy_2012, Berry_2004 |
| 19 |
Ren_Y_2016 |
A Strategy for Searching Antigenic Regions in the SARS-CoV Spike Protein |
Ren, Yan; Zhou, Zhengfeng; Liu, Jinxiu; Lin, Liang; Li, Shuting; Wang, Hao; Xia, Ji; Zhao, Zhe; Wen, Jie; Zhou, Cuiqi; Wang, Jingqiang; Yin, Jianning; Xu, Ningzhi; Liu, Siqi |
2016 |
2016-11-28 |
None |
N |
PMC5172407 |
15629033.0 |
10.1016/s1672-0229(03)01026-x |
ev0eco0n |
0.519481 |
|
Li_S_2016, Han_D_2004, Das_D_2006, Liu_G_2016 |
| 20 |
Wu_H_2004 |
Early detection of antibodies against various structural proteins of the SARS-associated coronavirus in SARS patients |
Wu, Ho-Sheng; Hsieh, Yueh-Chun; Su, In-Jen; Lin, Ting-Hsiang; Chiu, Shu-Chun; Hsu, Yu-Fen; Lin, Jih-Hui; Wang, Mei-Ching; Chen, Jeou-Yuan; Hsiao, Pei-Wen; Chang, Geen-Dong; Wang, Andrew H. -J.; Ting, Hsien-Wei; Chou, Chih-Ming; Huang, Chang-Jen |
2004 |
2004-01-23 |
PMC |
N |
PMC7089234 |
14730215.0 |
10.1007/bf02256554 |
5unlhxst |
0.513757 |
Lee_H_2010 |
Qiu_M_2005 |
| 21 |
Li_Y_2005 |
Detection of the nucleocapsid protein of severe acute respiratory syndrome coronavirus in serum: Comparison with results of other viral markers |
Li, Yong-Hua; Li, Jie; Liu, Xue-En; Wang, Ling; Li, Tong; Zhou, Yi-Hua; Zhuang, Hui |
2005 |
2005-12-31 |
PMC |
N |
PMC7112769 |
16024098.0 |
10.1016/j.jviromet.2005.06.001 |
tgowzrqo |
0.510225 |
Lee_H_2010, Che_X_2005, Saijo_2005, Elia_2003, Chan_2004 |
Saijo_2005, Yu_F_2007 |
| 22 |
Zhao_2005 |
Prokaryotic expression, refolding, and purification of fragment 450–650 of the spike protein of SARS-coronavirus |
Zhao, Jin-Cun; Zhao, Zhen-Dong; Wang, Wei; Gao, Xiao-Ming |
2005 |
2005-02-28 |
PMC |
N |
PMC7129930 |
15642467.0 |
10.1016/j.pep.2004.10.004 |
hyoroqit |
0.491187 |
Shenyang_2007, Andoh_2015, Mourez_2007, Nagesha_2001 |
Eshaghi_2005, Loa_C_2004 |
| 23 |
Guan_2004 |
Use of Viral Lysate Antigen Combined with Recombinant Protein in Western Immunoblot Assay as Confirmatory Test for Serodiagnosis of Severe Acute Respiratory Syndrome |
Guan, Ming; Chen, Hsiao Ying; Tan, Phuay Heng; Shen, Shuo; Goh, Phuay-Yee; Tan, Yee-Joo; Pang, Peow Hoon; Lu, Yang; Fong, Priscilla Yiquan; Chin, Daria |
2004 |
2004-11-01 |
None |
N |
PMC524763 |
15539520.0 |
10.1128/cdli.11.6.1148-1153.2004 |
aidfzzpw |
0.489696 |
Elia_2003, Shenyang_2007, Mourez_2007 |
Saijo_2005, Abdelwahab_2015 |
| 24 |
He_Q_2004 |
Development of a Western Blot Assay for Detection of Antibodies against Coronavirus Causing Severe Acute Respiratory Syndrome |
He, Qigai; Chong, Kooi Hoong; Hee Chng, Hiok; Leung, Bernard; Ee Ling, Ai; Wei, Ting; Chan, Shzu-Wei; Eong Ooi, Eng; Kwang, Jimmy |
2004 |
2004-03-01 |
None |
N |
PMC371214 |
15013997.0 |
10.1128/cdli.11.2.417-422.2004 |
jhn26qt9 |
0.488868 |
Lee_H_2010, Elia_2003, Hu_W_2013, Chang_2004 |
Saijo_2005, Chirnside_1995 |
| 25 |
Dutta_2008 |
Search for potential target site of nucleocapsid gene for the design of an epitope-based SARS DNA vaccine |
Dutta, Noton Kumar; Mazumdar, Kaushiki; Lee, Byoung-Hee; Baek, Min-Won; Kim, Dong-Jae; Na, Yi-Rang; Park, Sung-Hoon; Lee, Hyun-Kyoung; Kariwa, Hiroaki; Mai, Le Quynh; Park, Jae-Hak |
2008 |
2008-06-15 |
PMC |
N |
PMC7112843 |
18440652.0 |
10.1016/j.imlet.2008.03.003 |
rvrp5zvv |
0.488380 |
Okda_2017, Hu_W_2013, Wrammert_2011 |
Shi_S_2006, Li_S_2016 |
| 26 |
Zhao_2007 |
A study on antigenicity and receptor-binding ability of fragment 450–650 of the spike protein of SARS coronavirus |
Zhao, Jincun; Wang, Wei; Yuan, Zhihong; Jia, Rujing; Zhao, Zhendong; Xu, Xiaojun; Lv, Ping; Zhang, Yan; Jiang, Chengyu; Gao, Xiao-Ming |
2007 |
2007-03-15 |
PMC |
N |
PMC7103343 |
17055551.0 |
10.1016/j.virol.2006.09.022 |
anbxo55z |
0.478516 |
|
Elshabrawy_2012 |
| 27 |
Liu_J_2006 |
Production of an Anti-Severe Acute Respiratory Syndrome (SARS) Coronavirus Human Monoclonal Antibody Fab Fragment by Using a Combinatorial Immunoglobulin Gene Library Derived from Patients Who Recovered from SARS |
Liu, Jinye; Shao, Hongxia; Tao, Yanlin; Yang, Bin; Qian, Lisheng; Yang, Xiaoli; Cao, Brian; Hu, Gengxi; Tachibana, Hiroshi; Cheng, Xunjia |
2006 |
2006-05-01 |
None |
N |
PMC1459658 |
16682481.0 |
10.1128/cvi.13.5.594-597.2006 |
wc0b6ajt |
0.461476 |
Nagesha_2001, Okda_2017, Thullier_1999 |
Kang_2006, Lee_Y_2007, Elshabrawy_2012, Yu_X_2005 |
| 28 |
Chou_2005 |
Epitope mapping and biological function analysis of antibodies produced by immunization of mice with an inactivated Chinese isolate of severe acute respiratory syndrome-associated coronavirus (SARS-CoV) |
Chou, Te-hui W.; Wang, Shixia; Sakhatskyy, Pavlo V.; Mboudoudjeck, Innocent; Lawrence, John M.; Huang, Song; Coley, Scott; Yang, Baoan; Li, Jiaming; Zhu, Qingyu; Lu, Shan |
2005 |
2005-03-30 |
PMC |
N |
PMC7111783 |
15749129.0 |
10.1016/j.virol.2005.01.035 |
pq3nmags |
0.451920 |
Hu_W_2013, Okda_2017, Wrammert_2011 |
Elshabrawy_2012, He_Y_2005 |
| 29 |
Ho_T_2004 |
Antigenicity and receptor-binding ability of recombinant SARS coronavirus spike protein |
Ho, Tin-Yun; Wu, Shih-Lu; Cheng, Shin-Ei; Wei, Yen-Chiao; Huang, Shan-Ping; Hsiang, Chien-Yun |
2004 |
2004-01-23 |
PMC |
Y |
PMC7111049 |
14706633.0 |
10.1016/j.bbrc.2003.11.180 |
4h3tg6hg |
0.450550 |
|
Li_S_2016, Andoh_2015, Han_D_2004 |
| 30 |
Xiong_2004 |
Immunogenicity of SARS inactivated vaccine in BALB/c mice |
Xiong, Sheng; Wang, Yi-Fei; Zhang, Mei-Ying; Liu, Xin-Jian; Zhang, Chuan-Hai; Liu, Shi-Sheng; Qian, Chui-Wen; Li, Jiu-Xiang; Lu, Jia-Hai; Wan, Zhuo-Yue; Zheng, Huan-Yin; Yan, Xin-Ge; Meng, Min-Jie; Fan, Jiang-lin |
2004 |
2004-09-30 |
PMC |
N |
PMC7112924 |
15388253.0 |
10.1016/j.imlet.2004.06.014 |
kr11qpeo |
0.450164 |
Hu_W_2013, Wrammert_2011 |
|
| 31 |
Zhao_2005 |
Immune responses against SARS-coronavirus nucleocapsid protein induced by DNA vaccine |
Zhao, Ping; Cao, Jie; Zhao, Lan-Juan; Qin, Zhao-Lin; Ke, Jin-Shan; Pan, Wei; Ren, Hao; Yu, Jian-Guo; Qi, Zhong-Tian |
2005 |
2005-01-05 |
PMC |
N |
PMC7111813 |
15582659.0 |
10.1016/j.virol.2004.10.016 |
xieqepl2 |
0.443895 |
Okda_2017 |
Shi_S_2006, Li_S_2016, Liu_S_2006, Zhao_2004 |
| 32 |
Tripp_2005 |
Monoclonal antibodies to SARS-associated coronavirus (SARS-CoV): Identification of neutralizing and antibodies reactive to S, N, M and E viral proteins |
Tripp, Ralph A.; Haynes, Lia M.; Moore, Deborah; Anderson, Barbara; Tamin, Azaibi; Harcourt, Brian H.; Jones, Les P.; Yilla, Mamadi; Babcock, Gregory J.; Greenough, Thomas; Ambrosino, Donna M.; Alvarez, Rene; Callaway, Justin; Cavitt, Sheana; Kamrud, Kurt; Alterson, Harold; Smith, Jonathan; Harcourt, Jennifer L.; Miao, Congrong; Razdan, Raj; Comer, James A.; Rollin, Pierre E.; Ksiazek, Thomas G.; Sanchez, Anthony; Rota, Paul A.; Bellini, William J.; Anderson, Larry J. |
2005 |
2005-09-30 |
PMC |
N |
PMC7112802 |
15885812.0 |
10.1016/j.jviromet.2005.03.021 |
wi2k1183 |
0.434464 |
Okda_2017, Lee_H_2010, Paton_1991, Hu_W_2013 |
Qian_2006, Elshabrawy_2012, Saijo_2005 |
| 33 |
Che_X_2005 |
Antigenic Cross-Reactivity between Severe Acute Respiratory Syndrome—Associated Coronavirus and Human Coronaviruses 229E and OC43 |
Che, Xiao-yan; Qiu, Li-wen; Liao, Zhi-yong; Wang, Ya-di; Wen, Kun; Pan, Yu-xian; Hao, Wei; Mei, Ya-bo; Cheng, Vincent C. C.; Yuen, Kwok-yung |
2005 |
2005-06-15 |
PMC |
N |
PMC7109809 |
15897988.0 |
10.1086/430355 |
w5sub348 |
0.433288 |
Lee_H_2010 |
Saijo_2005 |
| 34 |
Carattoli_2005 |
Recombinant protein‐based ELISA and immuno‐cytochemical assay for the diagnosis of SARS |
Carattoli, Alessandra; Bonito, Paola Di; Grasso, Felicia; Giorgi, Colomba; Blasi, Francesco; Niedrig, Matthias; Cassone, Antonio |
2005 |
2005-04-15 |
PMC |
N |
PMC7166672 |
15834868.0 |
10.1002/jmv.20338 |
w79ktbfs |
0.429186 |
Elia_2003, Okda_2017, Lee_H_2010, Andoh_2015 |
|
| 35 |
Yu_X_2005 |
Production of a monoclonal antibody against SARS-CoV spike protein with single intrasplenic immunization of plasmid DNA |
Yu, Xiao Fei; Liang, Lin Hui; She, Ming; Liao, Xiao Long; Gu, Jie; Li, Yan Han; Han, Zhong Chao |
2005 |
2005-09-15 |
PMC |
Y |
PMC7112869 |
15893826.0 |
10.1016/j.imlet.2005.03.015 |
jv5wyup8 |
0.428060 |
Hu_W_2013, Okda_2017 |
Zhao_2004, Elshabrawy_2012 |
| 36 |
Zhang_2005 |
Preparation and characterization of SARS in-house reference antiserum |
Zhang, Jiansan; Liu, Yuxuan; Hu, Liangxiang; Gao, Qiang; Zhang, Zhenshan; Zhang, Xiaomei; Chen, Jiangting; Gong, Xuejie; Song, Lifei; Liu, Yufen; Li, Jing; Li, Shufen; Huang, Jinfeng; Ning, Ye; Gao, Hong; Qin, Chuan; Dong, Xiaoping; Wei, Jianguo; Dong, Guanmu; Yin, Weidong |
2005 |
2005-12-01 |
PMC |
N |
PMC7115399 |
16269206.0 |
10.1016/j.vaccine.2004.12.032 |
jp9w1jcr |
0.427361 |
Hu_W_2013, Wrammert_2011, Hohdatsu_1987, Saijo_2005 |
Saijo_2005, Poh_C_2020, Berry_2004, Zhao_2004 |
| 37 |
Maache_2006 |
False-Positive Results in a Recombinant Severe Acute Respiratory Syndrome-Associated Coronavirus (SARS-CoV) Nucleocapsid-Based Western Blot Assay Were Rectified by the Use of Two Subunits (S1 and S2) of Spike for Detection of Antibody to SARS-CoV |
Maache, Mimoun; Komurian-Pradel, Florence; Rajoharison, Alain; Perret, Magali; Berland, Jean-Luc; Pouzol, Stéphane; Bagnaud, Audrey; Duverger, Blandine; Xu, Jianguo; Osuna, Antonio; Paranhos-Baccalà, Glaucia |
2006 |
2006-03-01 |
None |
N |
PMC1391961 |
16522785.0 |
10.1128/cvi.13.3.409-414.2006 |
dh0lvoqq |
0.426965 |
|
Saijo_2005, Li_Y_2005, Woo_P_2004 |
| 38 |
WU_X_2004 |
The spike protein of severe acute respiratory syndrome (SARS) is cleaved in virus infected Vero-E6 cells |
WU, Xiao Dong; SHANG, Bo; YANG, Rui Fu; YU, Hao; MA, Zhi Hai; SHEN, Xu; JI, Yong Yong; LIN, Ying; WU, Ya Di; LIN, Guo Mei; TIAN, Lin; GAN, Xiao Qing; YANG, Sheng; JIANG, Wei Hong; DAI, Er Hei; WANG, Xiao Yi; JIANG, Hua Liang; XIE, You Hua; ZHU, Xue Liang; PEI, Gang; LI, Lin; WU, Jia Rui; SUN, Bing |
2004 |
2004-10-23 |
PMC |
N |
PMC7091875 |
15450134.0 |
10.1038/sj.cr.7290240 |
fy1lqk00 |
0.426103 |
|
|
| 39 |
Yu_M_2008 |
Determination and application of immunodominant regions of SARS coronavirus spike and nucleocapsid proteins recognized by sera from different animal species |
Yu, Meng; Stevens, Vicky; Berry, Jody D.; Crameri, Gary; McEachern, Jennifer; Tu, Changchun; Shi, Zhengli; Liang, Guodong; Weingartl, Hana; Cardosa, Jane; Eaton, Bryan T.; Wang, Lin-Fa |
2008 |
2008-02-29 |
PMC |
N |
PMC7094251 |
18191140.0 |
10.1016/j.jim.2007.11.009 |
4hqhty5o |
0.420624 |
Okda_2017, Hu_W_2013 |
Li_S_2016, Elshabrawy_2012 |
| 40 |
Cheng_2005 |
Cross-reactivity of antibody against SARS-coronavirus nucleocapsid protein with IL-11 |
Cheng, Man; Chan, Ceci W.L.; Cheung, Randy C.F.; Bikkavilli, Rama Kamesh; Zhao, Qi; Au, Shannon W.N.; Chan, Paul K.S.; Lee, Susanna S.T.; Cheng, Gregory; Ho, Walter K.K.; Cheung, Wing-Tai |
2005 |
2005-12-23 |
PMC |
N |
PMC7092895 |
16263078.0 |
10.1016/j.bbrc.2005.10.088 |
tlnao8y3 |
0.418663 |
Okda_2017, Thullier_1999, Andoh_2015, Nagesha_2001 |
Zhao_2005, Liu_S_2006, Oleszak_1990 |
| 41 |
Liu_G_2016 |
The C-Terminal Portion of the Nucleocapsid Protein Demonstrates SARS-CoV Antigenicity |
Liu, Guozhen; Hu, Shaohui; Hu, Yongwu; Chen, Peng; Yin, Jianning; Wen, Jie; Wang, Jingqiang; Lin, Liang; Liu, Jinxiu; You, Bo; Yin, Ye; Li, Shuting; Wang, Hao; Ren, Yan; Ji, Jia; Zhao, Xiaoqian; Sun, Yongqiao; Zhang, Xiaowei; Fang, Jianqiu; Wang, Jian; Liu, Siqi; Yu, Jun; Zhu, Heng; Yang, Huanming |
2016 |
2016-11-28 |
None |
N |
PMC5172413 |
15629031.0 |
10.1016/s1672-0229(03)01024-6 |
lwnkubnz |
0.418663 |
|
Das_D_2006, Li_S_2016 |
| 42 |
Leung_2004 |
Antibody Response of Patients with Severe Acute Respiratory Syndrome (SARS) Targets the Viral Nucleocapsid |
Leung, Danny Tze Ming; Chi Hang, Tam Frankie; Chun Hung, Ma; Sheung Chan, Paul Kay; Cheung, Jo Lai Ken; Niu, Haitao; Tam, John Siu Lun; Lim, Pak Leong |
2004 |
2004-07-15 |
PMC |
N |
PMC7110057 |
15216476.0 |
10.1086/422040 |
a9gkath5 |
0.416858 |
Lee_H_2010, Wrammert_2011, Hu_W_2013 |
Shi_Y_2004, Saijo_2005 |
| 43 |
Chou_2005 |
A novel cell-based binding assay system reconstituting interaction between SARS-CoV S protein and its cellular receptor |
Chou, Chih-Fong; Shen, Shuo; Tan, Yee-Joo; Fielding, Burtram C.; Tan, Timothy H.P.; Fu, Jianlin; Xu, Qiurong; Lim, Seng Gee; Hong, Wanjin |
2005 |
2005-01-31 |
PMC |
N |
PMC7112911 |
15582697.0 |
10.1016/j.jviromet.2004.09.008 |
w0pewq52 |
0.413364 |
Okda_2017 |
Han_D_2004, Elshabrawy_2012 |
| 44 |
Yip_C_2006 |
Naturally Occurring Anti-Escherichia coli Protein Antibodies in the Sera of Healthy Humans Cause Analytical Interference in a Recombinant Nucleocapsid Protein-Based Enzyme-Linked Immunosorbent Assay for Serodiagnosis of Severe Acute Respiratory Syndrome |
Yip, Chi Wai; Hon, Chung Chau; Zeng, Fanya; Chow, Ken Y. C.; Chan, Kwok Hung; Peiris, Joseph S. M.; Leung, Frederick C. C. |
2006 |
2006-11-15 |
None |
N |
PMC1797702 |
17108287.0 |
10.1128/cvi.00136-06 |
hyqya393 |
0.413117 |
Hohdatsu_1987, Elia_2003, Tuchiya_1991, Saijo_2005 |
Saijo_2005, Abdelwahab_2015 |
| 45 |
He_Q_2005 |
Characterization of monoclonal antibody against SARS coronavirus nucleocapsid antigen and development of an antigen capture ELISA |
He, Qigai; Du, Qingyun; Lau, Suelyn; Manopo, Ivanus; Lu, Liqun; Chan, Shzu-Wei; Fenner, Beau J.; Kwang, Jimmy |
2005 |
2005-07-31 |
PMC |
N |
PMC7112885 |
15893565.0 |
10.1016/j.jviromet.2005.03.004 |
sj8ngpk8 |
0.413061 |
Lee_H_2010, Okda_2017, Paton_1991, Hu_W_2013, Che_X_2005 |
Xing_2009, Saijo_2005 |
| 46 |
Hua_R_2004 |
Identification of two antigenic epitopes on SARS-CoV spike protein |
Hua, Ronghong; Zhou, Yanjun; Wang, Yunfeng; Hua, Yuzhuo; Tong, Guangzhi |
2004 |
2004-07-02 |
PMC |
N |
PMC7111154 |
15184071.0 |
10.1016/j.bbrc.2004.05.066 |
10qpje4d |
0.408027 |
Okda_2017, Nagesha_2001, Andoh_2015 |
Elshabrawy_2012, Li_S_2016 |
| 47 |
Duan_2005 |
A human SARS-CoV neutralizing antibody against epitope on S2 protein |
Duan, Jinzhu; Yan, Xiyun; Guo, Xueming; Cao, Wuchun; Han, Wei; Qi, Cai; Feng, Jing; Yang, Dongling; Gao, Guangxia; Jin, Gang |
2005 |
2005-07-22 |
PMC |
N |
PMC7092839 |
15939399.0 |
10.1016/j.bbrc.2005.05.089 |
mlz1rb1w |
0.399369 |
Okda_2017, Hu_W_2013, Wrammert_2011 |
Elshabrawy_2012, Zhao_2004 |
| 48 |
Das_D_2006 |
Copious production of SARS-CoV nucleocapsid protein employing codon optimized synthetic gene |
Das, Dipankar; Suresh, Mavanur R. |
2006 |
2006-11-30 |
PMC |
N |
PMC7112773 |
16904198.0 |
10.1016/j.jviromet.2006.06.029 |
7y5i2w8x |
0.396384 |
|
Liu_S_2006, Li_S_2016, Shi_S_2006 |
| 49 |
Temperton_2005 |
Longitudinally Profiling Neutralizing Antibody Response to SARS Coronavirus with Pseudotypes |
Temperton, Nigel J.; Chan, Paul K.; Simmons, Graham; Zambon, Maria C.; Tedder, Richard S.; Takeuchi, Yasuhiro; Weiss, Robin A. |
2005 |
2005-03-23 |
PMC |
N |
PMC3298259 |
15757556.0 |
10.3201/eid1103.040906 |
gvnylnen |
0.395492 |
Lee_H_2010, Hu_W_2013 |
Lv_H_2020 |
| 50 |
Chow_2004 |
Healthcare Worker Seroconversion in SARS Outbreak |
Chow, Pierce K. H.; Ooi, Eng-Eong; Tan, Hiang-Khoon; Ong, Kong-Wee; Sil, Bijon Kumar; Teo, Melissa; Ng, Timothy; Soo, Khee-Chee |
2004 |
2004-02-23 |
PMC |
N |
PMC3322936 |
15030691.0 |
10.3201/eid1002.030397 |
ifgef818 |
0.394076 |
Lee_H_2010, Che_X_2005, Saijo_2005 |
|
| 51 |
Chan_2013 |
Cross-reactive antibodies in convalescent SARS patients' sera against the emerging novel human coronavirus EMC (2012) by both immunofluorescent and neutralizing antibody tests |
Chan, Kwok-Hung; Chan, Jasper Fuk-Woo; Tse, Herman; Chen, Honglin; Lau, Candy Choi-Yi; Cai, Jian-Piao; Tsang, Alan Ka-Lun; Xiao, Xincai; To, Kelvin Kai-Wang; Lau, Susanna Kar-Pui; Woo, Patrick Chiu-Yat; Zheng, Bo-Jiang; Wang, Ming; Yuen, Kwok-Yung |
2013 |
2013-08-31 |
PMC |
N |
PMC7112694 |
23583636.0 |
10.1016/j.jinf.2013.03.015 |
26ey3fm8 |
0.383770 |
Lee_H_2010, Hu_W_2013 |
Shin_1993, Saijo_2005 |
| 52 |
He_Y_2005 |
Identification of a critical neutralization determinant of severe acute respiratory syndrome (SARS)-associated coronavirus: importance for designing SARS vaccines |
He, Yuxian; Zhu, Qingyu; Liu, Shuwen; Zhou, Yusen; Yang, Baoan; Li, Jiaming; Jiang, Shibo |
2005 |
2005-03-30 |
PMC |
N |
PMC7111853 |
15749124.0 |
10.1016/j.virol.2005.01.034 |
7y4bpjdw |
0.382214 |
Hu_W_2013, Okda_2017, Wrammert_2011 |
Elshabrawy_2012 |
| 53 |
Shin_2006 |
Preparation and characterization of a novel monoclonal antibody specific to severe acute respiratory syndrome-coronavirus nucleocapsid protein |
Shin, Gu-Choul; Chung, Yoon-Seok; Kim, In-Soo; Cho, Hae-Wol; Kang, Chun |
2006 |
2006-12-31 |
PMC |
N |
PMC7114302 |
16942813.0 |
10.1016/j.virusres.2006.07.004 |
gv1sgbk1 |
0.378436 |
Okda_2017, Hu_W_2013 |
Li_S_2016, Xue_G_2013 |
| 54 |
Zhao_2007 |
Comparison of Immunoglobulin G Responses to the Spike and Nucleocapsid Proteins of Severe Acute Respiratory Syndrome (SARS) Coronavirus in Patients with SARS |
Zhao, Jincun; Wang, Wei; Wang, Wenling; Zhao, Zhendong; Zhang, Yan; Lv, Ping; Ren, Furong; Gao, Xiao-Ming |
2007 |
2007-05-02 |
None |
N |
PMC1951070 |
17475765.0 |
10.1128/cvi.00432-06 |
mheawgn9 |
0.363408 |
Hasony_2005, Che_X_2005 |
Qiu_M_2005, Shi_Y_2004 |
| 55 |
Ohnishi_2007 |
Establishment and Characterization of Monoclonal Antibodies Against SARS Coronavirus |
Ohnishi, Kazuo |
2007 |
2007-11-28 |
PMC |
N |
PMC7120479 |
19057876.0 |
10.1007/978-1-59745-181-9_15 |
r0x8yaqj |
0.356666 |
Hu_W_2013, Chang_2004, Lee_H_2010 |
Berry_2004, Oleszak_1990 |
| 56 |
Kang_2006 |
Human Neutralizing Fab Molecules against Severe Acute Respiratory Syndrome Coronavirus Generated by Phage Display |
Kang, Xiaoping; Yang, Bao-an; Hu, Yuyang; Zhao, Hui; Xiong, Wei; Yang, Yinhui; Si, Bingyin; Zhu, Qingyu |
2006 |
2006-08-01 |
None |
N |
PMC1539127 |
16893997.0 |
10.1128/cvi.00037-06 |
55b7xvmk |
0.344819 |
Okda_2017, Nagesha_2001, Hu_W_2013 |
Elshabrawy_2012, Chen_2011 |
| 57 |
Liu_I_2004 |
Disease-specific B cell epitopes for serum antibodies from patients with severe acute respiratory syndrome (SARS) and serologic detection of SARS antibodies by epitope-based peptide antigens |
Liu, I-Ju; Hsueh, Po-Ren; Lin, Chin-Tarng; Chiu, Chien-Yu; Kao, Chuan-Liang; Liao, Mei-Ying; Wu, Han-Chung |
2004 |
2004-08-15 |
PMC |
Y |
PMC7109815 |
15272409.0 |
10.1086/422753 |
nqt9lhcc |
0.344819 |
Lee_H_2010, Hu_W_2013, Wrammert_2011 |
Yu_H_2007, Saijo_2005, Hua_R_2013 |
| 58 |
Liu_C_2007 |
Establishment of a reference panel for the detection of anti-SARS-CoV antibodies |
Liu, Chunyu; Li, Xiuhua; Zhang, Chuntao; Xu, Sihong; Shao, Yiming; Zhuang, Hui; Che, Xiaoyan; Qiu, Yan; Yin, Hongzhang; Li, Defu; Wang, Youchun |
2007 |
2007-06-30 |
PMC |
N |
PMC7129324 |
17261372.0 |
10.1016/j.biologicals.2006.11.001 |
zqjiiy4l |
0.343246 |
Lee_H_2010, Elia_2003, Che_X_2005, Leibowitz_1983 |
Saijo_2005, Xue_G_2013 |
| 59 |
Zhao_2004 |
DNA Vaccine of SARS-Cov S Gene Induces Antibody Response in Mice |
Zhao, Ping; Ke, Jin-Shan; Qin, Zhao-Lin; Ren, Hao; Zhao, Lan-Juan; Yu, Jian-Guo; Gao, Jun; Zhu, Shi-Ying; Qi, Zhong-Tian |
2004 |
2004-01-23 |
PMC |
N |
PMC7109828 |
14732873.0 |
10.1093/abbs/36.1.37 |
65iwx5nv |
0.336316 |
Hu_W_2013 |
Zhao_2005 |
| 60 |
Liang_2005 |
Comprehensive Antibody Epitope Mapping of the Nucleocapsid Protein of Severe Acute Respiratory Syndrome (SARS) Coronavirus: Insight into the Humoral Immunity of SARS |
Liang, Yunfei; Wan, Ying; Qiu, Li-wen; Zhou, Jingran; Ni, Bing; Guo, Bo; Zou, Qiang; Zou, Liyun; Zhou, Wei; Jia, Zhengcai; Che, Xiao-yan; Wu, Yuzhang |
2005 |
2005-08-01 |
PMC |
N |
PMC7108199 |
15976093.0 |
10.1373/clinchem.2005.051045 |
icuzy3vp |
0.335279 |
Hu_W_2013, Okda_2017, Wrammert_2011 |
Hua_R_2013, Li_S_2016 |
| 61 |
Lu_J_2005 |
Preparation and development of equine hyperimmune globulin F(ab′)(2) against severe acute respiratory syndrome coronavirus |
Lu, Jai-hai; Guo, Zhong-min; Han, Wen-yu; Wang, Guo-ling; Zhang, Ding-mei; Wang, Yi-fei; Sun, Sheng-yun; Yang, Qin-he; Zheng, Huan-ying; Wong, Bing L; Zhong, Nan-shan |
2005 |
2005-12-23 |
PMC |
N |
PMC7091834 |
16297347.0 |
10.1111/j.1745-7254.2005.00210.x |
z5z7p0n7 |
0.333128 |
Hohdatsu_1987, Lee_H_2010, Hu_W_2013, Wrammert_2011 |
Cui_Z_2019 |
| 62 |
Huang_2004 |
Evaluation of antibody responses against SARS coronaviral nucleocapsid or spike proteins by immunoblotting or ELISA |
Huang, Li‐Rung; Chiu, Chi‐Ming; Yeh, Shiou‐Hwei; Huang, Wen‐Hung; Hsueh, Po‐Ren; Yang, Wen‐Zieh; Yang, Jyh‐Yuan; Su, Ih‐Jen; Chang, Shan‐Chwen; Chen, Pei‐Jer |
2004 |
2004-05-24 |
PMC |
N |
PMC7167198 |
15170626.0 |
10.1002/jmv.20096 |
p8zp03cx |
0.333119 |
Elia_2003, Che_X_2005, Hohdatsu_1987, Chan_2004 |
|
| 63 |
Wuxing_2004 |
Expression and purification of SARS coronavirus membrane protein |
Wuxing, Dai; Mingjun, Lei; Shaoting, Wu; Zhihao, Chen; Liang, Liang; Hujrong, Pan; Li, Qin; Shitong, Gao; Shishan, Yuan; Renli, Zhang |
2004 |
2004-01-01 |
PMC |
N |
PMC7089427 |
15641679.0 |
10.1007/bf02831095 |
iw8oobbe |
0.332967 |
Shenyang_2007, Pan_X_2015 |
Loa_C_2004, Zhang_2010, Eshaghi_2005 |
| 64 |
Zhao_2007 |
Isolation and identification of an scFv antibody against nucleocapsid protein of SARS-CoV |
Zhao, Aizhi; Qin, Weijun; Han, Yueheng; Wen, Weihong; Zhang, Wenhong; Lian, Zhonghui; Chen, Gang; Zhang, Zhuoli; Peng, Jianqiang; Wang, He; Guo, Yinglu |
2007 |
2007-07-31 |
PMC |
N |
PMC7110486 |
17548223.0 |
10.1016/j.micinf.2007.04.008 |
mfrsk8mz |
0.327490 |
Nagesha_2001, Okda_2017, Pan_X_2015, Mourez_2007, Shenyang_2007 |
Li_S_2016, Liu_S_2006, Saijo_2005, Shi_S_2006 |
| 65 |
Qiu_X_2012 |
Calreticulin as a hydrophilic chimeric molecular adjuvant enhances IgG responses to the spike protein of severe acute respiratory syndrome coronavirus |
Qiu, Xiang; Hong, Chao; Li, Yue; Bao, Wanrong; Gao, Xiao‐Ming |
2012 |
2012-07-26 |
PMC |
N |
PMC7168421 |
22530918.0 |
10.1111/j.1348-0421.2012.00467.x |
ucfjo73c |
0.325366 |
|
|
| 66 |
Yu_F_2005 |
Evaluation of Inapparent Nosocomial Severe Acute Respiratory Syndrome Coronavirus Infection in Vietnam by Use of Highly Specific Recombinant Truncated Nucleocapsid Protein-Based Enzyme-Linked Immunosorbent Assay |
Yu, Fuxun; Le, Mai Quynh; Inoue, Shingo; Thai, Hong Thi Cam; Hasebe, Futoshi; del Carmen Parquet, Maria; Morita, Kouichi |
2005 |
2005-07-01 |
PMC |
N |
PMC1182204 |
16002634.0 |
10.1128/cdli.12.7.848-854.2005 |
4dz0ytwd |
0.325134 |
Lee_H_2010, Hohdatsu_1987 |
Saijo_2005, Yu_F_2007, Xue_G_2013 |
| 67 |
Timani_2004 |
Cloning, sequencing, expression, and purification of SARS-associated coronavirus nucleocapsid protein for serodiagnosis of SARS |
Timani, Khalid Amine; Ye, Li; Ye, Linbai; Zhu, Ying; Wu, Zhenghui; Gong, Zuojiong |
2004 |
2004-08-31 |
PMC |
Y |
PMC7130062 |
15163419.0 |
10.1016/j.jcv.2004.01.001 |
ejfp8gqz |
0.309909 |
Lee_H_2010, Che_X_2005, Elia_2003 |
Saijo_2005, Ren_A_2004 |
| 68 |
Han_D_2004 |
Development of a safe neutralization assay for SARS-CoV and characterization of S-glycoprotein |
Han, Dong P; Kim, Hyung G; Kim, Young B; Poon, Leo L.M; Cho, Michael W |
2004 |
2004-08-15 |
PMC |
Y |
PMC7127165 |
15262502.0 |
10.1016/j.virol.2004.05.017 |
isff6lp2 |
0.308044 |
|
Elshabrawy_2012 |
| 69 |
Pei_H_2005 |
Expression of SARS-coronavirus nucleocapsid protein in Escherichia coli and Lactococcus lactis for serodiagnosis and mucosal vaccination |
Pei, Huadong; Liu, Jingfang; Cheng, Yun; Sun, Chaomin; Wang, Chen; Lu, Yueping; Ding, Jie; Zhou, Jian; Xiang, Hua |
2005 |
2005-01-20 |
PMC |
N |
PMC7079895 |
15660214.0 |
10.1007/s00253-004-1869-y |
cu1713gy |
0.307514 |
Andoh_2015, Shenyang_2007, Pan_X_2015, Hohdatsu_1987 |
Saijo_2005, Zhao_2005, Shi_S_2006 |
| 70 |
Yu_H_2007 |
Selection of SARS-Coronavirus-specific B cell epitopes by phage peptide library screening and evaluation of the immunological effect of epitope-based peptides on mice |
Yu, Hua; Jiang, Li-Fang; Fang, Dan-Yun; Yan, Hui-Jun; Zhou, Jing-Jiao; Zhou, Jun-Mei; Liang, Yu; Gao, Yang; Zhao, Wei; Long, Bei-Guo |
2007 |
2007-03-15 |
PMC |
N |
PMC7103350 |
17055022.0 |
10.1016/j.virol.2006.09.016 |
djfj4262 |
0.306124 |
Okda_2017, Hu_W_2013 |
Lee_Y_2007 |
| 71 |
He_Y_2004 |
Receptor-binding domain of SARS-CoV spike protein induces highly potent neutralizing antibodies: implication for developing subunit vaccine |
He, Yuxian; Zhou, Yusen; Liu, Shuwen; Kou, Zhihua; Li, Wenhui; Farzan, Michael; Jiang, Shibo |
2004 |
2004-11-12 |
PMC |
N |
PMC7092904 |
15474494.0 |
10.1016/j.bbrc.2004.09.106 |
a787fd1v |
0.301712 |
Okda_2017, Hu_W_2013 |
Elshabrawy_2012 |
| 72 |
Lai_S_2005 |
Characterization of neutralizing monoclonal antibodies recognizing a 15-residues epitope on the spike protein HR2 region of severe acute respiratory syndrome coronavirus (SARS-CoV) |
Lai, Szu-Chia; Chong, Pele Choi-Sing; Yeh, Chia-Tsui; Liu, Levent Shih-Jen; Jan, Jia-Tsrong; Chi, Hsiang-Yun; Liu, Hwan-Wun; Chen, Ann; Wang, Yeau-Ching |
2005 |
2005-08-19 |
PMC |
N |
PMC7089214 |
16132115.0 |
10.1007/s11373-005-9004-3 |
bbn16uf1 |
0.300724 |
Okda_2017, Hu_W_2013 |
Elshabrawy_2012 |


Introduction
This document is the official ‘Regulatory Document List’ referred to in Condition J1.8 of our
General Conditions of Recognition
. It replaces all previous versions of that list.
The documents listed below are the Regulatory Documents (as defined in Condition J1.8) which are currently in force. For ease of reference, the list is organised alphabetically by qualification type, with hyperlinks to individual documents or lists of documents.
About Regulatory Documents
Regulatory Documents contain qualification-specific rules and guidance.
Our General Conditions of Recognition require an awarding organisation to ensure that:
-
it complies with any requirement to take or to refrain from taking any action specified in a Regulatory Document
-
it has regard to any guidelines or principles of good practice in relation to any behaviour on the part of an awarding organisation set out in a Regulatory Document
-
any qualification it makes available, or proposes to make available, complies with any requirement relating to that qualification which is set out in a Regulatory Document
-
in the development, delivery and award of any qualification which it makes available, or proposes to make available, it has regard to any guidelines and principles of good practice relating to that qualification which are set out in a Regulatory Document
-
it only makes available a qualification which uses a unit or Rule of Combination developed by another person where it reasonably believes that:
-
the unit or Rule of Combination complies with the requirements relating to it that are set out in any Regulatory Document
-
in the development of the unit or Rule of Combination, due regard has been had to the guidelines and principles of good practice set out in any Regulatory Document.
In any case of difference or contradiction, the General Conditions of Recognition (and, where relevant, any Qualification Level Conditions or Subject Level Conditions) take precedence over any requirements or guidance set out in a Regulatory Document.
Advanced Extension Awards (AEAs)
English for Speakers of other Languages (ESOL)
Functional Skills
GCE AS and A level
All GCE AS and A level qualifications
GCSE (graded A* to G)
Key skills
Level 1/2 Certificates


4 references to WriteConnectFailed
System.Management.Automation (4)
engine\remoting\commands\ConnectPSSession.cs (4)
559
WriteConnectFailed
(ex, _session);
602
WriteConnectFailed
(ex, session);
611
WriteConnectFailed
(ex, session);
658
WriteConnectFailed
(eArgs.RunspaceStateInfo.Reason, _session);


Remember the Titalns (2000) 3 1/2 stars out of 4. Starring Denzel Washington, Will Patton, Wood Harris and Ryan Hurst. Written by Gregory Allen Howard. Directed by Boaz Yakin.
Any football coach with a lick of smarts should take his team - en masse - to see "Remember the Titans."
Not because it is a great movie - it is very good, despite its usual quota of sports clichés - but because it is a film that amply displays how a team is forged and how the concept of team can overcome even the most hardened social structures and ideologies.
Alexandria, Va., 1971. The last vestiges of segregation are dying as the school district is finally integrated. At T.C. Williams High School football coach Bill Yoast (Will Patton) has a new assistant coach, Herman Boone (Denzel Washington), a black man with years of coaching experience in South Carolina.
Later, in a political move to appease the black community, Yoast is demoted and Boone is named head coach, but with a codicil: His team cannot lose one game or he will be fired.
This situation causes tension and animosity not only among the coaching staff, but among the players. Boone, though, is determined to fight through these obstacles. He surprises the black players by refusing to show them preferential treatment. Nor will he brook any insubordination from the white players or his assistant coaches.
His message is simple and direct: The only colors on the football field are those on the Titan uniform.
He is first tested when his players board buses to ride to practice. The white players get on one bus, blacks on another. Boone makes everyone disembark and the buses are designated for offense and defensive players, no matter what that player's color.
Washington creates a towering figure in Boone. He never allows his guard to fall, always appearing in control, self-confident, unswaying, single-minded and ferocious in his commitment to forge one cohesive unit from his diverse group of young men.
And Washington accomplishes this feat without being flashy or showy. He is steel, an uncompromising locomotive steaming over all who get in his way, including his assistants.
Washington's Boone is a bully, a tyrant, driving his players to the point where they focus all their thoughts on him, forgetting their differences and uniting in self protection. W orking uneasily at first Boone and Yoast mold these young men into a dynamic, winning team, triumphing over the town's prejudice and the intolerance of many of the people around them.
Patton's Yoast is a less flashy character than Washington's Boone. But in his quiet way, he is as strong as Boone, seeing what the coach is trying to accomplish and helping him along without calling attention to himself.
Patton's performance is something that should be studied by acting students. He serves the purpose of the supporting character, which is to advance the story without hogging the spotlight from the film's nominal star. In this Patton succeeds wonderfully, and he deserves a best supporting actor Oscar nomination if not the statue itself for his portrayal.
Two young actors also deserve recognition: Wood Harris as Julius Campbell, leader of the black players, and Ryan Hurst as Gerry Bertier, the Titans' captain. Like their elders these two begin their relationship under a cloud of distrust and suspicion.
But they rise above their preconceived biases, forging an alliance that puts team ahead of any personal glory.
"Remember the Titans" is a moving, heartfelt drama. It is masterful, packed with emotion and some humor. It is an inspiring movie that should not be missed.
Bob Bloom is the film critic at the Journal and Courier in Lafayette, IN. He can be reached by e-mail at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>Reviews by Bloom can be found on the Internet Movie Database at: http://www.imdb.com/M/reviews_by?Bob+Bloom
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Your Galileo is connected via a nodejs websocket to the button below. Use it to confirm the device is properly configured.


As a developer, I was exceptionally tired of using Word for documentation. It was always so heavy, both in file size as well as load time, and was such a pain to format content, indent, etc... without spending unnecessary mouse-time adjusting things. My primary use was to write large chunks of documentation that would need a table of contents that worked, and I really wanted a way for users to be able to load it up without having to download a copy of my doc, then open it up in Word. In addition, the ToC functionality of Word is beyond abysmal. So I wrote (and derived from others, particularly http://www.webtoolkit.info/) a tool that allows me to write clean HTML with exceptionally simple syntax that would produce content that I could post on our doc system, and would utilize the css of wherever it is dropped to fit right in, but still have all my content how I wanted it. In addition, I wanted to make sure that links to remote images didn't break the content, so I added in a derived work to automatically convert linked images into their base64 content versions locally. The end result is that you can write clean documentation, load it in a browser, then copy that HTML and paste anywhere to have all your content exactly as intended.
The auto-ToC tool simply watches h# tags, and nests them as it sees them. So simply write your content within 'p' or 'div' tags using 'h#' tags to divide things up, as you can see expressed within the code of this doc.
If you wish to serve up the content produced (ToC, images, etc...) elsewhere (Like a blog or doc management system)
simply load up your page in a browser locally, and browse the source of the page (I use Chrome's debug mode)
Copy/paste the HTML content within the body tags into whatever system you want. Your images will be converted from
remote links into their base64 versions, and you will have an operational ToC.


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The Multi-Dimensional Graphic Visualiser Design Document
Aims:
The Multi-Dimensional Graphic Visualiser was created so that it could become a part of the Core Data Mining System (CDMS). The idea of the Visualiser was to create an extendible set of classes that would enable a User to see a multi-dimensional representation of their data. It needed to allow the User to manipulate the representation so that patterns could be found. It also needed to cope with any amount and type of data that it was presented with.
Method:
Java was the programming language chosen for CDMS, and so the Visualiser is also written in Java, using the extended Java3D classes. The choice to use the pre-packaged classes was based on the assumption that Sun had probably written the classes for creating and viewing 3D constructs in the most efficient way possible, so creating my own would be "reinventing the wheel" and likely to be less efficient. Also, at the time of programming, Java3D implementations were available for Windows and Solaris platforms with the Linux version under development. It was also noted that the Java3D classes were being released with the updated versions of Java, and were therefore (theoretically) becoming more common.
Program Overview:
In the future, the CDMS core program will create an instance of a class called a GO3DVisualizer. This object will receive data in a form recognisable to CDMS and create a new object with that data, a GO3DVizPanel. This 'VizPanel' will be placed in a window by CDMS and displayed for the User automatically. The 'VizPanel' itself handles all operations on the data it displays (such as moving in 3D, changing axes types, changing sampling, etc) and does not (currently) allow outside functions (etc.) to modify it. There is no real reasoning behind this 'one-way' method of interaction implementation, and I expect that it will be altered so that it can be manipulated externally at some stage in the future.
The output of the 'VizPanel' is, for the most part, visual data. In the future it is assumed that the User will be able to select some of that data and pass it to yet another part of the CDMS, but this is not yet implemented.
Implementation details:
The inside of a 'VizPanel' is quite complex. It contains many Java3D constructs, most of which form the 'Scene Graph' which is the set of objects describing every part of everything in the virtual 3D space. A yet larger set of objects inside the 'VizPanel' deal with the buttons, panels, dialogs, etc. that make up the GUI that runs the visualiser. All these were created using the 'Swing' interface in keeping with the CDMS style. Of course, a copy of the input data values is kept in there too.
The most interesting classes inside the 'VizPanel' (at least from my point of view) were the GO3DAxis and GO3DSubObj classes. As you can tell from their names, these were also created by me and, therefore, require the most explanation.
| GO3DAxis | |
|
For future reference, I use the term "axis" (or the plural "axes") to describe a kind of transformation between a value in a kind of "data space" and a value in "representation space". For example, suppose you had height data that ranged between 1.0 meters and 4.0 meters. This data is going to be displayed on a gradated colour scale using the colour Green. A value of 2.5 meters is in "data space" and a "green colour axis" would convert this to a "representation space" value of 50% green. The axes in the visualiser pose an interesting problem because the CDMS is supposed to be flexible enough to allow a User to manipulate their data using any method they choose. Currently, the number of axes in the visualiser extends beyond just the 3 space axes (namely X, Y and Z) to another 3 separate colour axes (namely R, G and B). The visualiser could in fact cope with more than 6 axes and a User may well want a "Transparency Axis" or even a "Sound Axis". But not only do the representations of the axes change the method in which they transform data may also change. For example, some data may appear to have an undetectable pattern in its native form, but when you compare the natural log values the pattern may be quite obvious. Hence, we would expect some way of making any axis able to become a log scale. Besides, a User may not like the way I drew my axes and want them to be a funky purple and green pattern! The main problem is, that it is nigh on impossible to guess all the representations and methods every user will require. Therefore, the axis calculations and representations were abstracted away and made into a pattern that can be built on by subsequent Users. The basic axis system consists of an abstract GO3DAxis class which contains the data and methods common to all types of axes. There are two extensions of GO3DAxis, namely GO3DSpaceAxis and GO3DRGBAxis. These contain basic abilities that space and RGB-colour axes should be able to perform. Now, a "GO3DFunkySpaceAxis" class can be created from the GO3DSpaceAxis class that overwrites the method getBranch() and returns differently shaped and/or coloured axes. Or perhaps a User might create a "GO3DLogScale" interface that enables a "GO3DLogSpaceAxis" and a "GO3DLogRGBAxis". All of which can be created and added in as new axis representations. |
|
| GO3DSubObj | |
|
A similar problem occurred with the actual representation. Not everyone wants to see a simple scatter-plot of his or her data. Some people may want a histogram or a plot containing error margins, for example. The same design concept of creating a basic class and its specialities was used here too. The GO3DSubObj is a graphic object representing the data. Two implementations of which, the GO3DStarFieldPlot and the GO3DScatterPlot have been created. As with the axes, in the future the User will be able to make and use their own representations from within the CDMS. |
GUI Design:
The layout for the 'VizPanel' is quite simple: It is completely button oriented. This means that worrying about window focus and keystrokes is not needed. The 3D version of the Canvas takes up most of the space with two toolbars along the bottom and right hand edges. The bottom edge contains all the navigational controls and the right hand edge contains the other tools.
The navigation was based on the simple idea that the less buttons, the easier. A toggle switch chooses whether the User is in "Translate Mode" or "Rotate Mode". In "Translate Mode" the six directional arrows -move the object- in the direction of the arrow. In "Rotate Mode" the 6 directional arrows -rotate the object- in the direction of the arrow. Note that all navigation affects the object, not the camera position. For reasons only known to Java3D, I have been unable to find a way of making the transformations apply to the "camera" position rather than the object position.
On the other tool-bar are:


Finding the right next book after finishing the last one is often a hard task. Generally, the amount of books in a bookshop or library is so big that it is hard to determine where to start looking. Titles can be deceiving and reading the back cover of each book would also take way too long. Search engines are biased and the recommendation systems often recommend books that are very popular and may overlook possible very good matches that get little attention.
You want to find a good book anywhere, on any shelf, at the very moment that you’re standing in front of it. BookLab will help you discover books that may otherwise have gone unnoticed.
BookLab is a proud initiative of {{vera}}, {{fabian}}, {{sayra}}, {{marino}} and {{christian}}.


Quantization Algorithms
The following quantization methods are currently implemented in Distiller:
DoReFa
(As proposed in DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients)
In this method, we first define the quantization function , which takes a real value and outputs a discrete-valued , where is the number of bits used for quantization.
Activations are clipped to the range and then quantized as follows:
For weights, we define the following function , which takes an unbounded real valued input and outputs a real value in :
Now we can use to get quantized weight values, as follows:
This method requires training the model with quantization, as discussed here. Use the DorefaQuantizer
class to transform an existing model to a model suitable for training with quantization using DoReFa.
Notes:
- Gradients quantization as proposed in the paper is not supported yet.
- The paper defines special handling for binary weights which isn't supported in Distiller yet.
PACT
(As proposed in PACT: Parameterized Clipping Activation for Quantized Neural Networks)
This method is similar to DoReFa, but the upper clipping values, , of the activation functions are learned parameters instead of hard coded to 1. Note that per the paper's recommendation, is shared per layer.
This method requires training the model with quantization, as discussed here. Use the PACTQuantizer
class to transform an existing model to a model suitable for training with quantization using PACT.
WRPN
(As proposed in WRPN: Wide Reduced-Precision Networks)
In this method, activations are clipped to and quantized as follows ( is the number of bits used for quantization):
Weights are clipped to and quantized as follows:
Note that bits are used to quantize weights, leaving one bit for sign.
This method requires training the model with quantization, as discussed here. Use the WRPNQuantizer
class to transform an existing model to a model suitable for training with quantization using WRPN.
Notes:
- The paper proposed widening of layers as a means to reduce accuracy loss. This isn't implemented as part of
WRPNQuantizer
at the moment. To experiment with this, modify your model implementation to have wider layers. - The paper defines special handling for binary weights which isn't supported in Distiller yet.
Symmetric Linear Quantization
In this method, a float value is quantized by multiplying with a numeric constant (the scale factor), hence it is Linear. We use a signed integer to represent the quantized range, with no quantization bias (or "offset") used. As a result, the floating-point range considered for quantization is symmetric with respect to zero.
In the current implementation the scale factor is chosen so that the entire range of the floating-point tensor is quantized (we do not attempt to remove outliers).
Let us denote the original floating-point tensor by , the quantized tensor by , the scale factor by and the number of bits used for quantization by . Then, we get:
(The operation is round-to-nearest-integer)
Let's see how a convolution or fully-connected (FC) layer is quantized using this method: (we denote input, output, weights and bias with and respectively) Note how the bias has to be re-scaled to match the scale of the summation.
Implementation
We've implemented convolution and FC using this method.
- They are implemented by wrapping the existing PyTorch layers with quantization and de-quantization operations. That is - the computation is done on floating-point tensors, but the values themselves are restricted to integer values. The wrapper is implemented in the
RangeLinearQuantParamLayerWrapper
class. - All other layers are unaffected and are executed using their original FP32 implementation.
- To automatically transform an existing model to a quantized model using this method, use the
SymmetricLinearQuantizer
class. - For weights and bias the scale factor is determined once at quantization setup ("offline"), and for activations it is determined dynamically at runtime ("online").
- Important note: Currently, this method is implemented as inference only, with no back-propagation functionality. Hence, it can only be used to quantize a pre-trained FP32 model, with no re-training. As such, using it with is likely to lead to severe accuracy degradation for any non-trivial workload.


We can set some breakpoints and tell our media queries to change the background color of our page (or anything else we want) at each breakpoint.
Check out the media query examples at the bottom of your styles.css file!


Our first location was at Dau, Mabalacat Pampanga, which is in front of S&R Dau. We are very happy to see our customers getting excited whenever they order and being curious about our BBC varieties (which we think that's the reason why they are still coming back to us even if we relocated!) We see their eyes brighten up as we serve them our specialties, and it really really brightens up our day, seeing our customer satisfied upon leaving. Until then, we keep on striving for the better, not just for our sake, but for our consistent returnees who have faith on our capabilities.
We took a big step by taking the opportunity to relocate to a place where people are active, loves to eat, and whom might be missing the moments of their lives to eat the most delicious steaks and burgers in the town of Angeles City!
Yes, we accept. 8 y/o below are free.
Present an ID and they are subjected to 20% discount. (Discount is only applied to the PWD & Senior citizen)
We are open daily, 2PM-12MN.
No, only walk-ins. Please come early.
As of now, we deliver around Angeles City and nearby places only. Additional charges may apply.
We are located here at Miranda Ext. Brgy. San Nicolas, Angeles City, Pampanga.
Near New Star, beside Chicken Star.
Absolutely YES. We serve cocktails and beer towers, check our menu from our menu tab. Drink responsibly!
Yes, we have parkings nearby our restaurant.
Yes, we have a beer pong game.
There's no time limit, but leftovers will be charged 200php per head.
We only accept cash and Gcash.
We offer burgers, steaks, salads, and pastas.
Unlimited Wings & Unlimited Steaks.
For more inquiries, bookings and reservations, please message our social media pages by clicking the buttons below.


WEE
URL:
Zoom
Fuzzy
Dithering:
None
Rob Ordered
Rob Atkinson
Diffusion
Colors:
B&W
64-Color
Greyscale
Brightness:
0
Contrast:
0
Your browser does not support the HTML5 canvas tag.
Your browser does not support the HTML5 canvas tag.


|
Elektra
0.8.21
|
Every key in Elektra needs a unique name so that administrators can refer to them unambiguously. Sometimes, multiple keys denote the same configuration item from different sources, e.g.:
To allow such keys to exist in parallel, Elektra uses namespaces.
A namespace has following properties:
user
namespace are from the users home directory, even if an absolute configuration file name was used.Following parts of Elektra source code are affected by namespaces:
In the rest of this document all currently available namespaces in the default order are described.
Unlike the other namespaces, the specification namespace does not contain values of the keys, but instead metadata as described in METADATA.ini.
When a cascading key is looked up, keys from the spec-namespace are the first to be searched. When a spec-key is found, the rest of the lookup will be done as specified, probably in a different order than the namespaces enlisted here.
Usually, the spec-keys do not directly contribute to the value, with one notable exception: the default value (metadata default
, see in cascading below) might be used if every other way as specified in the spec-key failed.
Spec-keys typically include a explanation and description for the key itself (but not comments which are specific for individual keys).
The spec configuration files are below CMAKE_INSTALL_PREFIX/KDB_DB_SPEC
.
spec is not part of cascading mounts, because the specifications often are written in different syntax than the configuration files.
Derived from the process (e.g. by parsing /proc/self or by arguments passed from the main method):
Keys in the namespace proc can not be stored by their nature. Thus they are ignored by kdbGet
and kdbSet
. They might be different for every invocation of an application.
Keys from the namespace dir
are derived from a directory special to the user starting/using the application, e.g.:
.git
.htaccess
Note that Elektra only supports a single special directory per KDB instance. Start a new KDB instance if you need different special directories for different parts of your application. How to change the directory may be different dependent on the resolver, e.g. by using chdir or by setting the environment variable PWD.
On multi-user operating systems obviously every user wants her/his own configuration. The user configuration is located in the users home directory typically below the folder KDB_DB_USER. Other paths below the home directory are possible too (absolute path for resolver).
Note that Elektra only supports a user directory per KDB instance. Start a new KDB instance if you need different user configuration for different parts of your application. How to change the user may be different dependent on the resolver, e.g. by seteuid() or by environment variables like HOME, USER
The system configuration is the same for every chroot.
The configuration is typically located below KDB_DB_SYSTEM. Other absolute paths, e.g. below /opt or /usr/local/etc are possible too.
Keys that are not in a namespace (i.e. start with an /
) are called cascading keys. Cascading keys do not stem from a configuration source, but are used by applications to lookup a key in different namespaces. So, multiple keys can contribute to each cascading key name.
Cascading is the same as a name resolution and provides a namespace unification as described in Versatility and Unix semantics in namespace unification.
Keys without a namespace can not be stored by their nature. So they are transient: after a restart they are forgotten.
Keys of that namespace are only used by ksLookup when no other suitable key was found. So they have the lowest possible priority, even fallback keys are preferred.


Commons Logging uses Maven 2.0.x as its primary build system. Ant can also be used.
To build the full website, run
mvn site
The result will be in the target/site
folder.
You must be online and using JDK 1.4 or higher to successfully complete this target.
To build the jar files, run
mvn package
The resulting 4 jar files will be in the target
folder.
You must use JDK 1.4 or higher to successfully complete this target.
To create a full distribution, run
mvn clean site assembly:assembly
The resulting .zip and .tar.gz files will be in the target
folder.
You must use JDK 1.4 or higher to successfully complete this target.
Further details can be found in the commons build instructions.
We still use Ant to test the artifacts built my Maven.
Please follow the instructions in the file build-testing.xml
.
Note: A 1.2 JDK is needed to run the tests.


There are 22 major languages in India, written in 13 different scripts, with over 720 dialects. The official Indian languages are Hindi (with approximately 420 million speakers) and English, which is also widely spoken.
In addition, several states in India have their own official languages, which are usually only spoken particular areas. Among them are Bengali (83 million speakers), Telugu (spoken by 74 million people) and Marathi (72 million speakers). However, standard Hindi, which is based on a colloquial dialect around Delhi, is taught at all schools in India.
Hindi is spoken in north and central India. However, there are many dialects in India and Hindi is more like a rubric for different dialects. Whether a regional variation is considered Hindi or a dialect depends solely on social perceptions and not on mutual intelligibility. As a rule, the further the distance between regions in India using Hindi, the harder it will be for speakers to understand each other. The relationships between dialects far away from each other are probably roughly proportional to the relationships of Latin-derived languages, such as French, Spanish and Portuguese.
In the south of India there is a greater diversity of languages and you will have difficulties getting along with Hindi. Languages differ even between the important industrial centers Bangalore, Madras and Hyderabad. English proves to be helpful here. However, you may have problems understanding Indian English (Hinglish) as there are peculiarities in grammar and vocabulary. So if someone in India says he passed out of school it doesn't mean that it knocked him unconscious, just that he finished successfully. The main languages in South India are Malayalam, Tamil, Telugu and Kannada. They are all Dravidian languages and, therefore, share structural aspects. Much of the vocabulary was borrowed from languages such as Hindi, so there are often only different pronunciations and slight shifts in meaning.
Hindi and many Indian languages use the Devanagari alphabet, which was originally used to write Sanskrit. It is written from left to right and can be easily identified by a horizontal bar at the top of each letter. Each letter resembles a single consonant or vowel. To being able to read languages using Devanagari without having to know their letters, there is the International Alphabet of Sanskrit Transliteration (IAST). Each Devanagari letter is resembled by a Roman character which sounds, more or less, equal to its Devanagari equivalent.
You will also meet people in the north of India saying they speak Urdu. However, Hindi and Urdu are basically the same language. The only main difference is that Hindi uses the Sanskrit-based Devanagari script in contrast to the Perso-Arabic script of Urdu. The vocabulary of both languages is essentially the same. If there is no word for a concept, both will borrow words from either Sanskrit or Persian, respectively. However, speakers of Urdu and Hindi will not encounter communication difficulties in everyday conversations.


{% extends "email/email_base.html" %} {% block content%}
Hi,
An event "{{ event.title }}" has been created.
Start Date: {{ event.start_date }}
End Date: {{ event.end_date }}
{{ event.description }}
Visit {{ site_url }}{{ event.get_absolute_url }} to review the event.
{% endblock %}


Base class for all operations; used to create new instances of derived classes from text-based source.
More...
#include <BotOperation.hpp>
|
|
std::string | code |
| |
|
std::string | rawText |
| |
Base class for all operations; used to create new instances of derived classes from text-based source.
| BotOperation::BotOperation |
( |
| ) |
|
| BotOperation::BotOperation |
( |
const std::string |
pRawText | ) |
|
Constructor for BotOperation; creates an instance of the base class that is possibly capable of being transformed into a derived class executable object.
- Parameters
-
| pRawText | std::string containing a possible operation code and details that could be transformed into an executable operation |
| BotOperation::BotOperation |
( |
const std::string |
pRawText, |
|
|
const std::string |
pCode |
|
) |
| |
Constructor for BotOperation; creates an instance of the base class that is possibly capable of being transformed into a derived class object that executable
- Parameters
-
| pRawText | std::string containing only the details of the operation specified in the pCode parameter |
| pCode | std::string containing an operation code that may be recognized as a valid operation code during transformation |
| std::string BotOperation::getCode |
( |
| ) |
|
Provides access to the code in an operation through the base class - primarily for testing purposes.
- Returns
- std::string code from this object
Base class method to construct a derived class object from source text (inserted by constructor)
- Parameters
-
| [in] | opParams | provides operational parameters for the system used to verify this operation |
- Returns
- boost::shared_ptr<BotOperation> for the derived class object (non-executable base object returned if transformation failed)
The documentation for this class was generated from the following files:


--- title: Command bar category: navbar order: 5 description: Command bars can be added to a navbar to support page-specific tasks, actions, etc. ---


Operation(arity: Arity, func: Function<T>)
An operation has an Arity and some function that it can perform on Arguments given to it.
Operations are specified as Modules, meaning that custom operations can be implemented and use when generating instructions for an individual in the population.
Operations should have some representation with them, so that the operation that they convey can be expressed in a textual form.
T
- Type of arguments that the operation operates on.


The update is currently being uploaded to the router. Please do not disconnect or turn off the router and don't refresh this page while it's being updated.
The update was successful and currently it's being installed. The router is being rebooted and you will lose access to the internet. Please allow the timer to expire before you connect back to the router.


Working out the fascia is different from cardiovascular, strength training or even stretching workouts, although, the body being, as ever, complex and an integrated functional unit, fascia workout shares elements with these other types of workouts.
But first, what is fascia? The definitions vary, it can be considered as synonymous with connective tissue or as a subset of connective tissue. Fascia is truly best understood at the cellular and molecular levels and in vivo. At the gross anatomical level it is the white stuff of tendons and ligaments, the sheets and streaks in the meat of muscle and the spider web type of filament tissue which reveals itself when separating tissue layers.
Among other things, Fascia is the true support structure of the body. It can be conceived of as a three dimensional net or web which embraces all the other anatomy of the body. If all was removed from the body, but the fascia, you would have the shape of a body down to its cellular details but with no content.
Without it we would be water filled skin bags with everything else floating randomly around inside.
Andrew Taylor Still, the founder of Osteopathic Manual Therapy, wrote over 150 years ago that the disease and health of the body is to be found in the fascia. It is very hard and somewhat unsatisfactory to dissect, as at the moment of death it collapses and we are left merely with the shell of its appearance. Fascia connects, separates, wraps and contains and transmits forces throughout the body, it is also the chemical laboratory of the body.
Blood is maybe too dirty and chaotic for delicate cell membranes, and maybe tho§e red blood cells are too big and potentially damaging to cell membranes should they bump against them. So the blood interfaces with the fascia and the fascia interfaces with the cell membranes. Put in other words, the cells of the body are intimate with the fascia not the blood, if not they die.
To work with fascia is to work with the fractal, multivacuolar, icosahedral and apparently chaotic biotensegrity system of the body. Humility helps as does non-egoic use of muscle contraction. It feels different than other forms of work-out although yoga and Asian chi types of exercise if taught correctly come close.
Fascia is affected by thoughts, feelings and emotions, for example, there are up to 10 times more proprioceptors (sensing receptors) in the fascia than in muscle cells. Tissue memory gets lodged in the fascia.
Mercifully there are practical ways to work with understand and feel fascia. Awareness plays a huge part in this and certainly willingness and openness to change.
To work out with fascia is to work with qualities of fluidity and flow, patience, observation and non egoic goals of movement and awareness. A useful image can be that of a spider managing its three-dimensional web. By the way, dysfunctions and pain and pathologies can be compared to flies stuck in the web.
Fascia has only recently been filmed and photographed for the first time in human history, in vivo, during forearm tendon surgery (with permission of the patient) by Dr. Guimberteau in France, and has opened up more questions than answers and revealed chasms of human ignorance on the subject with concommitant possibilities for scientific inquiry and research.
It is important not to overwork fascia more than once or twice a week would be counterproductive.
Loose light clothing and warmth is important.
The exercises are mostly simple with great attention placed to the awareness and quality of the movement.


Example: Accessing external Webservices
Load realtime data from the public
ITIS
Web Services
and convert the provided JSON data to Fancytree format.
See the
Taxonomy Browser
for a more sophisticated example.
Skin:
Integrated Taxonomic Information System
jquery.fancytree.js project home
Link to this page
Example Browser
View source code


@import uk.gov.hmrc.govukfrontend.views.html.components._
@this(govukInput : GovukInput,
govukButton : GovukButton)
@()
@govukInput(Input(
id = "utr",
name = "utr",
label = Label(
isPageHeading = true,
classes = "govuk-label--xl",
content = Text("What is your Corporation Tax Unique Taxpayer Reference?")
),
hint = Some(Hint(
content = HtmlContent("""This is 10 numbers, for example<PHONE_NUMBER>. It will be on tax returns and other letters about Corporation Tax. It may be called ‘reference’, ‘UTR’ or ‘official use’. You can find a lost UTR number.""")
)),
classes = "govuk-input--width-10"
))
@govukButton(Button(
content = Text("Continue")
))


RVO2 Library
Copyright © 2008-2010 University of North Carolina at Chapel Hill. All rights reserved.
Permission to use, copy, modify, and distribute this software and its documentation for educational, research, and non-profit purposes, without fee, and without a written agreement is hereby granted, provided that the above copyright notice, this paragraph, and the following four paragraphs appear in all copies.
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2017.08.03
on Aug 03, 2017 — Hubei, Xiangyang
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The Nim language has a couple of interesting features:
One typical example of numerical integration is the calculation of pi by approximation, specifically by estimation of area of a circle and area of a square.
area of circle = pi * r * r
area of enclosing square is (2*r)*(2*r)
select a random point
if a point is inside the circle then increment n
m = total number points
pi = 4 * n/m, give or take
This is an example of numerical integration but only on two dimensions. Usually this method is used for many more dimensions. Also, you often don’t have an absolute truth to compare your answer against!
The core of an implementation in Nim looks like
proc integpi(rand: Rand): float =
var r = rand
var randx, randy: float
var ctr: float = 0
for i in 0..<Nlim:
randx = float(r.next and int32bits)
randy = float(r.next and int32bits)
if ((randx*randx + randy*randy) < float(int32max)*float(int32max)):
ctr = ctr + 1
return ctr
Here we use 64-bit random integers masked to 32 bits. Then compare the circle boundary x * x + y * y < r * r. Pi is then 4*ctr/Nlim. This code uses floating point because that happened to be a quick way to avoid some Nim value conversion issues by this novice Nim programmer. It is a bit slower than using unsigned int64s throughout.
This is also an example of something that is embarrasingly parallel. You could run independent threads of integpi, and as long as the random number generators are independent, add up the results of each thread. Up to the limit of the density of random numbers in this 32-bit space of numbers, that is.
The threading model in Nim allows basic threads, and the various lock functions allow to synchronize threads.
An interesting feature of threads is they are non-deterministic. They are serial, but the priority and speed of each thread is up to the operating system. If you oversubscribe your CPUs, then you cannot expect anything other than eventual completion.
For example, on 2-core Penryn:
epi64timed.nim using 2 threads x<PHONE_NUMBER>0 loops
Thread report:
|***************************************************|
|***************************************************|
pi 3.141592653589793 estimated 3.141586181705268 diff -6.471884524739124e-06
The stars begin at earliest thread start time, and end at latest thread completion. Here it is no surprise both threads are concurrent.
epi64timed.nim using 8 threads x<PHONE_NUMBER>0 loops
Thread report:
|**************************************** |
|************** |
|*************************************** |
|************************************* |
| ************* |
| ************** |
| ***************|
| *************|
pi 3.141592653589793 estimated 3.141588725343425 diff -3.928246368190003e-06
Now that is an 8-thread program on a 2-core machine. Obviously some threads don’t start until later. These are listed in order of thread creation but there is no guarantee this pattern will repeat.
What about Linux, on a 4-core Raspberry Pi?
Here is that result:
pi 3.141592653589793 estimated 3.141593079161661 diff 4.255718679679887e-07
epi64timed.nim using 8 threads x<PHONE_NUMBER>0 loops
Thread report:
|************************** |
|************************** |
|************************** |
|************************** |
| **************************|
| **************************|
| **************************|
| **************************|
pi 3.141592653589793 estimated 3.141588725343425 diff -3.928246368190003e-06
This pattern tends to be the case for several Linux distributions, where four or so threads are run, they all complete, and the next four threads are run. I see a similar pattern on Mint(Ubuntu) on the Penryn 2-core machine.
Here is the code, annotated, from beginning to end, showing how pi is calculated and how the star-bars are calculated and printed.
# epi64timed.nim
# estimate pi with threads
# use uint64 wherever possible
# report relative thread timings graphically
import math, os, random, strutils, threadpool
import std/monotimes, times
{.experimental: "parallel".}
This code uses various standard modules from Nim. The monotimes module is for timing. It defines the MonoTime type used for Durations. This code uses the still-experimental parallel features of Nim
const realpi = 4.0*math.arctan(1.0)
const Nlim =<PHONE_NUMBER>0
const int32max = high(int32)
const int32bits = cast[uint64](int32max)
type
intresult = tuple
ctr: uint64
btime, etime: MonoTime
var mypi: float
var nthreads: int
Here we define the truth value of pi, a loop count for each thread, a couple of constants for our 2n x 2n box, where a box is 2 x int32max on a side.
To be clear, high(int32) is a 31-bit number so “int32max” is a 31-bit number too. We also declare a value for the estimate, and a tuple defining the result of a calculation. The tuple includes begin-time and end-time of each thread.
proc integpi(rand: Rand): intresult =
var r = rand
var randx, randy: uint64
var ctr: uint64 = 0
result.btime = getMonoTime()
for i in 0..<Nlim:
randx = r.next and int32bits
randy = r.next and int32bits
if ((randx*randx + randy*randy) < int32bits*int32bits): ctr = ctr + 1
result.etime = getMonoTime()
result.ctr = ctr
This is an implementation of the algorithm above, in uint64 with 31-bit ints randomly sprinkled around a box. The variables are not named well.
proc estimatepi(t: int): float =
var numers = newSeq[intresult](t+2) # 0 not used
var sumnumerator: float = 0.0
var rstate = initRand(23415332)
parallel:
for k in 1..t:
numers[k] = spawn integpi(rstate)
rstate.skipRandomNumbers() # skip 2^64 results
for k in 1..t:
sumnumerator = sumnumerator + float(numers[k].ctr)
This is the parallel code section calling the integpi routine once per thread. The interesting bits for non-Nim programmers are:
Here is the code for the star-bars:
block:
var mint, maxt: MonoTime
var linsp: string
var lspace, espace: int
var difft: float
mint=numers[1].btime
maxt=numers[1].etime
for k in 1..t:
mint=min(numers[k].btime,mint)
maxt=max(numers[k].etime,maxt)
difft=float((maxt-mint).inMilliseconds)
echo " Thread report:"
for k in 1..t:
linsp=" ".repeat(51)
lspace=toInt(50*float((numers[k].btime-mint).inMilliseconds)/difft)
espace=toInt(50*float((numers[k].etime-mint).inMilliseconds)/difft)
for i in lspace..espace: linsp[i] = '*'
echo "|",linsp,"|"
This is a block that prints out the text-based graphs showing relative thread begin/end times. There is no scale factor or actual numbers reported; the intent is to show relative start/stop times, not actual values.
I suspect this code can be simplified to eliminate loops, such as the mint and maxt calculation or placing ‘*’ characters.
Nim is an interesting language with useful features (careful type checking; spaces for grouping and defining implicit blocks; object-oriented features; generics; introspection of the compiler during compilation, etc etc).
$ nim c -d:deploy epi64timed.nim
$ ./epi64timed
May 2020
Asahi Super Dry
Links:
Nim Language site
Nim random module
OpenBSD Numerics Experience - 1 - RNG
OpenBSD Numerics Experience - 2 - RNG floats
OpenBSD Numerics Experience - 3 - FFTW
OpenBSD Numerics Experience - 4 - CAF
OpenBSD Numerics Experience - 5 - MPI Networking
OpenBSD Numerics Experience - 6 - Memory Models
OpenBSD Numerics Experience - 7 - Python Image Display
OpenBSD Numerics Experience - 8 - RNGs, again
OpenBSD Numerics Experience - 9 - Nim
OpenBSD Numerics Experience - A - Graphical Display
OpenBSD Numerics Experience - B - ParaView
OpenBSD Numerics Experience - C - Numerical Debugging
OpenBSD Numerics


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Aruth is a tool for Sinhala word sense disambiguation. This is a research project carried out by the Department of Computer Science and Engineering , University of Moratuwa, Sri Lanka. Re-deployed in March 2020.


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Before:
seq.find(p).isDefined seq.find(p) != None seq.find(p).isEmpty
seq.exists(p) seq.exists(p) !seq.exists(p)


practis is a middleware that controls exhaustive executions on a cluster. This web page enables users to check the current states of practis execution.
The source code and samples are available on Github. If you want to get a full source code, please get it from Github.


{% extends "layout.html" %} {% block content %}
Please upload STOCKHOLM alignment file. You can generate one using Clustal Omega service.


ShotSpotter Alerts by Census Tract
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Define the top directory of an automatic project. To start work with the project, just run an Ant build.


{% extends "_post.html" %}
{% load webdesign %}
{% hyde
title: Announcing Cast Preview Release
created: 2011-04-25
%}
{% block article %}
{% article %}
{% excerpt %}
Today we are happy to announce the first preview release of Cast.
{% endexcerpt %}
One of the more popular categories of cloud services recently has been the
"Platform as a Service". Services such as Heroku or Google App Engine have a
lot of benefits - deployment, administration and scaling are a snap. The
problem is that such services have all of the well-established drawbacks of
closed systems: in short, the service users depend on the service providers.
Users never have full control, but when things go wrong migration away from
such systems is non-trivial.
We set out to correct this by creating an open service deployment and
management "Platform" that anyone can run, wherever they like. In this first
preview release Cast allows you to:
1. Upload application tarballs
2. Create instances of uploaded applications
3. Upgrade instances to newer versions of their application
4. Manage (start, stop, restart, etc) services provided by instances
All of this is performed over a [REST API](/docs/rest-api/) - so while we make
a command line [client](/docs/client/) available, users are free (and
encouraged!) to integrate Cast into their systems in any way they see fit.
A key to making this an open and community driven project is using an open
development process. Cast is distributed under the Apache License, Version 2.0,
and all development takes place on [Github](https://github.com/cloudkick/cast).
If this sounds like your sort of thing, we'd love to have you involved!
* [Try Cast](/downloads)
* [Report a bug](https://github.com/cloudkick/cast/issues)
* [Share your thoughts](https://groups.google.com/group/cast-dev)
* Join the discussion in
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{% endarticle %}
{% endblock %}


Collections
PyCon China 2011 was successfully ended at Dec 4 (Local Time)
Conference photos PyCon China 2011 's Album
Conference speech playback The PyCon China 2011 Playback
Keynote download Offical website "Schedule" page
News report Offical website "About" page
Opensource project during inferred in conference speech:
- The open PyCon China 2011 offical website project - Lightning Talk: "Develop of PyCon China offical website"
- Python version of Xunlei script - Lightning Talk:" Improve Thunder offline by Python - A Python Successful Story "
- XBMC plugin of Xunlei - Lightning Talk:" Improve Thunder offline by Python - A Python Successful Story "


The problem has been solved when you are at the mall entrance.
Of course you know how to cross a parking lot. You would probably describe the process as "...keep walking until you reach the entrance."
Let us describe the solution in more detail:
I've described the solution in a recursive style. There are two parts to recursion:
The over-all strategy is to find some easily applied action that breaks the problem into smaller pieces. Some of the pieces can be dealt with immediately; others need to be further broken up.


${properties.numb} ${properties.time}
${properties.email} ${properties.website}
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Experience
Data Scientist
DueDil Jan 2017 - present
- Core responsibilities include scoping out, building and testing data pipelines and data products. Have worked both independently and in teams on a variety of core and experimental projects.
- Onboard and maintain datasets from third-party providers (numbering up to ~2M records per batch), from point of raw data collection to exposure to the site. Use in-house data pipeline framework (Python, Spark, Hadoop, Postgres, Jenkins) to automate daily or weekly batch running of ETL jobs and continuous integration of data. Build automatic data validation frameworks to control for data quality.
- Used machine learning model (word2vec) to expand existing keywords by finding nearest neighbouring keywords in vector space. Resulted in addition of keywords for 22mn companies in 10 countries to the site.
- Scope out MVPs for exploratory projects/new features using open-source packages/ ipynb/ etc.
Scientific software intern
Enthought Sept 2016 - Jan 2017
- Built a plugin for Enthought's Canopy Geoscience application (a research platform for analysing geological data) that adds additionaly functionality to how a user can analyse data
- Wrote and deployed Python code to production using Enthought's open source packages (Traits, Envisage)
- Presented work at internal seminars
- 14-week fellowship; worked in a team of four to build an early intervention system for the Metro Nashville Police Department that predicts police officers at high risk of adverse incidents. Our work has featured in the Economist, New Scientist, and the Chicago Tribune
- Designed and built a database system that can accommodate data from diverse sources and multiple police departments; this formed the starting point for a machine learning pipeline in Python and Luigi
- Using machine learning, we were able to correctly predict 80% of officers who would go on to have an adverse incident, while flagging only a third of officers in the department. Our system flagged fewer than half the number of officers needed for this level of accuracy under current systems
- 12-week educational retreat for programmers; improved core programming and CS knowledge by writing open-source software, pair programming, and attending workshops
Data science fellow
S2DS Aug - Sept 2015
- 5-week bootcamp for STEM PhD holders moving into the data science industry; worked in a team of three to perform proof-of-concept machine learning analyses for
the financial technology company Intelliflo
-
Performed data analyses on dataset of >9 million records in Python, Pandas and scikit-learn; delivered a set of recommendations for data storage and usage, as well as Python scripts for automated data cleaning
Graduate researcher
University of Cambridge 2011 - 2015
- Studied plant gene evolution; used bioinformatic, molecular and microscopy techniques to understand changes in gene function over time
-
Used statistical methods to build evolutionary trees to infer the ancestral traits of a group of flowering plants. Presented work frequently at international conferences and internal seminars
Data analyst and researcher
RBG Kew 2009 - 2010
- Estimated plants' endangerment by approximating their geographic ranges using statistical analysis of plant sighting data
-
Created recommendations for how to use these types of data to make conservation assessments; this work resulted in two publications
Volunteering
Workshop organiser
Cambridge codebar.io 2014 - 2015
- Organised a monthly workshop for women and LGBTQ individuals to learn
programming, with the aim of increasing their representation in the tech industry
-
During my involvement we grew by 60 new students and coaches
(from ~50 to 110)
Selected open source projects
-
A biological name-matching game using data from an open Encyclopedia of Life;
collaborated extensively with a colleague using git branching and merging workflow
-
Received 1200 unique visitors in its first week
-
Python, Flask, HTML/CSS, Heroku, Redis, git
iPython notebooks
-
I frequently use iPython notebooks for data cleaning and analysis. Below are a selection of projects I have worked on:


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Coded by
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EMOathDevice Protocol Reference
| Conforms to | NSObject |
|---|---|
| Declared in | EMOathDevice.h |
– hotpWithAuthInput:error:
required method
Gets an event based OTP (HOTP).
- (id<EMSecureString>)hotpWithAuthInput:(id<EMAuthInput>)authInput error:(NSError **)error
Parameters
authInput |
The authInput. |
|---|---|
error |
If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, you may pass in |
Return Value
The OTP.
Availability
3.2
Discussion
Warning: Depending of the EMAuthInput type you are using, you may have to use this function asynchronously, please @see EMAuthInput for more details
Exceptions
NSInternalInconsistencyException |
When the associated token has the |
|---|
Declared In
EMOathDevice.h
– totpWithAuthInput:error:
required method
Gets a time based OTP (TOTP).
- (id<EMSecureString>)totpWithAuthInput:(id<EMAuthInput>)authInput error:(NSError **)error
Parameters
authInput |
The authInput. |
|---|---|
error |
If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, you may pass in |
Return Value
The OTP.
Availability
3.2
Discussion
Warning: Depending of the EMAuthInput type you are using, you may have to use this function asynchronously, please @see EMAuthInput for more details
Declared In
EMOathDevice.h
– ocraOtpWithAuthInput:serverChallengeQuestion:clientChallengeQuestion:passwordHash:session:error:
required method
Gets an OCRA OTP.
- (id<EMSecureString>)ocraOtpWithAuthInput:(id<EMAuthInput>)authInput serverChallengeQuestion:(id<EMSecureByteArray>)serverChallengeQuestion clientChallengeQuestion:(id<EMSecureByteArray>)clientChallengeQuestion passwordHash:(id<EMSecureByteArray>)passwordHash session:(id<EMSecureByteArray>)session error:(NSError **)error
Parameters
authInput |
The authInput. |
|---|---|
serverChallengeQuestion |
The server question. mandatory field, cannot be |
clientChallengeQuestion |
The client question, |
passwordHash |
The hash value of password, |
session |
The session data, |
error |
If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, you may pass in |
Return Value
The OTP.
Availability
3.2
Discussion
Warning: Depending of the EMAuthInput type you are using, you may have to use this function asynchronously, please @see EMAuthInput for more details
Exceptions
NSInvalidArgumentException |
When the serverChallengeQuestion or the
|
|---|---|
NSInvalidArgumentException |
When the passwordHash is |
NSInvalidArgumentException |
When the session is not |
NSInvalidArgumentException |
When the session’s byte length is longer than the value returned by [EMSoftOathSettings ocraSessionLength]. |
NSInvalidArgumentException |
When the session cannot be decoded using UTF-8. |
NSInvalidArgumentException |
When the token’s key length is not compatible with the OCRA hash algorithm (see [EMSoftOathSettings ocraHashAlgorithm]). |
NSInternalInconsistencyException |
When the associated token has the
|
Declared In
EMOathDevice.h
– ocraPasswordHash:error:
required method
Gets password hash value according the algorithm defined by device settings.
- (id<EMSecureString>)ocraPasswordHash:(id<EMSecureString>)password error:(NSError **)error
Parameters
password |
The password, can be |
|---|---|
error |
If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, you may pass in |
Return Value
passwordHash
- The hash value of the password.
- 'nil' if password is 'nil' or hash algorithm for OCRA password is set to 'EMOcraPasswordNone' by the device settings
Declared In
EMOathDevice.h
– lastOtpLifespan
required method
Returns lifespan of the last OTP computed by this device.
- (NSInteger)lastOtpLifespan
Return Value
lifespan
- In case last OTP computed with this device is time-based
- If positive, the last OTP is still valid according current time and device's timestep settings. The returned value indicates the remaining seconds before the OTP becomes obsolete.
- If negative, the last OTP computed is obsolete. The absolute value indicates the time elapsed since the OTP has become obsolete.
- In case last OTP computed with this device is event-based, or no OTP has been computed yet, the function returns 'NSIntegerMax'
Availability
2.3
Discussion
The following example illustrates the usage.
// Create OATH settings
id
// Set up OATH time-based settings (for example a 30 seconds timestep) [oathSettings setTotpTimestepSize:30];
// Create a OATH device
id
// Compute a time-based OTP with device (with pin EMSecureString) [device getTotpWithPin:pin];
// Each time selector [… lastOtpLifespan] is called, it returns the // remaining lifespan in seconds of the last time-based OTP. Lifespan is // computed with respect of device’s settings (in this example it returns // the lifespan according the 30-seconds timestep). NSInteger lifespan = [device lastOtpLifespan];
Declared In
EMOathDevice.h