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| 1 | Measurements of dihadron correlations relative to the event plane in Au+Au collisions at√^(S)NN=200 GeV显示文摘Dihadron azimuthal correlations containing a high transverse momentum(pr)trigger particle are sensit-ive to the properties of the nuclear medium created at RHIC through the strong interactions occurring between the traversing parton and the medium,ie.jet-quenching.Previous measurements revealed a strong modification to di-hadron azimuthal correlations in Au+Au collisions with respect to ptp and d+Au collisions.The modification in-creases with the collision centrality,suggesting a path-length or energy density dependence to the je-quenching ef-fect.This paper reports STAR measurements of dihadron azimuthal correlations in mid-central(20%-60%)Au+Au collisions at√^(S)NN=200 GeV as a function of the trigger particle's azimuthal angle relative to the event plane,Ф_(s)=|Ф_(t)-ψ_(Ep)|.The azimuthal correlation is studied as a function of both the trigger and associated particle pr.The subtractions of the combinatorial background and anisotropic flow,assuming Zero Yield At Minimum(ZYAM),are described.The correlation results are first discussed with subtraction of the even harmonic(elliptic and quadrangu-lar)flow backgrounds.The away-side correlation is strongly modifed,and the modification varies withФ_(s),with a double-peak structure for out-of-plane trigger particles.The near-side ridge(long range pseudo-rapidity△_(η)correla-tion)appears to drop with increasingФ_(s)while the jet-like component remains approximately constant.The correla-tion functions are further studied with the subtraction of odd harmonic triangular flow background arising from fluc-tuations.It is found that the triangular flow,while responsible for the majority of the amplitudes,is not sufficient to explain theφs-dependence of the ridge or the away-side double-peak structure.The dropping ridge withФ_(s)could be attributed to aФ_(s)-dependent lliptie anisotropy;however,the physics mechanism of the ridge remains an open ques-tion.Even with aФ_(s)-dependent elliptic flow,the away-side correlation structure is robust.These results,with extens-ive systematic studies of the dihadron correlations as a function ofФ_(s),trigger and associated particle pT,and the pseudo-rapidity range△_(η),should provide stringent inputs to help understand the underlying physics mechanisms of jet-medium interactions in high energy nuclear collisions. | H.Agakishiev M.M.Aggarwal Z.Ahammed A.V.Alakhverdyants I.Alekseev J.Alford B.D.Anderson C.D.Anson D.Arkhipkin G.S.Averichev J.Balewski D.R.Beavis N.K.Behera R.Bellwied M.J.Betancourt R.R.Betts A.Bhasin A.K.Bhat H.Bichsel J.Bieleik J.Bielcikova B.Biritz L.C.Bland W.Borowski J.Bouchet E.Braidot A.V.Brandin A.Bridgeman S.G.Brovko E.Bruna S.Bueltmann I.Bunzarov T.P.Burton X.Z.Cai H.Caines M.Calderon de la Barca Sanchez D.Cebra R.Cendejas M.C.Cervantes Z.Chajecki P.Chaloupka S.Chattopadhyay H.F.Chen J.H.Chen J.Y.Chen L.Chen J.Cheng M.Cherney A.Chikanian K.E.Choi W.Christie P.Chung M.J.M.Codrington R.Corliss J.G.Cramer H.J.Crawford S.Dash A.Davila Leyva L.C.De Silvat R.R.Debbe T.G.Dedovich A.A.Derevschikov R.Derradi de Souza L.Didenko P.Djawotho S.M.Dogra X.Dong J.L.Drachenberg J.E.Draper J.C.Dunlop L.G Efimov M.Elnim J.Engelage G Eppley M.Estienne L.Eun O.Evdokimov R.Fatemi J.Fedorisin A.Feng R.G.Fersch P.Filip E.Finch V.Fine Y.Fisyak C.A.Gagliardi D.R.Gangadharan A.Geromitsos F.Geurts P.Ghosh Y.N.Gorbunov A.Gordon O.Grebenyuk D.Grosnick S.M.Guertin A.Gupta W.Guryn B.Haag O.Hajkova A.Hamed L-X.Han J.W.Harris J.P.Hays-Wehle M.Heinz S.Heppelmann A.Hirsch E.Hjort G.W.Hoffmann D.J.Hofiman B.Huang H.Z.Huang T.J.Humanic L.Huo G.Igo P.Jacobs W.W.Jacobs C.Jena F.Jin J.Joseph E.G.Judd S.Kabana K.Kang J.Kapitan K.Kauder H.Ke D.Keane A.Kechechyan D.Kettler D.P.Kikola J.Kiryluk A.Kisiel V.Kizka A.G.Knospe D.D.Koetke T.Kollegger J.Konzer I.Koralt L.Koroleva W.Korsch L.Kotchenda V.Kouchpil P.Kravtsov K.Krueger M.Krus L.Kumar P.Kurnadi M.A.C.Lamont J.M.Landgraf S.LaPointe J.Lauret A.Lebedev R.Lednicky J.H.Lee W.Leight M.J.LeVine C.Lil L.Li N.Li W.Li X.Li X.Li Y.Li Z.M.Li M.A.Lisa F.Liu H.Liu J.Liu T.Ljubicic W.J.Llope R.S.Longacre W.A.Love Y.Lu E.V.Lukashov X.Luo G.L.Ma Y.G.Mai D.P.Mahapatra R.Majka O.I.Mall L.K.Mangotra R.Manweiler S.Margetis C.Markert H.Masui H.S.Matis Yu.A.Matulenko D.MeDonald T.S.McShane A.Meschanin R.Milner N.G.Minaev S.Mioduszewski A.Mischke M.K.Mitrovski B.Mohanty M.M.Mondal B.Morozov D.A.Morozov M.G.Munhoz M.Naglis B.K.Nandi T.K.Nayak P.K.Netrakanti L.V.Nogach S.B.Nurushev G.Odyniec A.Ogawa Oh Ohlson V.Okorokov E.W.Oldag D.Olsont M.Pachr B.S.Page S.K.Pal Y.Pandit Y.Panebratsev T.Pawlak H.Pei T.Peitzmann C.Perkins W.Peryt S.C.Phatak P.Pile M.Planinic M.A.Ploskon J.Pluta D.Plyku N.Poljak A.M.Poskanzer B.V.K.S.Potukuchi C.B.Powell D.Prindle N.K.Pruthi A.M.Poskanzer B.V.K.S.Potukuchi B.Powell D.Prindle N.K.Pruthi P.R.Pujahar J.Putschke H.Qiu R.Raniwala S.Raniwala R.L.Ray R.Redwine R.Reed H.G.Riter J.B.Roberts O.V.Rogachevskiy J.L.Romero A.Rose L.Ruan J.Rusnak N.R.Sahoo S.Sakai I.Sakrejda T.Sakuma S.Salur J.Sandweiss E.Sangaline A.Sarkar J.Schambach R.P.Scharenberg A.M.Schmah N.Schmitz T.R.Schuster J.Seele J.Seger I.Selyuzhenkov P.Seyboth E.Shahaliev M.Shao M.Sharma S.S.Shi Q.Y.Shou E.P.Sichtermann F.Simon R.N.Singaraju M.J.Skoby N.Smirnov H.M.Spinka B.Srivastava T.D.S.Stanislaus D.Staszak S.G.Steadman J.R.Stevens R.Stock M.Strikhanov B.Stringfellow A.A.P.Suaide M.C.Suarez N.L.Subba M.Sumbera X.M.Sun Y.Sun Z.Sun B.Surrow D.N.Svirida T.J.M.Symons A.Szanto de Toledo J.Takahashi A.H.Tang Z.Tang L.H.Tarini T.Tarnowsky D.Thein J.H.Thomas J.Tian A.R.Timmins D.Tlusty M.Tokarev V.N.Tram S.Trentalange R.E.Tribble Tribedy O.D.Tsai T.Ullrich D.G.Underwood G.Van Buren G.van Nieuwenhuizen J.A.Vanfossen R.Varma G.M.S.Vasconcelos A.N.Vasiliev F.Videbaek Y.P.Viyogi S.Vokal M.Wadat M.Walker F.Wang G.Wang H.Wang J.S.Wang Q.Wang X.L.Wang Y.Wang G.Webb J.C.Webb G.D.Westfall C.Whitten H.Wieman S.W.Wissink R.Witt W.Witzke Y.F.Wu Xiao W.Xie H.Xu N.Xu Q.H.Xu W.Xu Y.Xu Z.Xu L.Xue Y.Yang P.Yepes K.Yip I-K.Yoo M.Zawisza H.Zbroszczyk W.Zhan J.B.Zhang S.Zhang W.M.Zhang X.P.Zhang Y.Zhang Z.P.Zhang J.Zhao C.Zhong W.Zhou X.Zhu Y.H.Zhu R.Zoulkarneev Y.Zoulkarneeva | 2021 | Chinese Physics C2021，45，4： | 351 |
| 2 | Methods for a blind analysis of isobar data collected by the STAR collaboration显示文摘In 2018,the STAR collaboration collected data from^(96)_(44)Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zr at√^(S)NN=200 Ge V to search for the presence of the chiral magnetic effect in collisions of nuclei.The isobar collision species alternated frequently between 9644 Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zr.In order to conduct blind analyses of studies related to the chiral magnetic effect in these isobar data,STAR developed a three-step blind analysis procedure.Analysts are initially provided a'reference sample'of data,comprised of a mix of events from the two species,the order of which respects time-dependent changes in run conditions.After tuning analysis codes and performing time-dependent quality assurance on the reference sample,analysts are provided a species-blind sample suitable for calculating efficiencies and corrections for individual≈30-min data-taking runs.For this sample,species-specific information is disguised,but individual output files contain data from a single isobar species.Only run-by-run corrections and code alteration subsequent to these corrections are allowed at this stage.Following these modifications,the'frozen'code is passed over the fully un-blind data,completing the blind analysis.As a check of the feasibility of the blind analysis procedure,analysts completed a'mock data challenge,'analyzing data from Au+Au collisions at√^(S)NN=27 Ge V,collected in 2018.The Au+Au data were prepared in the same manner intended for the isobar blind data.The details of the blind analysis procedure and results from the mock data challenge are presented. | J.Adam L.Adamczyk J.R.Adams J.K.Adkins G.Agakishiev M.M.Aggarwal Z.Ahammed I.Alekseev D.M.Anderson A.Aparin E.C.Aschenauer M.U.Ashraf F.G.Atetalla A.Attri G.S.Averichev V.Bairathi K.Barish A.Behera R.Bellwied A.Bhasin J.Bielcik J.Bielcikova L.C.Bland I.G.Bordyuzhin J.D.Brandenburg A.V.Brandin J.Butterworth H.Caines M.Calderon de la Barca Sanchez D.Cebra I.Chakaberia P.Chaloupka B.K.Chan F-H.Chang Z.Chang N.Chankova-Bunzarova A.Chatterjee D.Chen J.Chen J.H.Chen X.Chen Z.Chen J.Cheng M.Cherney M.Chevalier S.Choudhury W.Christie X.Chu H.J.Crawford M.Csanad M.Daugherity T.G.Dedovich I.M.Deppner A.A.Derevschikov L.Didenko X.Dong J.L.Drachenberg J.C.Dunlop T.Edmonds N.Elsey J.Engelage G.Eppley S.Esumi O.Evdokimov A.Ewigleben O.Eyser R.Fatemi S.Fazio P.Federic J.Fedorisin C.J.Feng Y.Feng P.Filip E.Finch Y.Fisyak A.Francisco L.Fulek C.A.Gagliardi T.Galatyuk F.Geurts A.Gibson K.Gopal X.Gou D.Grosnick W.Guryn A.I.Hamad A.Hamed S.Harabasz J.W.Harris S.He W.He X.H.He Y.He S.Heppelmann S.Heppelmann N.Herrmann E.Hoffman L.Holub Y.Hong S.Horvat Y.Hu H.Z.Huang S.L.Huang T.Huang X.Huang T.J.Humanic P.Huo G.Igo D.Isenhower W.W.Jacobs C.Jena A.Jentsch Y.Ji J.Jia K.Jiang S.Jowzaee X.Ju E.G.Judd S.Kabana M.L.Kabir S.Kagamaster D.Kalinkin K.Kang D.Kapukchyan K.Kauder H.W.Ke D.Keane A.Kechechyan M.Kelsey Y.V.Khyzhniak D.P.Kikoła C.Kim B.Kimelman D.Kincses T.A.Kinghorn I.Kisel A.Kiselev M.Kocan L.Kochenda L.K.Kosarzewski L.Kramarik P.Kravtsov K.Krueger N.Kulathunga Mudiyanselage L.Kumar S.Kumar R.Kunnawalkam Elayavalli J.H.Kwasizur R.Lacey S.Lan J.M.Landgraf J.Lauret A.Lebedev R.Lednicky J.H.Lee Y.H.Leung C.Li C.Li W.Li W.Li X.Li Y.Li Y.Liang R.Licenik T.Lin Y.Lin M.A.Lisa F.Liu H.Liu P.Liu P.Liu T.Liu X.Liu Y.Liu Z.Liu T.Ljubicic W.J.Llope R.S.Longacre N.S.Lukow S.Luo X.Luo G.L.Ma L.Ma R.Ma Y.G.Ma N.Magdy R.Majka D.Mallick S.Margetis C.Markert H.S.Matis J.A.Mazer N.G.Minaev S.Mioduszewski B.Mohanty I.Mooney Z.Moravcova D.A.Morozov M.Nagy J.D.Nam Md.Nasim K.Nayak D.Neff J.M.Nelson D.B.Nemes M.Nie G.Nigmatkulov T.Niida L.V.Nogach T.Nonaka A.S.Nunes G.Odyniec A.Ogawa S.Oh V.A.Okorokov B.S.Page R.Pak A.Pandav Y.Panebratsev B.Pawlik D.Pawlowska H.Pei C.Perkins L.Pinsky R.L.Pinter J.Pluta J.Porter M.Posik N.K.Pruthi M.Przybycien J.Putschke H.Qiu A.Quintero S.K.Radhakrishnan S.Ramachandran R.L.Ray R.Reed H.G.Ritter O.V.Rogachevskiy J.L.Romero L.Ruan J.Rusnak N.R.Sahoo H.Sako S.Salur J.Sandweiss S.Sato W.B.Schmidke N.Schmitz B.R.Schweid F.Seck J.Seger M.Sergeeva R.Seto P.Seyboth N.Shah E.Shahaliev P.V.Shanmuganathan M.Shao A.I.Sheikh W.Q.Shen S.S.Shi Y.Shi Q.Y.Shou E.P.Sichtermann R.Sikora M.Simko J.Singh S.Singha N.Smirnov W.Solyst P.Sorensen H.M.Spinka B.Srivastava T.D.S.Stanislaus M.Stefaniak D.J.Stewart M.Strikhanov B.Stringfellow A.A.P.Suaide M.Sumbera B.Summa X.M.Sun X.Sun Y.Sun Y.Sun B.Surrow D.N.Svirida P.Szymanski A.H.Tang Z.Tang A.Taranenko T.Tarnowsky J.H.Thomas A.R.Timmins D.Tlusty M.Tokarev C.A.Tomkiel S.Trentalange R.E.Tribble P.Tribedy S.K.Tripathy O.D.Tsai Z.Tu T.Ullrich D.G.Underwood I.Upsal G.Van Buren J.Vanek A.N.Vasiliev I.Vassiliev F.Videbæk S.Vokal S.A.Voloshin F.Wang G.Wang J.S.Wang P.Wang Y.Wang Y.Wang Z.Wang J.C.Webb P.C.Weidenkaff L.Wen G.D.Westfall H.Wieman S.W.Wissink R.Witt Y.Wu Z.G.Xiao G.Xie W.Xie H.Xu N.Xu Q.H.Xu Y.F.Xu Y.Xu Z.Xu Z.Xu C.Yang Q.Yang S.Yang Y.Yang Z.Yang Z.Ye Z.Ye L.Yi K.Yip Y.Yu H.Zbroszczyk W.Zha C.Zhang D.Zhang S.Zhang S.Zhang X.P.Zhang Y.Zhang Y.Zhang Z.J.Zhang Z.Zhang Z.Zhang J.Zhao C.Zhong C.Zhou X.Zhu Z.Zhu M.Zurek M.Zyzak STAR Collaboration Abilene | 2021 | Nuclear Science and Techniques2021，32，5： | 3 |
| 3 | Measurement of away-side broadening with self-subtraction of flow in Au+Au collisions at √sNN=200 GeV显示文摘High transverse momentum(pT)particle production is suppressed owing to the parton(jet)energy loss in the hot dense medium created in relativistic heavy-ion collisions.Redistribution of energy at low-to-modest pT has been difficult to measure,owing to large anisotropic backgrounds.We report a data-driven method for background evaluation and subtraction,exploiting the away-side pseudorapidity gaps,to measure the jetlike correlation shape in Au+Au collisions at √sNN=200 GeV in the STAR experiment.The correlation shapes,for trigger particles pT>3GeV/c and various associated particle pT ranges within 0.5 | L.Adamczyk J.R.Adams J.K.Adkins G.Agakishiev M.M.Aggarwal Z.Ahammed I.Alekseev D.M.Anderson A.Aparin E.C.Aschenauer M.U.Ashraf F.G.Atetalla A.Attri G.S.Averichev V.Bairathi K.Barish A.Behera R.Bellwied A.Bhasin J.Bielcik J.Bielcikova L.C.Bland I.G.Bordyuzhin J.D.Brandenburg A.V.Brandin J.Butterworth H.Caines M.Calderón de la Barca Sánchez D.Cebra I.Chakaberia P.Chaloupka B.K.Chan F-H.Chang Z.Chang N.Chankova-Bunzarova A.Chatterjee D.Chen J.H.Chen X.Chen Z.Chen J.Cheng M.Cherney M.Chevalier S.Choudhury W.Christie X.Chu H.J.Crawford M.Csanád M.Daugherity T.G.Dedovich I.M.Deppner A.A.Derevschikov L.Didenko X.Dong J.L.Drachenberg J.C.Dunlop T.Edmonds N.Elsey J.Engelage G.Eppley S.Esumi O.Evdokimov A.Ewigleben O.Eyser R.Fatemi S.Fazio P.Federic J.Fedorisin C.J.Feng Y.Feng P.Filip E.Finch Y.Fisyak A.Francisco L.Fulek C.A.Gagliardi T.Galatyuk F.Geurts A.Gibson K.Gopal D.Grosnick W.Guryn A.I.Hamad A.Hamed S.Harabasz J.W.Harris S.He W.He X.H.He S.Heppelmann S.Heppelmann N.Herrmann E.Hoffman L.Holub Y.Hong S.Horvat Y.Hu H.Z.Huang S.L.Huang T.Huang X.Huang T.J.Humanic P.Huo G.Igo D.Isenhower W.W.Jacobs C.Jena A.Jentsch Y.JI J.Jia K.Jiang S.Jowzaee X.Ju E.G.Judd S.Kabana M.L.Kabir S.Kagamaster D.Kalinkin K.Kang D.Kapukchyan K.Kauder H.W.Ke D.Keane A.Kechechyan M.Kelsey Y.V.Khyzhniak D.P.Kikoła C.Kim B.Kimelman D.Kincses T.A.Kinghorn I.Kisel A.Kiselev M.Kocan L.Kochenda L.K.Kosarzewski L.Kramarik P.Kravtsov K.Krueger N.Kulathunga Mudiyanselage L.Kumar S.Kumar R.Kunnawalkam Elayavalli J.H.Kwasizur R.Lacey S.Lan J.M.Landgraf J.Lauret A.Lebedev R.Lednicky J.H.Lee Y.H.Leung C.Li W.Li W.Li X.Li Y.Li Y.Liang R.Licenik T.Lin Y.Lin M.A.Lisa F.Liu H.Liu P.Liu P.Liu T.Liu X.Liu Y.Liu Z.Liu T.Ljubicic W.J.Llope R.S.Longacre N.S.Lukow S.Luo X.Luo G.L.Ma L.Ma R.Ma Y.G.Ma N.Magdy R.Majka D.Mallick S.Margetis C.Markert H.S.Matis J.A.Mazer N.G.Minaev S.Mioduszewski B.Mohanty I.Mooney Z.Moravcova D.A.Morozov M.Nagy J.D.Nam Nasim Md K.Nayak D.Neff J.M.Nelson D.B.Nemes M.Nie G.Nigmatkulov T.Niida L.V.Nogach T.Nonaka A.S.Nunes G.Odyniec A.Ogawa S.Oh V.A.Okorokov B.S.Page R.Pak A.Pandav Y.Panebratsev B.Pawlik D.Pawlowska H.Pei C.Perkins L.Pinsky R.L.Pintér J.Pluta J.Porter M.Posik N.K.Pruthi M.Przybycien J.Putschke H.Qiu A.Quintero S.K.Radhakrishnan S.Ramachandran R.L.Ray R.Reed H.G.Ritter O.V.Rogachevskiy J.L.Romero L.Ruan J.Rusnak N.R.Sahoo H.Sako S.Salur J.Sandweiss S.Sato W.B.Schmidke N.Schmitz B.R.Schweid F.Seck J.Seger M.Sergeeva R.Seto P.Seyboth N.Shah E.Shahaliev P.V.Shanmuganathan M.Shao A.I.Sheikh F.Shen W.Q.Shen S.S.Shi Q.Y.Shou E.P.Sichtermann R.Sikora M.Simko J.Singh S.Singha N.Smirnov W.Solyst P.Sorensen H.M.Spinka B.Srivastava T.D.S.Stanislaus M.Stefaniak D.J.Stewart M.Strikhanov B.Stringfellow A.A.P.Suaide M.Sumbera B.Summa X.M.Sun X.Sun Y.Sun Y.Sun B.Surrow D.N.Svirida P.Szymanski A.H.Tang Z.Tang A.Taranenko T.Tarnowsky J.H.Thomas A.R.Timmins D.Tlusty M.Tokarev C.A.Tomkiel S.Trentalange R.E.Tribble P.Tribedy S.K.Tripathy O.D.Tsai Z.Tu T.Ullrich D.G.Underwood I.Upsal G.Van Buren J.Vanek A.N.Vasiliev I.Vassiliev F.Videbæk S.Vokal S.A.Voloshin F.Wang G.Wang J.S.Wang P.Wang Y.Wang Y.Wang Z.Wang J.C.Webb P.C.Weidenkaff L.Wen G.D.Westfall H.Wieman S.W.Wissink R.Witt Y.Wu Z.G.Xiao G.Xie W.Xie H.Xu N.Xu Q.H.Xu Y.F.Xu Y.Xu Z.Xu Z.Xu C.Yang Q.Yang S.Yang Y.Yang Z.Yang Z.Ye Z.Ye L.Yi K.Yip H.Zbroszczyk W.Zha C.Zhang D.Zhang S.Zhang S.Zhang X.P.Zhang Y.Zhang Y.Zhang Z.J.Zhang Z.Zhang Z.Zhang J.Zhao C.Zhong C.Zhou X.Zhu Z.Zhu M.Zurek M.Zyzak | 2020 | Chinese Physics C2020，44，10： | 2 |
| 4 | Assessment of cognitive function in patients with myasthenia gravis显示文摘Aim:During the past decade,there has been an increasing interest in the evaluation of cognitive function in myasthenia gravis(MG),neuromuscular transmission disorder caused by acetylcholine receptor auto-antibodies.However,the results of previous studies on cognition and MG are inconsistent and controversial.This study aimed to evaluate cognition in patients with mild/moderate grades of MG.Methods:This study included 20 patients with MG with a mean age of 28.45±8.89 years and duration of illness of 3.52±1.15 years.Cognition was tested using a sensitive battery of psychometric testing(Mini-mental State Examination[MMSE],Stanford-Binet Intelligence Scale 4^(th) edition[SBIS]and Wechsler Memory Scale-Revised[WMS-R])and by recording P300 component of event-related potentials(ERPs),a neurophysiological analog for cognitive function.Results:Compared with healthy subjects(n=20),patients had lower total scores of cognitive testing(MMSE,SBIS and WMS-R)(P=0.001),higher Beck Depression Inventory 2^(nd) edition scores(P=0.0001)and prolonged latencies(P=0.01)and reduced amplitudes(P=0.001)of P300 component of ERPs.Correlations were identified between total scores of cognitive testing and age(r=-0.470,P=0.010),duration of illness(r=-0.788,P=0.001)and depression scores(r=-0.323,P=0.045).Using linear regression analysis and after controlling for age and depression scores,a significant correlation was identified between total scores of cognitive testing and duration of illness(β=-0.305,P=0.045).Conclusion:Patients with mild/moderate MG may have cognitive dysfunction.This is important to determine prognosis and managing patients. | Sherifa A.Hamed Ahmad H.Youssef Mohamad A.Abd ElHameed Mohamed F.Mohamed Amal M.Elattar | 2014 | Neuroimmunology and Neuroinflammation2014，1，1： | 1 |
| 5 | 轴流透平中煤灰粒径分布对粒子动态特性和叶片磨蚀的影响显示文摘本文提出了轴流式燃气透平中煤灰粒径分布对粒子动态特性和叶片磨蚀方面影响的研究结果。在透平叶片流道内应用三元流分析法求解粒子动态特性及其对叶片的冲击。用由实验测量导出的经验公式来描述粒子的回弹情况和叶片材料的磨蚀特性。对典型的煤灰粒径分布所做的研究结果表明,煤灰粒径分布对叶片磨蚀的程度和图样有着显著的影响。 | W.Tabakoff A.Hamed M.Metwally 钱正元 | 1993 | 燃气轮机技术1993，6，1： | 0 |
| 6 | Reactivity of 6-anisyl-5-cyano-4-oxo-2-thioxo-1,2,3,4-tetrahydro-pyrimidine towards some electrophiles and nucleophiles显示文摘The title compound was subjected to react with some electrophiles and nucleophiles,such as alkyl halides,ethyl chloroacetate or amines,hydrazines etc.The resulting compounds were usedin further syntheses for the purpose of obtaining some new types of heterocycles with possible bio-logical and pharmaceutical activities. | HASSAN M.F.Madkour MAHAMED A.E.Sayed ASHRAF A.Hamed ADEL M.Gaber ABD EL-KHALIK A.Hataba | 1991 | Chinese Journal of Chemistry1991，9，3： | 0 |
| 7 | Deep Learning Methods Used in Remote Sensing Images: A Review显示文摘Undeniably,Deep Learning(DL)has rapidly eroded traditional machine learning in Remote Sensing(RS)and geoscience domains with applications such as scene understanding,material identification,extreme weather detection,oil spill identification,among many others.Traditional machine learning algorithms are given less and less attention in the era of big data.Recently,a substantial amount of work aimed at developing image classification approaches based on the DL model’s success in computer vision.The number of relevant articles has nearly doubled every year since 2015.Advances in remote sensing technology,as well as the rapidly expanding volume of publicly available satellite imagery on a worldwide scale,have opened up the possibilities for a wide range of modern applications.However,there are some challenges related to the availability of annotated data,the complex nature of data,and model parameterization,which strongly impact performance.In this article,a comprehensive review of the literature encompassing a broad spectrum of pioneer work in remote sensing image classification is presented including network architectures(vintage Convolutional Neural Network,CNN;Fully Convolutional Networks,FCN;encoder-decoder,recurrent networks;attention models,and generative adversarial models).The characteristics,capabilities,and limitations of current DL models were examined,and potential research directions were discussed. | Ekram M.Rewhel Jianqiang Li Amal A.Hamed Hatem M.Keshk Amira S.Mahmoud Sayed A.Sayed Ehab Samir Hind H.Zeyada Sayed A.Mohamed Marwa S.Moustafa Ayman H.Nasr Ashraf K.Helmy | 2023 | Journal of Environmental & Earth Sciences2023，5，1： | 0 |
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