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| 1 | 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 |
| 2 | 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 |
| 3 | Ability to detect and locate gross errors on DEM matching algorithm显示文摘Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.However,all existing methods only emphasise their deformation detecting ability,and neglect another important aspect:only when the gross error can be detected and located,can this system be useful.This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem.The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors.Therefore,treating the terrain changes as gross errors is theoretically feasible,allowing real DEM deformations to be detected by employing a surface matching technique. | T.Zhang M.Cen Z.Ren R.Yang Y.Feng J.Zhu | 2010 | International Journal of Digital Earth2010，3，1： | 2 |
| 4 | Impact of tertiary Gleason pattern 5 on prostate cancer aggressiveness:Lessons from a contemporary single institution radical prostatectomy series显示文摘Objective:To better evaluate tertiary Gleason pattern reporting and to evaluate the impact of tertiary Gleason pattern 5(TP5)on prostate cancer pathological features and biochemical recurrence at our large single institution.Methods:We retrospectively reviewed 1962 patients who underwent radical prostatectomy(RP)for prostate cancer;TP5 was reported in 159 cases(8.1%).Men with Gleason score(GS)7 and GS 8 disease were divided into subgroups with and without TP5,and histopathological features were compared.Multivariate analyses were conducted to assess the impact on TP5 on biochemical-free survival(BFS).Results:Tumors possessing GS 3+4 with TP5 were more likely to exhibit extraprostatic extension(EPE)and had a larger tumor diameter(TD)than GS 3+4 alone.GS 3+4 with TP5 was also associated with positive surgical margins(SM),seminal vesicle involvement(SVI),and higher pre-operative prostate-specific antigen(PSA)values,but without statistical significance.GS 4+3 with TP5 more commonly presented with EPE,positive SM,SVI,and greater TD and pre-operative PSA level than GS 4+3 alone.In multivariate analysis,Gleason score,EPE,and TP5 were overall independent risk factors for PSA recurrence in this cohort.Additionally,GS 4+3 with TP5 was associated with shorter time to recurrence versus GS 4+3 alone.Conclusion:Our results emphasize the importance of TP5 and suggest that criteria for tertiary pattern reporting in prostate cancer should be standardized.Further studies are needed to evaluate the role of tertiary patterns in prognostic models. | Zachary B.Koloff Daniel A.Hamstra John T.Wei Jeffrey S.Montgomery Scott A.Tomlins Angela J.Wu Todd M.Morgan Javed Siddiqui Kellie Paich Arul M.Chinnaiyan Felix Y.Feng Alon Z.Weizer Lakshmi P.Kunju Brent K.Hollenbeck David C.Miller Ganesh S.Palapattu Rohit Mehra | 2015 | Asian Journal of Urology2015，2，1： | 1 |
| 5 | Excitonic artificial atoms: Engineering optical properties of quantum dots显示文摘 | P.Hawrylak C.Gould A.Sachrajda Y.Feng and Z.Wasilewski | | 0，，04： | 1 |
| 6 | 查看详情显示文摘 | M.Ciorga A.S.Sachrajda P.Hawrylak C.Gould P.Za-wadzki S.Jullian Y.Feng and Z.Wasilewski | | 0，，24： | 1 |
| 7 | Development of a headspace solid-phase microextraction method combined with gas chromatography mass spectrometry for the determination of phthalate esters in cow milk显示文摘 | Y.Feng J.Zhu R.Sensenstein | | 0，，： | 1 |
| 8 | 查看详情显示文摘 | S.Fafard K.Hinzer S.Raymond M.Dion J.McCaffrey Y.Feng and S.Charbonneau | | 0，，5291： | 1 |
| 9 | Lasing in quantum-dot ensembles with sharp adjustable electronic shells显示文摘 | S.Fafaxd Z.R.Wasilewski C.Ni Allen K.Hinzer J.P.McCaffrey and Y.Feng | | 0，，07： | 1 |
| 10 | FAST Observations of an Extremely Active Episode of FRB 20201124A:Ⅰ.Burst Morphology显示文摘We report the properties of more than 600 bursts(including cluster-bursts)detected from the repeating fast radio burst(FRB)source FRB 20201124A with the Five-hundred-meter Aperture Spherical radio Telescope during an extremely active episode on UTC 2021 September 25–28,in a series of four papers.The observations were carried out in the band of 1.0–1.5 GHz by using the center beam of the L-band 19-beam receiver.We monitored the source in sixteen1 hr sessions and one 3 hr session spanning 23 days.All the bursts were detected during the first four days.In this first paper of the series,we perform a detailed morphological study of 624 bursts using the two-dimensional frequencytime“waterfall”plots,with a burst(or cluster-burst)defined as an emission episode during which the adjacent emission peaks have a separation shorter than 400 ms.The duration of a burst is therefore always longer than 1 ms,with the longest up to more than 120 ms.The emission spectra of the sub-bursts are typically narrow within the observing band with a characteristic width of~277 MHz.The center frequency distribution has a dominant peak at about 1091.9 MHz and a secondary weak peak around 1327.9 MHz.Most bursts show a frequencydownwarddrifting pattern.Based on the drifting patterns,we classify the bursts into five main categories:downward drifting(263)bursts,upward drifting(3)bursts,complex(203),no drifting(35)bursts,and no evidence for drifting(121)bursts.Subtypes are introduced based on the emission frequency range in the band(low,middle,high and wide)as well as the number of components in one burst(1,2,or multiple).We measured a varying scintillation bandwidth from about 0.5 MHz at 1.0 GHz to 1.4 MHz at 1.5 GHz with a spectral index of 3.0. | D.J.Zhou J.L.Han B.Zhang K.J.Lee W.W.Zhu D.Li W.C.Jing W.-Y.Wang Y.K.Zhang J.C.Jiang J.R Niu R Luo H.Xu C.F.Zhang B.J.Wang J.W.Xu P.Wang Z.L.Yang Y.Feng | 2022 | Research in Astronomy and Astrophysics2022，22，12： | 0 |
| 11 | A new scale for optimized cryogenic magnetocaloric effect in ErAl_2@Al_2O_3 nanocapsules显示文摘The Er Al_2@Al_2O_3nanocapsules with Er Al_2core and Al_2O_3shell were synthesized by modified arc-charge technique.The typical core-shell structure of the nanocapsules was confirmed by high resolution transmission electron microscopy and X-ray photoelectron spectroscopy.Transmission electron microscopy analysis shows the irregular sphere of the nanocapules with an average diameter of 26 nm.Magnetic investigation revealed the Curie temperature of Er Al_2@Al_2O_3nanocapsules at 20 K and the typical superparamagnetic behavior between blocking temperature and Curie temperature.Based on the blocking temperature and average diameter,the magnetocrystalline anisotropy constant of Er Al_2@Al_2O_3nanocapsules was estimated to illustrate the magnetic contribution to the-S_M.The large-S_Mof 14.25 J/(kg K)was obtained under 50 k Oe at 5 K.A vital parameterˇwas introduced in the present work to scale the optimized magnetic characteristics and the optimized mechanism was discussed in detail according to classical superparamagnetic theory.The results demonstrate that the optimal-S_Mwill be obtained when the magnetic parameterˇis close to the theoretical coefficient. | F.Wei S.Ma L.Yang Y.Feng J.Z.Wang A.Hua X.G.Zhao D.Y.Geng Z.D.Zhang | 2018 | Journal of Materials Science & Technology2018，34，5： | 0 |
| 12 | INFLUENCE OF SURFACE-ACTIVE ELEMENTS ON FLUID FLOW OF MIG WELDPOOL显示文摘A mathematical model describing the behavior of metal inert gas(MIG)welding is formulated in the paper.By means of numerical simulation,the influence of surfaceactive elements on fluid flow of MIG weldpool is studied.The calculation results show that by adding surface-active elements,the fluid flow behavior is drastically changed and the flow fluid flows from lower to upper in vertical direction at the rear of weldpool(w>0).The physical phenomenon is explained from the viewpoint of fluid flow behavior of weldpool that the properties of weld metal is greatly improved and the content of diffused hydrogen is reduced,thus providing a basis for developing new welding materials. | J.S.Sun J.Q.Gao Y.Feng Y.W.Luan | 2004 | Acta Metallurgica Sinica(English Letters)2004，17，2： | 0 |
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