Responsible Innovation in Business

This chapter introduces responsible innovation in a business context. The first part explains the basic terms that constitute responsible innovation from a busi-ness perspective. The second part presents tangible business practices that opera-tionalise responsible innovation and introduces two good practice examples that hint at the variety of ways in which responsible innovation can be implemented in companies

Transcriptomic Coordination in the Human Metabolic Network Reveals Links between n-3 Fat Intake, Adipose Tissue Gene Expression and Metabolic Health

Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF2α. These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress

Radioactivity control strategy for the JUNO detector

602siopenJUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV. [Figure not available: see fulltext.]openAbusleme A.; Adam T.; Ahmad S.; Ahmed R.; Aiello S.; Akram M.; An F.; An Q.; Andronico G.; Anfimov N.; Antonelli V.; Antoshkina T.; Asavapibhop B.; de Andre J.P.A.M.; Auguste D.; Babic A.; Baldini W.; Barresi A.; Basilico D.; Baussan E.; Bellato M.; Bergnoli A.; Birkenfeld T.; Blin S.; Blum D.; Blyth S.; Bolshakova A.; Bongrand M.; Bordereau C.; Breton D.; Brigatti A.; Brugnera R.; Bruno R.; Budano A.; Buscemi M.; Busto J.; Butorov I.; Cabrera A.; Cai H.; Cai X.; Cai Y.; Cai Z.; Cammi A.; Campeny A.; Cao C.; Cao G.; Cao J.; Caruso R.; Cerna C.; Chang J.; Chang Y.; Chen P.; Chen P.-A.; Chen S.; Chen X.; Chen Y.-W.; Chen Y.; Chen Y.; Chen Z.; Cheng J.; Cheng Y.; Chetverikov A.; Chiesa D.; Chimenti P.; Chukanov A.; Claverie G.; Clementi C.; Clerbaux B.; Conforti Di Lorenzo S.; Corti D.; Cremonesi O.; Dal Corso F.; Dalager O.; De La Taille C.; Deng J.; Deng Z.; Deng Z.; Depnering W.; Diaz M.; Ding X.; Ding Y.; Dirgantara B.; Dmitrievsky S.; Dohnal T.; Dolzhikov D.; Donchenko G.; Dong J.; Doroshkevich E.; Dracos M.; Druillole F.; Du S.; Dusini S.; Dvorak M.; Enqvist T.; Enzmann H.; Fabbri A.; Fajt L.; Fan D.; Fan L.; Fang J.; Fang W.; Fargetta M.; Fedoseev D.; Fekete V.; Feng L.-C.; Feng Q.; Ford R.; Formozov A.; Fournier A.; Gan H.; Gao F.; Garfagnini A.; Giammarchi M.; Giaz A.; Giudice N.; Gonchar M.; Gong G.; Gong H.; Gornushkin Y.; Gottel A.; Grassi M.; Grewing C.; Gromov V.; Gu M.; Gu X.; Gu Y.; Guan M.; Guardone N.; Gul M.; Guo C.; Guo J.; Guo W.; Guo X.; Guo Y.; Hackspacher P.; Hagner C.; Han R.; Han Y.; Hassan M.S.; He M.; He W.; Heinz T.; Hellmuth P.; Heng Y.; Herrera R.; Hor Y.K.; Hou S.; Hsiung Y.; Hu B.-Z.; Hu H.; Hu J.; Hu J.; Hu S.; Hu T.; Hu Z.; Huang C.; Huang G.; Huang H.; Huang W.; Huang X.; Huang X.; Huang Y.; Hui J.; Huo L.; Huo W.; Huss C.; Hussain S.; Ioannisian A.; Isocrate R.; Jelmini B.; Jen K.-L.; Jeria I.; Ji X.; Ji X.; Jia H.; Jia J.; Jian S.; Jiang D.; Jiang X.; Jin R.; Jing X.; Jollet C.; Joutsenvaara J.; Jungthawan S.; Kalousis L.; Kampmann P.; Kang L.; Karaparambil R.; Kazarian N.; Khan W.; Khosonthongkee K.; Korablev D.; Kouzakov K.; Krasnoperov A.; Kruth A.; Kutovskiy N.; Kuusiniemi P.; Lachenmaier T.; Landini C.; Leblanc S.; Lebrin V.; Lefevre F.; Lei R.; Leitner R.; Leung J.; Li D.; Li F.; Li F.; Li H.; Li H.; Li J.; Li M.; Li M.; Li N.; Li N.; Li Q.; Li R.; Li S.; Li T.; Li W.; Li W.; Li X.; Li X.; Li X.; Li Y.; Li Y.; Li Z.; Li Z.; Li Z.; Liang H.; Liang H.; Liao J.; Liebau D.; Limphirat A.; Limpijumnong S.; Lin G.-L.; Lin S.; Lin T.; Ling J.; Lippi I.; Liu F.; Liu H.; Liu H.; Liu H.; Liu H.; Liu H.; Liu J.; Liu J.; Liu M.; Liu Q.; Liu Q.; Liu R.; Liu S.; Liu S.; Liu S.; Liu X.; Liu X.; Liu Y.; Liu Y.; Lokhov A.; Lombardi P.; Lombardo C.; Loo K.; Lu C.; Lu H.; Lu J.; Lu J.; Lu S.; Lu X.; Lubsandorzhiev B.; Lubsandorzhiev S.; Ludhova L.; Luo F.; Luo G.; Luo P.; Luo S.; Luo W.; Lyashuk V.; Ma B.; Ma Q.; Ma S.; Ma X.; Ma X.; Maalmi J.; Malyshkin Y.; Mantovani F.; Manzali F.; Mao X.; Mao Y.; Mari S.M.; Marini F.; Marium S.; Martellini C.; Martin-Chassard G.; Martini A.; Mayer M.; Mayilyan D.; Mednieks I.; Meng Y.; Meregaglia A.; Meroni E.; Meyhofer D.; Mezzetto M.; Miller J.; Miramonti L.; Montini P.; Montuschi M.; Muller A.; Nastasi M.; Naumov D.V.; Naumova E.; Navas-Nicolas D.; Nemchenok I.; Nguyen Thi M.T.; Ning F.; Ning Z.; Nunokawa H.; Oberauer L.; Ochoa-Ricoux J.P.; Olshevskiy A.; Orestano D.; Ortica F.; Othegraven R.; Pan H.-R.; Paoloni A.; Parmeggiano S.; Pei Y.; Pelliccia N.; Peng A.; Peng H.; Perrot F.; Petitjean P.-A.; Petrucci F.; Pilarczyk O.; Pineres Rico L.F.; Popov A.; Poussot P.; Pratumwan W.; Previtali E.; Qi F.; Qi M.; Qian S.; Qian X.; Qian Z.; Qiao H.; Qin Z.; Qiu S.; Rajput M.U.; Ranucci G.; Raper N.; Re A.; Rebber H.; Rebii A.; Ren B.; Ren J.; Ricci B.; Robens M.; Roche M.; Rodphai N.; Romani A.; Roskovec B.; Roth C.; Ruan X.; Ruan X.; Rujirawat S.; Rybnikov A.; Sadovsky A.; Saggese P.; Sanfilippo S.; Sangka A.; Sanguansak N.; Sawangwit U.; Sawatzki J.; Sawy F.; Schever M.; Schwab C.; Schweizer K.; Selyunin A.; Serafini A.; Settanta G.; Settimo M.; Shao Z.; Sharov V.; Shaydurova A.; Shi J.; Shi Y.; Shutov V.; Sidorenkov A.; Simkovic F.; Sirignano C.; Siripak J.; Sisti M.; Slupecki M.; Smirnov M.; Smirnov O.; Sogo-Bezerra T.; Sokolov S.; Songwadhana J.; Soonthornthum B.; Sotnikov A.; Sramek O.; Sreethawong W.; Stahl A.; Stanco L.; Stankevich K.; Stefanik D.; Steiger H.; Steinmann J.; Sterr T.; Stock M.R.; Strati V.; Studenikin A.; Sun S.; Sun X.; Sun Y.; Sun Y.; Suwonjandee N.; Szelezniak M.; Tang J.; Tang Q.; Tang Q.; Tang X.; Tietzsch A.; Tkachev I.; Tmej T.; Treskov K.; Triossi A.; Troni G.; Trzaska W.; Tuve C.; Ushakov N.; van den Boom J.; van Waasen S.; Vanroyen G.; Vassilopoulos N.; Vedin V.; Verde G.; Vialkov M.; Viaud B.; Vollbrecht M.C.; Volpe C.; Vorobel V.; Voronin D.; Votano L.; Walker P.; Wang C.; Wang C.-H.; Wang E.; Wang G.; Wang J.; Wang J.; Wang K.; Wang L.; Wang M.; Wang M.; Wang M.; Wang R.; Wang S.; Wang W.; Wang W.; Wang W.; Wang X.; Wang X.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Z.; Wang Z.; Wang Z.; Wang Z.; Waqas M.; Watcharangkool A.; Wei L.; Wei W.; Wei W.; Wei Y.; Wen L.; Wiebusch C.; Wong S.C.-F.; Wonsak B.; Wu D.; Wu F.; Wu Q.; Wu Z.; Wurm M.; Wurtz J.; Wysotzki C.; Xi Y.; Xia D.; Xie X.; Xie Y.; Xie Z.; Xing Z.; Xu B.; Xu C.; Xu D.; Xu F.; Xu H.; Xu J.; Xu J.; Xu M.; Xu Y.; Xu Y.; Yan B.; Yan T.; Yan W.; Yan X.; Yan Y.; Yang A.; Yang C.; Yang C.; Yang H.; Yang J.; Yang L.; Yang X.; Yang Y.; Yang Y.; Yao H.; Yasin Z.; Ye J.; Ye M.; Ye Z.; Yegin U.; Yermia F.; Yi P.; Yin N.; Yin X.; You Z.; Yu B.; Yu C.; Yu C.; Yu H.; Yu M.; Yu X.; Yu Z.; Yu Z.; Yuan C.; Yuan Y.; Yuan Z.; Yuan Z.; Yue B.; Zafar N.; Zambanini A.; Zavadskyi V.; Zeng S.; Zeng T.; Zeng Y.; Zhan L.; Zhang A.; Zhang F.; Zhang G.; Zhang H.; Zhang H.; Zhang J.; Zhang J.; Zhang J.; Zhang J.; Zhang J.; Zhang P.; Zhang Q.; Zhang S.; Zhang S.; Zhang T.; Zhang X.; Zhang X.; Zhang X.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Z.; Zhang Z.; Zhao F.; Zhao J.; Zhao R.; Zhao S.; Zhao T.; Zheng D.; Zheng H.; Zheng M.; Zheng Y.; Zhong W.; Zhou J.; Zhou L.; Zhou N.; Zhou S.; Zhou T.; Zhou X.; Zhu J.; Zhu K.; Zhu K.; Zhu Z.; Zhuang B.; Zhuang H.; Zong L.; Zou J.Abusleme, A.; Adam, T.; Ahmad, S.; Ahmed, R.; Aiello, S.; Akram, M.; An, F.; An, Q.; Andronico, G.; Anfimov, N.; Antonelli, V.; Antoshkina, T.; Asavapibhop, B.; de Andre, J. P. A. M.; Auguste, D.; Babic, A.; Baldini, W.; Barresi, A.; Basilico, D.; Baussan, E.; Bellato, M.; Bergnoli, A.; Birkenfeld, T.; Blin, S.; Blum, D.; Blyth, S.; Bolshakova, A.; Bongrand, M.; Bordereau, C.; Breton, D.; Brigatti, A.; Brugnera, R.; Bruno, R.; Budano, A.; Buscemi, M.; Busto, J.; Butorov, I.; Cabrera, A.; Cai, H.; Cai, X.; Cai, Y.; Cai, Z.; Cammi, A.; Campeny, A.; Cao, C.; Cao, G.; Cao, J.; Caruso, R.; Cerna, C.; Chang, J.; Chang, Y.; Chen, P.; Chen, P. -A.; Chen, S.; Chen, X.; Chen, Y. -W.; Chen, Y.; Chen, Y.; Chen, Z.; Cheng, J.; Cheng, Y.; Chetverikov, A.; Chiesa, D.; Chimenti, P.; Chukanov, A.; Claverie, G.; Clementi, C.; Clerbaux, B.; Conforti Di Lorenzo, S.; Corti, D.; Cremonesi, O.; Dal Corso, F.; Dalager, O.; De La Taille, C.; Deng, J.; Deng, Z.; Deng, Z.; Depnering, W.; Diaz, M.; Ding, X.; Ding, Y.; Dirgantara, B.; Dmitrievsky, S.; Dohnal, T.; Dolzhikov, D.; Donchenko, G.; Dong, J.; Doroshkevich, E.; Dracos, M.; Druillole, F.; Du, S.; Dusini, S.; Dvorak, M.; Enqvist, T.; Enzmann, H.; Fabbri, A.; Fajt, L.; Fan, D.; Fan, L.; Fang, J.; Fang, W.; Fargetta, M.; Fedoseev, D.; Fekete, V.; Feng, L. -C.; Feng, Q.; Ford, R.; Formozov, A.; Fournier, A.; Gan, H.; Gao, F.; Garfagnini, A.; Giammarchi, M.; Giaz, A.; Giudice, N.; Gonchar, M.; Gong, G.; Gong, H.; Gornushkin, Y.; Gottel, A.; Grassi, M.; Grewing, C.; Gromov, V.; Gu, M.; Gu, X.; Gu, Y.; Guan, M.; Guardone, N.; Gul, M.; Guo, C.; Guo, J.; Guo, W.; Guo, X.; Guo, Y.; Hackspacher, P.; Hagner, C.; Han, R.; Han, Y.; Hassan, M. S.; He, M.; He, W.; Heinz, T.; Hellmuth, P.; Heng, Y.; Herrera, R.; Hor, Y. K.; Hou, S.; Hsiung, Y.; Hu, B. -Z.; Hu, H.; Hu, J.; Hu, J.; Hu, S.; Hu, T.; Hu, Z.; Huang, C.; Huang, G.; Huang, H.; Huang, W.; Huang, X.; Huang, X.; Huang, Y.; Hui, J.; Huo, L.; Huo, W.; Huss, C.; Hussain, S.; Ioannisian, A.; Isocrate, R.; Jelmini, B.; Jen, K. -L.; Jeria, I.; Ji, X.; Ji, X.; Jia, H.; Jia, J.; Jian, S.; Jiang, D.; Jiang, X.; Jin, R.; Jing, X.; Jollet, C.; Joutsenvaara, J.; Jungthawan, S.; Kalousis, L.; Kampmann, P.; Kang, L.; Karaparambil, R.; Kazarian, N.; Khan, W.; Khosonthongkee, K.; Korablev, D.; Kouzakov, K.; Krasnoperov, A.; Kruth, A.; Kutovskiy, N.; Kuusiniemi, P.; Lachenmaier, T.; Landini, C.; Leblanc, S.; Lebrin, V.; Lefevre, F.; Lei, R.; Leitner, R.; Leung, J.; Li, D.; Li, F.; Li, F.; Li, H.; Li, H.; Li, J.; Li, M.; Li, M.; Li, N.; Li, N.; Li, Q.; Li, R.; Li, S.; Li, T.; Li, W.; Li, W.; Li, X.; Li, X.; Li, X.; Li, Y.; Li, Y.; Li, Z.; Li, Z.; Li, Z.; Liang, H.; Liang, H.; Liao, J.; Liebau, D.; Limphirat, A.; Limpijumnong, S.; Lin, G. -L.; Lin, S.; Lin, T.; Ling, J.; Lippi, I.; Liu, F.; Liu, H.; Liu, H.; Liu, H.; Liu, H.; Liu, H.; Liu, J.; Liu, J.; Liu, M.; Liu, Q.; Liu, Q.; Liu, R.; Liu, S.; Liu, S.; Liu, S.; Liu, X.; Liu, X.; Liu, Y.; Liu, Y.; Lokhov, A.; Lombardi, P.; Lombardo, C.; Loo, K.; Lu, C.; Lu, H.; Lu, J.; Lu, J.; Lu, S.; Lu, X.; Lubsandorzhiev, B.; Lubsandorzhiev, S.; Ludhova, L.; Luo, F.; Luo, G.; Luo, P.; Luo, S.; Luo, W.; Lyashuk, V.; Ma, B.; Ma, Q.; Ma, S.; Ma, X.; Ma, X.; Maalmi, J.; Malyshkin, Y.; Mantovani, F.; Manzali, F.; Mao, X.; Mao, Y.; Mari, S. M.; Marini, F.; Marium, S.; Martellini, C.; Martin-Chassard, G.; Martini, A.; Mayer, M.; Mayilyan, D.; Mednieks, I.; Meng, Y.; Meregaglia, A.; Meroni, E.; Meyhofer, D.; Mezzetto, M.; Miller, J.; Miramonti, L.; Montini, P.; Montuschi, M.; Muller, A.; Nastasi, M.; Naumov, D. V.; Naumova, E.; Navas-Nicolas, D.; Nemchenok, I.; Nguyen Thi, M. T.; Ning, F.; Ning, Z.; Nunokawa, H.; Oberauer, L.; Ochoa-Ricoux, J. P.; Olshevskiy, A.; Orestano, D.; Ortica, F.; Othegraven, R.; Pan, H. -R.; Paoloni, A.; Parmeggiano, S.; Pei, Y.; Pelliccia, N.; Peng, A.; Peng, H.; Perrot, F.; Petitjean, P. -A.; Petrucci, F.; Pilarczyk, O.; Pineres Rico, L. F.; Popov, A.; Poussot, P.; Pratumwan, W.; Previtali, E.; Qi, F.; Qi, M.; Qian, S.; Qian, X.; Qian, Z.; Qiao, H.; Qin, Z.; Qiu, S.; Rajput, M. U.; Ranucci, G.; Raper, N.; Re, A.; Rebber, H.; Rebii, A.; Ren, B.; Ren, J.; Ricci, B.; Robens, M.; Roche, M.; Rodphai, N.; Romani, A.; Roskovec, B.; Roth, C.; Ruan, X.; Ruan, X.; Rujirawat, S.; Rybnikov, A.; Sadovsky, A.; Saggese, P.; Sanfilippo, S.; Sangka, A.; Sanguansak, N.; Sawangwit, U.; Sawatzki, J.; Sawy, F.; Schever, M.; Schwab, C.; Schweizer, K.; Selyunin, A.; Serafini, A.; Settanta, G.; Settimo, M.; Shao, Z.; Sharov, V.; Shaydurova, A.; Shi, J.; Shi, Y.; Shutov, V.; Sidorenkov, A.; Simkovic, F.; Sirignano, C.; Siripak, J.; Sisti, M.; Slupecki, M.; Smirnov, M.; Smirnov, O.; Sogo-Bezerra, T.; Sokolov, S.; Songwadhana, J.; Soonthornthum, B.; Sotnikov, A.; Sramek, O.; Sreethawong, W.; Stahl, A.; Stanco, L.; Stankevich, K.; Stefanik, D.; Steiger, H.; Steinmann, J.; Sterr, T.; Stock, M. R.; Strati, V.; Studenikin, A.; Sun, S.; Sun, X.; Sun, Y.; Sun, Y.; Suwonjandee, N.; Szelezniak, M.; Tang, J.; Tang, Q.; Tang, Q.; Tang, X.; Tietzsch, A.; Tkachev, I.; Tmej, T.; Treskov, K.; Triossi, A.; Troni, G.; Trzaska, W.; Tuve, C.; Ushakov, N.; van den Boom, J.; van Waasen, S.; Vanroyen, G.; Vassilopoulos, N.; Vedin, V.; Verde, G.; Vialkov, M.; Viaud, B.; Vollbrecht, M. C.; Volpe, C.; Vorobel, V.; Voronin, D.; Votano, L.; Walker, P.; Wang, C.; Wang, C. -H.; Wang, E.; Wang, G.; Wang, J.; Wang, J.; Wang, K.; Wang, L.; Wang, M.; Wang, M.; Wang, M.; Wang, R.; Wang, S.; Wang, W.; Wang, W.; Wang, W.; Wang, X.; Wang, X.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Z.; Wang, Z.; Wang, Z.; Wang, Z.; Waqas, M.; Watcharangkool, A.; Wei, L.; Wei, W.; Wei, W.; Wei, Y.; Wen, L.; Wiebusch, C.; Wong, S. C. -F.; Wonsak, B.; Wu, D.; Wu, F.; Wu, Q.; Wu, Z.; Wurm, M.; Wurtz, J.; Wysotzki, C.; Xi, Y.; Xia, D.; Xie, X.; Xie, Y.; Xie, Z.; Xing, Z.; Xu, B.; Xu, C.; Xu, D.; Xu, F.; Xu, H.; Xu, J.; Xu, J.; Xu, M.; Xu, Y.; Xu, Y.; Yan, B.; Yan, T.; Yan, W.; Yan, X.; Yan, Y.; Yang, A.; Yang, C.; Yang, C.; Yang, H.; Yang, J.; Yang, L.; Yang, X.; Yang, Y.; Yang, Y.; Yao, H.; Yasin, Z.; Ye, J.; Ye, M.; Ye, Z.; Yegin, U.; Yermia, F.; Yi, P.; Yin, N.; Yin, X.; You, Z.; Yu, B.; Yu, C.; Yu, C.; Yu, H.; Yu, M.; Yu, X.; Yu, Z.; Yu, Z.; Yuan, C.; Yuan, Y.; Yuan, Z.; Yuan, Z.; Yue, B.; Zafar, N.; Zambanini, A.; Zavadskyi, V.; Zeng, S.; Zeng, T.; Zeng, Y.; Zhan, L.; Zhang, A.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, H.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, P.; Zhang, Q.; Zhang, S.; Zhang, S.; Zhang, T.; Zhang, X.; Zhang, X.; Zhang, X.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Z.; Zhang, Z.; Zhao, F.; Zhao, J.; Zhao, R.; Zhao, S.; Zhao, T.; Zheng, D.; Zheng, H.; Zheng, M.; Zheng, Y.; Zhong, W.; Zhou, J.; Zhou, L.; Zhou, N.; Zhou, S.; Zhou, T.; Zhou, X.; Zhu, J.; Zhu, K.; Zhu, K.; Zhu, Z.; Zhuang, B.; Zhuang, H.; Zong, L.; Zou, J

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure