Immunological and ultrastructural characterization of spirotrichonymphid flagellates from Reticulitermes grassei and R. flavipes (syn. R. santonensis), with special reference to Spirotrichonympha, Spironympha and Microjoenia

AbstractFive species of spirotrichonymphids representing three genera have been studied by light and immunofluorescence microscopy, and by transmission electron microscopy. The genus Spirotrichonympha, represented by S. flagellata from Reticulitermes grassei, is characterized by a compound axostyle composed of several fibers or subaxostyles. The genus Spironympha, represented by S. kofoidi from Reticulitermes flavipes (syn. R. santonensis) and by the two new species S. verticis and S. lanceata, is characterized by flagellar lines restricted to the anterior area and a simple, tubular axostyle. Spironympha verticis and S. lanceata are mainly distinguished by ultrastructural details of their flagellar lines and axostyle. These three Spironympha species were found in hosts identified as R. flavipes or R. santonensis, but not in R. grassei. This provides additional support for the synonymy of R. santonensis with R. flavipes recently demonstrated by molecular methods. The generic diagnosis of Microjoenia is emended, based on an ultrastructure study of M. fallax

Polydisperse hard spheres at a hard wall

The structural properties of polydisperse hard spheres in the presence of a hard wall are investigated via Monte Carlo simulation and density functional theory (DFT). Attention is focussed on the local density distribution $\rho(\sigma,z)$, measuring the number density of particles of diameter $\sigma$ at a distance $z$ from the wall. The form of $\rho(\sigma,z)$ is obtained for bulk volume fractions $\eta_b=0.2$ and $\eta_b=0.4$ for two choices of the bulk parent distribution: a top-hat form, which we study for degrees of polydispersity $\delta=11.5$ and $\delta=40.4$, and a truncated Schulz form having $\delta=40.7$. Excellent overall agreement is found between the DFT and simulation results, particularly at $\eta_b=0.2$. A detailed analysis of $\rho(\sigma,z)$ confirms the presence of oscillatory size segregation effects observed in a previous DFT study (Pagonabarraga {\em et al.}, Phys. Rev. Lett. {\bf 84}, 911 (2000)). For large $\delta$, the character of these oscillation is observed to depend strongly on the shape of the parent distribution. In the vicinity of the wall, attractive $\sigma$-dependent depletion interactions are found to greatly enhance the density of the largest particles. The local degree of polydispersity $\delta(z)$ is suppressed in this region, while further from the wall it exhibits oscillations.Comment: 12 pages revte

TAO Conceptual Design Report: A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to provide a reference spectrum for future reactor neutrino experiments, and to provide a benchmark measurement to test nuclear databases. A spherical acrylic vessel containing 2.8 ton gadolinium-doped liquid scintillator will be viewed by 10 m^2 Silicon Photomultipliers (SiPMs) of >50% photon detection efficiency with almost full coverage. The photoelectron yield is about 4500 per MeV, an order higher than any existing large-scale liquid scintillator detectors. The detector operates at -50 degree C to lower the dark noise of SiPMs to an acceptable level. The detector will measure about 2000 reactor antineutrinos per day, and is designed to be well shielded from cosmogenic backgrounds and ambient radioactivities to have about 10% background-to-signal ratio. The experiment is expected to start operation in 2022

Modern termites inherited the potential of collective construction from their common ancestor

Animal collective behaviors give rise to various spatial patterns, such as the nests of social insects. These structures are built by individuals following a simple set of rules, slightly varying within and among species, to produce a large diversity of shapes. However, little is known about the origin and evolution of the behavioral mechanisms regulating nest structures. In this study, we discuss the perspective of inferring the evolution of collective behaviors behind pattern formations using a phylogenetic framework. We review the collective behaviors that can be described by a single set of behavioral rules, and for which variations of the environmental and behavioral parameter values produce diverse patterns. We propose that this mechanism could be at the origin of the pattern diversity observed among related species, and that, when they are placed in the proper conditions, species have the behavioral potential to form patterns observed in related species. The comparative analysis of shelter tube construction by lower termites is consistent with this hypothesis. Although the use of shelter tubes in natural conditions is variable among species, most modern species have the potential to build them, suggesting that the behavioral rules for shelter tube construction evolved once in the common ancestor of modern termites. Our study emphasizes that comparative studies of behavioral rules have the potential to shed light on the evolution of collective behaviors.journal articl

Do Termites Avoid Carcasses? Behavioral Responses Depend on the Nature of the Carcasses

BACKGROUND: Undertaking behavior is a significant adaptation to social life in enclosed nests. Workers are known to remove dead colony members from the nest. Such behavior prevents the spread of pathogens that may be detrimental to a colony. To date, little is known about the ethological aspects of how termites deal with carcasses. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we tested the responses to carcasses of four species from different subterranean termite taxa: Coptotermes formosanus Shiraki and Reticulitermes speratus (Kolbe) (lower termites) and Microcerotermes crassus Snyder and Globitermes sulphureus Haviland (higher termites). We also used different types of carcasses (freshly killed, 1-, 3-, and 7-day-old, and oven-killed carcasses) and mutilated nestmates to investigate whether the termites exhibited any behavioral responses that were specific to carcasses in certain conditions. Some behavioral responses were performed specifically on certain types of carcasses or mutilated termites. C. formosanus and R. speratus exhibited the following behaviors: (1) the frequency and time spent in antennating, grooming, and carcass removal of freshly killed, 1-day-old, and oven-killed carcasses were high, but these behaviors decreased as the carcasses aged; (2) the termites repeatedly crawled under the aging carcass piles; and (3) only newly dead termites were consumed as a food source. In contrast, M. crassus and G. sulphureus workers performed relatively few behavioral acts. Our results cast a new light on the previous notion that termites are necrophobic in nature. CONCLUSION: We conclude that the behavioral response towards carcasses depends largely on the nature of the carcasses and termite species, and the response is more complex than was previously thought. Such behavioral responses likely are associated with the threat posed to the colony by the carcasses and the feeding habits and nesting ecology of a given species

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

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

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

White-gutted soldiers: simplification of the digestive tube for a non-particulate diet in higher Old World termites (Isoptera: Termitidae)

Previous observations have noted that in some species of higher termites the soldier caste lacks pigmented particles in its gut and, instead, is fed worker saliva that imparts a whitish coloration to the abdomen. In order to investigate the occurrence of this trait more thoroughly, we surveyed a broad diversity of termite specimens and taxonomic descriptions from the Old World subfamilies Apicotermitinae, Cubitermitinae, Foraminitermitinae, Macrotermitinae, and Termitinae. We identified 38 genera that have this “white-gutted” soldier (WGS) trait. No termite soldiers from the New World were found to possess a WGS caste. Externally, the WGS is characterized by a uniformly pale abdomen, hyaline gut, and proportionally smaller body-to-head volume ratio compared with their “dark-gutted” soldier (DGS) counterparts found in most termitid genera. The WGS is a fully formed soldier that, unlike soldiers in other higher termite taxa, has a small, narrow, and decompartmentalized digestive tube that lacks particulate food contents. The presumed saliva-nourished WGS have various forms of simplified gut morphologies that have evolved at least six times within the higher termites