Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Randomized trials of artemisinin-piperaquine, dihydroartemisinin-piperaquine phosphate and artemether-lumefantrine for the treatment of multi-drug resistant falciparum malaria in Cambodia-Thailand border area

<p>Abstract</p> <p>Background</p> <p>Drug resistance of falciparum malaria is a global problem. Sulphadoxine/pyrimethamine-resistant and mefloquine-resistant strains of falciparum malaria have spread in Southeast Asia at lightning speed in 1980s-1990s, and the Cambodia-Thailand border is one of the malaria epidemic areas with the most severe forms of multi-drug resistant falciparum malaria.</p> <p>Methods</p> <p>Artemisinin-piperaquine (AP), dihydroartemisinin-piperaquine phosphate (DHP) and artemether-lumefantrine (AL) were used to treat 110, 55 and 55 uncomplicated malaria patients, respectively. The total dosage for adults is 1,750 mg (four tablets, twice over 24 hours) of AP, 2,880 mg (eight tablets, four times over two days) of DHP, and 3,360 mg (24 tablets, six times over three days) of AL. The 28-day cure rate, parasite clearance time, fever clearance time, and drug tolerance of patients to the three drugs were compared. All of the above methods were consistent with the current national guidelines.</p> <p>Results</p> <p>The mean parasite clearance time was similar in all three groups (66.7 ± 21.9 hrs, 65.6 ± 27.3 hrs, 65.3 ± 22.5 hrs in AP, DHP and AL groups, respectively), and there was no remarkable difference between them; the fever clearance time was also similar (31.6 ± 17.7 hrs, 34.6 ± 21.8 hrs and 36.9 ± 15.4 hrs, respectively). After following up for 28-days, the cure rate was 95.1%(97/102), 98.2%(54/55) and 82.4%(42/51); and the recrudescence cases was 4.9%(5/102), 1.8%(1/55) and 17.6%(9/51), respectively. Therefore, the statistical data showed that 28-day cure rate in AP and DHP groups was superior to AL group obviously.</p> <p>The patients had good tolerance to all the three drugs, and some side effects (anoxia, nausea, vomiting, headache and dizziness) could be found in every group and they were self-limited; patients in control groups also had good tolerance to DHP and AL, there was no remarkable difference in the three groups.</p> <p>Conclusions</p> <p>AP, DHP and AL all remained efficacious treatments for the treatment of falciparum malaria in Cambodia-Thailand border area. However, in this particular setting, the AP regimen turned out to be favourable in terms of efficacy and effectiveness, simplicity of administration, cost and compliance.</p> <p>Trial Registration</p> <p>The trial was registered at <it>Chinese Clinical Trial Register </it>under identifier 2005L01041.</p

"You have to get wet to learn how to swim" applied to bridging the gap between research into personnel scheduling and its implementation in practice

Personnel scheduling problems have attracted research interests for several decades. They have been considerably changed over time, accommodating a variety of constraints related to legal and organisation requirements, part-time staff, flexible hours of staff, staff preferences, etc. This led to a myriad of approaches developed for solving personnel scheduling problems including optimisation, meta-heuristics, artificial intelligence, decision-support, and also hybrids of these approaches. However, this still does not imply that this research has a large impact on practice and that state-of-the art models and algorithms are widely in use in organisations. One can find a reasonably large number of software packages that aim to assist in personnel scheduling. A classification of this software based on its purpose will be proposed, accompanied with a discussion about the level of support that this software offers to schedulers. A general conclusion is that the available software, with some exceptions, does not benefit from the wealth of developed models and methods. The remaining of the paper will provide insights into some characteristics of real-world scheduling problems that, in the author’s opinion, have not been given a due attention in the personnel scheduling research community yet and which could contribute to the enhancement of the implementation of research results in practice. Concluding remarks are that in order to bridge the gap that still exists between research into personnel scheduling and practice, we need to engage more with schedulers in practice and also with software developers; one may say we need to get wet if we want to learn how to swim

Crystal Structures of the ATPase Domains of Four Human Hsp70 Isoforms: HSPA1L/Hsp70-hom, HSPA2/Hsp70-2, HSPA6/Hsp70B', and HSPA5/BiP/GRP78

The 70-kDa heat shock proteins (Hsp70) are chaperones with central roles in processes that involve polypeptide remodeling events. Hsp70 proteins consist of two major functional domains: an N-terminal nucleotide binding domain (NBD) with ATPase activity, and a C-terminal substrate binding domain (SBD). We present the first crystal structures of four human Hsp70 isoforms, those of the NBDs of HSPA1L, HSPA2, HSPA5 and HSPA6. As previously with Hsp70 family members, all four proteins crystallized in a closed cleft conformation, although a slight cleft opening through rotation of subdomain IIB was observed for the HSPA5-ADP complex. The structures presented here support the view that the NBDs of human Hsp70 function by conserved mechanisms and contribute little to isoform specificity, which instead is brought about by the SBDs and by accessory proteins.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1

Flow shop rescheduling under different types of disruption

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 2013, available online:http://www.tandfonline.com/10.1080/00207543.2012.666856Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimise the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand, and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.The authors would like to thank the anonymous referees for their careful and detailed comments that helped to improve the paper considerably. This work is partially financed by the Small and Medium Industry of the Generalitat Valenciana (IMPIVA) and by the European Union through the European Regional Development Fund (FEDER) inside the R + D program "Ayudas dirigidas a Institutos tecnologicos de la Red IMPIVA" during the year 2011, with project number IMDEEA/2011/142.Katragjini Prifti, K.; Vallada Regalado, E.; Ruiz García, R. (2013). Flow shop rescheduling under different types of disruption. International Journal of Production Research. 51(3):780-797. https://doi.org/10.1080/00207543.2012.666856S780797513Abumaizar, R. J., & Svestka, J. A. (1997). Rescheduling job shops under random disruptions. International Journal of Production Research, 35(7), 2065-2082. doi:10.1080/002075497195074Adiri, I., Frostig, E., & Kan, A. H. G. R. (1991). Scheduling on a single machine with a single breakdown to minimize stochastically the number of tardy jobs. Naval Research Logistics, 38(2), 261-271. doi:10.1002/1520-6750(199104)38:23.0.co;2-iAkturk, M. S., & Gorgulu, E. (1999). Match-up scheduling under a machine breakdown. European Journal of Operational Research, 112(1), 81-97. doi:10.1016/s0377-2217(97)00396-2Allahverdi, A. (1996). Two-machine proportionate flowshop scheduling with breakdowns to minimize maximum lateness. Computers & Operations Research, 23(10), 909-916. doi:10.1016/0305-0548(96)00012-3Arnaout, J. P., & Rabadi, G. (2008). Rescheduling of unrelated parallel machines under machine breakdowns. International Journal of Applied Management Science, 1(1), 75. doi:10.1504/ijams.2008.020040Artigues, C., Billaut, J.-C., & Esswein, C. (2005). Maximization of solution flexibility for robust shop scheduling. European Journal of Operational Research, 165(2), 314-328. doi:10.1016/j.ejor.2004.04.004Azizoglu, M., & Alagöz, O. (2005). Parallel-machine rescheduling with machine disruptions. IIE Transactions, 37(12), 1113-1118. doi:10.1080/07408170500288133Bean, J. C., Birge, J. R., Mittenthal, J., & Noon, C. E. (1991). Matchup Scheduling with Multiple Resources, Release Dates and Disruptions. Operations Research, 39(3), 470-483. doi:10.1287/opre.39.3.470Caricato, P., & Grieco, A. (2008). An online approach to dynamic rescheduling for production planning applications. International Journal of Production Research, 46(16), 4597-4617. doi:10.1080/00207540601136225CHURCH, L. K., & UZSOY, R. (1992). Analysis of periodic and event-driven rescheduling policies in dynamic shops. International Journal of Computer Integrated Manufacturing, 5(3), 153-163. doi:10.1080/09511929208944524Cowling, P., & Johansson, M. (2002). Using real time information for effective dynamic scheduling. European Journal of Operational Research, 139(2), 230-244. doi:10.1016/s0377-2217(01)00355-1Curry, J., & Peters *, B. (2005). Rescheduling parallel machines with stepwise increasing tardiness and machine assignment stability objectives. International Journal of Production Research, 43(15), 3231-3246. doi:10.1080/00207540500103953DUTTA, A. (1990). Reacting to Scheduling Exceptions in FMS Environments. IIE Transactions, 22(4), 300-314. doi:10.1080/07408179008964185Ghezail, F., Pierreval, H., & Hajri-Gabouj, S. (2010). Analysis of robustness in proactive scheduling: A graphical approach. Computers & Industrial Engineering, 58(2), 193-198. doi:10.1016/j.cie.2009.03.004Goren, S., & Sabuncuoglu, I. (2008). Robustness and stability measures for scheduling: single-machine environment. IIE Transactions, 40(1), 66-83. doi:10.1080/07408170701283198Hall, N. G., & Potts, C. N. (2004). Rescheduling for New Orders. Operations Research, 52(3), 440-453. doi:10.1287/opre.1030.0101Herrmann, J. W., Lee, C.-Y., & Snowdon, J. L. (1993). A Classification of Static Scheduling Problems. Complexity in Numerical Optimization, 203-253. doi:10.1142/9789814354363_0011Herroelen, W., & Leus, R. (2005). Project scheduling under uncertainty: Survey and research potentials. European Journal of Operational Research, 165(2), 289-306. doi:10.1016/j.ejor.2004.04.002Hozak, K., & Hill, J. A. (2009). Issues and opportunities regarding replanning and rescheduling frequencies. International Journal of Production Research, 47(18), 4955-4970. doi:10.1080/00207540802047106Huaccho Huatuco, L., Efstathiou, J., Calinescu, A., Sivadasan, S., & Kariuki, S. (2009). Comparing the impact of different rescheduling strategies on the entropic-related complexity of manufacturing systems. International Journal of Production Research, 47(15), 4305-4325. doi:10.1080/00207540701871036Jensen, M. T. (2003). Generating robust and flexible job shop schedules using genetic algorithms. IEEE Transactions on Evolutionary Computation, 7(3), 275-288. doi:10.1109/tevc.2003.810067King, J. R. (1976). The theory-practice gap in job-shop scheduling. Production Engineer, 55(3), 137. doi:10.1049/tpe.1976.0044Kopanos, G. M., Capón-García, E., Espuña,, A., & Puigjaner, L. (2008). Costs for Rescheduling Actions: A Critical Issue for Reducing the Gap between Scheduling Theory and Practice. Industrial & Engineering Chemistry Research, 47(22), 8785-8795. doi:10.1021/ie8005676Lee, C.-Y., Leung, J. Y.-T., & Yu, G. (2006). Two Machine Scheduling under Disruptions with Transportation Considerations. Journal of Scheduling, 9(1), 35-48. doi:10.1007/s10951-006-5592-7Li, Z., & Ierapetritou, M. (2008). Process scheduling under uncertainty: Review and challenges. Computers & Chemical Engineering, 32(4-5), 715-727. doi:10.1016/j.compchemeng.2007.03.001Liao, C. J., & Chen, W. J. (2004). Scheduling under machine breakdown in a continuous process industry. Computers & Operations Research, 31(3), 415-428. doi:10.1016/s0305-0548(02)00224-1Mehta, S. V. (1999). Predictable scheduling of a single machine subject to breakdowns. International Journal of Computer Integrated Manufacturing, 12(1), 15-38. doi:10.1080/095119299130443MUHLEMANN, A. P., LOCKETT, A. G., & FARN, C.-K. (1982). Job shop scheduling heuristics and frequency of scheduling. International Journal of Production Research, 20(2), 227-241. doi:10.1080/00207548208947763Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91-95. doi:10.1016/0305-0483(83)90088-9O’Donovan, R., Uzsoy, R., & McKay, K. N. (1999). Predictable scheduling of a single machine with breakdowns and sensitive jobs. International Journal of Production Research, 37(18), 4217-4233. doi:10.1080/002075499189745Özlen, M., & Azizoğlu, M. (2009). Generating all efficient solutions of a rescheduling problem on unrelated parallel machines. International Journal of Production Research, 47(19), 5245-5270. doi:10.1080/00207540802043998Pfeiffer, A., Kádár, B., & Monostori, L. (2007). Stability-oriented evaluation of rescheduling strategies, by using simulation. Computers in Industry, 58(7), 630-643. doi:10.1016/j.compind.2007.05.009Pierreval, H., & Durieux-Paris, S. (2007). Robust simulation with a base environmental scenario. European Journal of Operational Research, 182(2), 783-793. doi:10.1016/j.ejor.2006.07.045Damodaran, P., Hirani, N. S., & Gallego, M. C. V. (2009). Scheduling identical parallel batch processing machines to minimise makespan using genetic algorithms. European J. of Industrial Engineering, 3(2), 187. doi:10.1504/ejie.2009.023605Qi, X., Bard, J. F., & Yu, G. (2006). Disruption management for machine scheduling: The case of SPT schedules. International Journal of Production Economics, 103(1), 166-184. doi:10.1016/j.ijpe.2005.05.021Rangsaritratsamee, R., Ferrell, W. G., & Kurz, M. B. (2004). Dynamic rescheduling that simultaneously considers efficiency and stability. Computers & Industrial Engineering, 46(1), 1-15. doi:10.1016/j.cie.2003.09.007Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-2049. doi:10.1016/j.ejor.2005.12.009Sabuncuoglu, I., & Goren, S. (2009). Hedging production schedules against uncertainty in manufacturing environment with a review of robustness and stability research. International Journal of Computer Integrated Manufacturing, 22(2), 138-157. doi:10.1080/09511920802209033Sabuncuoglu, I., & Kizilisik, O. B. (2003). Reactive scheduling in a dynamic and stochastic FMS environment. International Journal of Production Research, 41(17), 4211-4231. doi:10.1080/0020754031000149202Salveson, M. E. (1952). On a Quantitative Method in Production Planning and Scheduling. Econometrica, 20(4), 554. doi:10.2307/1907643Samarghandi, H., & ElMekkawy, T. Y. (2011). An efficient hybrid algorithm for the two-machine no-wait flow shop problem with separable setup times and single server. European J. of Industrial Engineering, 5(2), 111. doi:10.1504/ejie.2011.039869Subramaniam *, V., Raheja, A. S., & Rama Bhupal Reddy, K. (2005). Reactive repair tool for job shop schedules. International Journal of Production Research, 43(1), 1-23. doi:10.1080/0020754042000270412Taillard, E. (1990). Some efficient heuristic methods for the flow shop sequencing problem. European Journal of Operational Research, 47(1), 65-74. doi:10.1016/0377-2217(90)90090-xTaillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278-285. doi:10.1016/0377-2217(93)90182-mValente, J. M. S., & Schaller, J. E. (2010). Improved heuristics for the single machine scheduling problem with linear early and quadratic tardy penalties. European J. of Industrial Engineering, 4(1), 99. doi:10.1504/ejie.2010.029572Vallada, E., & Ruiz, R. (2010). Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem☆. Omega, 38(1-2), 57-67. doi:10.1016/j.omega.2009.04.002Vieira, G. E., Herrmann, J. W., & Lin, E. (2000). Predicting the performance of rescheduling strategies for parallel machine systems. Journal of Manufacturing Systems, 19(4), 256-266. doi:10.1016/s0278-6125(01)80005-4Vieira, G. E., Herrmann, J. W., & Lin, E. (2003). Journal of Scheduling, 6(1), 39-62. doi:10.1023/a:1022235519958Yang, J., & Yu, G. (2002). Journal of Combinatorial Optimization, 6(1), 17-33. doi:10.1023/a:1013333232691Zandieh, M., & Gholami, M. (2009). An immune algorithm for scheduling a hybrid flow shop with sequence-dependent setup times and machines with random breakdowns. International Journal of Production Research, 47(24), 6999-7027. doi:10.1080/0020754080240063

Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

published_or_final_versio

Measurement of electron antineutrino oscillation based on 1230 days of operation of the Daya Bay experiment

published_or_final_versio

Improved Search for a Light Sterile Neutrino with the Full Configuration of the Daya Bay Experiment

published_or_final_versio

Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay

published_or_final_versio