Preparation of C2-Symmetric Biaryl Bisiminium Salts and Their Use as Organocatalysts for Asymmetric Epoxidation

Two C2-symmetric bisiminium salt species containing biphenylazepinium units and derived from two chiral diamines were prepared and tested as organocatalysts for asymmetric epoxidation

Epidemiology of Cardiopulmonary Resuscitation in Critically Ill Children Admitted to Pediatric Intensive Care Units Across England: A Multicenter Retrospective Cohort Study

Background Cardiopulmonary arrests are a major contributor to mortality and morbidity in pediatric intensive care units (PICUs). Understanding the epidemiology and risk factors for CPR may inform national quality improvement initiatives. Methods and Results A retrospective cohort analysis using prospectively collected data from the Paediatric Intensive Care Audit Network database. The Paediatric Intensive Care Audit Network contains data on all PICU admissions in the United Kingdom. We identified children who received cardiopulmonary resuscitation (CPR) in 23 PICUs in England (2013-2017). Incidence rates of CPR and associated factors were analyzed. Logistic regression was used to estimate the size and precision of associations. Cumulative incidence of CPR was 2.2% for 68 114 admissions over 5 years with an incidence rate of 4.9 episodes/1000 bed days. Cardiovascular diagnosis (odds ratio [OR], 2.30; 95% CI, 2.02-2.61), age <1 year (OR, 1.84; 95% CI, 1.65-2.04), the Paediatric Index of Mortality 2 score on admission (OR, 1.045; 95% CI, 1.042-1.047) and longer length of stay (OR, 1.013; 95% CI, 1.012-1.014) were associated with increased odds of receiving CPR. We also found a higher risk of CPR associated with a history of preadmission cardiac arrest (OR, 20.69; [95% CI, 18.16-23.58) and for children with a cardiac condition admitted to a noncardiac PICU (OR, 2.75; 95% CI, 1.91-3.98). Children from Black (OR, 1.68; 95% CI, 1.36-2.07) and Asian (OR, 1.49; 95% CI, 1.28-1.74) racial/ethnic backgrounds were at higher risk of receiving CPR in PICU than White children. Conclusions Data from this first multicenter study from England provides a foundation for further research and evidence for benchmarking and quality improvement for prevention of cardiac arrests in PICU

Optogenetic Control of Subcellular Protein Location and Signaling in Vertebrate Embryos.

This chapter describes the use of optogenetic heterodimerization in single cells within whole-vertebrate embryos. This method allows the use of light to reversibly bind together an "anchor" protein and a "bait" protein. Proteins can therefore be directed to specific subcellular compartments, altering biological processes such as cell polarity and signaling. I detail methods for achieving transient expression of fusion proteins encoding the phytochrome heterodimerization system in early zebrafish embryos (Buckley et al., Dev Cell 36(1):117-126, 2016) and describe the imaging parameters used to achieve subcellular light patterning

In the eye of the storm: impact of COVID-19 pandemic on admission patterns to paediatric intensive care units in the UK and Eire

Background The coronavirus disease-19 (COVID-19) pandemic had a relatively minimal direct impact on critical illness in children compared to adults. However, children and paediatric intensive care units (PICUs) were affected indirectly. We analysed the impact of the pandemic on PICU admission patterns and patient characteristics in the UK and Ireland. Methods We performed a retrospective cohort study of all admissions to PICUs in children < 18 years during Jan–Dec 2020, using data collected from 32 PICUs via a central database (PICANet). Admission patterns, case-mix, resource use, and outcomes were compared with the four preceding years (2016–2019) based on the date of admission. Results There were 16,941 admissions in 2020 compared to an annual average of 20,643 (range 20,340–20,868) from 2016 to 2019. During 2020, there was a reduction in all PICU admissions (18%), unplanned admissions (20%), planned admissions (15%), and bed days (25%). There was a 41% reduction in respiratory admissions, and a 60% reduction in children admitted with bronchiolitis but an 84% increase in admissions for diabetic ketoacidosis during 2020 compared to the previous years. There were 420 admissions (2.4%) with either PIMS-TS or COVID-19 during 2020. Age and sex adjusted prevalence of unplanned PICU admission reduced from 79.7 (2016–2019) to 63.1 per 100,000 in 2020. Median probability of death [1.2 (0.5–3.4) vs. 1.2 (0.5–3.4) %], length of stay [2.3 (1.0–5.5) vs. 2.4 (1.0–5.7) days] and mortality rates [3.4 vs. 3.6%, (risk-adjusted OR 1.00 [0.91–1.11, p = 0.93])] were similar between 2016–2019 and 2020. There were 106 fewer in-PICU deaths in 2020 (n = 605) compared with 2016–2019 (n = 711). Conclusions The use of a high-quality international database allowed robust comparisons between admission data prior to and during the COVID-19 pandemic. A significant reduction in prevalence of unplanned admissions, respiratory diseases, and fewer child deaths in PICU observed may be related to the targeted COVID-19 public health interventions during the pandemic. However, analysis of wider and longer-term societal impact of the pandemic and public health interventions on physical and mental health of children is required

Interleaved Parton Showers and Tuning Prospects

General-purpose Monte Carlo event generators have become important tools in particle physics, allowing the simulation of exclusive hadronic final states. In this article we examine the Pythia 8 generator, in particular focusing on its parton-shower algorithms. Some relevant new additions to the code are introduced, that should allow for a better description of data. We also implement and compare with 2 to 3 real-emission QCD matrix elements, to check how well the shower algorithm fills the phase space away from the soft and collinear regions. A tuning of the generator to Tevatron data is performed for two PDF sets and the impact of first new LHC data is examined

Measuring the Meltdown: Drivers of Global Amphibian Extinction and Decline

Habitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation

First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ

On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models

[EN] In order to be reusable, history-based feature-based parametric CAD models must reliably allow for modifications while maintaining their original design intent. In this paper, we demonstrate that relations that fix the location of geometric entities relative to the reference system produce inflexible profiles that reduce model reusability. We present the results of an experiment where novice students and expert CAD users performed a series of modifications in different versions of the same 2D profile, each defined with an increasingly higher number of fix geometric constraints. Results show that the amount of fix constraints in a 2D profile correlates with the time required to complete reusability tasks, i.e., the higher the number of fix constraints in a 2D profile, the less flexible and adaptable the profile becomes to changes. In addition, a pilot software tool to automatically track this type of constraints was developed and tested. Results suggest that the detection of fix constraint overuse may result in a new metric to assess poor quality models with low reusability. The tool provides immediate feedback for preventing high semantic level quality errors, and assistance to CAD users. Finally, suggestions are introduced on how to convert fix constraints in 2D profiles into a negative metric of 3D model quality.The authors would like to thank Raquel Plumed for her support in the statistical analysis. This work has been partially funded by Grant UJI-A02017-15 (Universitat Jaume I) and DPI201784526-R (MINECO/AEI/FEDER, UE), project CAL-MBE. The authors also wish to thank the editor and reviewers for their valuable comments and suggestions that helped us improve the quality of the paper.González-Lluch, C.; Company, P.; Contero, M.; Pérez Lopez, DC.; Camba, JD. (2019). On the effects of the fix geometric constraint in 2D profiles on the reusability of parametric 3D CAD models. International Journal of Technology and Design Education. 29(4):821-841. https://doi.org/10.1007/s10798-018-9458-zS821841294Ait-Aoudia, S., & Foufou, S. (2010). A 2D geometric constraint solver using a graph reduction method. Advances in Engineering Software, 41(10), 1187–1194. https://doi.org/10.1016/j.advengsoft.2010.07.008 .Ault, H. K. (1999). Using geometric constraints to capture design intent. Journal for Geometry and Graphics, 3(1), 39–45.Ault, H. K. (2004). Over-constrained, under-constrained or just right? Goldilocks evaluates DOF of sketched profiles. Paper presented at American Society for Engineering Education, 59th annual midyear meeting past, present and future? Williamsburg, November 21–23.Ault, H. K., Bu, L., & Liu, K. (2014). Solid modeling strategies-analyzing student choices. Paper presented at proceedings of the 121st ASEE annual conference and exposition, Indianapolis, June 15–18.Ault, H. K., & Fraser, A. (2013). A comparison of manual vs. online grading for solid models. Paper presented at 120th ASEE annual conference and exposition, Atlanta, GA, June 23–26, 2013, Paper ID #7233.Barbero, B. R., Pedrosa, C. M., & Samperio, R. Z. (2016). Learning CAD at university through summaries of the rules of design intent. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-016-9358-z .Bodein, Y., Bertrand, R., & Caillaud, E. (2014). Explicit reference modeling methodology in parametric CAD system. Computers in Industry, 65(1), 136–147. https://doi.org/10.1016/j.compind.2013.08.004 .Bouma, W., Fudos, I., Hoffmann, C., Cai, J., & Paige, R. (1995). Geometric constraint solver. Computer-Aided Design, 27(6), 487–501. https://doi.org/10.1016/0010-4485(94)00013-4 .Briggs, J. C., Hepworth, A. I., Stone, B. R., Cobum, J. Q., Jensen, C. G., & Red, E. (2015). Integrated, synchronous multi-user design and analysis. Journal of Computing and Information Science in Engineering, 15(3), 031002. https://doi.org/10.1115/1.4029801 .Buckley, J., Seery, N., & Canty, D. (2017). Heuristics and CAD modelling: An examination of student behaviour during problem solving episodes within CAD modelling activities. International Journal of Technology and Design Education. https://doi.org/10.1007/s10798-017-9423-2 .Camba, J. D., & Contero, M. (2015). Assessing the impact of geometric design intent annotations on parametric model alteration activities. Computers in Industry, 71, 35–45. https://doi.org/10.1016/j.compind.2015.03.006 .Camba, J. D., Contero, M., & Company, P. (2016). Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design, 74, 18–31. https://doi.org/10.1016/j.cad.2016.01.003 .Camba, J. D., Contero, M., & Company, P. (2017). CAD reusability and the role of modeling information in the MBE context. Model-based enterprise summit 2017. National Institute of Standards and Technology (NIST), Gaithersburg, MD, April 3–7. MBE17-020. https://www.nist.gov/file/361581 .Cheng, Z., & Ma, Y. (2017). A functional feature modeling method. Advanced Engineering Informatics, 33, 1–15. https://doi.org/10.1016/j.aei.2017.04.003 .Cheng, Z., Xie, Y., & Ma, Y. (2018). Graph centrality analysis of feature dependencies to unveil modeling intents. Computer-Aided Design and Applications. https://doi.org/10.1080/16864360.2018.1441236 .Chester, I. (2007). Teaching for CAD expertise. International Journal of Technology and Design Education, 17, 23–35. https://doi.org/10.1007/s10798-006-9015-z .Company, P., Contero, M., Otey, J., & Plumed, R. (2015). Approach for developing coordinated rubrics to convey quality criteria in CAD training. Computer-Aided Design, 63, 101–117. https://doi.org/10.1016/j.cad.2014.10.00 .Company, P., & González-Lluch, C. (2013). CAD 3D con SolidWorks ® Tomo I: Diseño básico. Publicacions de la Universitat Jaume I. (Colección Sapientia, Núm. 86). http://cad3dconsolidworks.uji.es .Contero, M., Company, P., Vila, C., & Aleixos, N. (2002). Product data quality and collaborative engineering. IEEE Computer Graphics Applications, 22(3), 32–42. https://doi.org/10.1109/MCG.2002.999786 .Dixon, B. M., & Dannenhoffer, J. F., III. (2014). Geometric sketch constraint solving with user feedback. Journal of Aerospace Information Systems, 11(5), 316–325. https://doi.org/10.2514/1.I010110 .Fudos, I., & Hoffmann, C. M. (1997). A graph-constructive approach to solving systems of geometric constraints. ACM Transactions on Graphics, 16(2), 179–216. https://doi.org/10.1145/248210.248223 .Ge, J. X., Chou, S. C., & Gao, X. S. (1999). Geometric constraint satisfaction using optimization methods. Computer-Aided Design, 31(14), 867–879. https://doi.org/10.1016/S0010-4485(99)00074-3 .González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Colom, J. (2017a). A case study on the use of model quality testing tools for the assessment of MCAD models and drawings. International Journal of Engineering Education, 33(5), 1643–1653.González-Lluch, C., Company, P., Contero, M., Camba, J. D., & Plumed, R. (2017b). A survey on 3D CAD model quality assurance and testing tools. Computer-Aided Design, 83, 64–79. https://doi.org/10.1016/j.cad.2016.10.003 .Hamade, R. F. (2009). Profiling the desirable CAD trainee: Technical background, personality attributes, and learning preferences. Journal of Mechanical Design, 131(12), 121009–121019. https://doi.org/10.1115/1.4000455 .Hekman, K. A., & Gordon, M. T. (2013). Automated grading of first year student CAD work. Paper presented at the 120th ASEE annual conference and exposition 2013, Atlanta, GA, June 23–26. Paper ID #6379.Hepworth, A., Tew, K., Trent, M., Ricks, R., Jensen, C. G., & Red, E. R. (2014). Model consistency and conflict resolution with data preservation in multi-user computer aided design. Journal of Computing and Information Science in Engineering, 14(2), 021008. https://doi.org/10.1115/1.4026553 .Jackson, C., & Buxton, M. (2007). The design reuse benchmark report: Seizing the opportunity to shorten product development. Boston: Aberdeen Group.Joan-Arinyo, R., Soto-Riera, A., Vila-Marta, S., & Vilaplana-Pastó, J. (2003). Transforming an under-constrained geometric constraint problem into a well-constrained one. Paper presented at proceedings of ACM SM03, Seatle, June 16–20.Kirstukas, S. J. (2016). Development and evaluation of a computer program to assess student CAD models. Paper presented at ASEE annual conference and exposition, New Orleans, June 26.Kramer, G. (1991). Using degrees of freedom analysis to solve geometric constraint systems. Paper presented at proceedings of the first ACM symposium on solid modeling foundations and CAD/CAM applications 1991, Austin, June 05–07.Kwon, S., Kim, B. C., Mun, D., & Han, S. (2015). Graph-based simplification of feature-based three-dimensional computer-aided design models for preserving connectivity. Journal of Computing and Information Science in Engineering, 15(3), 031010. https://doi.org/10.1115/1.4030748 .Leea, J. Y., & Kimb, K. (1998). A 2-D geometric constraint solver using DOF-based graph reduction. Computer-Aided Design, 30(11), 883–896. https://doi.org/10.1016/S0010-4485(98)00045-1 .Mata Burgarolas, N. (1997). Solving incidence and tangency constraints in 2D. Technical report LSI-97-3R, Departament LiSI, Universitat Politècnica de Catalunya.Petrina, S. (2003). Two cultures of technical courses and discourses: The case of computer aided design. International Journal of Technology and Design Education, 13, 47–73.Race, P. (2001). The lecturers toolkit—A practical guide to learning, teaching and assessment. Great Britain: Glasgow.Red, E., French, D., Jensen, G., Walker, S. S., & Madsen, P. (2013). Emerging design methods and tools in collaborative product development. Journal of Computing and Information Science in Engineering, 13(3), 031001. https://doi.org/10.1115/1.4023917 .Robertson, B. F., Walther, J., & Radcliffe, D. (2007). Creativity and the use of CAD tools: Lessons for engineering design education from industry. Journal of Mechanical Design, 129(7), 753–760. https://doi.org/10.1115/1.2722329 .Stone, B., Salmon, J., Eves, K., Killian, M., Wright, L., Oldroyd, J., et al. (2017). A multi-user computer-aided design competition: Experimental findings and analysis of team-member dynamics. Journal of Computing and Information Science in Engineering, 17(3), 031003. https://doi.org/10.1115/1.4035674 .Summers, J. D., & Shah, J. J. (2010). Mechanical engineering design complexity metrics: Size, coupling, and solvability. Journal of Mechanical Design, 132(2), 21004–21015. https://doi.org/10.1115/1.4000759 .Szewczyk, J. (2003). Difficulties with the novices’ comprehension of the computer-aided design (CAD) interface: Understanding visual representations of CAD tools. Journal of Engineering Design, 14(2), 169–185. https://doi.org/10.1080/0954482031000091491

Dataset of manually measured QT intervals in the electrocardiogram

BACKGROUND: The QT interval and the QT dispersion are currently a subject of considerable interest. Cardiac repolarization delay is known to favor the development of arrhythmias. The QT dispersion, defined as the difference between the longest and the shortest QT intervals or as the standard deviation of the QT duration in the 12-lead ECG is assumed to be reliable predictor of cardiovascular mortality. The seventh annual PhysioNet/Computers in Cardiology Challenge, 2006 addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations? METHOD: The PTB Diagnostic ECG Database was given to 4 cardiologists and 1 biomedical engineer for manual marking of QRS onsets and T-wave ends in 458 recordings. Each recording consisted of one selected beat in lead II, chosen visually to have minimum baseline shift, noise, and artifact. In cases where no T wave could be observed or its amplitude was very small, the referees were instructed to mark a 'group-T-wave end' taking into consideration leads with better manifested T wave. A modified Delphi approach was used, which included up to three rounds of measurements to obtain results closer to the median. RESULTS: A total amount of 2*5*548 Q-onsets and T-wave ends were manually marked during round 1. To obtain closer to the median results, 8.58 % of Q-onsets and 3.21 % of the T-wave ends had to be reviewed during round 2, and 1.50 % Q-onsets and 1.17 % T-wave ends in round 3. The mean and standard deviation of the differences between the values of the referees and the median after round 3 were 2.43 ± 0.96 ms for the Q-onset, and 7.43 ± 3.44 ms for the T-wave end. CONCLUSION: A fully accessible, on the Internet, dataset of manually measured Q-onsets and T-wave ends was created and presented in additional file: 1 (Table 4) with this article. Thus, an available standard can be used for the development of automated methods for the detection of Q-onsets, T-wave ends and for QT interval measurements

Direct and indirect interactions between ants ( Pheidole megacephala ), scales ( Coccus viridis ) and plants ( Pluchea indica )

This study investigated direct and indirect interactions between the ant, Pheidole megacephala (Fabr.), the green scale, Coccus viridis (Green), and the scale's host plant, Pluchea indica (L.). To examine the influence of ants on scales and host plants, scale population densities, scale mortality rates, and plant performance were studied on control host plants with ants and host plants from which ants had been removed. Plants with ants present had significantly greater scale population densities and scale reproductive rates than did plants without ants. Scale mortality from both parasitism and other causes was increased on plants without ants relative to plants with ants. Predator introduction experiments showed that P. megacephala removes predatory coccinellid larvae, even when they are covered with a protective coating. Host plants from which ants had been removed had significantly higher degrees of honeydew accumulation, which resulted in greater colonization by sooty mold and greater rates of leaf death and abscission. Ants also removed herbivorous lepidopteran larvae from plants. Results are discussed in terms of the potential of P. megacephala to exert direct and indirect positive effects on scale populations and an indirect positive effect on Pluchea indica .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47790/1/442_2004_Article_BF00325261.pd