On Parabolic Subgroups and Hecke Algebras of some Fractal Groups

* The authors thank the “Swiss National Science Foundation” for its support.

Groups with the Minimal Condition on Non-“Nilpotent-by-Finite” Subgroups

We characterize the groups which do not have non-trivial perfect sections and such that any strictly descending chain of non-“nilpotent-by-finite” subgroups is finite.

Sylow P-Subgroups of Abelian Group Rings

2000 Mathematics Subject Classification: Primary 20C07, 20K10, 20K20, 20K21; Secondary 16U60, 16S34.

Kneser and Hereditarily Kneser Subgroups of a Profinite Group

2000 Mathematics Subject Classification: 20E18, 12G05, 12F10, 12F99.

Finite Groups as the Union of Proper Subgroups

2000 Mathematics Subject Classification: 20D60,20E15.

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Psychosocial morbidity in women with abnormal cervical cytology managed by cytological surveillance or initial colposcopy : longitudinal analysis from the TOMBOLA randomised trial

We are grateful for the co-operation and assistance that we received from NHS staff in the co-ordinating centres and clinical sites. We thank the women who participated in TOMBOLA. The TOMBOLA trial was supported by the Medical Research Council (G9700808) and the NHS in England and Scotland. The TOMBOLA Group comprises the following: Grant-holders: University of Aberdeen and NHS Grampian, Aberdeen, Scotland: Maggie Cruickshank, Graeme Murray, David Parkin, Louise Smart, Eric Walker, Norman Waugh (Principal Investigator 2004–2008) University of Nottingham and Nottingham NHS, Nottingham, England: Mark Avis, Claire Chilvers, Katherine Fielding, Rob Hammond, David Jenkins, Jane Johnson, Keith Neal, Ian Russell, Rashmi Seth, Dave Whynes University of Dundee and NHS Tayside, Dundee, Tayside: Ian Duncan, Alistair Robertson (deceased) University of Ottawa, Ottawa, Canada: Julian Little (Principal Investigator 1999–2004) National Cancer Registry, Cork, Ireland: Linda Sharp Bangor University, Bangor, Wales: Ian Russell University of Hull, Hull, England: Leslie G Walker Staff in clinical sites and co-ordinating centres Grampian Breda Anthony, Sarah Bell, Adrienne Bowie, Katrina Brown (deceased), Joe Brown, Kheng Chew, Claire Cochran, Seonaidh Cotton, Jeannie Dean, Kate Dunn, Jane Edwards, David Evans, Julie Fenty, Al Finlayson, Marie Gallagher, Nicola Gray, Maureen Heddle, Alison Innes, Debbie Jobson, Mandy Keillor, Jayne MacGregor, Sheona Mackenzie, Amanda Mackie, Gladys McPherson, Ike Okorocha, Morag Reilly, Joan Rodgers, Alison Thornton, Rachel Yeats Tayside Lindyanne Alexander, Lindsey Buchanan, Susan Henderson, Tine Iterbeke, Susanneke Lucas, Gillian Manderson, Sheila Nicol, Gael Reid, Carol Robinson, Trish Sandilands Nottingham Marg Adrian, Ahmed Al-Sahab, Elaine Bentley, Hazel Brook, Claire Bushby, Rita Cannon, Brenda Cooper, Ruth Dowell, Mark Dunderdale, Dr Gabrawi, Li Guo, Lisa Heideman, Steve Jones, Salli Lawson, Zoë Philips, Christopher Platt, Shakuntala Prabhakaran, John Rippin, Rose Thompson, Elizabeth Williams, Claire Woolley Statistical analysis Seonaidh Cotton, Kirsten Harrild, John Norrie, Linda Sharp External Trial Steering Committee Nicholas Day (chair, 1999–2004), Theresa Marteau (chair 2004-), Mahesh Parmar, Julietta Patnick and Ciaran Woodman.

Centralizers of normal subgroups and the Z*-theorem

Peer reviewed

Abnormal Pedestrian Trajectory analysis based on arbitrary-length clustering

This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.

Searching for Predictive Subgroups

Thesis (Ph.D.)--University of Washington, 2016-08

Omega-3 Fatty Acids are Related to Abnormal Emotion Processing in Adolescent Boys with Attention Deficit Hyperactivity Disorder

Background In addition to the core symptoms, attention deficit hyperactivity disorder (ADHD) is associated with poor emotion regulation. There is some evidence that children and young adults with ADHD have lower omega-3 levels and that supplementation with omega-3 can improve both ADHD and affective symptoms. We therefore investigated differences between ADHD and non-ADHD children in omega-3/6 fatty acid plasma levels and the relationship between those indices and emotion-elicited event-related potentials (ERPs). Methods Children/adolescents with (n=31) and without ADHD (n=32) were compared in their plasma omega-3/6 indices and corresponding ERPs during an emotion processing task. Results Children with ADHD had lower mean omega-3/6 and ERP abnormalities in emotion processing, independent of emotional valence relative to control children. ERP abnormalities were significantly associated with lower omega-3 levels in the ADHD group. Conclusions The findings reveal for the first time that lower omega-3 fatty acids are associated with impaired emotion processing in ADHD children.