James Taylor

Bio: James Taylor is an academic researcher from Newcastle University. The author has contributed to research in topics: Laser & Fiber laser. The author has an hindex of 95, co-authored 1161 publications receiving 39945 citations. Previous affiliations of James Taylor include Institut national de la recherche agronomique & European Spallation Source.

Association between parents' preferences and perceptions of barriers to vaccination and the immunization status of their children: a study from Pediatric Research in Office Settings and the National Medical Association.

Abstract: Objectives. To assess the association between parents’ perceptions of various barriers to vaccination and their preferences regarding specific strategies designed to reduce missed vaccination opportunities and the immunization status of their children and to estimate the overall contribution of the perception of barriers on underimmunization among children who are vaccinated in pediatricians’ offices. Methods. As part of a nationwide study on the immunization status of children followed by practicing pediatricians, parents of children who were 8 to 35 months of age and seen consecutively at 177 participating practice sites completed a survey on health beliefs regarding the vaccination process. In addition to demographic information, parents were asked to identify the most difficult thing about obtaining immunizations, as well as their preferences regarding the maximum number of vaccine injections that should be administered to their child at 1 visit and for receiving a needed immunization during an office visit for a mild illness. Immunization data on study children were abstracted from the practice medical record, and specific survey responses for each parent were compared with the immunization status of his or her child at 8 months of age using χ2 tests. For parental health beliefs associated with immunization status by bivariate analyses, the relative risks for underimmunization and population-attributable risk percentages of each belief were calculated after potentially confounding variables were adjusted for. Results. Immunization data were collected on 13 520 children; 13 516 parents responded to at least 1 question regarding vaccination health beliefs. Two thirds of the responding parents indicated that their child should receive no more than 2 immunizations at 1 visit. However, there was no difference in the preferred maximum number of vaccines between parents of children who were fully immunized at 8 months of age and those of underimmunized children. Similarly, there was no difference in a stated preference for receiving a needed immunization during an illness visit. Overall, 74% of respondents indicated that there was “nothing” difficult about obtaining vaccines for their children. The most commonly cited barrier was concern about the side effects of vaccines, identified by 22.6% of parents. However, this barrier was not associated with immunization status. Each of the remaining barriers—including the confusing vaccination schedule, expense of vaccines, the inconvenience of the vaccination process, having a child who was often too ill to receive vaccines, religious objections, and other identified barriers—was statistically associated with immunization status, with adjusted relative risks for underimmunization ranging from 1.42 to 3.04. However, because each of these barriers was identified as important by Conclusions. Parental preferences regarding vaccination practices designed to reduce missed opportunities were not associated with the immunization status of their children. Although several barriers to vaccination were associated with immunization status, individual barriers were identified by a small minority of parents. Overall, parental perceptions of barriers to vaccination do not seem to be a significant cause of underimmunization in this population of children.

Femtosecond pulse generation from a titanium-doped sapphire laser using nonlinear external cavity feedback.

Abstract: A continuous-wave, argon-ion-pumped, titanium-doped sapphire laser has been constructed. Pulses of 80-psec duration obtained through active mode locking have been compressed to less than 800 fsec using nonlinear external cavity feedback.

Implications for the origin of GRB 051103 from LIGO observations

Abstract: We present the results of a LIGO search for gravitational waves (GWs) associated with GRB 051103, a short-duration hard-spectrum gamma-ray burst (GRB) whose electromagnetically determined sky position is coincident with the spiral galaxy M81, which is 3.6 Mpc from Earth. Possible progenitors for short-hard GRBs include compact object mergers and soft gamma repeater (SGR) giant flares. A merger progenitor would produce a characteristic GW signal that should be detectable at a distance of M81, while GW emission from an SGR is not expected to be detectable at that distance. We found no evidence of a GW signal associated with GRB 051103. Assuming weakly beamed γ-ray emission with a jet semi-angle of 30°, we exclude a binary neutron star merger in M81 as the progenitor with a confidence of 98%. Neutron star-black hole mergers are excluded with >99% confidence. If the event occurred in M81, then our findings support the hypothesis that GRB 051103 was due to an SGR giant flare, making it one of the most distant extragalactic magnetars observed to date.

Search for gravitational waves associated with gamma-ray bursts during LIGO science run 6 and Virgo science runs 2 and 3

Abstract: We present the results of a search for gravitational waves associated with 154 gamma-ray bursts (GRBs) that were detected by satellite-based gamma-ray experiments in 2009-2010, during the sixth LIGO science run and the second and third Virgo science runs. We perform two distinct searches: a modeled search for coalescences of either two neutron stars or a neutron star and black hole; and a search for generic, unmodeled gravitational-wave bursts. We find no evidence for gravitational-wave counterparts, either with any individual GRB in this sample or with the population as a whole. For all GRBs we place lower bounds on the distance to the progenitor, under the optimistic assumption of a gravitational-wave emission energy of 10^-2 M c^2 at 150 Hz, with a median limit of 17 Mpc. For short hard GRBs we place exclusion distances on binary neutron star and neutron star-black hole progenitors, using astrophysically motivated priors on the source parameters, with median values of 16 Mpc and 28 Mpc respectively. These distance limits, while significantly larger than for a search that is not aided by GRB satellite observations, are not large enough to expect a coincidence with a GRB. However, projecting these exclusions to the sensitivities of Advanced LIGO and Virgo, which should begin operation in 2015, we find that the detection of gravitational waves associated with GRBs will become quite possible.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Using Multivariate Statistics

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The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Linear Matrix Inequalities in System and Control Theory

Abstract: Preface 1. Introduction Overview A Brief History of LMIs in Control Theory Notes on the Style of the Book Origin of the Book 2. Some Standard Problems Involving LMIs. Linear Matrix Inequalities Some Standard Problems Ellipsoid Algorithm Interior-Point Methods Strict and Nonstrict LMIs Miscellaneous Results on Matrix Inequalities Some LMI Problems with Analytic Solutions 3. Some Matrix Problems. Minimizing Condition Number by Scaling Minimizing Condition Number of a Positive-Definite Matrix Minimizing Norm by Scaling Rescaling a Matrix Positive-Definite Matrix Completion Problems Quadratic Approximation of a Polytopic Norm Ellipsoidal Approximation 4. Linear Differential Inclusions. Differential Inclusions Some Specific LDIs Nonlinear System Analysis via LDIs 5. Analysis of LDIs: State Properties. Quadratic Stability Invariant Ellipsoids 6. Analysis of LDIs: Input/Output Properties. Input-to-State Properties State-to-Output Properties Input-to-Output Properties 7. State-Feedback Synthesis for LDIs. Static State-Feedback Controllers State Properties Input-to-State Properties State-to-Output Properties Input-to-Output Properties Observer-Based Controllers for Nonlinear Systems 8. Lure and Multiplier Methods. Analysis of Lure Systems Integral Quadratic Constraints Multipliers for Systems with Unknown Parameters 9. Systems with Multiplicative Noise. Analysis of Systems with Multiplicative Noise State-Feedback Synthesis 10. Miscellaneous Problems. Optimization over an Affine Family of Linear Systems Analysis of Systems with LTI Perturbations Positive Orthant Stabilizability Linear Systems with Delays Interpolation Problems The Inverse Problem of Optimal Control System Realization Problems Multi-Criterion LQG Nonconvex Multi-Criterion Quadratic Problems Notation List of Acronyms Bibliography Index.