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.

Watts-level frequency doubling of a narrow line linearly polarized Raman fiber laser to 589nm.

Abstract: A single-mode, linearly polarized, 1118 nm ytterbium fiber laser was applied to pumping of a short fiber length, polarization-maintaining Raman cavity, resulting in a 0.4 nm linewidth, 23 W CW source at 1179 nm. Efficient, single-pass frequency doubling of the Raman source in MgO doped PPLN to 589 nm was demonstrated with CW power levels in excess of 3 W. No beam quality degradation was observed due to photorefraction at pump power densities up to 2 MW/cm2. The proposed approach can be readily extended to Watt-level generation of any desired wavelength in the 560 to 770 nm range.

The influence of provider communication behaviors on parental vaccine acceptance and visit experience

Abstract: Objectives. We investigated how provider vaccine communication behaviors influence parental vaccination acceptance and visit experience.Methods. In a cross-sectional observational study, we videotaped provider–parent vaccine discussions (n = 111). We coded visits for the format providers used for initiating the vaccine discussion (participatory vs presumptive), parental verbal resistance to vaccines after provider initiation (yes vs no), and provider pursuit of recommendations in the face of parental resistance (pursuit vs mitigated or no pursuit). Main outcomes were parental verbal acceptance of recommended vaccines at visit’s end (all vs ≥ 1 refusal) and parental visit experience (highly vs lower rated).Results. In multivariable models, participatory (vs presumptive) initiation formats were associated with decreased odds of accepting all vaccines at visit’s end (adjusted odds ratio [AOR] = 0.04; 95% confidence interval [CI] = 0.01, 0.15) and increased odds of a highly rated visit experience (AOR = 17.3;...

Gamma Radiation from PSR B1055–52

Abstract: The telescopes on the Compton Gamma Ray Observatory (CCRO) have observed PSR B1055-52 a number of times between 1991 and 1998. From these data, a more detailed picture of the gamma radiation from this source has been developed, showing several characteristics which distinguish this pulsar: the light curve is complex; there is no detectable unpulsed emission; the energy spectrum is flat, with no evidence of a sharp high-energy cutoff up to greater than 4 GeV. Comparisons of the gamma-ray data with observations at longer wavelengths show that no two of the known gamma-ray pulsars have quite the same characteristics; this diversity makes interpretation in terms of theoretical models difficult.

The Influence of Provider Behavior, Parental Characteristics, and a Public Policy Initiative on the Immunization Status of Children Followed by Private Pediatricians: A Study From Pediatric Research in Office Settings

Abstract: Objectives. To determine the relative impact of parental characteristics, provider behavior, and the provision of free vaccines through state-sponsored vaccine volume programs (VVPs) on the immunization status of children followed by private pediatricians. Study Design. Retrospective and cross-sectional surveys of immunization data. Setting. The offices of 15 private pediatricians, from 11 states, who were members of the Pediatric Research in Office Settings network. Seven of these physicians used vaccines provided through VVPs. Patients. Children 2 to 3 years old followed by the participating physicians. Methods. The immunization status of children was assessed from two separate samples. For sample 1, immunization data were abstracted from the medical records of 60 consecutive eligible children seen in each office. Parents of the selected children indicated the method of payment for immunizations and the education levels of the mothers. Because this cross-sectional survey might have oversampled frequent health care users, a retrospective chart review of up to 75 randomly selected children in each pediatrician9s practice was also conducted (sample 2). Additional data were collected from the parents of children in sample 2 by telephone interviews. For both samples, patients were considered to be fully immunized if they had received four diphtheria-tetanus-pertussis/diphtheria-tetanus vaccines, three oral poliovirus/inactivated poliovirus vaccines, and one measles-mumps-rubella vaccine before their second birthdays. Before collecting vaccination data, pediatricians completed a survey detailing their immunization beliefs and practices. Logistic regression was used to identify factors that were independently associated with a child being fully immunized. Results. For sample 1, 81.7% of the 857 children surveyed were fully immunized. Practitioner-specific immunization rates varied widely, ranging from 51% to 97%. The immunization rate of children who received vaccines provided by VVPs was similar to that of children whose immunizations were not provided by VVPs (81.2% vs 82.2%; odds ratio [OR] for a VVP as a predictor for being fully immunized, 0.94, 95% confidence interval [CI], 0.66 to 1.32). In addition, parents who paid for immunizations out of pocket were as likely to have fully immunized children as those who had little or no out-of-pocket expenditures for vaccines (OR, 1.13; 95% CI, 0.75 to 1.13). In the logistic model, only individual pediatrician and size of the metropolitan area in which the pediatrician9s practice was located were significant predictors of a child9s immunization status. The results from sample 2 were similar; 82.1% of the 772 surveyed patients were fully immunized. With sample 2, individual pediatrician and age of the child at the time of the survey were the only predictors of immunization status. The OR of a VVP as a predictor of a child being fully immunized was 1.37 (95% CI, 0.65 to 2.90). Conclusions. Individual provider behavior may be the most important determinant of the immunization status of children followed by private pediatricians. In our samples, the effect of parental characteristics was limited. State-sponsored VVPs were not associated with higher immunization rates, perhaps because cost of vaccines did not seem to be a significant barrier to immunization in this population.

Extended blue supercontinuum generation in cascaded holey fibers

Abstract: By combining multiple photonic crystal fibers with sequentially decreasing zero-dispersion wavelengths we have produced a 1.2?W average-power white-light continuum, covering the visible–near-infrared spectrum from 0.44to1.89??m (10?dB width), with an all-fiber picosecond ytterbium pump laser. Wavelengths as short as the ultraviolet (0.35??m), and spectral power densities of more than 2?mW?nm in the blue spectral region, have been generated. The process is understood in terms of optimizing four-wave mixing phase matching to enhance short-wavelength generation.

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.