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.

Calculating electron momentum densities and Compton profiles using the linear tetrahedron method

Abstract: A method for computing electron momentum densities and Compton profiles from ab initio calculations is presented. Reciprocal space is divided into optimally-shaped tetrahedra for interpolation, and the linear tetrahedron method is used to obtain the momentum density and its projections such as Compton profiles. Results are presented and evaluated against experimental data for Be, Cu, Ni, Fe3Pt, and YBa2Cu4O8, demonstrating the accuracy of our method in a wide variety of crystal structures.

Multigigabit/s pulse source based on switching of an optical beat signal in a nonlinear fiber loop mirror

Abstract: A novel technique for the generation of a high repetition rate train of transform-limited pulses is demonstrated. A 32 GHz train of 4.2 ps pulses has been generated. >

Previsit Screening for Parental Vaccine Hesitancy: A Cluster Randomized Trial.

Abstract: OBJECTIVE: To evaluate the effect of vaccine hesitancy screening on childhood vaccine uptake. METHODS: We conducted a cluster randomized controlled trial in pediatric primary care clinics in Washington state. Vaccine-hesitant parents (VHPs) with a healthy newborn receiving health supervision at participating clinics were eligible. VHPs were identified by using a 4-item version of the validated Parent Attitudes About Childhood Vaccines Survey (PACV). Before their child’s 2- and 6-month health supervision visits, VHPs at intervention clinics completed the 15-item PACV embedded in a survey containing placebo items. Intervention providers received a summary of parents’ 15-item PACV responses and interpretation of their PACV score; discretion was given to providers regarding how they acted on this information. VHPs at control clinics completed only the placebo survey items, and their child’s provider received a summary of their responses; control providers remained blinded to parent VHP status. Our outcome was child immunization status at 8 months of age expressed as percent of days underimmunized. We compared outcomes in control and intervention participants using t test and linear mixed-effects regression. RESULTS: We enrolled 24 clinics (12 in each arm) and 156 parents (65 in the intervention arm). Parent characteristics were similar across arms except more intervention (versus control) parents had a first-born child (60.9% vs 44%; P = .04). No significant difference in outcome was detected between arms (25.2% [95% confidence interval: 16.0% to 34.5%] vs 19.1% [95% confidence interval: 12.0% to 26.3%] mean days underimmunized in the intervention and control arms, respectively). CONCLUSION: Vaccine hesitancy screening was not significantly associated with days underimmunized.

Development of a Symptom Score for Clinical Studies to Identify Children With a Documented Viral Upper Respiratory Tract Infection

Abstract: The objective of this study was to develop a symptom scoring system for use in clinical studies that differentiates children with cold symptoms who have an identifiable viral etiology for their upper respiratory tract infection (URI) from those in whom no virus is detected. Nasal swabs for PCR testing for identification of respiratory viruses were obtained on children aged 2-11 y at baseline and when parents thought their child was developing a cold. Parental-recorded severity of specific symptoms in children with and without a documented viral URI were compared. Nasal swabs were obtained on 108 children whose parents reported their child was developing a cold. A viral etiology was identified in 62 of 108 (57.4%) samples. Symptom measures that best differentiated children with a viral etiology from those without were significant runny nose and significant cough on days 1-4 of the illness. A URI symptom score was developed based on these symptoms, with a sensitivity of 81.4%, specificity of 61.9%, and accuracy of 73.3%. Parental impression is only a moderately accurate predictor of viral URI in children. Our URI symptom score provided a more accurate method for identifying children with viral URIs for clinical studies.

Duration-tunable picosecond source at 560 nm with watt-level average power.

Abstract: A pulse source at 560 nm that is tunable in duration between 50 ps and 2.7 ns with >1 W of average power and near diffraction-limited beam quality is demonstrated. The source is based on efficient (up to 50%) second-harmonic generation in a periodically poled lithium tantalate crystal of a linearly polarized fiber-integrated Raman amplifier operating at 1120 nm. A duration-tunable ytterbium master-oscillator power-fiber amplifier is used to pulse-pump the Raman amplifier, which is seeded by a continuous-wave distributed-feedback laser diode at 1120 nm. The performance of the system using two different master oscillator schemes is compared. A pulse energy of up to 765 nJ is achieved with a conversion efficiency of 25% from the ytterbium fiber pump, demonstrating a compact and turn-key architecture for obtaining high peak-power radiation at 560 nm.

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.