Another derivation of the geometrical KPZ relations

We give a physicist's derivation of the geometrical (in the spirit of Duplantier-Sheffield) KPZ relations, via heat kernel methods. It gives a covariant way to define neighborhoods of fractals in 2d quantum gravity, and shows that these relations are in the realm of conformal field theory

Refitting successful daily wear GP patients into thirty day continuous wear gas permeable lenses: A case series

Current rigid gas permeable lens wearers were refit into the thirty day continuous wear Menicon Z gas permeable lens. The purpose of the study was to evaluate how the subjects transitioned to the new Menicon Z lenses and the thirty day wearing schedule. Subjects were monitored for two months for an ocular health changes by assessing visual acuity, performing biomicroscopy and lens fit evaluation, and corneal topography

Extending Bauer's corollary to fractional derivatives

We comment on the method of Dreisigmeyer and Young [D. W. Dreisigmeyer and P. M. Young, J. Phys. A \textbf{36}, 8297, (2003)] to model nonconservative systems with fractional derivatives. It was previously hoped that using fractional derivatives in an action would allow us to derive a single retarded equation of motion using a variational principle. It is proven that, under certain reasonable assumptions, the method of Dreisigmeyer and Young fails.Comment: Accepted Journal of Physics A at www.iop.org/EJ/journal/JPhys

Nonconservative Lagrangian mechanics II: purely causal equations of motion

This work builds on the Volterra series formalism presented in [D. W. Dreisigmeyer and P. M. Young, J. Phys. A \textbf{36}, 8297, (2003)] to model nonconservative systems. Here we treat Lagrangians and actions as `time dependent' Volterra series. We present a new family of kernels to be used in these Volterra series that allow us to derive a single retarded equation of motion using a variational principle

Syzygies of torsion bundles and the geometry of the level l modular variety over M_g

We formulate, and in some cases prove, three statements concerning the purity or, more generally the naturality of the resolution of various rings one can attach to a generic curve of genus g and a torsion point of order l in its Jacobian. These statements can be viewed an analogues of Green's Conjecture and we verify them computationally for bounded genus. We then compute the cohomology class of the corresponding non-vanishing locus in the moduli space R_{g,l} of twisted level l curves of genus g and use this to derive results about the birational geometry of R_{g, l}. For instance, we prove that R_{g,3} is a variety of general type when g>11 and the Kodaira dimension of R_{11,3} is greater than or equal to 19. In the last section we explain probabilistically the unexpected failure of the Prym-Green conjecture in genus 8 and level 2.Comment: 35 pages, appeared in Invent Math. We correct an inaccuracy in the statement of Prop 2.

Confluence of geodesic paths and separating loops in large planar quadrangulations

We consider planar quadrangulations with three marked vertices and discuss the geometry of triangles made of three geodesic paths joining them. We also study the geometry of minimal separating loops, i.e. paths of minimal length among all closed paths passing by one of the three vertices and separating the two others in the quadrangulation. We concentrate on the universal scaling limit of large quadrangulations, also known as the Brownian map, where pairs of geodesic paths or minimal separating loops have common parts of non-zero macroscopic length. This is the phenomenon of confluence, which distinguishes the geometry of random quadrangulations from that of smooth surfaces. We characterize the universal probability distribution for the lengths of these common parts.Comment: 48 pages, 33 color figures. Final version, with one concluding paragraph and one reference added, and several other small correction

Validation of machine learning-based assessment of major depressive disorder from paralinguistic speech characteristics in routine care

New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from telephone-based clinical interviews with 267 individuals in routine care. With this data, we trained and evaluated a machine learning system to identify the absence/presence of a MDD diagnosis (as assessed with the Structured Clinical Interview for DSM-IV) from paralinguistic speech characteristics. Our system classified diagnostic status of MDD with an accuracy of 66% (sensitivity: 70%, specificity: 62%). Permutation tests indicated that the machine learning system classified MDD significantly better than chance. However, deriving diagnoses from cut-off scores of common depression scales was superior to the machine learning system with an accuracy of 73% for the Hamilton Rating Scale for Depression (HRSD), 74% for the Quick Inventory of Depressive Symptomatology–Clinician version (QIDS-C), and 73% for the depression module of the Patient Health Questionnaire (PHQ-9). Moreover, training a machine learning system that incorporated both speech analysis and depression scales resulted in accuracies between 73 and 76%. Thus, while findings of the present study demonstrate that automated speech analysis shows the potential of identifying patterns of depressed speech, it does not substantially improve the validity of classifications from common depression scales. In conclusion, speech analysis may not yet be able to replace common depression scales in clinical practice, since it cannot yet provide the necessary accuracy in depression detection. This trial is registered with DRKS00023670

Development and evaluation of a computer-based medical work assessment programme

Background: There are several ways to conduct a job task analysis in medical work environments including pencil-paper observations, interviews and questionnaires. However these methods implicate bias problems such as high inter-individual deviations and risks of misjudgement. Computer-based observation helps to reduce these problems. The aim of this paper is to give an overview of the development process of a computer-based job task analysis instrument for real-time observations to quantify the job tasks performed by physicians working in different medical settings. In addition reliability and validity data of this instrument will be demonstrated. Methods: This instrument was developed in consequential steps. First, lists comprising tasks performed by physicians in different care settings were classified. Afterwards content validity of task lists was proved. After establishing the final task categories, computer software was programmed and implemented in a mobile personal computer. At least inter-observer reliability was evaluated. Two trained observers recorded simultaneously tasks of the same physician. Results: Content validity of the task lists was confirmed by observations and experienced specialists of each medical area. Development process of the job task analysis instrument was completed successfully. Simultaneous records showed adequate interrater reliability. Conclusion: Initial results of this analysis supported the validity and reliability of this developed method for assessing physicians' working routines as well as organizational context factors. Based on results using this method, possible improvements for health professionals' work organisation can be identified