Report for passive data acquired in the 1998-1999 Los Angeles Region Seismic Experiment II: a transect from Santa Monica Bay to the Westernmost Mojave Desert

Between October, 1998 and April, 1999, 83 seismic stations were installed in the greater western Los Angeles, California area to record teleseismic, regional, and local earthquakes. The near-linear 93-km long array extended between Santa Monica Bay and the western Mojave Desert, through the epicentral region of the Northridge earthquake. The goals of the experiment were to determine crustal thickness below the western Transverse Ranges, San Fernando Valley basin, and western Mojave Desert, measure anistropy along the line with special emphasis on the San Andreas fault region, evaluate the potential for future strong ground shaking at sites in the basins, and determine the kinematic relationship between crustal and uppermost mantle deformation by three-dimensional tomographic inversion using regional network data combined with the array data. The stations consisted of three-component, broadband and short-period seismometers, and timing was controlled by Global Positioning System (GPS) receivers. The array recorded 165 Gb of raw waveform data in continuous (25 sps) and triggered (50 sps) streams. Approximately 144 teleseismic earthquakes with magnitudes ≥ 5.5, and 2025 local earthquakes with magnitude ≥ 2.0 were recorded. Preliminary results from three-dimensional teleseismic traveltime inversion tomography indicate that uppermost mantle seismic anomalies strongly correlate with thickened crust in the Transverse Ranges suggesting that the width of the compressional region and convergence rate control the location of deformation more than the San Andreas shear zone does

Optimal Choice of Sample Substrate and Laser Wavelength for Raman Spectroscopic Analysis of Biological Specimen

Raman spectroscopy is an optical technique based on the inelastic scattering of monochromatic light that can be used to identify the biomolecular composition of biological cells and tissues. It can be used as both an aid for understanding the etiology of disease and for accurate clinical diagnostics when combined with multivariate statistical algorithms. This method is nondestructive,potentially non-invasive and can be applied in vitro or in vivo directly or via a fiber optic probe. However, there exists a high degree of variability across experimental protocols, some of which result in large background signals that can often overpower the weak Raman signals being emitted. These protocols need to be standardised before the technique can provide reliable and reproducible experimental results in an everyday clinical environment. The objective of this study is to investigate the impact of different experimental parameters involved in the analysis of biological specimen. We investigate the Raman signals generated from healthy human cheek cells using different source laser wavelengths; 473 nm, 532 nm, 660 nm, 785 nm and 830 nm, and different sample substrates; Raman-grade calcium fluoride, IR polished calcium fluoride, magnesium fluoride, aluminium (100 nm and 1500 nm thin films on glass), glass, fused silica, potassium bromide, sodium chloride and zinc selenide, whilst maintaining all other experimental parameters constant throughout the study insofar as possible

Factors affecting pathways to care for children and adolescents with complex vascular malformations: Parental perspectives

BACKGROUND: Complex vascular malformations (VMs) are rare disorders that can cause pain, coagulopathy, disfigurement, asymmetric growth, and disability. Patients with complex VMs experience misdiagnosis, delayed diagnosis, delayed or inappropriate treatments, and worsened health. Given the potential consequences of delaying expert care, we must identify the factors that impede or facilitate this access to care. RESULTS: We performed semi-structured interviews with 24 parents (21 mothers; 3 fathers; median age = 42.5 years) of children with complex VMs and overgrowth disorders living in the US, recruited through two patient advocacy groups - CLOVES Syndrome Community, and Klippel-Trenaunay Support Group. We performed thematic analysis to assess parental perspectives on barriers and facilitators to accessing expert care. We identified 11 factors, representing 6 overarching themes, affecting families\u27 ability to access and maintain effective care for their child: individual characteristics (clinician behaviors and characteristics, parent behaviors and characteristics), health care system (availability of specialist multidisciplinary teams, care coordination and logistics, insurance and financial issues, treatments and services), clinical characteristics (accuracy and timing of diagnosis, features of clinical presentation), social support networks, scientific progress, and luck and privilege. Additionally, access to information about VMs and VM care was a crosscutting theme affecting each of these factors. These factors influenced both the initial access to care and the ongoing maintenance of care for children with VMs. CONCLUSION: Parents of children with VMs report multiple factors that facilitate or impede their ability to provide their child with optimal care. These factors represent possible targets for future interventions to improve care delivery for families affected by VMs

Fast and Accurate Tactile Object Recognition using a Random Convolutional Kernel Transform

The task of tactile object recognition is an ever-evolving research area comprising of the gathering and processing of features related to the physical interaction between a robotic system and an object or material. For a robotic system to be capable of interacting with the real-world, the ability to identify the object it is interacting with in real-time is required. Information about the object is often strongly enhanced using tactile sensing. Recent advancements in time series classifiers have allowed for the accuracy of real-time tactile object recognition to be improved, therefore generating opportunities for enhanced solutions within this field of robotics. In this paper, improvements are proposed to the state-of-the-art time series classifier ROCKET for analysis of tactile data for the purposes of object recognition. A variety of classifier heads are implemented within the ROCKET pipeline; these models are then trained and tested on the PHAC-2 tactile dataset, achieving state-of-the-art performance of 96.3% for single-modality tactile object recognition while only requiring 11 minutes to train