Topological descriptors for 3D surface analysis

We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D surface reconstructions we compute persistence diagrams for a 2D cubical filtration. In the next step we investigate different topological descriptors and measure their ability to discriminate structurally different 3D surface patches. We evaluate their sensitivity to different parameters and compare the performance of the resulting topological descriptors to alternative (non-topological) descriptors. We present a comprehensive evaluation that shows that topological descriptors are (i) robust, (ii) yield state-of-the-art performance for the task of 3D surface analysis and (iii) improve classification performance when combined with non-topological descriptors.Comment: 12 pages, 3 figures, CTIC 201

Characterization of Silicon Crystals Grown from Melt in a Granulate Crucible

The growth of silicon crystals from a melt contained in a granulate crucible significantly differs from the classical growth techniques because of the granulate feedstock and the continuous growth process. We performed a systematic study of impurities and structural defects in several such crystals with diameters up to 60 mm. The possible origin of various defects is discussed and attributed to feedstock (concentration of transition metals), growth setup (carbon concentration), or growth process (dislocation density), showing the potential for further optimization. A distinct correlation between crystal defects and bulk carrier lifetime is observed. A bulk carrier lifetime with values up to 600 μs on passivated surfaces of dislocation-free parts of the crystal is currently achieved

First Light Measurements of Capella with the Low Energy Transmission Grating Spectrometer aboard the Chandra X-ray Observatory

We present the first X-ray spectrum obtained by the Low Energy Transmission Grating Spectrometer (LETGS) aboard the Chandra X-ray Observatory. The spectrum is of Capella and covers a wavelength range of 5-175 A (2.5-0.07 keV). The measured wavelength resolution, which is in good agreement with ground calibration, is $\Delta \lambda \simeq$ 0.06 A (FWHM). Although in-flight calibration of the LETGS is in progress, the high spectral resolution and unique wavelength coverage of the LETGS are well demonstrated by the results from Capella, a coronal source rich in spectral emission lines. While the primary purpose of this letter is to demonstrate the spectroscopic potential of the LETGS, we also briefly present some preliminary astrophysical results. We discuss plasma parameters derived from line ratios in narrow spectral bands, such as the electron density diagnostics of the He-like triplets of carbon, nitrogen, and oxygen, as well as resonance scattering of the strong Fe XVII line at 15.014 A.Comment: 4 pages (ApJ letter LaTeX), 2 PostScript figures, accepted for publication in ApJ Letters, 200

Impact of COVID-19 social-distancing on sleep timing and duration during a university semester

Social-distancing directives to contain community transmission of the COVID-19 virus can be expected to affect sleep timing, duration or quality. Remote work or school may increase time available for sleep, with benefits for immune function and mental health, particularly in those individuals who obtain less sleep than age-adjusted recommendations. Young adults are thought to regularly carry significant sleep debt related in part to misalignment between endogenous circadian clock time and social time. We examined the impact of social-distancing measures on sleep in young adults by comparing sleep self-studies submitted by students enrolled in a university course during the 2020 summer session (entirely remote instruction, N = 80) with self-studies submitted by students enrolled in the same course during previous summer semesters (on-campus instruction, N = 452; cross-sectional study design). Self-studies included 2–8 week sleep diaries, two chronotype questionnaires, written reports, and sleep tracker (Fitbit) data from a subsample. Students in the 2020 remote instruction semester slept later, less efficiently, less at night and more in the day, but did not sleep more overall despite online, asynchronous classes and ~44% fewer work days compared to students in previous summers. Subjectively, the net impact on sleep was judged as positive or negative in equal numbers of students, with students identifying as evening types significantly more likely to report a positive impact, and morning types a negative impact. Several features of the data suggest that the average amount of sleep reported by students in this summer course, historically and during the 2020 remote school semester, represents a homeostatic balance, rather than a chronic deficit. Regardless of the interpretation, the results provide additional evidence that social-distancing measures affect sleep in heterogeneous ways.Science, Faculty ofNon UBCPsychiatry, Department ofReviewedFacultyGraduat