341 research outputs found
Beyond conventional factorization: Non-Hermitian Hamiltonians with radial oscillator spectrum
The eigenvalue problem of the spherically symmetric oscillator Hamiltonian is
revisited in the context of canonical raising and lowering operators. The
Hamiltonian is then factorized in terms of two not mutually adjoint factorizing
operators which, in turn, give rise to a non-Hermitian radial Hamiltonian. The
set of eigenvalues of this new Hamiltonian is exactly the same as the energy
spectrum of the radial oscillator and the new square-integrable eigenfunctions
are complex Darboux-deformations of the associated Laguerre polynomials.Comment: 13 pages, 7 figure
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Design and Additive Fabrication of Foot and Ankle-Foot Orthoses
Foot and ankle-foot orthoses are prescribed in order to promote mobility through supporting
and/or realigning the lower leg and alleviating pain in the foot in different parts of the gait
cycle. This paper will outline new approaches to the design and manufacture of personalised
foot and ankle-foot orthoses (FO and AFO) using additive fabrication technology. The
research is addressing the need for specific software design tools for orthosis design which
enable their properties to be locally tailored within a mass customisation framework.
Structure/material testing to support that activity is also being undertaken and will be
described.Mechanical Engineerin
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A large-scale validation study of aircraft noise modeling for airport arrivals
In the U.S., the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT) is approved to predict the impacts of aircraft noise and emissions. AEDT's critical role in regulatory compliance and evaluating the environmental impacts of aviation requires asking how accurate are its noise predictions. Previous studies suggest that AEDT's predictions lack desired accuracy. This paper reports on a large-scale study, using 200 000 flight trajectories paired with measured sound levels for arrivals to Runways 28L/28R at San Francisco International Airport, over 12 months. For each flight, two AEDT studies were run, one using the approved mode for regulatory filing and the other using an advanced non-regulatory mode with exact aircraft trajectories. AEDT's per aircraft noise predictions were compared with curated measured sound levels at two locations. On average, AEDT underestimated LAmax by -3.09 dB and SEL by -2.04 dB, combining the results from both AEDT noise-modeling modes. Discrepancies appear to result from limitations in the physical modeling of flight trajectories and noise generation, combined with input data uncertainties (aircraft weight, airspeed, thrust, and lift configuration) and atmospheric conditions
Cardiac troponin I release after a basketball match in elite, amateur and junior players
BACKGROUND:
Available scientific data related to cardiac troponin I (cTnI) release after intermittent exercise is limited. It is also of interest to determine what personal or environmental factors mediate the exercise-induced release of cTnI. This study had two objectives: 1) to examine the individual release of cTnI to a basketball match; and 2) to establish the influence of athlete status as well as biological age on cTnI release.
METHODS:
Thirty-six basketball players (12 adult elite [PBA]: 27.3±4.1 years, 12 adult amateur [ABA]: 29.6±2.9 years, and 12 junior elite [JBA]: 16.6±0.9 years) participated in a simulated basketball match with serial assessment of cTnI at rest, immediately post- and at 1, 3, 6, 12, and 24 h post-exercise.
RESULTS:
The basketball match increased cTnI levels (pre: median [range]; 0.006 [0.001-0.026]; peak post: 0.024 [0.004-0.244] μg/L; p=0.000), with substantial individual variability in peak values. PBA and JBA players showed higher baseline and post-exercise cTnI values than ABA (all p<0.05). Peak cTnI exceeded the upper reference limit (URL) in the 26% of players (3 PBA; 6 JBA).
CONCLUSIONS:
The current results suggest that intermittent exercise can promote the appearance of cTnI and that this is potentially mediated by athlete status
Visual 3-D SLAM from UAVs
The aim of the paper is to present, test and discuss the implementation of Visual SLAM techniques to images taken from Unmanned Aerial Vehicles (UAVs) outdoors, in partially structured environments. Every issue of the whole process is discussed in order to obtain more accurate localization and mapping from UAVs flights. Firstly, the issues related to the visual features of objects in the scene, their distance to the UAV, and the related image acquisition system and their calibration are evaluated for improving the whole process. Other important, considered issues are related to the image processing techniques, such as interest point detection, the matching procedure and the scaling factor. The whole system has been tested using the COLIBRI mini UAV in partially structured environments. The results that have been obtained for localization, tested against the GPS information of the flights, show that Visual SLAM delivers reliable localization and mapping that makes it suitable for some outdoors applications when flying UAVs
Non-existence of stationary two-black-hole configurations: The degenerate case
In a preceding paper we examined the question whether the spin-spin repulsion
and the gravitational attraction of two aligned sub-extremal black holes can
balance each other. Based on the solution of a boundary value problem for two
separate (Killing-) horizons and a novel black hole criterion we were able to
prove the non-existence of the equilibrium configuration in question. In this
paper we extend the non-existence proof to extremal black holes.Comment: 18 pages, 2 figure
Mfingerprint: Privacy-preserving user modeling with multimodal mobile device footprints
Abstract. The dramatic increase of daily usage of mobile devices generates massive digital footprints of users. Such footprints come from physical sensing such as GPS, WiFi, and Bluetooth, as well as social behavior sensing, e.g., call logs, application usage, etc. Many existing studies apply the mobile device footprints to infer daily activities like sitting/standing and social contexts such as personality traits and emotional states. In this paper, we propose a different approach to explore multimodal mobile footprints and build a novel user modeling framework called mFingerprint that can effectively and uniquely depict users. mFingerprint does not expose raw sensitive information from mobile device, e.g., the exact location, WiFi access points, or apps installed, but computes privacy-preserving statistical features to model the user discriminatively. These descriptive features protect sensitive information, thus can be shared, transmitted, and reused with less privacy concerns. By testing on 22 users' mobile phone data collected over 2 months, we demonstrate the effectiveness of mFingerprint in user modeling and identification. In particular, our conditional entropy footprint statistics can achieve 81% accuracy across all 22 users while evaluating over 10-day intervals
Mfingerprint: Privacy-preserving user modeling with multimodal mobile device footprints
Abstract. Mobile devices collect a variety of information about their environments, recording "digital footprints" about the locations and activities of their human owners. These footprints come from physical sensors such as GPS, WiFi, and Bluetooth, as well as social behavior logs like phone calls, application usage, etc. Existing studies analyze mobile device footprints to infer daily activities like driving/running/walking, etc. and social contexts such as personality traits and emotional states. In this paper, we propose a different approach that uses multimodal mobile sensor and log data to build a novel user modeling framework called mFingerprint that can effectively and uniquely depict users. mFingerprint does not expose raw sensitive information from the mobile device, e.g., the exact location, WiFi access points, or apps installed, but computes privacy-preserving statistical features to model the user. These descriptive features obscure sensitive information, and thus can be shared, transmitted, and reused with fewer privacy concerns. By testing on 22 users' mobile phone data collected over 2 months, we demonstrate the effectiveness of mFingerprint in user modeling and identification, with our proposed statistics achieving 81% accuracy across 22 users over 10-day intervals
Adopting sustainability competence-based education in academic disciplines: Insights from 13 higher education institutions
Higher Education Institutions (HEIs) have been incorporating sustainability into education and curricula, where recent research has focussed on sustainability competences, pedagogical approaches, and how to connect them, generally on a single HEI. The process of integrating sustainability into education based on curricula assessment has been explained using adoption of innovations; and has the potential to explain the process of developing competences through pedagogical approaches. The aim of this paper is to investigate this process at academic discipline level. An online survey was developed to investigate teaching sustainability competences in 13 HEIs, from which 678 responses from educators were obtained. The competences and pedagogical approaches from the responses were ranked, and then the connections between the competences and pedagogical approaches per discipline were analysed using a correlations-based framework, from which three disciplines groups were created. The groups were categorised using diffusion of innovations theory, which indicated that some disciplines are more innovative than others in adopting sustainability competence-based teaching. The results are used to propose two frameworks to better understand the adoption of sustainability competence-based teaching: (a) the D-RAPID framework; and (b) the Disciplinary Multi-dimensional Sustainability Influence Change for Academia (D-MuSICA) memework. The adoption of sustainability competence-base education must expand from a single HEI perspective to a disciplinary collaborative one spanning many HEIs, where academic disciplines should learn from each other''s insights and mistakes and provide students with more transdisciplinary skillsets to make societies more sustainable. © 2021 The Authors. Sustainable Development published by ERP Environment and John Wiley & Sons Ltd
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