Hybrid statistical and mechanistic mathematical model guides mobile health intervention for chronic pain

Nearly a quarter of visits to the Emergency Department are for conditions that could have been managed via outpatient treatment; improvements that allow patients to quickly recognize and receive appropriate treatment are crucial. The growing popularity of mobile technology creates new opportunities for real-time adaptive medical intervention, and the simultaneous growth of big data sources allows for preparation of personalized recommendations. Here we focus on the reduction of chronic suffering in the sickle cell disease community. Sickle cell disease is a chronic blood disorder in which pain is the most frequent complication. There currently is no standard algorithm or analytical method for real-time adaptive treatment recommendations for pain. Furthermore, current state-of-the-art methods have difficulty in handling continuous-time decision optimization using big data. Facing these challenges, in this study we aim to develop new mathematical tools for incorporating mobile technology into personalized treatment plans for pain. We present a new hybrid model for the dynamics of subjective pain that consists of a dynamical systems approach using differential equations to predict future pain levels, as well as a statistical approach tying system parameters to patient data (both personal characteristics and medication response history). Pilot testing of our approach suggests that it has significant potential to predict pain dynamics given patients' reported pain levels and medication usages. With more abundant data, our hybrid approach should allow physicians to make personalized, data driven recommendations for treating chronic pain.Comment: 13 pages, 15 figures, 5 table

pgm: A Python package for free energy calculations within the phonon gas model

The quasi-harmonic approximation (QHA) is a powerful method that uses the volume dependence of non-interacting phonons to compute the free energy of materials at high pressures (P) and temperatures (T). However, anharmonicity, electronic excitations in metals, or both, introduce an intrinsic T-dependence on phonon frequencies, rendering the QHA inadequate. Here we present a Python code, pgm, to compute the free energy and thermodynamic property within the phonon gas model (PGM) that uses T-dependent phonon quasiparticle frequencies. In this case, the vibrational contribution to the Helmholtz free energy is obtained by integrating the vibrational entropy, which can be readily calculated for a system of phonon quasiparticles. Other thermodynamic properties are then obtained from standard thermodynamic relations. We demonstrate the successful applications of pgm to two cases of geophysical significance: cubic CaSiO3-perovskite (cCaPv), a strongly anharmonic insulator and the third most abundant phase of the Earth's lower mantle, and NiAs-type (B8) FeO, a partially covalent-metallic system. This is the oxide endmember of a recently discovered iron-rich Fe$_n$O alloy phase likely to exit in the Earth's inner core.Comment: 26 pages, 9 figures, 5 table

Perovskite quantum dot topological laser

Various topological laser concepts have recently enabled the demonstration of robust light-emitting devices that are immune to structural deformations and tolerant to fabrication imperfections. Current realizations of photonic cavities with topological boundaries are often limited by outcoupling issues or poor directionality and require complex design and fabrication that hinder operation at small wavelengths. Here we propose a topological cavity design based on interface states between two one-dimensional photonic crystals with distinct Zak phases and demonstrate a lithography-free, single-mode perovskite laser emitting in the green. Few monolayers of solution processed all-inorganic cesium lead halide perovskite quantum dots are used as ultrathin gain medium. The topological laser has planar design with large output aperture, akin to vertical-cavity surface-emitting lasers (VCSELs) and is robust against variations of the thickness of the gain medium, from deeply subwavelength to thick quantum dot films. This experimental observation also unveils the topological nature of VCSELs, that is usually overlooked in the description of conventional Fabry-Perot cavity lasers. The design simplicity and topological characteristics make this perovskite quantum dot laser architecture suitable for low-cost and fabrication tolerant vertical emitting lasers operating across the visible spectral region

Ray-Space Epipolar Geometry for Light Field Cameras

Light field essentially represents rays in space. The epipolar geometry between two light fields is an important relationship that captures ray-ray correspondences and relative configuration of two views. Unfortunately, so far little work has been done in deriving a formal epipolar geometry model that is specifically tailored for light field cameras. This is primarily due to the high-dimensional nature of the ray sampling process with a light field camera. This paper fills in this gap by developing a novel ray-space epipolar geometry which intrinsically encapsulates the complete projective relationship between two light fields, while the generalized epipolar geometry which describes relationship of normalized light fields is the specialization of the proposed model to calibrated cameras. With Plecker parameterization, we propose the ray-space projection model involving a 6 6 ray-space intrinsic matrix for ray sampling of light field camera. Ray-space fundamental matrix and its properties are then derived to constrain ray-ray correspondences for general and special motions. Finally, based on ray-space epipolar geometry, we present two novel algorithms, one for fundamental matrix estimation, and the other for calibration. Experiments on synthetic and real data have validated the effectiveness of ray-space epipolar geometry in solving 3D computer vision tasks with light field cameras.Qi Zhang is also sponsored by Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University under CX201919 and China Scholarship Council (CSC)

Noninvasive Monitoring of Vital Signs Based on Highly Sensitive Fiber Optic Mattress

A smart mattress based on optical fiber Mach-zender interferometer (OF-MZI) is designed for noninvasive and continuous monitoring of human vital signs. Through arranging the sensing fiber between two elastic covering layers with sandwich structure, the mattress was sensitive to the respiration and heartbeat induced micro-pressure. In the processing terminal, the waveforms of vital signs were demodulated by 3 *3 coupler based differentiate and cross-multiplying method, and then four characteristic indicators including the heart rate, heartbeat amplitude, respiration rate, and respiration amplitude were respectively extracted through feature extraction algorithm, for evaluating the human health condition. Clinical experimental results of eighteen subjects indicate that the mattress system could not only distinguish the activity states of no body, on bed, body movement and off bed, but also contribute to clinical diagnosis of bradycardia, tachycardia, polypnea and apnoea. By adopting Bland–Altman analysis method, good reproducibility and accuracy were confirmed, where the max errors of heart rate and respiration rate are respectively 2 bpm and 1 bpm. Moreover, the responses at different positions of the mattress are identical and the continuous monitoring results in one day are consistent with daily change of vital signs, which proves that the fiber optic mattress has good reliability and stability. Beneficial from high-sensitivity, multiple parameters, long-term continuous monitoring, high comfortability and low cost, the mattress is promising in the early detection and prevention of cardiac and respiratory diseases as a household medical device