A5057398160- Stellar, planetary, and galactic studies
- Astro and Planetary Science
- Astronomy and Astrophysical Research
- Astrophysics and Star Formation Studies
- Nutrition and Health in Aging
- Trauma and Emergency Care Studies
- Magnetic confinement fusion research
- Gamma-ray bursts and supernovae
- Parallel Computing and Optimization Techniques
- Body Composition Measurement Techniques
- Gas Dynamics and Kinetic Theory
- Enhanced Recovery After Surgery
- Superconducting Materials and Applications
- Adversarial Robustness in Machine Learning
- Frailty in Older Adults
- Anomaly Detection Techniques and Applications
- Advanced Neural Network Applications
- Cardiovascular and exercise physiology
- Cancer survivorship and care
Drexel University
2019-2023
Versus Arthritis
2023
University of Nottingham
2023
Royal Derby Hospital
2023
Medical Research Council
2023
Lockheed Martin (United States)
2022
Abstract Feedback from massive stars plays an important role in the formation of star clusters. Whether a very is born early or late cluster timeline has profound implications for and assembly processes. We carry out controlled experiment to characterize effects early-forming on formation. use software suite Torch , combining self-gravitating magnetohydrodynamics, ray-tracing radiative transfer, N -body dynamics, stellar feedback, model four initially identical 10 4 M ⊙ giant molecular...
The fraction of stars in binary systems within star clusters is important for their evolution, but what proportion binaries form by dynamical processes after initial stellar accretion remains unknown. In previous work, we showed that interactions alone produced too few low-mass compared to observations. We therefore implement an population the coupled MHD and direct N-body cluster formation code Torch. compare simulations with, without, populations follow evolution both sets simulations,...
We describe a star cluster formation model that includes individual from self-gravitating, magnetized gas, coupled to collisional stellar dynamics. The uses the Astrophysical Multi-purpose Software Environment (AMUSE) integrate an adaptive-mesh magnetohydrodynamics code (FLASH) with fourth order Hermite N-body (ph4), evolution (SeBa), and method for resolving binary (multiples). This combination yields unique simulations allow us study binaries formed dynamically interactions both other...
Understanding the formation of stellar clusters requires following interplay between gas and newly formed stars accurately. We therefore couple magnetohydrodynamics code FLASH to N-body ph4 evolution SeBa using Astrophysical Multipurpose Software Environment (AMUSE) model dynamics, evolution, collisional dynamics binary higher-order multiple systems, while implementing feedback in form radiation, winds supernovae FLASH. here describe algorithms used for each these processes. denote this...
Cardiorespiratory fitness (CRF) declines with advancing and has also, independent of age, been shown to be predictive all-cause mortality, morbidity, poor clinical outcomes. In relation the older patient, there is a particular wealth evidence highlighting relationship between low CRF surgical Cardiopulmonary exercise testing (CPET) accepted as gold-standard measure CRF. However, this form assessment significant personnel equipment demands not feasible for those certain age-associated...
Feedback from massive stars plays an important role in the formation of star clusters. Whether a very is born early or late cluster timeline has profound implications for and assembly processes. We carry out controlled experiment to characterize effects early-forming on formation. use software suite \texttt{Torch}, combining self-gravitating magnetohydrodynamics, ray-tracing radiative transfer, $N$-body dynamics, stellar feedback model four initially identical $10^4$ M$_\odot$ giant...
With the ever-growing quantity of information generated by commercial and intelligence platforms, it is imperative that community moves toward solutions provide not just automated outputs, but a more accurate explanation into why outputs are predicted. Automated Target Recognition (ATR) rely on deep learning being leveraged to derive automatically, these networks can produce incorrect answers in some circumstances, reducing user trust. Most analysts cautiously trust results, they typically...
Abstract Background Since the publication of Emergency General Surgery Commissioning Guide by ASGBI in 2014, there has been a drive to develop ambulatory pathways for acute surgical patients, saving inpatient stays and reducing risk hospital-acquired infections. Many units, like ours, had large workload increased seeing next day returns as well presentations. In October 2020 an Institute was formed who developed pathway ameliorate some these issues provide point contact primary care...