4,626 research outputs found
Estimating the Spectrum in Computed Tomography Via Kullback–Leibler Divergence Constrained Optimization
Purpose
We study the problem of spectrum estimation from transmission data of a known phantom. The goal is to reconstruct an x‐ray spectrum that can accurately model the x‐ray transmission curves and reflects a realistic shape of the typical energy spectra of the CT system. Methods
Spectrum estimation is posed as an optimization problem with x‐ray spectrum as unknown variables, and a Kullback–Leibler (KL)‐divergence constraint is employed to incorporate prior knowledge of the spectrum and enhance numerical stability of the estimation process. The formulated constrained optimization problem is convex and can be solved efficiently by use of the exponentiated‐gradient (EG) algorithm. We demonstrate the effectiveness of the proposed approach on the simulated and experimental data. The comparison to the expectation–maximization (EM) method is also discussed. Results
In simulations, the proposed algorithm is seen to yield x‐ray spectra that closely match the ground truth and represent the attenuation process of x‐ray photons in materials, both included and not included in the estimation process. In experiments, the calculated transmission curve is in good agreement with the measured transmission curve, and the estimated spectra exhibits physically realistic looking shapes. The results further show the comparable performance between the proposed optimization‐based approach and EM. Conclusions
Our formulation of a constrained optimization provides an interpretable and flexible framework for spectrum estimation. Moreover, a KL‐divergence constraint can include a prior spectrum and appears to capture important features of x‐ray spectrum, allowing accurate and robust estimation of x‐ray spectrum in CT imaging
Updated clinical recommendations for the use of tibolone in Asian women
Tibolone, which is indicated for the relief of climacteric symptoms and the prevention of osteoporosis in postmenopausal women, has a tissue-specific mode of action different to that of conventional hormone replacement therapy (HRT). A large proportion of Asian postmenopausal women experience symptoms that most frequently include musculoskeletal pain, insomnia, forgetfulness, hot flushes and sexual dysfunction, and there is a need to address their specific requirements. Recent studies show that, in comparison to HRT, tibolone is as effective in alleviating menopausal symptoms and preventing bone loss, has a greater positive effect on sexual dysfunction and is associated with less vaginal bleeding, but it is rarely mentioned in guidelines for menopausal treatment. Levels of awareness amongst women about treatments for menopausal symptoms vary between Asian countries but, even in countries where awareness is high, HRT usage is much lower than in the West. To provide a practical approach to the use of tibolone in Asian postmenopausal women, a panel of experts in the management of menopause from 11 Asia Pacific countries has developed recommendations for its use, based on the evidence from clinical studies published since 2005. However, as much of the clinical data reviewed are from international studies, the recommendations and the treatment algorithm presented here are widely applicable
The ALMaQUEST Survey - V. The non-universality of kpc-scale star formation relations and the factors that drive them
ABSTRACT
Using a sample of ∼15 000 kpc-scale star-forming spaxels in 28 galaxies drawn from the ALMA-MaNGA QUEnching and STar formation (ALMaQUEST) survey, we investigate the galaxy-to-galaxy variation of the ‘resolved’ Schmidt–Kennicutt relation (rSK; –ΣSFR), the ‘resolved’ star-forming main sequence (rSFMS; Σ⋆–ΣSFR), and the ‘resolved’ molecular gas main sequence (rMGMS; Σ⋆–). The rSK relation, rSFMS, and rMGMS all show significant galaxy-to-galaxy variation in both shape and normalization, indicating that none of these relations is universal between galaxies. The rSFMS shows the largest galaxy-to-galaxy variation and the rMGMS the least. By defining an ‘offset’ from the average relations, we compute a ΔrSK, ΔrSFMS, ΔrMGMS for each galaxy, to investigate correlations with global properties. We find the following correlations with at least 2σ significance: The rSK is lower (i.e. lower star formation efficiency) in galaxies with higher M⋆, larger Sersic index, and lower specific SFR (sSFR); the rSFMS is lower (i.e. lower sSFR) in galaxies with higher M⋆ and larger Sersic index; and the rMGMS is lower (i.e. lower gas fraction) in galaxies with lower sSFR. In the ensemble of all 15 000 data points, the rSK relation and rMGMS show equally tight scatters and strong correlation coefficients, compared with a larger scatter and weaker correlation in the rSFMS. Moreover, whilst there is no correlation between ΔrSK and ΔrMGMS in the sample, the offset of a galaxy’s rSFMS does correlate with both of the other two offsets. Our results therefore indicate that the rSK and rMGMS are independent relations, whereas the rSFMS is a result of their combination.ERC
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The ALMaQUEST survey IX: The nature of the resolved star forming main sequence
We investigate the nature of the scaling relations between the surface
density of star formation rate (), stellar mass (), and molecular gas mass (), aiming at distinguishing
between the relations that are primary, i.e. more fundamental, and those which
are instead an indirect by-product of the other relations. We use the ALMaQUEST
survey and analyse the data by using both partial correlations and Random
Forest regression techniques. We unambiguously find that the strongest
intrinsic correlation is between and
(i.e. the resolved Schmidt-Kennicutt relation), followed by the correlation
between and (resolved Molecular Gas Main
Sequence, rMGMS). Once these two correlations are taken into account, we find
that there is no evidence for any intrinsic correlation between and , implying that SFR is entirely driven by the amount of
molecular gas, while its dependence on stellar mass (i.e. the resolved Star
Forming Main Sequence, rSFMS) simply emerges as a consequence of the
relationship between molecular gas and stellar mass.Science and Technology Facilities Council (STFC).
ERC Advanced Grant 695671 "QUENCH"
Vision-Based Autonomous Driving: A Model Learning Approach
We present an integrated approach for perception and control for an
autonomous vehicle and demonstrate this approach in a high-fidelity urban
driving simulator. Our approach first builds a model for the environment, then
trains a policy exploiting the learned model to identify the action to take at
each time-step. To build a model for the environment, we leverage several deep
learning algorithms. To that end, first we train a variational autoencoder to
encode the input image into an abstract latent representation. We then utilize
a recurrent neural network to predict the latent representation of the next
frame and handle temporal information. Finally, we utilize an
evolutionary-based reinforcement learning algorithm to train a controller based
on these latent representations to identify the action to take. We evaluate our
approach in CARLA, a high-fidelity urban driving simulator, and conduct an
extensive generalization study. Our results demonstrate that our approach
outperforms several previously reported approaches in terms of the percentage
of successfully completed episodes for a lane keeping task.Comment:
Developed graphene/Si Schottky junction solar cells based on the top-window structure
Chemical Vapor Deposition (CVD)-graphene has potentially been integrated with silicon (Si) substrates for developing graphene/n-Si Schottky junction solar cells prepared with the top window structure. However, there are drawbacks to prepared devices such as complex silicon dioxide (SiO2)-etching steps, low fill factors and stability of doped devices. In this work, SiO2 patterns are simply formed using a sputtering process rather than the previous complex method. Additionally, the fill factor for prepared devices is developed by using transferred residue-free multi-graphene layers. The usage of 3 graphene layers improves the power conversion efficiency (PCE) to 7.1%. A recorded PCE of around 17% with a fill factor of 74% is achieved by the HNO3 dopant. To overcome the issue of stability, Poly(methyl methacrylate) as an encapsulated layer is introduced. Hence, the doped devices show great stability for storage in air for 2 weeks, and devices recovered about 95% of their efficiency. This work shows that the developed fabrication process is suitable to develop simple, low cost, stable and efficient graphene/Si Schottky solar cells
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