Semilogarithmic Nonuniform Vector Quantization of Two-Dimensional Laplacean Source for Small Variance Dynamics

In this paper high dynamic range nonuniform two-dimensional vector quantization model for Laplacean source was provided. Semilogarithmic A-law compression characteristic was used as radial scalar compression characteristic of two-dimensional vector quantization. Optimal number value of concentric quantization domains (amplitude levels) is expressed in the function of parameter A. Exact distortion analysis with obtained closed form expressions is provided. It has been shown that proposed model provides high SQNR values in wide range of variances, and overachieves quality obtained by scalar A-law quantization at same bit rate, so it can be used in various switching and adaptation implementations for realization of high quality signal compression

Probing the radial temperature structure of protoplanetary disks with Herschel/HIFI

Herschel/HIFI spectroscopic observations of CO J=10-9, CO J=16-15 and [CII] towards HD 100546 are presented. The objective is to resolve the velocity profile of the lines to address the emitting region of the transitions and directly probe the distribution of warm gas in the disk. The spectra reveal double-peaked CO line profiles centered on the systemic velocity, consistent with a disk origin. The J=16-15 line profile is broader than that of the J=10-9 line, which in turn is broader than those of lower J transitions (6-5, 3-2, observed with APEX), thus showing a clear temperature gradient of the gas with radius. A power-law flat disk model is used to fit the CO line profiles and the CO rotational ladder simultaneously, yielding a temperature of T_0=1100 \pm 350 K (at r_0 = 13 AU) and an index of q=0.85 \pm 0.1 for the temperature radial gradient. This indicates that the gas has a steeper radial temperature gradient than the dust (mean q_{dust} ~ 0.5), providing further proof of the thermal decoupling of gas and dust at the disk heights where the CO lines form. The [CII] line profile shows a strong single-peaked profile red-shifted by 0.5 km s-1 compared to the systemic velocity. We conclude that the bulk of the [CII] emission has a non-disk origin (e.g., remnant envelope or diffuse cloud).Comment: Accepted for publication in ApJ

Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy

Predicting response to neo-adjuvant chemotherapy of liver metastases (mts) using CT images is of key importance to provide personalized treatments. However, manual segmentation of mts should be avoid to develop methods that could be integrated into the clinical practice. The aim of this study is to evaluate if and how much automatic segmentation can affect a radiomics-based method to predict response to neoadjuvant chemotherapy of individual liver mts. To this scope, we developed an automatic deep learning method to segment liver mts, based on the U-net architecture, and we compared the classification results of a classifier fed with manual and automatic masks. In the validation set composed of 39 liver mts, the automatic deeplearning algorithm was able to detect 82% of mts, with a median precision of 67%. Using manual and automatic masks, we obtained the same classification in 19/32 mts. In case of mts with largest diameter > 20 mm, the precision of the segmentation does not impact the classification results and we obtained the same classification with both masks. Conversely, with smaller mts, we showed that a Dice coefficient of at least 0.5 should be obtained to extract the same information from the two segmentations. This are very important results in the perspective of using radiomics-based approach to predict response to therapy into clinical practice. Indeed, either precisely manually segment all lesions or refine them after automatic segmentation is a time-consuming task that cannot be performed on a daily basis

TW Hya: an old protoplanetary disc revived by its planet

Dark rings with bright rims are the indirect signposts of planets embedded in protoplanetary discs. In a recent first, an azimuthally elongated AU-scale blob, possibly a planet, was resolved with ALMA in TW Hya. The blob is at the edge of a cliff-like rollover in the dust disc rather than inside a dark ring. Here we build time-dependent models of TW Hya disc. We find that the classical paradigm cannot account for the morphology of the disc and the blob. We propose that ALMA-discovered blob hides a Neptune mass planet losing gas and dust. We show that radial drift of mm-sized dust particles naturally explains why the blob is located on the edge of the dust disc. Dust particles leaving the planet perform a characteristic U-turn relative to it, producing an azimuthally elongated blob-like emission feature. This scenario also explains why a 10 Myr old disc is so bright in dust continuum. Two scenarios for the dust-losing planet are presented. In the first, a dusty pre-runaway gas envelope of a ∼40M⊕ Core Accretion planet is disrupted, e.g. as a result of a catastrophic encounter. In the second, a massive dusty pre-collapse gas giant planet formed by Gravitational Instability is disrupted by the energy released in its massive core. Future modelling may discriminate between these scenarios and allow us to study planet formation in an entirely new way – by analysing the flows of dust and gas recently belonging to planets, informing us about the structure of pre-disruption planetary envelopes

CI observations in the CQ Tau proto-planetary disk: evidence for a very low gas-to-dust ratio ?

Gas and dust dissipation processes of proto-planetary disks are hardly known. Transition disks between Class II (proto-planetary disks) and Class III (debris disks) remain difficult to detect. We investigate the carbon chemistry of the peculiar CQ Tau gas disk. It is likely a transition disk because it exhibits weak CO emission with a relatively strong millimeter continuum, indicating that the disk might be currently dissipating its gas content. We used APEX to observe the two CI lines at 492GHz and 809 GHz in the disk orbiting CQ Tau. We compare the observations to several chemical model predictions. We focus our study on the influence of the stellar UV radiation shape and gas-to-dust ratio. We did not detect the CI lines. However, our upper limits are deep enough to exclude high-CI models. The only available models compatible with our limits imply very low gas-to-dust ratio, of the order of a few, only. These observations strengthen the hypothesis that CQ Tau is likely a transition disk and suggest that gas disappears before dust.Comment: 5 pages, 5 figures, accepted for publication in A&

Comparison of different classifiers to recognize active bone marrow from CT images

One of the main problems during in the treatment of anal cancer with chemotherapy and radiation is the occurrence of Hematologic Toxicity (HT). In particular, during radiotherapy it is crucial to spare Bone Marrow (BM), since the radiation dose received by BM in pelvic bones predicts the onset of HT. In this direction, the most popular strategies are based on the identification of the hematopoietically active BM (actBM), that is the part of BM in charge of blood cells generation, using MRI, SPECT or PET, but no approached have been proposed based on CT. In this study we compare four different classifiers in recognizing actBM from CT images using 36 radiomic features. We used Genetic Algorithms (GAs) to simultaneously optimize the feature subsets and the classifier parameters, separately for three pelvic subregions: iliac bone marrow (IBM), lower pelvis bone marrow (LPBM), and lumbosacral bone marrow (LSBM). The obtained classifiers were applied to CT sequences of a cohort of 25 patients affected by carcinoma of the anal canal. Classifiers results were compared with the actBM identified from 18FDG-PET (reference standard, RS). It emerged that the performances of the 4 classifiers are similar and they are satisfactory for IBM and LSBM subregions (Dice > 0.7) whereas they are poor for LPBM (Dice < 0.5)

Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil

Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for cancer detection. Unfortunately, MRI acquired in different centers with different scanners leads to images with different characteristics. In this work, we propose an automatic algorithm for prostate segmentation, based on a U-Net applying transfer learning method in a bi-center setting. First, T2w images with and without endorectal coil from 80 patients acquired at Center A were used as training set and internal validation set. Then, T2w images without endorectal coil from 20 patients acquired at Center B were used as external validation. The reference standard for this study was manual segmentation of the prostate gland performed by an expert operator. The results showed a Dice similarity coefficient >85% in both internal and external validation datasets.Clinical Relevance- This segmentation algorithm could be integrated into a CAD system to optimize computational effort in prostate cancer detection

“I’m Not Waving, I’m Drowning”: An Autoethnographical Exploration of Biographical Disruption and Reconstruction During Recovery From Prescribed Benzodiazepine Use

Benzodiazepines are group of drugs used mainly as sedatives, hypnotics, muscle relaxants, and anti-epileptics. Tapering off benzodiazepines is, for some users, a painful, traumatic, and protracted process. In this article, I use an autoethnographic approach, adopting the metaphor of water, to examine heuristically my experience of iatrogenic illness and recovery. I draw on personal journals and blog entries and former users’ narratives to consider the particular form of biographical disruption associated with benzodiazepines and the processes involved in identity reconstruction. I emphasize the role of the online community in providing benzodiazepine users such as myself with a co-cultural community through which to share a voice and make sense of our experiences. I explain how the success stories of former users provided me with the hope that I, the “medical victim,” could become the “victor” and in the process construct a new life and fresh identity

CHANNEL CAPACITY OF THE MACRO-DIVERSITY SC SYSTEM IN THE PRESENCE OF KAPPA-MU FADING AND CORRELATED SLOW GAMMA FADING

In this paper macrodiversity system consisting of two microdiversity SC (Selection Combiner) receivers and one macrodiversity SC receiver are analyzed. Independent κ-μ fading and correlated slow Gamma fading are present at the inputs to the microdiversity SC receivers. For this system model, analytical expression for the probability density of the signal at the output of the macrodiversity receiver SC, and the output capacity of the macrodiversity SC receiver are calculated. The obtained results are graphically presented to show the impact of Rician κ factor, the shading severity of the channel c, the number of clusters µ and correlation coefficient ρ on the probability density of the signal at the output of the macrodiversity system and channel capacity at the output of the macrodiversity system. Based on the obtained results it is possible to analyze the real behavior of the macrodiversity system in the presence of  κ-μ fading