Unusual cause of chest pain: Thoracic aorta calcification

A 40-year-old woman treated for pulmonary tuberculosis presented with chest pain which was aggravated with exertion without radiation. Chest X-ray shows widening of mediastinum, old healed, and calcified parenchymal lesion. Computed tomography scan showed annular calcification of aorta (solar eclipse sign) with significant narrowing of aorta. The patient responded well with vasodilator nifedipine, and almost 75% reduction in symptoms was seen after 1 month of the treatment

Generalized Adversarially Learned Inference

Allowing effective inference of latent vectors while training GANs can greatly increase their applicability in various downstream tasks. Recent approaches, such as ALI and BiGAN frameworks, develop methods of inference of latent variables in GANs by adversarially training an image generator along with an encoder to match two joint distributions of image and latent vector pairs. We generalize these approaches to incorporate multiple layers of feedback on reconstructions, self-supervision, and other forms of supervision based on prior or learned knowledge about the desired solutions. We achieve this by modifying the discriminator's objective to correctly identify more than two joint distributions of tuples of an arbitrary number of random variables consisting of images, latent vectors, and other variables generated through auxiliary tasks, such as reconstruction and inpainting or as outputs of suitable pre-trained models. We design a non-saturating maximization objective for the generator-encoder pair and prove that the resulting adversarial game corresponds to a global optimum that simultaneously matches all the distributions. Within our proposed framework, we introduce a novel set of techniques for providing self-supervised feedback to the model based on properties, such as patch-level correspondence and cycle consistency of reconstructions. Through comprehensive experiments, we demonstrate the efficacy, scalability, and flexibility of the proposed approach for a variety of tasks.Comment: AAAI 2021 (accepted for publication

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents

Diffusion probabilistic models have been shown to generate state-of-the-art results on several competitive image synthesis benchmarks but lack a low-dimensional, interpretable latent space, and are slow at generation. On the other hand, standard Variational Autoencoders (VAEs) typically have access to a low-dimensional latent space but exhibit poor sample quality. We present DiffuseVAE, a novel generative framework that integrates VAE within a diffusion model framework, and leverage this to design novel conditional parameterizations for diffusion models. We show that the resulting model equips diffusion models with a low-dimensional VAE inferred latent code which can be used for downstream tasks like controllable synthesis. The proposed method also improves upon the speed vs quality tradeoff exhibited in standard unconditional DDPM/DDIM models (for instance, FID of 16.47 vs 34.36 using a standard DDIM on the CelebA-HQ-128 benchmark using T=10 reverse process steps) without having explicitly trained for such an objective. Furthermore, the proposed model exhibits synthesis quality comparable to state-of-the-art models on standard image synthesis benchmarks like CIFAR-10 and CelebA-64 while outperforming most existing VAE-based methods. Lastly, we show that the proposed method exhibits inherent generalization to different types of noise in the conditioning signal. For reproducibility, our source code is publicly available at https://github.com/kpandey008/DiffuseVAE.Comment: 12 pages main content. Camera-Ready version accepted at Transactions on Machine Learning Researc

A clinico-radiological and pathological profile of lung cancer patients presented to All India Institute of Medical Sciences (Patna)

Background: Lung cancer is one of the most common cancers and cause of cancer-related deaths worldwide. The clinicopathologicalprofile of lung cancer has shown marked regional and geographical variation. Majority of the patients have locallyadvanced or disseminated disease at presentation and are not candidates for surgery. Objective: The aim of this study was toevaluate the clinico-radiological and pathological profile of lung cancer patients and difference in histopathology betweensmoker and non-smoker. We also assessed yield of the various diagnostic procedures used for confirmation of lung cancer.Materials and Methods: A total of 30 patients diagnosed between May 1, 2016, and December 31, 2016. The completedemographic profile, smoking status, clinical, radiological, and diagnostic details were recorded in the study. Data were enteredand analyzed using SPSS software. Results: A total of 30 patients (19 male and 11 female) included in our study with mean age of55.26 years. Cough (80%) and dyspnea (80%) were the most common symptom and mass (86%), pleural effusion (53.3%) was themost common radiological presentation of patients. Clubbing and hemoptysis both was found only in 8 out of 30 (26%) patients.Adenocarcinoma (46.6%) was the most common histopathological type followed by squamous cell carcinoma (16.6%) and smallcell carcinoma (13.3%). The majority of patients (60%) presented in Stage 4. Computed tomography guided biopsy had better yieldin compare to ultrasonography guided (80% vs. 70.8%). Bronchoscopic procedure had lowest yield (38.8%). Conclusion: Theclinicopathological profile of lung cancer has changed in last few years, especially in the increase in adenocarcinoma incidence,and now it is the most common cause in both smokers and non-smoker

Publication Trend in Library Philosophy and Practice (e-journal) : A Scientometric Approach

Scientometrics is an effective method to quantitatively analyse the productivity and progress of all forms of written communication. This study aims to examine the scientific research productivity on Library Philosophy and Practice (e-journal) during 1998-2019. Required data was collected from Scopus database. The year wise distribution of articles, relative growth rate, doubling time, collaboration coefficient, country and affiliation wise distribution, citation patterns etc., were analysed. Findings revealed that the highest numbers of articles were published in the year 2019 and lowest in 1998. In 2013, there was no single article. The highest contribution was countrywise Nigeria and institution wise University of Ibadan. Study also revealed the average citation per paper was 1.51. The paper 'Using Google Analytics for improving library website content and design: A case study' by Fang W. received a citation of 67 and ranked as the highly cited paper

Quasiperiodic ordering in thick Sn layer on ii-Al-Pd-Mn: A possible quasicrystalline clathrate

Realization of an elemental solid-state quasicrystal has remained a distant dream so far in spite of extensive work in this direction for almost two decades. Here, we report the discovery of quasiperiodic ordering in a thick layer of elemental Sn grown on icosahedral ($i$)-Al-Pd-Mn. The STM images and the LEED patterns of the Sn layer show specific structural signatures that portray quasiperiodicity but are distinct from the substrate. Photoemission spectroscopy reveals the existence of the pseudogap around the Fermi energy up to the maximal Sn thickness. The structure of the Sn layer is modeled as a novel form of quasicrystalline clathrate on the basis of the following: Firstly, from ab-initio theory, the energy of bulk Sn clathrate quasicrystal is lower than the high temperature metallic $\beta$-Sn phase, but higher than the low temperature $\alpha$-Sn phase. A comparative study of the free slab energetics shows that surface energy favors clathrate over $\alpha$-Sn up to about 4 nm layer thickness, and matches $\beta$-Sn for narrow window of slab thickness of 2-3 nm. Secondly, the bulk clathrate exhibits gap opening near Fermi energy, while the free slab form exhibits a pronouced pseudogap, which explains the pseudogap observed in photoemission. Thirdly, the STM images exhibit good agreement with clathrate model. We establish the adlayer-substrate compatibility based on very similar (within 1%) the cage-cage separation in the Sn clathrate and the pseudo-Mackay cluster-cluster separation on the $i$-Al-Pd-Mn surface. Furthermore, the nucleation centers of the Sn adlayer on the substrate are identified and these are shown to be a valid part of the Sn clathrate structure. Thus, based on both experiment and theory, we propose that 4 nm thick Sn adlayer deposited on 5-fold surface of $i$-Al-Pd-Mn substrate is in fact a metastable realization of elemental, clathrate family quasicrystal.Comment: 10 figures in the Manuscript and the 8 figures in the Supplementary materia