Not Your Typical Case Of Ascites: Pancreatic Ascites In A Patient With Cirrhosis And Pancreatic Duct Leak

Case A 55-year-old male with a history of hepatic cirrhosis secondary to Hepatitis C and alcohol abuse presented to an outside hospital with progressive abdominal pain and distension. The patient initially complained of “punching” right upper quadrant and epigastric abdominal pain that was 10/10 in intensity and non-radiating. Although the pain had started one to two days prior to presentation, the patient had been experiencing several weeks of increasing abdominal distension. He reported drinking eight 40oz beers daily for over 40 years, and he felt that the abdominal pain improved slightly with cessation of alcohol use. The patient complained of nausea and non-bloody, non-bilious vomiting, progressive dyspnea on exertion, and worsening lower extremity edema. He denied fevers or chills

The prospects of measuring the angular power spectrum of the diffuse Galactic synchrotron emission with SKA1 Low

The diffuse Galactic synchrotron emission (DGSE) is the most important diffuse foreground component for future cosmological 21-cm observations. The DGSE is also an important probe of the cosmic ray electron and magnetic field distributions in the turbulent interstellar medium (ISM) of our Galaxy. In this paper we briefly review the Tapered Gridded Estimator (TGE) which can be used to quantify the angular power spectrum of the sky signal directly from the visibilities measured in radio-interferometric observations. The salient features of the TGE are (1.) it deals with the gridded data which makes it computationally very fast (2.) it avoids a positive noise bias which normally arises from the system noise inherent to the visibility data, and (3.) it allows us to taper the sky response and thereby suppresses the contribution from unsubtracted point sources in the outer parts and the sidelobes of the antenna beam pattern. We also summarize earlier work where the TGE was used to measure the C_l of the DGSE using 150 MHz GMRT data. Earlier measurements of the angular power spectrum are restricted to smaller angular multipole l ~ 10^3 for the DGSE, the signal at the larger l values is dominated by the residual point sources after source subtraction. The higher sensitivity of the upcoming SKA1 Low will allow the point sources to be subtracted to a fainter level than possible with existing telescopes. We predict that it will be possible to measure the angular power spectrum of the DGSE to larger values of l with SKA1 Low. Our results show that it should be possible to achieve l_{max} ~ 10^4 and ~ 10^5 with 2 minutes and 10 hours of observations respectively.Comment: 10 pages, 3 figures; Accepted for publication in Journal of Astrophysics and Astronomy (JOAA) special issue on "Science with the SKA: an Indian perspective

Sarcomatoid Mesothelioma in a Patient with Asbestos Exposure

Case A 76-year-old man with no significant past medical history presented with a two month history of progressive shortness of breath, 25-pound weight loss, and sharp right-sided chest, abdomen, and pelvic pain without radiation. The patient noted his dyspnea became more pronounced in recent weeks, notably worse with climbing stairs or performing work around the house. He described the pain as having a positional component, and exacerbated with deep-inspiration. On further questioning, the patient reported a 50-pack-year history of smoking and past exposure to asbestos while working with heating insulation. Physical examination revealed an age-appropriate, but cachectic appearing male with tenderness of the right abdomen to palpation, mild tachypnea with 95% oxygen saturation on two liters of oxygen, and normal cardiac rate and rhythm. Initial chest radiograph revealed a large mass causing near complete opacification of the right hemithorax (Figure 1) which was a new finding compared to the patient’s previous chest radiograph two years prior (Figure 2). Computed tomography (CT) scan of the chest/abdomen/pelvis performed to further evaluate this mass (Figure 3) revealed a 20 x 21 x 23 cm heterogeneous tumor above the right hemidiaphragm with extension into the left atrium via the right pulmonary vein (white arrow), as well as lateral and anterior diaphragmatic and pleural involvement. Differential diagnosis at this stage included malignant mass, benign pleural wall tumor, and mesothelioma. Pathology from surgical biopsy (Figure 4) suggested Sarcomatoid mesothelioma

Robust Principal Component Analysis using Density Power Divergence

Principal component analysis (PCA) is a widely employed statistical tool used primarily for dimensionality reduction. However, it is known to be adversely affected by the presence of outlying observations in the sample, which is quite common. Robust PCA methods using M-estimators have theoretical benefits, but their robustness drop substantially for high dimensional data. On the other end of the spectrum, robust PCA algorithms solving principal component pursuit or similar optimization problems have high breakdown, but lack theoretical richness and demand high computational power compared to the M-estimators. We introduce a novel robust PCA estimator based on the minimum density power divergence estimator. This combines the theoretical strength of the M-estimators and the minimum divergence estimators with a high breakdown guarantee regardless of data dimension. We present a computationally efficient algorithm for this estimate. Our theoretical findings are supported by extensive simulations and comparisons with existing robust PCA methods. We also showcase the proposed algorithm's applicability on two benchmark datasets and a credit card transactions dataset for fraud detection

Availability, storage capacity, and diffusion: Stationary states of an asymmetric exclusion process connected to two reservoirs

We explore how the interplay of finite availability, carrying capacity of particles at different parts of a spatially extended system and particle diffusion between them control the steady state currents and density profiles in a one-dimensional current-carrying channel connecting the different parts of the system. To study this, we construct a minimal model consisting of two particle reservoirs of finite carrying capacities connected by a totally asymmetric simple exclusion process (TASEP). In addition to particle transport via TASEP between the reservoirs, the latter can also directly exchange particles, modeling particle diffusion between them that can maintain a steady current in the system. We investigate the steady state density profiles and the associated particle currents in the TASEP lane. The resulting phases and the phase diagrams are quite different from an open TASEP, and are characterised by the model parameters defining particle exchanges between the TASEP and the reservoirs, direct particle exchanges between the reservoirs, and the filling fraction of the particles that determines the total resources available. These parameters can be tuned to make the density on the TASEP lane globally uniform or piecewise continuous, and can make the two reservoirs preferentially populated or depopulated.Comment: Comments are welcom

rSVDdpd: A Robust Scalable Video Surveillance Background Modelling Algorithm

A basic algorithmic task in automated video surveillance is to separate background and foreground objects. Camera tampering, noisy videos, low frame rate, etc., pose difficulties in solving the problem. A general approach that classifies the tampered frames, and performs subsequent analysis on the remaining frames after discarding the tampered ones, results in loss of information. Several robust methods based on robust principal component analysis (PCA) have been introduced to solve this problem. To date, considerable effort has been expended to develop robust PCA via Principal Component Pursuit (PCP) methods with reduced computational cost and visually appealing foreground detection. However, the convex optimizations used in these algorithms do not scale well to real-world large datasets due to large matrix inversion steps. Also, an integral component of these foreground detection algorithms is singular value decomposition which is nonrobust. In this paper, we present a new video surveillance background modelling algorithm based on a new robust singular value decomposition technique rSVDdpd which takes care of both these issues. We also demonstrate the superiority of our proposed algorithm on a benchmark dataset and a new real-life video surveillance dataset in the presence of camera tampering. Software codes and additional illustrations are made available at the accompanying website rSVDdpd Homepage (https://subroy13.github.io/rsvddpd-home/