CancerLinker: Explorations of Cancer Study Network

Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which is responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them detect the common proteins in cancer studies and hence reveal the pattern of interactions of those proteins. We introduce the CancerLinker, a visual analytic tool that helps researchers explore cancer study interaction network. Twenty-six cancer studies are merged to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. The CancerLinker also helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer studyComment: 7 pages, 9 figure

Abdominal intercostal hernia: a rare complication after blunt trauma.

Abdominal intercostal hernia (AIH) is uncommonly reported in the literature with only 20 cases reported to date.1–3 We report a case of a delayed incarcerated AIH secondary to blunt trauma from a motor vehicle accident in which the colon and diaphragm herniated through an associated chest defect that was repaired successfully through a transabdominal approach using primary repair of the defect in combination with onlay porcine patch reinforcement

Delay-Exponent of Bilayer Anytime Code

In this paper, we study the design and the delay-exponent of anytime codes over a three terminal relay network. We propose a bilayer anytime code based on anytime spatially coupled low-density parity-check (LDPC) codes and investigate the anytime characteristics through density evolution analysis. By using mathematical induction technique, we find analytical expressions of the delay-exponent for the proposed code. Through comparison, we show that the analytical delay-exponent has a close match with the delay-exponent obtained from numerical results.Comment: Accepted for presentation in ITW-2014. 5 Pages, 3 Figure

Finite Length Analysis of LDPC Codes

In this paper, we study the performance of finite-length LDPC codes in the waterfall region. We propose an algorithm to predict the error performance of finite-length LDPC codes over various binary memoryless channels. Through numerical results, we find that our technique gives better performance prediction compared to existing techniques.Comment: Submitted to WCNC 201

Vaccine-preventable diseases and foreign-born populations

Foreign-born individuals account for over 12% of the U.S. population, according to the most recent census data. Since many vaccine-preventable outbreaks in the U.S. have been correlated with disease importation, Congress has mandated vaccinations for numerous immigrant populations. It is essential for primary care physicians to be knowledgeable on the unique immunization-related needs of foreign-born individuals, to recognize some of the cultural and linguistic challenges that immigrants have accessing healthcare, and remember to use each medical encounter as an opportunity to provide necessary vaccinations

Chevalier Jackson, M.D. (1865-1958): Il ne se repose jamais.

In the final year of the American Civil War, 1865, Chevalier Jackson was born on the 4th of November just outside Pittsburgh, Pennsylvania. The eldest of three sons of a poor, livestock-raising family, Jackson was raised in a period of social and political unrest. He was perhaps an even more unrestful boy. The description of his childhood days from his father’s father—Il ne se repose jamais, ‘‘He never rests’’—would ultimately reflect the man, doctor, and evangelist Jackson would later become.1 Indeed, he never did rest, Jackson would tirelessly pave the way for modern bronchoscopy and endoscopy as a whole; bringing international renown not only to himself, but also to his specialty

Repairing Deep Neural Networks: Fix Patterns and Challenges

Significant interest in applying Deep Neural Network (DNN) has fueled the need to support engineering of software that uses DNNs. Repairing software that uses DNNs is one such unmistakable SE need where automated tools could be beneficial; however, we do not fully understand challenges to repairing and patterns that are utilized when manually repairing DNNs. What challenges should automated repair tools address? What are the repair patterns whose automation could help developers? Which repair patterns should be assigned a higher priority for building automated bug repair tools? This work presents a comprehensive study of bug fix patterns to address these questions. We have studied 415 repairs from Stack overflow and 555 repairs from Github for five popular deep learning libraries Caffe, Keras, Tensorflow, Theano, and Torch to understand challenges in repairs and bug repair patterns. Our key findings reveal that DNN bug fix patterns are distinctive compared to traditional bug fix patterns; the most common bug fix patterns are fixing data dimension and neural network connectivity; DNN bug fixes have the potential to introduce adversarial vulnerabilities; DNN bug fixes frequently introduce new bugs; and DNN bug localization, reuse of trained model, and coping with frequent releases are major challenges faced by developers when fixing bugs. We also contribute a benchmark of 667 DNN (bug, repair) instances

A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles' positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme

Hematemesis, a Distended Abdomen, and Pulseless Electrical Activity – An Unusual Presentation of Boerhaave’s Syndrome

Case Presentation An 82-year-old male with a past medical history significant for coronary artery disease with three stents placed over the last 15 months, diastolic heart failure with preserved EF, atrial fibrillation on warfarin, colon cancer status-post sigmoid resection and prostate cancer status-post prostatectomy who presented with three episodes of melena, hematemesis, and weakness. The patient was in his usual state of health prior to these symptoms. He had no history of gastrointestinal (GI) bleeding or other GI pathology and was a non-drinker and non-smoker. He denied frequent use of non-steroidal anti-inflammatory medications

Informing Policy on Built Environments to Safeguard Children in Environmental Justice Communities: Case Study of Five AAP Climate Advocates

Climate change’s health effects are most strongly felt in Environmental Justice (EJ) communities which are predominantly people of color. This results in a disproportionate burden of climate change health effects on EJ communities. Climate change is a public health crisis, and more importantly to pediatricians – it is a pediatric public health crisis. We are five pediatricians who are part of the American Academy of Pediatrics (AAP) Climate Advocate Program representing four diverse regions; Colorado, California, Puerto Rico, and North Carolina. We are applied research practitioners, as we live in the world between academic research and clinical practice. We are natural advocates to ensure that the future world is rebuilt with children’s health, especially children of EJ communities, at the center. Each of us has seen the direct effects of climate change adversely impact EJ Communities. In this article, we will briefly review the literature on the dangers that children face in the air they breathe, the lack of natural green spaces, and the increasingly hostile built environments, especially to children in EJ communities. We will review opportunities in our local areas to change the built environment that will work toward reducing carbon emissions and increase overall pediatric health. We will illustrate the commonalities that helped us succeed as Climate Advocates including collaboration, working locally, and purposefully choosing to identify ourselves as climate advocates and child-advocates. The intersection between public health, policy, and medicine will now become increasingly important as we head into this new decade and approach the point of no return on climate change