Motion Planning from Demonstrations and Polynomial Optimization for Visual Servoing Applications

Vision feedback control techniques are desirable for a wide range of robotics applications due to their robustness to image noise and modeling errors. However in the case of a robot-mounted camera, they encounter difficulties when the camera traverses large displacements. This scenario necessitates continuous visual target feedback during the robot motion, while simultaneously considering the robot's self- and external-constraints. Herein, we propose to combine workspace (Cartesian space) path-planning with robot teach-by-demonstration to address the visibility constraint, joint limits and “whole arm” collision avoidance for vision-based control of a robot manipulator. User demonstration data generates safe regions for robot motion with respect to joint limits and potential “whole arm” collisions. Our algorithm uses these safe regions to generate new feasible trajectories under a visibility constraint that achieves the desired view of the target (e.g., a pre-grasping location) in new, undemonstrated locations. Experiments with a 7-DOF articulated arm validate the proposed method.published_or_final_versio

Polypill for prevention of cardiovascular disease in an Urban Iranian population with special focus on nonalcoholic steatohepatitis: A pragmatic randomized controlled trial within a cohort (PolyIran - Liver) – Study protocol

Background: Cardiovascular disease (CVD) is among the most common causes of mortality in all populations. Nonalcoholic steatohepatitis is a common finding in patients with CVD. Prevention of CVD in individual patients typically requires periodic clinical evaluation, as well as diagnosis and management of risk factors such as hypertension and hyperlipidemia. However, this is resource consuming and hard to implement, especially in developing countries. We designed a study to investigate the effects of a simpler strategy: a fixed-dose combination pill consisting of aspirin, valsartan, atorvastatin and hydrochlorthiazide (PolyPill) in an unselected group of persons aged over 50 years. Design: The PolyIran-Liver study was performed in Gonbad city as an open label pragmatic randomized controlled trial nested within the Golestan Cohort Study. We randomly selected 2,400 cohort study participants aged above 50 years, randomly assigned them to intervention or usual care and invited them to participate in an additional measurement study (if they met the eligibility criteria) to measure liver related outcomes. Those agreeing and randomized to the intervention arm were offered a daily single dose of PolyPill. We will follow participants for 5 years. The primary outcome is major cardiovascular events, secondary outcomes include all-cause mortality and liver related outcomes: liver stiffness and liver enzyme levels. Cardiovascular outcomes and mortality will be determined from the cohort study and liver-related outcomes in those consenting to follow up. Analysis will be by allocated group. Trial Status: Between October and December 2011, 1,320 intervention and 1,080 control participants were invited to participate in the additional measurement study. For all these participants, the major cardiovascular events will be determined using blind assessment of outcomes through the cohort study. In the intervention and control arms, 875 (66%) and 721 (67%) respectively, met the eligibility criteria and agreed to participate in the additional measurement study. Liver related outcomes will be measured in these participants. Of the 1,320 participants randomized to the intervention, 787 (60%) accepted the PolyPill. Conclusion: The PolyIran-liver urban study will provide us with important information on the effectiveness of PolyPill on major cardiovascular events, all-cause mortality and liver related outcomes. (ClinicalTrials.gov ID: NCT01245608). © 2015, Academy of Medical Sciences of I.R. Iran. All rights reserved

The prevalence of hepatitis B surface antigen and anti-hepatitis B core antibody in Iran: A population-based study

Background: Hepatitis B virus infection is a very common cause of chronic liver disease worldwide. It is estimated that 3 of Iranians are chronically infected with hepatitis B virus. Current population-based studies on both rural and urban prevalence of hepatitis B virus infection in Iran are sparse with results that do not always agree. We performed this study to find the prevalence of hepatitis B surface antigen, anti-hepatitis B core antibody, and associated factors in the general population of three provinces of Iran. Methods: We randomly selected 6,583 subjects from three provinces in Iran, namely Tehran, Golestan, and Hormozgan. The subjects were aged between 18 and 65 years. Serum samples were tested for hepatitis B surface antigen and anti-hepatitis B core antibody. Various risk factors were recorded and multivariate analysis was performed. Results: The prevalence of hepatitis B surface antigen and anti-hepatitis B core antibody in Iran was 2.6 and 16.4, respectively. Predictors of hepatitis B surface antigen or anti-hepatitis B core antibody in multivariate analysis included older age, not having high-school diploma, living in a rural area, and liver disease in a family member. We did not find any significant differences between males and females. Conclusion: In spite of nationwide vaccination of newborns against hepatitis B virus since 1992, hepatitis B virus infection remains a very common cause of chronic liver disease in Iran which should be dealt with for at least the next 30-50 years

Diagnostic Accuracy of Age and Alarm Symptoms for Upper GI Malignancy in Patients with Dyspepsia in a GI Clinic: A 7-Year Cross-Sectional Study

<div><h3>Objectives</h3><p>We investigated whether using demographic characteristics and alarm symptoms can accurately predict cancer in patients with dyspepsia in Iran, where upper GI cancers and <em>H. pylori</em> infection are common.</p> <h3>Methods</h3><p>All consecutive patients referred to a tertiary gastroenterology clinic in Tehran, Iran, from 2002 to 2009 were invited to participate in this study. Each patient completed a standard questionnaire and underwent upper gastrointestinal endoscopy. Alarm symptoms included in the questionnaire were weight loss, dysphagia, GI bleeding, and persistent vomiting. We used logistic regression models to estimate the diagnostic value of each variable in combination with other ones, and to develop a risk-prediction model.</p> <h3>Results</h3><p>A total of 2,847 patients with dyspepsia participated in this study, of whom 87 (3.1%) had upper GI malignancy. Patients reporting at least one of the alarm symptoms constituted 66.7% of cancer patients compared to 38.9% in patients without cancer (p<0.001). Esophageal or gastric cancers in patients with dyspepsia was associated with older age, being male, and symptoms of weight loss and vomiting. Each single predictor had low sensitivity and specificity. Using a combination of age, alarm symptoms, and smoking, we built a risk-prediction model that distinguished between high-risk and low-risk individuals with an area under the ROC curve of 0.85 and acceptable calibration.</p> <h3>Conclusions</h3><p>None of the predictors demonstrated high diagnostic accuracy. While our risk-prediction model had reasonable accuracy, some cancer cases would have remained undiagnosed. Therefore, where available, low cost endoscopy may be preferable for dyspeptic older patient or those with history of weight loss.</p> </div

Diversity-Based Geometry Optimization in MIMO Passive Coherent Location

Applying the recently emerged technique‎, ‎MIMO (Multiple Input Multiple Output) to PCL (Passive Coherent‎ ‎Location) is expected to improve performance of localization schemes‎. ‎In this paper‎, ‎we explore the‎ ‎application of MIMO technology to PCL schemes and see how it improves the spatial diversity of such systems‎. ‎Specifically‎, ‎we use the DVB-T stations as the‎ ‎illuminators of opportunity in the simulations‎, ‎mainly because of their unique features which‎ ‎make them quite suitable for both MIMO and PCL application as will be demonstrated in this‎ ‎paper‎. ‎In addition‎, ‎we address the key problem of finding optimum locations for placement of receive antennas‎

Proposing a novel deep network for detecting COVID-19 based on chest images

The rapid outbreak of coronavirus threatens humans’ life all around the world. Due to the insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. To date, researchers have proposed several detection models based on chest imaging analysis, primarily based on deep neural networks; however, none of which could achieve a reliable and highly sensitive performance yet. Therefore, the nature of this study is primary epidemiological research that aims to overcome the limitations mentioned above by proposing a large-scale publicly available dataset of chest computed tomography scan (CT-scan) images consisting of more than 13k samples. Secondly, we propose a more sensitive deep neural networks model for CT-scan images of the lungs, providing a pixel-wise attention layer on top of the high-level features extracted from the network. Moreover, the proposed model is extended through a transfer learning approach for being applicable in the case of chest X-Ray (CXR) images. The proposed model and its extension have been trained and evaluated through several experiments. The inclusion criteria were patients with suspected PE and positive real-time reverse-transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. The exclusion criteria were negative or inconclusive RT-PCR and other chest CT indications. Our model achieves an AUC score of 0.886, significantly better than its closest competitor, whose AUC is 0.843. Moreover, the obtained results on another commonly-used benchmark show an AUC of 0.899, outperforming related models. Additionally, the sensitivity of our model is 0.858, while that of its closest competitor is 0.81, explaining the efficiency of pixel-wise attention strategy in detecting coronavirus. Our promising results and the efficiency of the models imply that the proposed models can be considered reliable tools for assisting doctors in detecting coronavirus

Potential MR enterography features to differentiate primary small intestinal lymphoma from Crohn disease

OBJECTIVE. The purpose of this study was to assess the MR enterographic features of primary small intestinal lymphoma (PSIL) and compare them with active Crohn disease (CD) presenting with severe (≥ 10 mm) mural thickening of the small bowel. MATERIALS AND METHODS. This retrospective study included 15 patients with pathologically proven PSIL and 15 patients with active inflammatory CD with severe mural thickening. Various morphologic, enhancement, and diffusion parameters were compared between the two groups at MR enterography. The ratios of the upstream to involved luminal diameter and mural thickness to luminal diameter in the involved segment were calculated. An attempt was made to define a predictive model (morphologic score) for discriminating PSIL from CD with severe mural thickening. RESULTS. Patients with PSIL were more likely than those with CD to have unifocal disease (66.7% vs 20.0%, p = 0.025), circumferential involvement (86.7% vs 26.7%, p &lt; 0.001), luminal dilatation (60.0% vs 7.0%, p = 0.005), and an attenuated fold pattern (53.3% vs none, p &lt; 0.001). They were less likely to have serosal surface involvement (40.0% vs 100%, p = 0.001) and mesenteric fat infiltration (33.3% vs 100%, p &lt; 0.001). Median upstream to involved luminal diameter ratio (1.5 vs 9.6, p &lt; 0.001) and mural thickness to involved luminal diameter ratio (1.1 vs 4.3, p = 0.044) were significantly lower in patients with PSIL than in those with CD with severe mural thickening. No significant difference was observed in enhancement and diffusion measures. Morphologic score was based on the presence of luminal dilatation, unifocal involvement, mesenteric fat infiltration, and luminal stricture, yielding accuracy of 98% for differentiation between PSIL and CD with severe mural thickening. CONCLUSION. Morphologic features seen at MR enterography rather than enhancement or diffusion parameters may be valuable for differentiation of PSIL from active CD with severe mural thickening with significantly lower ratios of upstream to involved luminal diameter and mural thickness to involved luminal diameter in PSIL