Enhanced selection method for genetic algorithm to solve traveling salesman problem

Genetic algorithms (GAs) have been applied by many researchers to get an optimized solution for hard problems such as Traveling Salesman Problem (TSP). The selection method in GA plays a significant role in the runtime to get the optimized solution as well as in the quality of the solution. Stochastic Universal Selection (SUS) is one of the selection methods in GA which is considered fast but it leads to lower quality solution.Although using Rank Method Selection (RMS) may lead to high quality solution, it has long runtime.In this work, an enhanced selection method is presented which maintains both fast runtime and high solution quality.First, we present a framework to solve TSP using GA with the original selection method SUS. Then, the SUS is replaced by the proposed enhanced selection method.The experimental results show that a better quality solution was obtained by using the proposed enhanced selection method compared to the original SUS

Quality of life in children treated for craniopharyngiomas

Craniopharyngiomas are common but complex paediatric brain lesions that present interesting management challenges. Quality of life is an important consideration while choosing management options. In this review, we have discussed the existing literature on various aspects of quality of life in patients treated for craniopharyngioma, assessed by variety of measurement tools

Mitochondrial myopathy presenting as fibromyalgia: a case report

<p>Abstract</p> <p>Introduction</p> <p>To the best of our knowledge, we describe for the first time the case of a woman who met the diagnostic criteria for fibromyalgia, did not respond to therapy for that disorder, and was subsequently diagnosed by biochemical and genetic studies with a mitochondrial myopathy. Treatment of the mitochondrial myopathy resulted in resolution of symptoms. This case demonstrates that mitochondrial myopathy may present in an adult with a symptom complex consistent with fibromyalgia.</p> <p>Case presentation</p> <p>Our patient was a 41-year-old Caucasian woman with symptoms of fatigue, exercise intolerance, headache, and multiple trigger points. Treatment for fibromyalgia with a wide spectrum of medications including non-steroidal anti-inflammatory drugs, antidepressants, gabapentin and pregabalin had no impact on her symptoms. A six-minute walk study demonstrated an elevated lactic acid level (5 mmol/L; normal < 2 mmol/L). Biochemical and genetic studies from a muscle biopsy revealed a mitochondrial myopathy. Our patient was started on a compound of coenzyme Q10 (ubiquinone) 200 mg, creatine 1000 mg, carnitine 200 mg and folic acid 1 mg to be taken four times a day. She gradually showed significant improvement in her symptoms over a course of several months.</p> <p>Conclusions</p> <p>This case demonstrates that adults diagnosed with fibromyalgia may have their symptom complex related to an adult onset mitochondrial myopathy. This is an important finding since treatment of mitochondrial myopathy resulted in resolution of symptoms.</p

Metabolic myopathy presenting with polyarteritis nodosa: a case report

<p>Abstract</p> <p>Introduction</p> <p>To the best of our knowledge, we describe for the first time a patient in whom an unusual metabolic myopathy was identified after failure to respond to curative therapy for a systemic vasculitis, polyarteritis nodosa. We hope this report will heighten awareness of common metabolic myopathies that may present later in life. It also speculates on the potential relationship between metabolic myopathy and systemic vasculitis.</p> <p>Case presentation</p> <p>A 78-year-old African-American woman with a two-year history of progressive fatigue and exercise intolerance presented to our facility with new skin lesions and profound muscle weakness. Skin and muscle biopsies demonstrated a medium-sized artery vasculitis consistent with polyarteritis nodosa. Biochemical studies of the muscle revealed diminished cytochrome C oxidase activity (0.78 μmol/minute/g tissue; normal range 1.03 to 3.83 μmol/minute/g tissue), elevated acid maltase activity (23.39 μmol/minute/g tissue; normal range 1.74 to 9.98 μmol/minute/g tissue) and elevated neutral maltase activity (35.89 μmol/minute/g tissue; normal range 4.35 to 16.03 μmol/minute/g tissue). Treatment for polyarteritis nodosa with prednisone and cyclophosphamide resulted in minimal symptomatic improvement. Additional management with a diet low in complex carbohydrates and ubiquinone, creatine, carnitine, folic acid, α-lipoic acid and ribose resulted in dramatic clinical improvement.</p> <p>Conclusions</p> <p>Our patient's initial symptoms of fatigue, exercise intolerance and progressive weakness were likely related to her complex metabolic myopathy involving both the mitochondrial respiratory chain and glycogen storage pathways. Management of our patient required treatment of both the polyarteritis nodosa as well as metabolic myopathy. Metabolic myopathies are common and should be considered in any patient with exercise intolerance. Metabolic myopathies may complicate the management of various disease states.</p

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A Comparative Analysis of Camera, LiDAR and Fusion Based Deep Neural Networks for Vehicle Detection

Self-driving cars are an active area of interdisciplinary research spanning Artificial Intelligence (AI), Internet of Things (IoT), embedded systems, and control engineering. One crucial component needed in ensuring autonomous navigation is to accurately detect vehicles, pedestrians, or other obstacles on the road and ascertain their distance from the self-driving vehicle. The primary algorithms employed for this purpose involve the use of cameras and Light Detection and Ranging (LiDAR) data. Another category of algorithms consists of a fusion between these two sensor data. Sensor fusion networks take input as 2D camera images and LiDAR point clouds to output 3D bounding boxes as detection results. In this paper, we experimentally evaluate the performance of three object detection methods based on the input data type. We offer a comparison of three object detection networks by considering the following metrics - accuracy, performance in occluded environment, and computational complexity. YOLOv3, BEV network, and Point Fusion were trained and tested on the KITTI benchmark dataset. The performance of a sensor fusion network was shown to be superior to single-input networks.  Full Tex

A Comparative Analysis of Camera, LiDAR and Fusion Based Deep Neural Networks for Vehicle Detection

Self-driving cars are an active area of interdisciplinary research spanning Artificial Intelligence (AI), Internet of Things (IoT), embedded systems, and control engineering. One crucial component needed in ensuring autonomous navigation is to accurately detect vehicles, pedestrians, or other obstacles on the road and ascertain their distance from the self-driving vehicle. The primary algorithms employed for this purpose involve the use of cameras and Light Detection and Ranging (LiDAR) data. Another category of algorithms consists of a fusion between these two sensor data. Sensor fusion networks take input as 2D camera images and LiDAR point clouds to output 3D bounding boxes as detection results. In this paper, we experimentally evaluate the performance of three object detection methods based on the input data type. We offer a comparison of three object detection networks by considering the following metrics - accuracy, performance in occluded environment, and computational complexity. YOLOv3, BEV network, and Point Fusion were trained and tested on the KITTI benchmark dataset. The performance of a sensor fusion network was shown to be superior to single-input networks.  Full Tex

Initial experience of video capsule endoscopy at a tertiary center in Saudi Arabia

Background/Aim: No prior experience with video capsule endoscopy (VCE) has been published from Saudi Arabia. In this study, we aim to report the first Saudi experience with VCE. Patients and Methods: A prospective study was conducted between March 2013 and September 2017 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Eligible patients underwent VCE and their data (age, sex, indication for VCE, type of obscure gastrointestinal bleeding [OGIB: overt vs occult], VCE findings, and complications) were recorded. Approval was obtained from the institutional ethics board before the study began and all patients provided verbal and signed consent for the procedure. The procedure was performed according to the established guidelines. Results: During the study period, a total 103 VCE procedures were performed on 96 patients. Overall, 60 participants (62.5%) were male (mean age, 58.8 years; range, 25–97 years) and 36 (37.5%) were female (mean age, 52.8 years; range, 18–78 years). The most frequent indication for VCE was OGIB (n = 91, 88.35%; overt, n = 46, 50.55%; occult, n = 45, 49.45%). Other indications were suspected Crohn's disease (n = 4, 3.88%), suspected complicated celiac disease (n = 4, 3.88%), and unexplained chronic abdominal pain (n = 4, 3.88%). The VCE results were categorized as incomplete (n = 2, 1.94%), poor-quality (n = 7; 6.8%), normal (n = 39, 37.86%), and abnormal (n = 55, 53.4%). The completion rate was 98.06% (n = 101), and the overall diagnostic yield was 53.4%. Of the 55 patients with abnormal VCE results, 43 (78.2%) had small bowel (SB) abnormalities and 12 (21.8%) had abnormalities in the proximal or distal gut. The most frequent SB abnormalities were angiodysplasia (n = 22, 40.0%) and tumors (n = 7, 12.7%). Conclusion: The diagnostic yield of VCE for Saudi patients with OGIB is comparable to that reported internationally; however, data for other VCE indications, including inflammatory bowel disease, are still lacking