String Cosmology in Anisotropic Bianchi-II Space-time

The present study deals with a spatially homogeneous and anisotropic Bianchi-II cosmological model representing massive strings. The energy-momentum tensor, as formulated by Letelier (1983), has been used to construct a massive string cosmological model for which the expansion scalar is proportional to one of the components of shear tensor. The Einstein's field equations have been solved by applying a variation law for generalized Hubble's parameter that yields a constant value of deceleration parameter in Bianchi-II space-time. A comparative study of accelerating and decelerating modes of the evolution of universe has been carried out in the presence of string scenario. The study reveals that massive strings dominate the early Universe. The strings eventually disappear from the Universe for sufficiently large times, which is in agreement with the current astronomical observations.Comment: 11 pages, 6 figures (To appear in Mod. Phys. Lett. A) In this version, the cosmic string has been directed along z-direction and the resultant field equations have been solved exactl

ESTIMATION OF ENTRANCE SURFACE RADIATION DOSE TO THYROID REGION IN COMPUTED TOMOGRAPHY BRAIN EXAMINATION

Objective: The objective of this study was to estimate the entrance surface radiation dose to the thyroid region in a computed tomography (CT) brain scan.Methods: Unfors Multi-O-Meter equipment was used to measure the entrance surface at the thyroid region of adult patients ranging from 18 to 70 years of age. A total of 115 patients were included in the study based on convenience sampling. The Multi-O-Meter was kept at the thyroid region during the scan, and the values for entrance surface dose (ESD) were noted from its monitor after the scan was complete.Results: The obtained data were analyzed and violate normal distribution; therefore, the median and quartiles were computed. The overall median (Q1, Q2), ESD of the patients, was 1.335 (1.213, 1.529) mGy. The minimum and maximum dose values recorded were 1.015 mGy and 1.964 mGy, respectively.Conclusions: The result showed a significant amount of entrance surface radiation dose to the thyroid region while taking a brain scan. This data can be used for optimization of radiation protection while undergoing CT scans of brain to reduce exposure to thyroid region

Temporary cardiac pacing induced electrocardiographic changes simulating myocardial infarction

Temporary transvenous pacing is an immediate lifesaving measure in patients with Stokes-Adams syndrome and in patients with symptomatic bradycardia. Bradyarrhythmias are known to occur in acute myocardial infarction. But in a paced heart, it is difficult to diagnose myocardial infarction from electrocardiogram (ECG) because pacemaker rhythm causes distortion of natural wave forms. On the other hand, remarkable T wave inversions and ST depressions do occur in the ventricular paced ECG as secondary changes. The case report describes a patient who developed profound de novo T wave inversions and ST depressions in the unpaced ECG following temporary transvenous pacing simulating MI

Effective Image Clustering with Differential Evolution Technique

The paper presents a novel approach of clustering image datasets with differential evolution (DE) technique. The differential evolution is a parallel direct search population based optimization method. From our simulations it is found that DE is able to optimize the quality measures of clusters of image datasets. To claim the superiority of DE based clustering we have compared the outcomes of DE with the classical K-means and popular Particle Swarm Optimization (PSO) algorithms for the same datasets. The comparisons results reveal the suitability of DE for image clustering in all image datasets

Energy Aware Genetic Algorithm for Independent Task Scheduling in Heterogeneous Multi-Cloud Environment

Cloud datacentres contain a vast number of processors. The rapid expansion of cloud computing is resulting in massive energy usage and carbon emissions which has reported a substantial increase day by day. Consequently, the cloud service providers are looking for eco-friendly solutions. The energy consumption can be evaluated with an energy model, which identifies that, server energy consumption scales linearly with resource (cloud) utilization. This research provides an alternate solution to task scheduling problem which designs an optimized task schedule to minimize the makespan and energy consumptions in cloud datacenters. The proposed method is based on the principle of Genetic Algorithm (GA). In the context of task-scheduling using GA, chromosomal representation is considered as a schedule of set of independent tasks mapped with available cloud or machine in the proposed methodology. A fitness function is taken to optimize the overall execution time or makespan. Energy consumption is evaluated based on minimum makespan value. The proposed technique also tested upon synthesized and benchmark dataset which outperforms the conventional cloud task scheduling algorithms like Min-Min, Max-Min, and suffrage heuristics in heterogeneous multi-cloud system

Clinical and etiological spectrum of prolonged fever and special reference to HIV patients at a tertiary care centre

Background: Prolonged fever is a diagnostic challenge and will tend to remain so in times to come because of the changing spectrum of etiologies and influence of technology, environmental changes, and many other ill-understood factors which influence the etiological spectrum. Prolonged fever is also undergoing change in its duration. The aim of the present was study to determine the etiologies of prolonged fever in patients in India and to evaluate the clinical and etiological relationship between the diagnosis and patient’s laboratory data.Methods: Patients aged more 13 years with fever >38.3ºC for more than three weeks without apparent source after preliminary investigations were included prospectively over a period of twenty two months. Fever duration, symptom, signs, laboratory investigations and final diagnosis were recorded. The distribution of etiologies and age, fever duration, laboratory examinations, and associated symptoms and signs were analyzed.Results: Out of total of 86 patients were enrolled, fifty one (59.3%) were men. The median age was 28 years (range, 13-65 yr). Among 86 patients, diagnosis could be made in only 69 (80.2%) patients. Infections, neoplasms, NIIDs, miscellaneous causes were responsible for prolonged fever in 42 (48.8%), 18 (20.9%), 6 (7%), and 3 (3.5%) patients respectively. Seveteen (19.8%) cases remained undiagnosed, even after relevant investigations, six of them recovered spontaneously. Tuberculosis (TB) was the cause of prolonged fever in 21 (24.4%) patients.Conclusions: Infections, amongst which tuberculosis, remain the major cause of prolonged fever and its subset: fever of unknown origin (FUO), in this country. The percent of undiagnosed cases appears to be identical worldwide

Efficient Behavior-aware Control of Automated Vehicles at Crosswalks using Minimal Information Pedestrian Prediction Model

For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians’ crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future pedestrian behaviors. In this paper, we present a Behavior aware Model Predictive Controller (B-MPC) for AVs that incorporates long-term predictions of pedestrian crossing behavior using a previously developed pedestrian crossing model. The model incorporates pedestrians’ gap acceptance behavior and utilizes minimal pedestrian information, namely their position and speed, to predict pedestrians’ crossing behaviors. The BMPC controller is validated through simulations and compared to a rule-based controller. By incorporating predictions of pedestrian behavior, the B-MPC controller is able to efficiently plan for longer horizons and handle a wider range of pedestrian interaction scenarios than the rule-based controller. Results demonstrate the applicability of the controller for safe and efficient navigation at crossing scenarios.Automotive Research Center (ARC) at the University of Michigan, with funding from government contract DoD-DoA W56HZV14-2-0001, through the U.S. Army Combat Capabilities Development Command (CCDC) /Ground Vehicle Systems Center (GVSC).National Science FoundationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154113/1/Jayaraman_etal_ACC_2020__Behavior_aware_controller_final.pdfDescription of Jayaraman_etal_ACC_2020__Behavior_aware_controller_final.pdf : MainFil

Analysis and Prediction of Pedestrian Crosswalk Behavior during Automated Vehicle Interactions

For safe navigation around pedestrians, automated vehicles (AVs) need to plan their motion by accurately predicting pedestrians’ trajectories over long time horizons. Current approaches to AV motion planning around crosswalks predict only for short time horizons (1-2 s) and are based on data from pedestrian interactions with human-driven vehicles (HDVs). In this paper, we develop a hybrid systems model that uses pedestrians’ gap acceptance behavior and constant velocity dynamics for long-term pedestrian trajectory prediction when interacting with AVs. Results demonstrate the applicability of the model for long-term (> 5 s) pedestrian trajectory prediction at crosswalks. Further, we compared measures of pedestrian crossing behaviors in the immersive virtual environment (when interacting with AVs) to that in the real world (results of published studies of pedestrians interacting with HDVs), and found similarities between the two. These similarities demonstrate the applicability of the hybrid model of AV interactions developed from an immersive virtual environment (IVE) for real-world scenarios for both AVs and HDVs.Toyota Research Institute (TRI) provided funds to assist the authors with their research, but this article solely reflects the opinions and conclusions of its authors and not TRI or any other Toyota entity. The work was also supported in part by the National Science Foundation and supported in part by the Automotive Research Center at the University of Michigan, with funding from government contract Department of the Army W56HZV- 14-2-0001 through the U.S. Army Tank Automotive Research, Development, and Engineering Center (TARDEC).Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154053/1/ICRA_2020_Analysis_and_Prediction_of_Pedestrian_Final_revised_03_03_20.pdfDescription of ICRA_2020_Analysis_and_Prediction_of_Pedestrian_Final_revised_03_03_20.pdf : Main fil