On exploiting task duplication in parallel program scheduling

One of the main obstacles in obtaining high performance from message-passing multicomputer systems is the inevitable communication overhead which is incurred when tasks executing on different processors exchange data. Given a task graph, duplication-based scheduling can mitigate this overhead by allocating some of the tasks redundantly on more than one processor. In this paper, we focus on the problem of using duplication in static scheduling of task graphs on parallel and distributed systems. We discuss five previously proposed algorithms and examine their merits and demerits. We describe some of the essential principles for exploiting duplication in a more useful manner and, based on these principles, propose an algorithm which outperforms the previous algorithms. The proposed algorithm generates optimal solutions for a number of task graphs. The algorithm assumes an unbounded number of processors. For scheduling on a bounded number of processors, we propose a second algorithm which controls the degree of duplication according to the number of available processors. The proposed algorithms are analytically and experimentally evaluated and are also compared with the previous algorithms     

Optimizing download time of embedded multimedia objects for Web browsing

Notoriously high delays in accessing Web pages loaded with massive multimedia objects are highly undesirable. Inspired by the requirements of news agencies and other information providers to include multimedia content in their pages, this paper proposes a new solution to the problem of minimizing the Web response time. We consider an environment that consists of a central multimedia repository and various sites physically dispersed. Our approach is based on simultaneous downloading of some of the embedded multimedia objects from the repository, and the rest from the regional servers. We propose a cost model to formalize the relative benefits of the proposed scheme, and design an algorithm that replicates multimedia objects so as to take advantage of concurrency in data transferring. An extensive simulation study evaluates the performance of the proposed replication policy under storage and processing capacity constraints, as well as with various network transfer rates. Comparisons are carried out with alternative schemes.     

Effects of helium massive gas injection level on disruption mitigation on EAST

In this study, NIMROD simulations are performed to investigate the effects of massive helium gas injection level on the induced disruption on EAST tokamak. It is demonstrated in simulations that two different scenarios of plasma cooling(complete cooling and partial cooling) take place for different amounts of injected impurities. For the impurity injection above a critical level, a single MHD activity is able to induce a complete core temperature collapse. For impurity injection below the critical level, a series of multiple minor disruptions occur before the complete thermal quench.     

Comparative study on stress–strain hysteresis response of SAC solder joints under thermal cycles

The present study attempts to evaluate the stress-strain hysteresis responses of SAC solder joints in Resistor and FleXBGA144 packages subjected to thermal cyclic loading using several constitutive models. The total deformation of the solder material consists of elastic, rate-independent plastic and rate-dependent creep components. The constitutive models discussed in this study each weighted elastic, plastic and creep deformations differently. At low stresses SAC solder alloys were found to be creep resistant, where at higher stresses, the influence of different microstructures disappears as matrix-creep dominates in this region. Thus, the proper constitutive model requires all the three ingredients of the elastic, the creep, and the time-independent plastic data for different stress levels to effectively predict the hysteresis behavior of the SAC solder alloys. The hysteresis loops predicted by constitutive models were also found in close agreement with the loops generated by FEM for the SAC solder joint subjected to thermal cycling.     

Comparison of urea clearance in low‐efficiency low‐flux vs. high‐efficiency high‐flux dialyzer membrane with reduced blood and dialysate flow: An in vitro analysis

Rapid removal of small molecules during hemodialysis places an acutely ill patient with kidney failure at an increased risk of hemodynamic instability and for dialysis disequilibrium syndrome. The use of high‐flux, high‐efficiency (HEF) dialyzers may increase this risk despite reductions in blood and dialysate flow. We performed in vitro experiments to compare urea clearance at low dialysate flow and various blood flows using a low‐efficiency low‐flux (LEF) and a HEF membrane. Compared to LEF, there was a significant increase in the clearance of urea at all blood flows with the HEF (all P values < 0.005). HEF dialyzer (F180NR) had higher urea clearance at a blood flow of 150 mL/min than LEF dialyzer (F5) at blood flow of 300 mL/min (144.1 ± 0.99 vs. 130.1 ± 0.001 mL/min for F180 vs. F5, respectively, P < 0.002). Our data suggest that use of HEF dialyzer are not as safe as LEF in high‐risk acute dialysis patients since these are associated with more rapid removal of urea despite reduction in blood and dialysate flow as compared to LEF.     

Design and development of bioinspired calcium phosphate nanoparticles of MTX: pharmacodynamic and pharmacokinetic evaluation

The aim of this investigation is the management of rheumatoid arthritis (RA) by developing methotrexate-loaded calcium phosphate nanoparticles (MTX-CAP-NP) and to evaluate pharmacokinetic and pharmacodynamic behavior in adjuvant induced arthritis model. The nanoparticles were synthesized by wet precipitation method and optimized by Box-Behnken experimental design. MTX-CAP-NPs were characterized by TEM, FTIR, DSC and XRD studies. The particle size, zeta potential and entrapment efficiency of the optimized nanoparticles were found to be 204.90?±?64?nm, ?11.58?±?4.80?mV, and 88.33?±?3.74%, respectively. TEM, FTIR, DSC and XRD studies revealed that the developed nanoparticles were nearly spherical in shape and the crystalline structure of CAP-NP was not changed after MTX loading. The pharmacokinetic studies revealed that MTX-CAP-NP enhanced bioavailability of MTX by 2.6-fold when compared to marketed formulation (FOLITRAX-10). Under pharmacodynamic evaluation, arthritic assessment, radiography and histopathology studies revealed that CAP has ability to regenerate cartilage and bone therefore, together with MTX, MTX-CAP-NPs have shown significant reduction in disease progression. The overall work demonstrated that the developed nanodelivery system was well tolerated and more effective than the marketed formulation.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

New Approaches in Monitoring Multivariate Categorical Processes based on Contingency Tables in Phase II

In some statistical process control (SPC) applications, quality of a process or product is characterized by contingency table. Contingency tables describe the relation between two or more categorical quality characteristics. In this paper, two new control charts based on the WALD and Stuart score test statistics are designed for monitoring of contingency table‐based processes in Phase‐II. The performances of the proposed control charts are compared with the generalized linear test (GLT) control chart proposed in the literature. The results show the better performance of the proposed control charts under small and moderate shifts. Moreover, new schemes are proposed to diagnose which cell corresponding to different levels of categorical variables is responsible for out‐of‐control signal. In addition, we propose EWMA–WALD and EWMA–Stuart score test control charts to improve the performance of Shewhart‐based control charts in detecting small and moderate shifts in contingency table parameters. Meanwhile, we compare the performances of two proposed EWMA‐based control charts with the ones of three existing control charts called EWMA–GLT, EWMA–GLRT and an EWMA‐type control chart for multivariate binomial/multinomial processes along with the ones of the corresponding Shewhart‐based control charts. A numerical example is given to show the efficiency of the proposed methods. Finally, the effect of parameter estimation in Phase I based on m historical contingency table on the performance of the Shewhart‐based control charts is studied. Copyright © 2016 John Wiley & Sons, Ltd.     

Broadband amplifier and high performance tunable laser with an extinction ratio of higher than 60 dB using bismuth oxide-based erbium-doped fiber

A Bi₂O₃-based erbium-doped fiber (Bi-EDF) ring laser with a 70?nm tunable range is demonstrated with a 49?cm long Bi-EDF in which tuning range can be extended to larger than 100?nm using an optical switch to alter the length of Bi-EDF in the laser cavity. With an extinction ratio of better than 60?dB throughout the entire tuning range, the measured FWHM of laser lines are measured to be 0.09?nm. In addition, the common amplification parameters are measured and studied in detail for various pumping configurations.     

New Beta-lactamases in Candidate Phyla Radiation: Owning Pleiotropic Enzymes Is a Smart Paradigm for Microorganisms with a Reduced Genome

The increased exploitation of microbial sequencing methods has shed light on the high diversity of new microorganisms named Candidate Phyla Radiation (CPR). CPR are mainly detected via 16S rRNA/metabarcoding analyses or metagenomics and are found to be abundant in all environments and present in different human microbiomes. These microbes, characterized by their symbiotic/epiparasitic lifestyle with bacteria, are directly exposed to competition with other microorganisms sharing the same ecological niche. Recently, a rich repertoire of enzymes with antibiotic resistance activity has been found in CPR genomes by using an in silico adapted screening strategy. This reservoir has shown a high prevalence of putative beta-lactamase-encoding genes. We expressed and purified five putative beta-lactamase sequences having the essential domains and functional motifs from class A and class B beta-lactamase. Their enzymatic activities were tested against various beta-lactam substrates using liquid chromatography-mass spectrometry (LC-MS) and showed some beta-lactamase activity even in the presence of a beta-lactamase inhibitor. In addition, ribonuclease activity was demonstrated against RNA that was not inhibited by sulbactam and EDTA. None of these proteins could degrade single- and double-stranded-DNA. This study is the first to express and test putative CPR beta-lactamase protein sequences in vitro. Our findings highlight that the reduced genomes of CPR members harbor sequences encoding for beta-lactamases known to be multifunction hydrolase enzymes.