Atypical case of retroperitoneal paraganglioma parasympaticum coexisting with recurrent bleeding from upper gastrointestinal tract

The authors report a case of 47 years old male who was treated for 1,5 year because of recurrent bleedings from upper GIT. Performed examinations showed the presence of retroperitoneal paraganglioma parasympaticum with multiple metastases in bones. A Zollinger-Ellison syndrome was suspected. The final correct diagnosis was established at last microscopically after surgical excision of the specimens.     

High temperature anti‐oxidation behavior of in situ and ex situ nanostructured C/SiC/ZrB2‐SiC gradient coatings: Thermodynamical evolution,microstructural characterization,and residual stress analysis

Nanostructured C/SiC/ZrB₂–SiC oxidation protective gradient coating was prepared by a two‐step reactive melt infiltration method. In order to reduce production cost, ZrB₂ phase was synthesized by the in situ reactive that included low‐cost ZrO₂ and B₂O₃ powders as raw materials. High‐temperature oxidation behavior of coatings was evaluated by isothermal oxidation test at 1773 K in air for 10 hours. Thermodynamical behavior of the coatings at various temperatures during oxidation test and coating process was predicted by HSC Chemistry 6.0 software. Compressive residual stresses of 36.9 MPa and 41 MPa were calculated for in situ and ex situ coatings by Williamson‐Hall method. After 10 hours of isothermal oxidation at 1773K, in situ and ex situ coatings showed 12.84% and 15.69% of weight losses with oxidation rates of 1.87 × 10^?2 g cm^?3 h^?1 and 0.91 × 10^?2 g cm^?3 h^?1, respectively. These results indicated that the oxidation protection ability of the coating produced by the in situ method was very close to ex situ coating.     

Improving the reliability of Byzantine fault‐tolerant distributed software‐defined networks

This paper presents a method to improve the reliability and fault tolerance of distributed software‐defined networks. This method is called “BIRDSDN (Byzantine‐Resilient Improved Reliable Distributed Software‐Defined Networks).” In BIRDSDN, a group communication is implemented among the controllers of the whole clusters. This method can detect the crash failure and Byzantine failure of any controller and undertakes a fast detection and recovery scheme to select the controllers to take over the orphan switches. BIRDSDN takes into account the reliability of the nodes considering the failure probability of intracluster and intercluster links, topology, load, and latency. The numerical results show that this approach performs better than the other approaches regarding failure detection, recovery, latency, throughput, reliability, and packet loss.     

Salicylic acid nanoparticles (SANPs) improve growth and phytoremediation efficiency of Isatis cappadocica Desv., under As stress

Arsenic (As) is a toxic metalloid dispersed in the environment and it cause serious toxicity to plants. Salicylic acid (SA) plays an important role in many plant growth processes involved in plant defence against heavy metal or metalloid stress. In the present study, for the first time, chitosan nanoparticles was synthesised, loaded by SA and the positive role of SA on growth and phytoremediation efficiency of Isatis cappadocica against As toxicity were evaluated. The highest arsenate treatment (1200 µM) caused a decrease in plant biomass that, however, its combined application with salicylic acid nanoparticles (SANPs) substantially increase in shoot height, root length and their biomass production compared with As stressed plants. The pretreatment of SANPs by increasing arsenate supply, simultaneously increased the As concentration in roots and shoots of I. cappadocica which reached a maximum of 705 and 1188 mg/kg, respectively. This results suggest that high levels of As stress induce stress status in I. cappadocica which SANPs pretreatment application limit these toxic effects of As. Therefore, SANPs has a significant beneficial effect on the growth and phytoremediation efficiency of I. cappadocica subjected to As stress.Inspec keywords: nanoparticles, nanobiotechnology, botany, toxicology, arsenic, biological techniques, polymersOther keywords: salicylic acid nanoparticles, SANP, plant growth efficiency, phytoremediation efficiency, Isatis cappadocica Desv, arsenic stress, toxic metalloid, plant toxicity, plant defence, metalloid stress, chitosan nanoparticles, plant biomass, shoot height, root length, biomass production, I. cappadocica, As     

Hybrid multi-verse optimizer with grey wolf optimizer for power scheduling problem in smart home using IoT

The Journal of Supercomputing - The power scheduling problem in smart home (PSPSH) is one of the complex NP-hard scheduling problems, where it has a deep and rugged search space due to the high...     

Mapping urban land cover based on spatial-spectral classification of hyperspectral remote-sensing data

In this article, an innovative classification framework for hyperspectral image data, based on both spectral and spatial information, is proposed. The main objective of this method is to improve the accuracy and efficiency of high-resolution land-cover mapping in urban areas. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MMSF) algorithm. A pixel-based support vector machine (SVM) algorithm is first used to classify the hyperspectral image data, then the enhanced MMSF algorithm is applied in order to increase the accuracy of less accurately classified land-cover types. The enhanced MMSF algorithm is used as a binary classifier. These two classes are the low-accuracy class and remaining classes. Finally, the SVM algorithm is trained for classes with acceptable accuracy. In the proposed approach, namely MSF-SVM, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithms, and are then used to build the MSF. Three benchmark hyperspectral data sets are used for the assessment: Berlin, Washington DC Mall, and Quebec City. Experimental results demonstrate the superiority of the proposed approach compared with SVM and the original MMSF algorithms. It achieves approximately 5, 6, and 7% higher rates in kappa coefficients of agreement in comparison with the original MMSF algorithm for the Berlin, Washington DC Mall, and Quebec City data sets, respectively.     

Semi fractal three leaf clover‐shaped CPW antenna for triple band operation

This article presents a unique and compact coplanar waveguide (CPW) antenna that exhibits triband operation with circular polarization. The single antenna was designed to operate simultaneously in the following bands: WiMAX (3.3–3.6 GHz), wireless local area network (WLAN) (5.15–5.825 GHz), ITS (5.795–6.400 GHz), and ITU‐R (7.725–8.5 GHz). The realization of the triband antenna was achieved by using two semi fractal ring patches resembling the shape of a three leaf clover, and by introducing a pair of symmetrical L‐shaped slits in its ground plane. The antenna's physical parameters were investigated to fully understand their affect on the antenna's performance. The salient parameters obtained from this analysis enabled the optimization of the antenna's overall characteristics. The design concept was confirmed by fabricating the antenna prototype and measuring its characteristics. The proposed antenna has dimensions of 20 × 20 × 1 mm³. Measured results show the antenna exhibits circular polarization in WiMAX and ITU‐R bands, and linear polarization in the WLAN band. The antenna radiates omnidirectionally in the H‐plane, and approximately bidirectionally in the E‐plane. In addition, the antenna presents stable gain over the triband. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:413–418, 2015.     

Distributed faulty node detection and recovery scheme for wireless sensor networks using cellular learning automata

Wireless Networks - In a wireless sensor network (WSN), there is always the possibility of failure in sensor nodes. Quality of Service (QoS) of WSNs is highly degraded due to the faulty sensor...     

Energy‐delay‐aware caching strategy in green CCN using markov approximation

One of the basic challenges in content‐centric networking (CCN) is how to optimize the overall energy consumption of content transmission and caching. Furthermore, designing an appropriate caching policy that considers both energy consumption and quality of service (QoS) is a major goal in green CCN. In this paper, the problem of minimizing the total CCN energy consumption while being aware of the end‐to‐end delay is formulated as an integer linear programming model. Since it is an Non‐deterministic Polynomial‐time (NP)‐hard problem, the Markov approximation method for an energy‐delay aware caching strategy (MAEDC) is proposed through a log‐sum‐exp function to find a near‐optimal solution in a distributed manner. The numerical results show that the MAEDC achieves near‐optimal energy consumption with better delay profile compared with the optimal solution. Moreover, due to the possibility of distributed and parallel processing, the proposed method is proper for the online situation where the delay is a crucial issue.     

Design and fabrication of a new high gain multilayer negative refractive index metamaterial antenna for X‐band applications

This article presents the design of a planar high gain and wideband antenna using a negative refractive index multilayer superstrate in the X‐band. This meta‐antenna is composed of a four‐layer superstrate placed on a conventional patch antenna. The structure resonates at a frequency of 9.4 GHz. Each layer of the metamaterial superstrate consists of a 7 × 7 array of electric‐field‐coupled resonators, with a negative refractive index of 8.66 to 11.83 GHz. The number of layers and the separation of superstrate layers are simulated and optimized. This metamaterial lens has significantly increased the gain of the patch antenna to 17.1 dBi. Measurements and simulation results proved about 10 dB improvement of the gain.