Selection of suitable model for different matrices of raw materials used in supercritical fluid extraction process

Supercritical fluid extraction (SFE) process is the sustainable green process for the extraction. Mathematical modeling of SFE process is carried out using mass transfer resistances, which vary with the types of solute. In this paper, the effect of matrices such as leaves, flower concrete, flower bud, herb plant, shrub seed and vegetable matter is studied on extraction yield through different models. These models are solved using COMSOL Multiphysics 5.2 solver and results are validated with that of literature. Experimental data of each type of solute matrix are fitted in various models and best suited model is predicted.     

A cost‐effective attack matrix based key management scheme with dominance key set for wireless sensor network security

To guarantee the proper functionality of wireless sensor network even in the presence of the potential threats, a well‐designed key management scheme is very important. The assumptions about attackers critically influence the performance of security mechanisms. This paper investigates the problem of node capture from adversarial view point in which the adversary intelligently exploits the different vulnerabilities of the network to establish a cost‐effective attack matrix. To counteract such attacks, the defender or the network designer constructs similar attack matrix. The defender will identify a set of critical nodes and use the key compromise relationship to assign a key dominance rank to each node of the network. The key dominance rank quantifies the possibility of attack on a particular node. It is used to determine the hash chain length. It is also used to improve the security of path key establishment as well as rekeying of the proposed scheme. The performance of the proposed scheme is analyzed with other existing schemes, and it is shown that it outperforms with increased resilience against node capture, reduced number of hash computations, reduced key compromise probability of proxy nodes, and reduced number of revoked links during rekeying process.     

Salt‐leaching technique for the synthesis of porous poly(2,5‐benzimidazole) (ABPBI) membranes for fuel cell application

The first instance of synthesizing porous poly(2,5‐benzimidazole) (ABPBI) membranes for high‐temperature polymer electrolyte membrane fuel cells (HT‐PEMFCs), using solvent evaporation/salt‐leaching technique, is reported herein. Various ratios of sodium chloride/ABPBI were dissolved in methanesulfonic acid and cast into membranes by solvent evaporation, followed by porogen (salt) leaching by water washing. The membranes were characterized using SEM, FTIR, TGA, and DSC. The proton conductivity, water and acid uptake of the membranes were measured and the chemical stability was determined by Fenton's test. SEM images revealed strong dependence of sizes and shapes of pores on the salt/polymer ratios. Surface porosities of membranes were estimated with Nis Elements‐D software; bulk porosities were measured by the fluid resaturation method. Thermogravimetric analysis showed enhanced dopant uptake with introduction of porosity, without the thermal stability of the membrane compromised. Incorporating pores enhanced solvent uptake and retention because of capillarity effects, enhancing proton conductivities of PEMs. Upon acid doping, a maximum conductivity of 0.0181 S/cm was achieved at 130 °C for a porous membrane compared with 0.0022 S/cm for the dense ABPBI membrane at the same temperature. Results indicated that with judicious optimization of porogen/polymer ratios, porous ABPBI membranes formed by salt‐leaching could be suitably used in HT‐PEMFCs. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45773.     

Efficient Route Selection Scheme in MANET Using Enhanced AODV Protocol

Mobile Ad Hoc network comprises of mobile nodes communicating over wireless medium. Due to ease of communication and flexibility, MANET has become an active area of research in wireless communication. However, issues such as limited battery capacity, dynamic topology and node mobility cause frequent link breakage due to which reroute discovery process is required to be initiated resulting in increase in latency and routing overheads. Many research works have been carried out for improvement of an existing routing scheme, however they do not scale-up well to provide stable and energy efficient route. This paper introduces a novel routing algorithm ENH-AODV (Enhanced AODV) that focuses on selection of an efficient route on the basis of quality of both links and nodes impending during route discovery process. In addition, each node maintains a list, consisting of details of nearby nodes with good energy level through hello mechanism. Simulation is carried out over network simulator and results prove that the proposed scheme is more effective and advantageous than AODV in terms of normalized routing load, end to end delay, packet delivery ratio and throughput.

     

Decision Tree-Based Entries Reduction scheme using multi-match attributes to prevent flow table overflow in SDN environment

The software-defined networking is used extensively in data centers that provide centralized control for the widely deployed networking resources. The traffic is shaped by rules created by the controller dynamically without modifying the individual switch. The key component that stores rules which are used to process the flows is the flow table which resides in the ternary content addressable memory. The current commercial OpenFlow appliances accommodate limited entries up to 8000 due to its high cost and high power consumption. There are two issues to be considered, where (1) flow table's inability to provide rules during flow table overflow leads to dropping of incoming packets and (2) the significant amount of rule replacement occurs when the traffic in data centers increases which creates massive route requests to controller creating overhead. The proposed scheme prevents flow table overflow using the robust machine learning algorithm called decision tree (Iterative Dichotomiser 3) that allows the flow table to learn its high prioritized fine-grained entries by means of multiple matching attributes. The entries are classified, and the usual eviction process is replaced by pushing the low important entries into counting bloom filter which acts as a cache to prevent flow entry miss. The simulations were carried out using real-time network traffic datasets, and the comparisons with the various existing schemes prove that the proposed approach reduces 99.99% of the controller's overhead and the entries are minimized to 99% providing extra space for new flows.     

Insider attack mitigation in a smart metering infrastructure using reputation score and blockchain technology

International Journal of Information Security - The increasing use of smart metering infrastructure invites security threats through trusted insiders in spite of the devices’ authentication...     

Current Technology of Supercapacitors: A Review

A supercapacitor is a solid-state device that can store electrical energy in the form of charges. It represents an advancement in the field of energy storage, as it overcomes many of the shortcomings of batteries. This paper presents an overview of the various types of supercapacitors, electrode materials, and electrolytes, and the future of supercapacitors. Due to their high storage capacity, supercapacitors are commonly used in portable electronic devices such as MP3 players and mobile phones, and in hybrid vehicles and other applications. In electrical and hybrid vehicles, supercapacitors are increasingly used as provisional energy storage for regenerative braking. Various materials are used in electrodes to boost the performance of the supercapacitor. This review presents details regarding the materials and electrolyte, and the improvements in the field of supercapacitors.     

Inhibitory effect of TiO2 NPs on symbiotic arbuscular mycorrhizal fungi in plant roots

While nanoparticles (NPs) are known to exhibit antimicrobial properties, their effects on symbiotic arbuscular mycorrhizal fungi (AMF) in plant roots has to be carefully examined as NPs particularly of titanium dioxide (TiO₂) reach plant roots through varied sources such as fertilisers, plant protection products and other nanoproducts. The objective of the present study is to assess the effect of TiO₂ NPs on the symbiotic behaviour of AMF colonising rice (Oryza sativa L.) plants. Using sol–gel method, TiO₂ NPs with three different sizes were successfully synthesised employing doping. Characterisation of the prepared material was done by X‐ray powder diffraction and scanning electron microscopy. The synthesised materials were applied at 0, 25, 50 and 100 mg plant–1 to the rhizosphere of mycorrhizal rice plants maintained in pots. The study revealed that the prepared NPs had an inhibitory effect on arbuscular mycorrhizal symbiosis in plant roots. Development of AMF structures such as vesicles and arbuscules was significantly reduced in TiO₂ ‐doped NPs with a relatively more inhibition in 2% TiO₂ ‐doped NPs. Among the concentrations of TiO₂ NPs applied to different treatments, %F was significantly (P < 0.001) affected at medium to higher levels of application.Inspec keywords: nanoparticles, titanium compounds, antibacterial activity, sol‐gel processing, X‐ray diffraction, scanning electron microscopy, microorganisms, cellular biophysics, nanomedicineOther keywords: symbiotic arbuscular mycorrhizal fungi, plant roots, nanoparticles, antimicrobial properties, fertilisers, plant protection, nanoproducts, AMF colonising rice, sol‐gel method, X‐ray powder diffraction, scanning electron microscopy, mycorrhizal rice plants, rhizosphere, arbuscular mycorrhizal symbiosis, soil biota, TiO₂      

Wireless sensor networks: a survey on recent developments and potential synergies

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future. Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.     

Development of balloon-borne impactor payload for profiling free tropospheric aerosol

Size-segregated aerosol vertical profiles in the troposphere are critically important for source attribution, transformation processes, atmospheric stability, and radiative forcing. For the first time, the development of a 6-stage impactor for real-time balloon-borne measurements of size-segregated (cutoff diameter [D_ae]: 0.15–5?µm) aerosol mass concentrations in the free troposphere was tested during spring 2016 over Hyderabad, India, is presented. Total aerosol mass concentrations obtained with the 6-stage impactor (M_TI) and a co-located optical particle counter (M_TOPC) measurements at the surface under ambient conditions agreed to within 15%. The effect of aerosol particle growth on the M_TI data are assessed using an urban aerosol particle model by scaling mass concentration of water-soluble (hydrophilic) aerosol particles at ambient relative humidity (RH) to that at RH = 50%. An overall uncertainty of the measurement of the M_TI was estimated to be about 19%. The altitude variation of size-segregated mass concentrations of aerosol particles along with thermodynamic variables depicted convectively well-mixed layer extending up to about 4.5?km within which aerosol particles showed two distinct layers, one at ～2?km and another at about 4.5?km. The size-resolved air samples containing aerosol particles collected using the balloon-borne 6-stage impactor will be useful for their chemical characterization and also long-range transport studies.

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