A Contemporary Survey on IoT Based Smart Cities: Architecture,Applications, and Open Issues

Wireless Personal Communications - Internet of Things (IoT) is one of the emerging technologies, which is widely used across the globe. As the idea of a smart city was founded, IoT has been...     

Middleware Technologies for Smart Wireless Sensor Networks towards Internet of Things: A Comparative Review

Wireless Personal Communications - Internet of Things (IoT) offers complex networks of connected devices, which are used to serve in the real-time environment. Interestingly, Wireless Sensor...     

Ionic liquid-based deep eutectic solvents as novel solvent-cum-catalyst media for thermal dehydrogenation of chemical hydrides

The current work explores the usage of novel synthesized Deep Eutectic Solvent (DES) as a catalyst cum solvent media for the thermal dehydrogenation of chemical hydrides, namely Ammonia Borane (AB) and Ethylene diamine bisborane (EDAB). In the first instance, the quantum chemistry based COSMO-SAC (COnductor like Screening MOdel Segment Activity Coefficient) model was used for the selection of the pertinent solvent. 1-Butyl-3-methylimidazolium methanesulfonate: Imidazole ([BMIM][MeSO₃]:[Im]) turned out to be an ideal eutectic mixture with the highest predicted solubility with amine boranes. The DES was synthesized by combining the Hydrogen Bond Acceptor (HBA), namely 1-Butyl-3-methylimidazolium methanesulfonate and Imidazole as Hydrogen Bond Donor (HBD) at a molar ratio of 1:2 and T = 70 °C. The formation of DES was confirmed by recording the NMR spectra. Further, the thermal dehydrogenation study was performed at a vacuum of 4 × 10^?2 mbar (gauge pressure) of AB/DES and EDAB/DES systems at 105 °C, where a hydrogen equivalent of 1.40 and 2.55 was produced, respectively. The residual samples were further analyzed through ¹H NMR analysis for the reaction mechanism and to confirm the role of Ionic Liquid-based DES as catalyst cum solvent media.     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

Efficient Design of Bi-circular Patch Antenna for 5G Communication with Mathematical Calculations for Resonant Frequencies

Wireless Personal Communications - In this paper the conventional circular patch has been reshaped by two circular arcs with the FR4 Epoxy material for substrate. This is supported by the...     

CMV colitis masquerading as colon cancer--an unusual presentation of acquired immunodeficiency syndrome

To determine whether there is any correlation between sudden decrease in barometric pressure and onset of labor, a non-experimental, retrospective study at a 948-bed tertiary care hospital was done. Pregnant patients of 36 weeks gestation or more who presented with spontaneous onset of labor during the 48 hours surrounding the 12 occurrences of significant drop in barometric pressure in 1992 were included in the study. Significantly more occurrences of onset of labor were identified in the 24 hours after a drop in barometric pressure than were identified in the 24 hours prior to the drop in barometric pressure (P < 0.05). Therefore, the overall number of labor onsets increased in the 24 hours following a significant drop in barometric pressure.