Flower‐shaped ultra‐wideband fractal antenna

A flower‐shaped ultra‐wideband fractal antenna is presented. It comprises a fourth iterative flower‐shaped radiator, asymmetrical stub‐loaded feeding line, and coplanar quarter elliptical ground planes. A wide operating band of 12.12 GHz (4.58‐16.7 GHz) for S ₁₁ ≤ ? 10 dB is achieved along with an overall antenna footprint of 15.7 × 11.4 mm². In addition, other desirable characteristics, that is, omnidirectional radiation patterns, peak gain upto 5 dB, and fidelity factor more than 75% are achieved. A good agreement exists between the simulation and measured results. The obtained results illustrate that this antenna has wide operating range and compact dimensions than available structures.     

An energy-efficient cloud system with novel dynamic resource allocation methods

The Journal of Supercomputing - In the last decade, cloud computing has brought enormous changes to people’s lives. Cloud computing gives a client-driven computational model. In this case,...     

In vivo evaluation of a mucoadhesive polymeric caplet for intravaginal anti-HIV-1 delivery and development of a molecular mechanistic model for thermochemical characterization

Context and objective: The aim of this study was to develop, characterize and evaluate a mucoadhesive caplet resulting from a polymeric blend (polymeric caplet) for intravaginal anti-HIV-1 delivery.

Materials and methods: Poly(lactic-co-glycolic) acid, ethylcellulose, poly(vinylalcohol), polyacrylic acid and modified polyamide 6, 10 polymers were blended and compressed to a caplet-shaped device, with and without two model drugs 3′-azido-3′-deoxythymidine (AZT) and polystyrene sulfonate (PSS). Thermal analysis, infrared spectroscopy and microscopic analysis were carried out on the caplets employing temperature-modulated DSC (TMDSC), Fourier transform infra-red (FTIR) spectrometer and scanning electron microscope, respectively. In vitro and in vivo drug release analyses as well as the histopathological toxicity studies were carried out on the drug-loaded caplets. Furthermore, molecular mechanics (MM) simulations were carried out on the drug-loaded caplets to corroborate the experimental findings.

Results and discussion: There was a big deviation between the T_g of the polymeric caplet from the T_g's of the constituent polymers indicating a strong interaction between constituent polymers. FTIR spectroscopy confirmed the presence of specific ionic and non-ionic interactions within the caplet. A controlled near zero-order drug release was obtained for AZT (20 d) and PSS (28 d). In vivo results, i.e. the drug concentration in plasma ranged between 0.012–0.332?mg/mL and 0.009–0.256?mg/mL for AZT and PSS over 1–28 d.

Conclusion: The obtained results, which were corroborated by MM simulations, attested that the developed system has the potential for effective delivery of anti-HIV-agents.     

Effect of Temperature on Reliability Issues of Ferroelectric Dopant Segregated Schottky Barrier Tunnel Field Effect Transistor (Fe DS-SBTFET)

This paper addresses reliability issues associated with temperature of Ferroelectric Dopant Segregated Schottky Barrier Tunnel Field Effect Transistor (Fe DS-SBTFET). The simulated results are compared with Dopant Segregated Schottky Barrier TFET (DS-SBTFET). This is achieved by varying the operating temperature from 300 to 500 K. DC parameters such as I_ON/I_OFF ratio, drain current characteristics and subthreshold swing (SS) for a range of temperature have been highlighted. Moreover, the influence of temperature on various RF figure of merits such as gate capacitance (C_GG), intrinsic delay, cutoff frequency (f_T) etc. have been investigated. The device linearity has been analyzed by considering the effect of temperature variation on linearity parameters like g_m2, g_m3, 1-dB compression point, VIP₂, VIP₃ and IIP₃. The device characteristics get upgraded by the increase in cut-off frequency and reduction in intrinsic delay at elevated temperature.

     

Deep autoencoders for feature learning with embeddings for recommendations: a novel recommender system solution

Neural Computing and Applications - We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from...     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Analytical Modeling of Surface Potential and Drain Current of Hetero-Dielectric DG TFET and Its Analog and Radio-Frequency Performance Evaluation

Semiconductors - In the present paper, analytical modeling of surface potential and drain current for hetero-dielectric double gate tunnel FET (HDG-TFET) has been done. The two dimensional (2D)...