One of the most interesting topics in bio-optics is measuring the refractive index of tissues. Accordingly, two novel optical biosensor configurations for cancer cell detections have been proposed in this paper. These structures are composed of one-dimensional photonic crystal (PC) lattices coupled to two metal–insulator–metal (MIM) plasmonic waveguides. Also, the tapering method is used to improve the matching between the MIM plasmonic waveguides and PC structure in the second proposed topology. The PC lattices at the central part of the structures generate photonic bandgaps (PBGs) with sharp edges in the transmission spectra of the biosensors. These sharp edges are suitable candidates for sensing applications. On the other hand, the long distance between two PBG edges causes that when the low PBG edge is used for sensing mechanism, it does not have an overlapping with the high PBG edge by changing the refractive index of the analyte. Therefore, the proposed biosensors can be used for a wide wavelength range. The maximum obtained sensitivities and FOM values of the designed biosensors are equal to 718.6, 714.3 nm/RIU, and 156.217, 60.1 RIU⁻¹, respectively. The metal and insulator materials which are used in the designed structures are silver, air, and GaAs, respectively. The finite-difference time-domain (FDTD) method is used for the numerical investigation of the proposed structures. Furthermore, the initial structure of the proposed biosensors is analyzed using the transmission line method to verify the FDTD simulations. The attractive and simple topologies of the proposed biosensors and their high sensitivities make them suitable candidates for biosensing applications.

This paper proposes a design approach for a high-efficiency continuous class-F power amplifier (PA) using quasi-elliptic low-pass filtering matching network (QELMN). In comparison with Chebyshev and modified elliptic matching networks, QELMN is composed of the quasi-elliptic low-pass filter (QEL) and optimized transmission lines (TL). QEL is a harmonic controller and matching circuit with low insertion loss, and its passband can be adjusted for each desired amplifier according to the operating band. Sharp roll-off and wide stopband of QEL controls harmonics, and low insertion loss of QEL improves delivered power from transistor to the load. The input impedance of QELMN is optimized with the goals of the stability and high power-added efficiency. The proposed approach is adopted to implement a continuous class-F PA using an LDMOS device under a class-AB bias condition. Experimental results verify a wide bandwidth from 0.3 to 1 GHz, with measured drain efficiency of 62-81%, the output power of 37-40.3 dBm and power gain of 12-15.3 dB.

A side orifice created in the side of a channel is a structure for diverting some of the flow from the main channel for different purposes. The prediction of the discharge through this side structure is very important in hydraulic and irrigation engineering. In the present study, three artificial neural network models including feed forward back propagation, radial basis function, and Generalized Regression neural networks as well as a multiple non-linear regression method were used to predict the discharge coefficient for flow through both square and circular shapes of sharp-crested side orifices. The discharge coefficient was modeled as a function of five input non-dimensional variables resulted from five dimensional variables, which were the type of orifice shape, the diameter or width of the orifice, crest height, depth and velocity of approach flow. The results obtained in this study indicated that all of the neural network models could successfully predict the discharge coefficient with adequate accuracy. However, according to different performance measures, the accuracy of radial basis function approach was a bit better than two other neural network models. The neural network models predicted the discharge coefficient more accurately than the non-linear regression relation.