Band-edge Bilayer Plasmonic Nanostructure for Surface Enhanced Raman Spectroscopy

Spectroscopic analysis of large biomolecules is critical in a number of applications, including medical diagnostics and label-free biosensing. Recently, it has been shown that Raman spectroscopy of proteins can be used to diagnose some diseases, including a few types of cancer. These experiments have however been performed using traditional Raman spectroscopy and the development of the Surface enhanced Raman spectroscopy (SERS) assays suitable for large biomolecules could lead to a substantial decrease in the amount of specimen necessary for these experiments. We present a new method to achieve high local field enhancement in surface enhanced Raman spectroscopy through the simultaneous adjustment of the lattice plasmons and localized surface plasmon polaritons, in a periodic bilayer nanoantenna array resulting in a high enhancement factor over the sensing area, with relatively high uniformity. The proposed plasmonic nanostructure is comprised of two interacting nanoantenna layers, providing a sharp band-edge lattice plasmon mode and a wide-band localized surface plasmon for the separate enhancement of the pump and emitted Raman signals. We demonstrate the application of the proposed nanostructure for the spectral analysis of large biomolecules by binding a protein (streptavidin) selectively on the hot-spots between the two stacked layers, using a low concentration solution (100 nM) and we successfully acquire its SERS spectrum

Discrete alpha-skew-Laplace Distribution

Classical discrete distributions rarely support modelling data on the set of whole integers. In this paper, we shall introduce a flexible discrete distribution on this set, which can, in addition, cover bimodal as well as unimodal data sets. The proposed distribution can also be fitted to positive and negative skewed data. The distribution is indeed a discrete counterpart of the continuous alpha-skew-Laplace distribution recently introduced in the literature. The proposed distribution can also be viewed as a weighted version of the discrete Laplace distribution. Several distributional properties of this class such as cumulative distribution function, moment generating function, moments, modality, infinite divisibility and its truncation are studied. A simulation study is also performed. Finally, a real data set is used to show applicability of the new model comparing to several rival models, such as the discrete normal and Skellam distributions

Synchronization and channel estimation in experimental M-QAM OFDM radio over fiber systems using CAZAC based training preamble

In this paper, we propose a new technique for synchronization and channel estimation in M-QAM OFDM radio over fiber (RoF) system by using constant amplitude zero auto-correlation (CAZAC) sequence based training preamble. Delay and correlate method is used to identify the training sequence in the received signal vector and to correct the symbol timing offset. For an optimum demodulation of OFDM signal, optimum down sampling offset position has to be identified before applying symbol timing algorithm. To solve this issue, we present the iterative method of finding optimum down sampling offset position. We show that the training preamble used for synchronization can also be applied to estimate the channel response using averaging technique. Moreover, we used the least square estimation based channel estimation method using pilot subcarriers and compare the results with training preamble based estimation

Jackiw-Teitelboim Gravity Generates Horndeski via Disformal Transformations

We show that the most general two-dimensional dilaton gravity theory with second-order field equations, which includes Horndeski and Kinetic Gravity Braiding families, may be obtained from the Jackiw-Teitelboim (JT) gravity through a general disformal transformation, up to boundary terms. We also show that this most general family of theories is closed under generic disformal transformations.Comment: 13 pages, 1 figure

Developing an Improved Shift-and-Invert Arnoldi Method

An algorithm has been developed for finding a number of eigenvalues close to a given shift and in interval [ Lb,Ub ] of a large unsymmetric matrix pair. The algorithm is based on the shift-andinvert Arnoldi with a block matrix method. The block matrix method is simple and it uses for obtaining the inverse matrix. This algorithm also accelerates the shift-and-invert Arnoldi Algorithm by selecting a suitable shift. We call this algorithm Block Shift-and-Invert or BSI. Numerical examples are presented and a comparison has been shown with the results obtained by Sptarn Algorithm in Matlab. The results show that the method works well

Electric Bus Charging Infrastructures: Technologies, Standards, and Configurations

Rapid growth in the electrification of bus fleets, driven by substantial environmental benefits, is facing challenges such as range anxiety, prolonged charging durations, and reduced flexibility compared to combustion engine buses. This study first conducts a comprehensive bibliometric analysis of diverse publications to identify key research trends in electric buses (E-buses). It then offers a thorough comparison of charging technologies, encompassing topologies, power flow capabilities, costs, grid impacts, and efficiency, along with an examination of existing standards, norms, and challenges. With a classification of nearly 150 references, the study aims to illuminate the strengths and weaknesses of each charging technology, providing a solid background for selecting optimal topologies and strategies for specific applications. Emphasizing the importance of a nuanced trade-off between the quantity and type of chargers and E-bus battery capacity in each scenario, the research goes beyond technical considerations to explore potential future trends in the field. The information gathered in this review is a helpful guide for policymakers, industry experts, and researchers dealing with the complexities of E-bus charging infrastructure

The effect of geogrid reinforcement of embankment over soft foundation

This paper deals with the usage of geogrids for soil improvement utilizing the PLAXIS 3D FE program's numerical analysis approach. Because of the low shear strength and instability of soft clay soils, reinforcement has been used to improve clay soils. The reinforcement mechanism was analyzed on the basis of results and output. The results of the program outputs are shown in PLAXIS. The reinforcement has little effect in the case of horizontal displacement and vertical displacement, but only a significant effect on the safety factor. This paper also deals with improving soft clay soil using stone columns. The main objective is to reduce settlement and increase the carrying capacity of the soil and shorten the consolidation period. The work investigates geogrid-reinforced stone columns that improved the behavior of soft clay soils under the influence of loading and construction. Underwent soil the stone columns testing covered with a geogrid and traffic load of 50 kpa. The improved method of using stone columns and PLAXIS 3D was used to create the FE model. The results concluded that the comparison results gave an improvement rate of up to 50 % of the improvement for the stone-column-reinforced clay soil in the construction phase