Role of Curvature-Sensing Proteins in the Uptake of Nanoparticles with Different Mechanical Properties

Nanoparticles of different properties, such as size, charge, and rigidity, are used for drug delivery. Upon interaction with the cell membrane, because of their curvature, nanoparticles can bend the lipid bilayer. Recent results show that cellular proteins capable of sensing membrane curvature are involved in nanoparticle uptake; however, no information is yet available on whether nanoparticle mechanical properties also affect their activity. Here liposomes and liposome-coated silica are used as a model system to compare uptake and cell behavior of two nanoparticles of similar size and charge, but different mechanical properties. High-sensitivity flow cytometry, cryo-TEM, and fluorescence correlation spectroscopy confirm lipid deposition on the silica. Atomic force microscopy is used to quantify the deformation of individual nanoparticles at increasing imaging forces, confirming that the two nanoparticles display distinct mechanical properties. Uptake studies in HeLa and A549 cells indicate that liposome uptake is higher than for the liposome-coated silica. RNA interference studies to silence their expression show that different curvature-sensing proteins are involved in the uptake of both nanoparticles in both cell types. These results confirm that curvature-sensing proteins have a role in nanoparticle uptake, which is not restricted to harder nanoparticles, but includes softer nanomaterials commonly used for nanomedicine applications.     

Development of n-type microcrystalline SiO<Subscript>x</Subscript>:H films and its application by innovative way to improve the performance of single junction µc-Si:H solar cell

Light trapping is one of the fundamental necessities of thin film based solar cell for its performance elevation. Back reflection of unused light of first pass is the key way to improve the light trapping phenomena. In this study we have reported the development of n-type hydrogenated microcrystalline silicon oxide (n-µc-SiO:H) layers of different characteristics. The deposition has been done by Plasma Enhanced Chemical Vapor Deposition (PECVD) technique. The detailed characterization of the films include the following: (1) electrical properties (2) optical properties like E₀₄ (3) structural studies which include crystalline fraction by Raman spectroscopy and grain size by X-ray diffraction measurement, FTIR spectroscopy, AFM and TEM studies. n-µc-SiO:H layer has been introduced as the n-layer of single junction p–i–n structure µc-Si solar cells. By various techniques the optimum use of n-µc-SiO:H layer for enhancing the performance of µc-Si:H solar cells has been done. It has been found that by using suitable bilayer of two different n-µc-SiO:H layers, it is possible to increase the solar cell performances. The maximum efficiency obtained without any back reflector is 8.44% that is about 8.9% higher than that obtained by using n-µc-Si:H layer as n-layer in the solar cells.     

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is mea sured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control, automatic generation control (AGC) plays a crucial role. In this paper, multi-area (Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative (PID) controller as a supplemen tary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm (FFA). The experimental results demonstrated the comparison of the proposed system performance (FFA-PID) with optimized PID controller based genetic algorithm (GA PID) and particle swarm optimization (PSO) technique (PSO PID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error (ITAE) cost function with one percent step load perturbation (1% SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.      

Eight Element Low-Cost Microstrip MIMO Antenna for Wi-MAX and 5G Applications

Wireless Personal Communications - In this communication, a low-cost four/eight-element MIMO antenna is proposed for Wi-MAX (IEEE 802.16d) and 5G applications band. A reverse U-shaped slot is...     

A Long Pathway to the Quantitative Assembly of Metallodendrimers

This overview describes our research progression from the study of heterocycle synthesis to dendritic architecture to simple metallomacrocycles, and finally to complex, fractal-based, suprametallomolecular materials. Construction of the first terpyridine-modified dendritic scaffold was followed by the construction and self-assembly of polyterpyridine monomers. Preparation of tristerpyridine building blocks used in concert with bisterpyridine analogs facilitated access to a Sierpiński gasket, as verified by direct visual observation with UHV-STEM, as well as other techniques. Numerous examples of heteroleptic self-assembly are described that include the quantitative preparation of a Sierpiński triangle. Addition of angled spacer moieties within polyterpyridine building blocks has generated a new family of 3D spherical materials that has facilitated the construction of hybrid fractal-dendritic materials that exhibit the unexpected concentration mediated, architectural transformations.     

RVCloud: a routing protocol for vehicular ad hoc network in city environment using cloud computing

Routing in Vehicular Ad hoc Network (VANET) is a challenging task due to high mobility of vehicles. In this paper, a RVCloud routing protocol is proposed for VANET to send the data efficiently to the destination vehicle using cloud computing technology. In this protocol, vehicle beacon information is send to the cloud storage through the Road Side Unit (RSU). As vehicles have less storage and computing facility, the information of all the vehicles moving in the city is maintained by the cloud. Source vehicle sends the data to the destination by sending the data to the nearby RSU. After receiving the data, RSU sends a request to the cloud for an optimal RSU information, that takes minimum packet forwarding delay to send the data to the destination. Cloud provides location service by providing destination location and optimal RSU information. Then RSU sends the data to the optimal RSU using internet. By using the internet facility, packet forwarding delay and link disruption problem are reduced. Simulation results show that, RVCloud performs better than VehiCloud, P-GEDIR, GyTAR, A-STAR, and GSR routing protocols.     

A novel transfer learning-based short-term solar forecasting approach for India

Neural Computing and Applications - Deep learning models in recent times have shown promising results for solar energy forecasting. Solar energy depends heavily on local weather conditions, and as...     

Design and testing of a reversible ALU by quantum cells automata electro-spin technology

The Journal of Supercomputing - Arithmetic logic unit (ALU), a core component of a processor, is one of the thrust areas of the current research. Presently, ALU is designed by transistor-based CMOS...