Docetaxel‐loaded solid lipid nanoparticles: a novel drug delivery system

Over the past few years, taxanes have emerged as a new class of anticancer drugs. Docetaxel (DTX) the prototype of this class has been approved for the treatment of broad range of cancers. However, to date the commercial preparation of DTX (Taxotere^®) is accompanying adverse side effects, intolerance, and poor solubility, which can be overcome by encapsulating them using solid lipid nanoparticles (SLNs). SLNs represent versatile delivery system of drugs with newer forms such as polymer–solid lipid hybrid, surface modified and long circulating nanoparticles bringing forth improved prospects for cancer chemotherapy. In this review, the authors have discussed the current uses of various SLNs formulations of DTX with key emphasis on controlled and site‐specific drug delivery along with enhanced antitumour activity elucidated via in vitro and in vivo studies. Furthermore, the review article highlights few approaches that can be used in combination with existing DTX‐loaded SLNs to supplement DTX drug delivery.Inspec keywords: nanoparticles, nanomedicine, drug delivery systems, biomedical materials, cancer, reviews, tumoursOther keywords: docetaxel‐loaded solid lipid nanoparticles, drug delivery system, taxanes, anticancer drugs, Taxotere, SLN encapsulation, polymer‐solid lipid hybrid, surface modified nanoparticles, long circulating nanoparticles, chemotherapy, review     

Study of (DNPs)<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>/CuTl-1223 Nanoparticle-Superconductor Composites

Sol-gel and solid-state reaction methods were used to synthesize diamond nanoparticles (DNPs) and (DNPs) _x /CuTl-1223 (x = 0, 0.25, 0.50, and 1.00 wt.%) nanoparticle-superconductor composites, respectively. Effects of these DNPs on structural, morphological, compositional, and transport properties of CuTl-1223 superconducting phase were investigated by different experimental techniques such as X-ray diffraction (XRD), energy dispersive X-ray (EDX) spectroscopy, scanning electron microscopy (SEM), and resistivity versus temperature (R-T) measurements. The unchanged crystal structure and stoichiometry of host CuTl-1223 superconducting matrix with addition of DNPs gave evidence about the dispersion of nanoparticles at the grain boundaries of the host matrix, which may heal up the inter-granular voids and pores resulting in enhanced inter-grain connectivity. Critical transition temperature T _c (0) and hole concentration of CuTl-1223 superconductor were observed to be increased with addition of DNPs up to a certain optimum value (i.e. x = 0.5 wt.%).     

News recommender system: a review of recent progress,challenges, and opportunities

Nowadays, more and more news readers read news online where they have access to millions of news articles from multiple sources. In order to help users find the right and relevant content, news recommender systems (NRS) are developed to relieve the information overload problem and suggest news items that might be of interest for the news readers. In this paper, we highlight the major challenges faced by the NRS and identify the possible solutions from the state-of-the-art. Our discussion is divided into two parts. In the first part, we present an overview of the recommendation solutions, datasets, evaluation criteria beyond accuracy and recommendation platforms being used in the NRS. We also talk about two popular classes of models that have been successfully used in recent years. In the second part, we focus on the deep neural networks as solutions to build the NRS. Different from previous surveys, we study the effects of news recommendations on user behaviors and try to suggest possible remedies to mitigate those effects. By providing the state-of-the-art knowledge, this survey can help researchers and professional practitioners have a better understanding of the recent developments in news recommendation algorithms. In addition, this survey sheds light on the potential new directions.

     

Miniaturized frequency reconfigurable pentagonal MIMO slot antenna for interweave CR applications

In this article, a miniaturized 4‐element frequency reconfigurable multiple‐input‐multiple‐output (MIMO) antenna system is presented. The proposed design is low profile with planar configuration. The design consists of pentagonal slot‐based frequency reconfigurable antenna elements. Varactor diodes are used to change the capacitive reactance of the slot. The MIMO antenna system can be tuned over a frequency band covering 3.2 to 3.9 GHz with at least 100 MHz bandwidth within each band. The proposed antenna covers several commercial standards including WiMAX (3.4‐3.6 GHz), TDD LTE (3.6‐3.8 GHz), and Wi‐Fi 802.11y (3.65‐3.7 GHz), along with several other bands. The proposed design was realized on a board of dimensions 60 × 120 mm². The isolation between adjacent antenna elements is improved using slot‐line based defected ground structures (DGS). The antenna maintains a minimum isolation of 10 dB in its entire covered operating bands. The antenna is also analyzed for its far‐field characteristics and MIMO performance parameters. The proposed design is suitable to be used in mobile handsets for cognitive radio (CR) platforms.     

Motion Planning of Humanoid Robot for Obstacle Negotiation

The motion planning for obstacle negotiation by humanoid robot BHR-2 through stepping over or stepping on/off the wide and flat obstacle at known locations is presented. In the trajectory generation method, first the constraints of the foot motion parameters which include obstacle dimensions and the distance of obstacle from the humanoid robot is formulated. By varying the values of the constraint parameters, different types of foot motion for different obstacles can be produced. In this method, first the foot trajectory is generated, and then the waist trajectory is computed by using cubic spline interpolation without first calculating the zero moment point (ZMP) trajectory . The dynamic stability during the execution of stepping over and stepping on/off trajectories are ensured by incorporating the ZMP criterion. The effectiveness of the proposed method is confirmed by simulations and experiments on humanoid robot BHR-2.     

Application of three unsupervised neural network models to singular nonlinear BVP of transformed 2D Bratu equation

In this paper, numerical techniques are developed for solving two-dimensional Bratu equations using different neural network models optimized with the sequential quadratic programming technique. The original two-dimensional problem is transformed into an equivalent singular, nonlinear boundary value problem of ordinary differential equations. Three neural network models are developed for the transformed problem based on unsupervised error using log-sigmoid, radial basis and tan-sigmoid functions. Optimal weights for each model are trained with the help of the sequential quadratic programming algorithm. Three test cases of the equation are solved using the proposed schemes. Statistical analysis based on a large number of independent runs is carried out to validate the models in terms of accuracy, convergence and computational complexity.     

Solution of the 2-dimensional Bratu problem using neural network,swarm intelligence and sequential quadratic programming

In this paper, stochastic techniques have been developed to solve the 2-dimensional Bratu equations with the help of feed-forward artificial neural networks, optimized with particle swarm optimization (PSO) and sequential quadratic programming (SQP) algorithms. A hybrid of the above two algorithms, referred to as the PSO-SQP method is also studied. The original 2-dimensional equations are solved by first transforming them into equivalent one-dimensional boundary value problems (BVPs). These are then modeled using neural networks. The optimization problem for training the weights of the network has been addressed using particle swarm techniques for global search, integrated with an SQP method for rapid local convergence. The methodology is evaluated by applying on three different test cases of BVPs for the Bratu equations. Monte Carlo simulations and extensive analyses are carried out to validate the accuracy, convergence and effectiveness of the schemes. A comparative study of proposed results is made with available exact solution, as well as, reported numerical results.     

Synthesize and characterization of ceria based nano-composite materials for low temperature solid oxide fuel cell

The present study is focused on ceria based mixed (ionic and electronic conductor) composite Al_0.05Ni_0.1Ti_0.05Zn_0.80-SDC (ATZN-SDC) oxide material was prepared by solid state reaction, which can be used as anode materials for solid oxide fuel cell. The effect of Ti and Al oxides were analyzed on the NiZn-SDC composite with respect to its conductivity and catalytic activity in hydrogen atmosphere. The average crystallite size of the composite was found to be 40–100 nm by XRD and SEM. The DC conductivity was determined by 4-probe technique. The electrochemical impedance spectrum (EIS) was also examined in hydrogen atmosphere within a temperature range of 350–550 °C. The maximum power density 370 mW/cm² was achieved at 650 °C.     

Energy management in residential buildings using energy hub approach

Building Simulation - Building-owned micro energy hubs (EHs) usually focus on optimal energy consumption cost and emission, whereas, macro energy hubs (MEHs) mainly concentrate on utility’s...