A dynamic programming method for analysis of bridges under multiple moving loads

A dynamic programming (DP) method is presented for analysis of statically determinate and indeterminate bridges subjected to moving loads such as those specified by the American Association of State Highway and Transportation Officials (AASHTO) specifications. These loads consist of uniform lane loading, two-axle truck loading and two-axle truck plus one-axle semitrailer loading. The solution of the DP problem is based on the use of influence line diagrams and extremum functions. Recurrence formulae have been developed for various types of AASHTO live loads. The procedure presented in this article is quite general and can be applied to any type of structures with linear behaviour and any type of moving loads. Six examples are presented: a simply-supported beam, a simply-supported Pratt truss, an arch bridge, a continuous Pratt truss, a continuous frame and a cable-stayed bridge.     

A parallel genetic/neural network learning algorithm for MIMDshared memory machines

A new algorithm is presented for training of multilayer feedforward neural networks by integrating a genetic algorithm with an adaptive conjugate gradient neural network learning algorithm. The parallel hybrid learning algorithm has been implemented in C on an MIMD shared memory machine (Cray Y-MP8/864 supercomputer). It has been applied to two different domains, engineering design and image recognition. The performance of the algorithm has been evaluated by applying it to three examples. The superior convergence property of the parallel hybrid neural network learning algorithm presented in this paper is demonstrated.     

Functionalized Graphene as Extracellular Matrix Mimics: Toward Well‐Defined 2D Nanomaterials for Multivalent Virus Interactions

Polysulfated nanomaterials that mimic the extracellular cell matrix are of great interest for their potential to modulate cellular responses and to bind and neutralize pathogens. However, control over the density of active functional groups on such biomimetics is essential for efficient interactions, and this remains a challenge. In this regard, producing polysulfated graphene derivatives with control over their functionality is an intriguing accomplishment in order to obtain highly effective 2D platforms for pathogen interactions. Here, a facile and efficient method for the controlled attachment of a heparin sulfate mimic on the surface of graphene is reported. Dichlorotriazine groups are conjugated to the surface of graphene by a one‐pot [2+1] nitrene cycloaddition reaction at ambient conditions, providing derivatives with defined functionality. Consecutive step by step conjugation of hyperbranched polyglycerol to the dichlorotriazine groups and eventual conversion to the polyglycerol sulfate result in the graphene based heparin biomimetics. Scanning force microscopy, cryo‐transmission electron microscopy, and in vitro bioassays reveal strong interactions between the functionalized graphene (thoroughly covered by a sulfated polymer) and vesicular stomatitis virus. Infection experiments with highly sulfated versions of graphene drastically promote the infection process, leading to higher viral titers compared to nonsulfated analogues.     

Principal component analysis-enhanced cosine radial basis function neural network for robust epilepsy and seizure detection.

A novel principal component analysis (PCA)-enhanced cosine radial basis function neural network classifier is presented. The two-stage classifier is integrated with the mixed-band wavelet-chaos methodology, developed earlier by the authors, for accurate and robust classification of electroencephalogram (EEGs) into healthy, ictal, and interictal EEGs. A nine-parameter mixed-band feature space discovered in previous research for effective EEG representation is used as input to the two-stage classifier. In the first stage, PCA is employed for feature enhancement. The rearrangement of the input space along the principal components of the data improves the classification accuracy of the cosine radial basis function neural network (RBFNN) employed in the second stage significantly. The classification accuracy and robustness of the classifier are validated by extensive parametric and sensitivity analysis. The new wavelet-chaos-neural network methodology yields high EEG classification accuracy (96.6%) and is quite robust to changes in training data with a low standard deviation of 1.4%. For epilepsy diagnosis, when only normal and interictal EEGs are considered, the classification accuracy of the proposed model is 99.3%. This statistic is especially remarkable because even the most highly trained neurologists do not appear to be able to detect interictal EEGs more than 80% of the times.     

Graphene Oxide‐Cyclic R10 Peptide Nuclear Translocation Nanoplatforms for the Surmounting of Multiple‐Drug Resistance

Multidrug resistance resulting from a variety of defensive pathways in cancer has become a global concern with a considerable impact on the mortality associated with the failure of traditional chemotherapy. Therefore, further research and new therapies are required to overcome this challenge. In this work, a cyclic R10 peptide (cR₁₀) is conjugated to polyglycerol‐covered nanographene oxide to engineer a nanoplatform for the surmounting of multidrug resistance. The nuclear translocation of the nanoplatform, facilitated by cR₁₀ peptide, and subsequently, a laser‐triggered release of the loaded doxorubicin result in efficient anticancer activity confirmed by both in vitro and in vivo experiments. The synthesized nanoplatform with a combination of different features, including active nucleus‐targeting, high‐loading capacity, controlled release of cargo, and photothermal property, provides a new strategy for circumventing multidrug resistant cancers.     

Solution combustion synthesis of ZnO powders using CTAB as fuel

Zinc oxide (ZnO) powders have been prepared by solution combustion synthesis method using cetyltrimethylammonium bromide (CTAB) as fuel. The effects of fuel to oxidant ratios (? = 0.5, 0.75, 1 and 1.5) on the combustion behavior, phase evolution, microstructure, optical properties and photocatalytic performance were investigated by thermal analysis, X-ray diffractometry, electron microscopy, and diffuse reflectance spectrometry techniques. The slow decomposition rate of CTAB guaranteed the direct formation of single phase and well-crystalline ZnO powders regardless of fuel content. The specific surface area of the as-combusted ZnO powders with platelet particles increased from 21 ± 1 to 35 ± 2?m²/g with fuel content. The band gap energy also increased from 2.99 to 3.13?eV due to the decrease of particle size. The as-combusted ZnO powders at ? = 1.5 exhibited the highest photodegradation (~69%) of methylene blue under ultraviolet light irradiation, due to their good crystallinity and smaller particle size.     

Convenient method for preparation of a new absorbent based on biofunctionalized graphene oxide hydrogels using nitrene chemistry and click reaction

A new graphene oxide (GO)-based hydrogel was synthesized through cross-linking of biofunctionalized graphene oxide nanosheets by di-alkyne polyethylene glycol as cross-linking agent. In this respect, nitrene chemistry as a convenient and straightforward protocol was developed for biofunctionalization of GO using an azido-starch as an eco-friendly, biodegradable and cost-effective material. In the next step, 1,3-dipolar cycloaddition chemistry, a green and highly efficient approach was utilized in cross-linking of functionalized GO by PEG through click reaction between remaining azido groups of starch on the surface of GO sheets and terminal alkyne groups of polyethylene glycol. Formation of aziridine and triazole rings during functionalization and cross-linking in this method could evidently improve biological activities of the obtained hydrogel compared to the conventional methods. The antibacterial activity of the new compounds was explored. The synthesized hydrogel showed antibacterial properties against Gram-positive and Gram-negative bacteria due to the presence of triazole rings. Also, the resulting hydrogel exhibited high dye removal efficiency and it can be utilized in water treatment effectively. The adsorption kinetics was analyzed through the effects of adsorption time and the dye concentration on the adsorption capacity. Kinetic data were accurately described by a pseudo-second-order model.