Back-analysis of geotechnical parameters on PVD-improved ground in the Mekong Delta

This study presents a back-analysis of geotechnical parameters on prefabricated vertical drain improved ground at a site in the Mekong Delta. Various time?settlement behaviors that reflected different clay thicknesses and loading patterns were observed. The total surface settlement behavior at several monitoring locations was simulated using an updated exponential method that considered staged construction. The analyzed results were validated by substituting the values into a theoretical solution for radial consolidation. The estimated theoretical behaviors were comparable with the monitored behaviors. The geotechnical parameters were back-analyzed by applying the previously analyzed results to various theoretical and empirical formulas. However, the use of extensometer data that were installed at large intervals produced different values of the geotechnical properties. Furthermore, finite element analysis supported the back-analyzed total settlement behaviors and nearly disregarded the application of the geotechnical properties that were obtained using either surface or subsurface settlement data. However, settlements and excess pore pressures in the sublayers were not successfully predicted even when the geotechnical properties were adjusted. Thus, subsurface instruments that can be installed closely in thick clay deposits are required to reliably reevaluate the variations in geotechnical properties along a certain depth.     

A localized surface plasmon resonance based immunosensor for the detection of casein in milk

In this research, a localized surface plasmon resonance (LSPR) immunosensor based on gold-capped nanoparticle substrate for detecting casein, one of the most potent allergens in milk, was developed. The fabrication of the gold-capped nanoparticle substrate involved a surface-modified silica nanoparticle layer (core) on the slide glass substrate between bottom and top gold layers (shell). The absorbance peak of the gold-capped nanoparticle substrate was observed at ∼520 nm. In addition, the atomic force microscopy (AFM) images demonstrated that the nanoparticles formed a monolayer on the slide glass. After immobilizing anti-casein antibody on the surface, our device, casein immunosensor, could be applied easily for the detection of casein in the raw milk sample without a difficult pretreatment. Under the optimum conditions, the detection limit of the casein immunosensor was determined as 10 ng/mL. Our device brings several advantages to the existing LSPR-based biosensors with its easy fabrication, simple handling, low-cost, and high sensitivity.     

Applying Wide & Deep Learning Model for Android Malware Classification

Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model.     

Self-assembled poly(ethylene glycol) methyl ether-grafted gelatin nanogels for efficient delivery of curcumin in cancer treatment

Curcumin (CUR) is a natural active ingredient that attracted much attention for its chemotherapeutic activity against tumors without causing toxicity in healthy cells. However, it has certain limitations for being used in chemotherapy such as low aqueous solubility and hydrolytic instability in the physiological environment. In this study, self-assembled poly(ethylene glycol) methyl ether-grafted gelatin (Gel-mPEG) nanogels were fabricated as delivery systems to improve the applicability of CUR in cancer treatment. CUR-loaded Gel-mPEG nanogels exhibited desired size range, relatively colloidal stability, and provided enhanced CUR stability in aqueous solutions. Especially, they showed significant high CUR loading capacity and better anticancer activity than free CUR as compared to previously reported CUR-loaded nanogels according to the best of our knowledge. Moreover, the in vitro release of CUR from the nanogels was controlled and prolonged up to 96 h. These results demonstrated that Gel-mPEG nanogels are the promising modality for the efficient delivery of CUR in cancer treatment. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47544.     

Secure Multi-hop Data Transmission in Cognitive Radio Networks Under Attack in the Physical Layer

Wireless Personal Communications - Cognitive radio networks (CRNs) have a shortcoming in that attackers can increase their ability to disturb secondary users (SUs). This paper focuses on jamming...     

Optimal resource allocation for energy efficiency in coordinated multicell OFDMA networks

Because energy efficiency (EE) is inevitable in future wireless cellular networks, in this paper, we focus on improving the number of bits delivered to users for each unit energy consumption in the downlink of orthogonal frequency‐division multiple access cellular networks with base stations (BSs) coordination. Specifically, each BS shares the channel qualities of users with others and jointly choose the set of co‐channel users and the transmit power allocated to maximize the EE of the system subject to the transmit power ceiling of each BS and minimum required data rate. We formulate the problem as a nonlinear fractional optimization problem, using nonlinear fractional programming, the original hard‐to‐solve problem is transferred to a new one that has the same optimal solution and is easier to solve, this enables two iterative algorithms that achieve nearly the same maximum EE. Numerical results are provided to show the convergence and superiority of the two proposed. Copyright © 2014 John Wiley & Sons, Ltd.     

Fabrication and characterization of porous poly(lactic-<Emphasis Type="Italic">co</Emphasis>-glycolic acid) (PLGA) microspheres for use as a drug delivery system

In this work, Simvastatin (SIM) loaded porous poly(lactic-co-glycolic acid) (PLGA) microspheres were fabricated using the W/O/W1/W2 double emulsion and solvent evaporation method. The optimal conditions for fabricating porous PLGA microspheres were determined to be 20% distilled water (v/v), 10% PLGA (m/v), and a 4:1 ratio of internal polyvinyl alcohol (PVA) to dichloromethane (DCM). The pores size distribution of porous PLGA microspheres was varied from 0.01 to 40 μm, while their particle displayed a bimodal size distribution that had two diameter peaks at around 100 μm and 500 μm. The SIM encapsulation efficacy was found to be very high with a yield near 80% and the porous PLGA microspheres showed the excellent biocompatibility. In addition, the drug release profile was found to be significantly different from a temporal basis. Base on the combined results of this study, SIM loaded PLGA microspheres holds great promise for use in biomedical applications, especially in drug delivery system or tissue regeneration.     

Polyglycolide‐based blends for drug delivery: A differential scanning calorimetry study of the melting behavior

The melting behavior of polyglycolide (PGA) with eight other biodegradable polymers was investigated to determine whether forming a blend could be used as a method of lowering the melting point of PGA. Blends were prepared by melt processing in differential scanning calorimetry (DSC) pans and were then analyzed by DSC. In every case, a comparison of the blend DSC plot with those of the two individual components showed that the melting behavior of PGA remained unchanged by blending. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2937–2939, 2003     

Functionally Antagonistic Hybrid Electrode with Hollow Tubular Graphene Mesh and Nitrogen‐Doped Crumpled Graphene for High‐Performance Ionic Soft Actuators

Ionic soft actuators, which exhibit large mechanical deformations under low electrical stimuli, are attracting attention in recent years with the advent of soft and wearable electronics. However, a key challenge for making high‐performance ionic soft actuators with large bending deformation and fast actuation speed is to develop a stretchable and flexible electrode having high electrical conductivity and electrochemical capacitance. Here, a functionally antagonistic hybrid electrode with hollow tubular graphene meshes and nitrogen‐doped crumpled graphene is newly reported for superior ionic soft actuators. Three‐dimensional network of hollow tubular graphene mesh provides high electrical conductivity and mechanically resilient functionality on whole electrode domain. On the contrary, nitrogen‐doped wrinkled graphene supplies ultrahigh capacitance and stretchability, which are indispensably required for improving electrochemical activity in ionic soft actuators. Present results show that the functionally antagonistic hybrid electrode greatly enhances the actuation performances of ionic soft actuators, resulting in much larger bending deformation up to 620%, ten times faster rise time and much lower phase delay in a broad range of input frequencies. This outstanding enhancement mostly attributes to exceptional properties and synergistic effects between hollow tubular graphene mesh and nitrogen‐doped crumpled graphene, which have functionally antagonistic roles in charge transfer and charge injection, respectively.