Cytotoxicity and Immunological Response of Gold and Silver Nanoparticles of Different Sizes

The immunological response of macrophages to physically produced pure Au and Ag nanoparticles (NPs) (in three different sizes) is investigated in vitro. The treatment of either type of NP at ≥10 ppm dramatically decreases the population and increases the size of the macrophages. Both NPs enter the cells but only AuNPs (especially those with smaller diamter) up‐regulate the expressions of proinflammatory genes interlukin‐1 (IL‐1), interlukin‐6 (IL‐6), and tumor necrosis factor (TNF‐α). Transmission electron microscopy images show that AuNPs and AgNPs are both trapped in vesicles in the cytoplasma, but only AuNPs are organized into a circular pattern. It is speculated that part of the negatively charged AuNPs might adsorb serum protein and enter cells via the more complicated endocytotic pathway, which results in higher cytotoxicity and immunological response of AuNPs as compared to AgNPS.     

Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm

This study develops a production well management model for the conjunctive management of water resources in semi-arid areas. The management model integrates a large-scale pressurized water distribution system and a three-dimensional groundwater model under an optimization framework. The well pump operations optimization problem is formulated as a Boolean integer nonlinear programming (BINLP) problem to optimize the periodic 24-h pump on/off operations over a 1-week operation horizon. The management model considers multiple objectives and is solved by a parallel genetic algorithm (PGA) to overcome the difficulty of solving the BINLP problem. The PGA significantly reduces computation time for a case study in Chandler, Arizona. The Chandler water distribution model is built based on EPANET, and the Chandler three-dimension groundwater model is developed using MODFLOW. The high performance computing (HPC) of the genetic algorithm makes it possible to obtain 24-h real-time operations in the 7-day forecast model. The tank reliability, resilience, and vulnerability (R-R-V) are evaluated to infer the system reliability. The Pareto curve provides compromise solutions between the two competing objectives of energy reduction and pressure violation reduction.     

Control of transient effects in distributed and lumped Ramanamplifiers

A robust control scheme for suppressing transients in both lumped and distributed Raman amplifiers is demonstrated. The control method uses only output power monitoring and holds gain fluctuations on surviving channels to <±0.06 dB in an experiment     

Simultaneous Q-switching and mode-locking in a diode-pumped Nd:YVO4-Cr4+:YAG laser

Parametric studies of passive Q-switching and mode-locking in a Nd ³⁺:YVO₄-Cr⁴⁺:YAG laser were theoretically carried out. Simultaneous mode-locking and Q-switching was also experimentally studied. It was found that over 90% of the output power could be mode-locked in a diode-pumped passively Q-switched Nd³⁺:YVO₄-Cr⁴⁺:YAG laser. The average pulse duration of the mode-locked pulse train was estimated to he around 110~150 ps. The highest peak power of a single pulse near the maximum of the Q-switched envelope was greater than 100 kW     

A case study on ground treatment for a rock tunnel with high groundwater ingression in Taiwan

This paper presents a case study on the collapse caused by sudden groundwater ingression in the Pinglin pilot tunnel, and the treatments developed for the adverse ground conditions encountered. The ideas for the ground treatment are to reduce groundwater pressure as well as to consolidate the fractured zone in rock formations. The paper highlights the importance of paying particular attention to the ground treatment process and grouting quality control. Ongoing adjustments of grouting mixture and pressure may be necessary with the changing ground conditions.     

Application of neural networks to laser ultrasonic NDE of bonded structures

The purpose of this study is to develop artificial neural networks for the nondestructive evaluation of a bounded structure using laser generated surface waves. The radial basis model is employed and the inputs of the networks are the sampled dispersion curves while the output is the thickness of the bonding layer or unbond ratio. Numerical simulated dispersion curves with noises were used to train and test the neural networks. The dispersion curves of laser ultrasonic experiments acquired by spectral analysis method were also utilized to test the systems. For comparison, simplex inverse method was also introduced. The results demonstrate that neural networks are well suited for on-line evaluation of bonding thickness and unbond ratio of a bonded layered structure.     

Synthesis of a polydimethylsiloxane-block-hydroxyl grafted acrylate prepolymer copolymer to improve the adhesion between silicone rubber and polyurethane by induced surface reconstruction

A new class of hydroxyl-functionalized polydimethylsiloxane-block-hydroxyl graft acrylate prepolymer (PDMS-b-HGAP) copolymers was synthesized. The copolymers were characterized using Fourier transform infrared spectroscopy as well as ¹H and ¹³C nuclear magnetic resonance spectroscopy. The hydroxyl groups of the HGAP were reacted with the chlorine terminal in the PDMS to yield a triblock copolymer consisting of two segments of PDMS linked to a HGAP segment. The induced surface reconstruction of silicone rubber (SR)by blending polysiloxane reactants with bifunctional PDMS-b-HGAP copolymers and curing using mold materials having high critical surface tension such as polyethyleneterephthalate was attempted to improve the adhesion between chemically-inert SR and polyurethane (PU). Surface characterization using Foruier transform infrared-attenuated total reflectance indicated that the surface of the SR was enriched with HGAP. The increased content of surface HGAP was suggested to account for the improved adhesion between SR and PU.     

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.     

A Distribution Management System for Relational Databases in Cloud Environments

For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID (atomic, consistent, isolated, and durable) properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management (DBDM) system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system (DBMS) or different partition algorithms.