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Journal Articles
Measurement of Solubility and Water Sorption of Dental Nanocomposites Light Cured by Argon Laser
Different parameters used for photoactivation process and also composition provide changes in the properties of dental composites. In the present work the effect of different power density of argon laser and filler loading on solubility (SL) and water sorption (WS) of light-cure dental nanocomposites was studied. The resin of nanocomposites was prepared by mixing bisphenol A glycol dimethacrylate (Bis-GMA) and triethylene glycol dimethacrylate (TEGDMA) with a mass ratio of 65/35. 20 wt.% and 25 wt.% of nanosilica fillers with a primary particle size of 10 nm were added to the resin. Camphorquinone (CQ) and DMAEMA were added as photoinitiator system. The nanocomposites were cured by applying the laser beam at the wavelength of 472 nm and power densities of 260 and 340 mW/cm2 for 40 sec. Solubility and water sorption were then measured according to ISO 4049, which in our case, the maximums were 2.2% and 4.3% at 260 mW/cm2 and 20% filler, respectively. The minimum solubility (1.2%) and water sorption (3.8%) were achieved for the composite containing 25% filler cured at 340 mW/cm2. The results confirmed that higher power density and filler loading decreased solubility of unreacted monomers and water sorption and improved physico-mechanical properties of nanocomposites. Read more
IEEE Transactions on NanoBioscience information for authors
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IEEE Transactions on NanoBioscience publication information
Provides a listing of current staff, committee members and society officers. Read more
Kinetics of Cisplatin Release by In-Vitro Using Poly(D,L-Lactide) Coated 
Applications of nanoparticles as drug delivery systems for anticancer therapeutics have great potential to revolutionize the future of cancer therapy. In the present study, Fe3O4 nanoparticles were synthesized by co-precipitation method in the alkaline pH medium. The synthesized nanoparticles were characterized by X- ray diffraction and high resolution scanning electron microscope techniques. These analyses reveal the formation of agglomerated single phase Fe3O4 nanoparticles with average crystallite size of 8 nm. The emulsification solvent evaporation method was employed to prepare anti-cancer drug cisplatin loaded biodegradable poly (D, L-lactide) coated magnetic carriers. Fourier transform infrared spectroscopy shows the presence of cisplatin loaded poly(D,L-lactide) coating on the surface of Fe3O4 nanoparticles. Cisplatin loading efficiency and kinetics of drug release in-vitro were investigated by UV-Vis spectrophotometer. The loading efficiency of the drug was found to be 80% and from that 53% of the drug was released over a period of 70 h in phosphate buffer saline (pH 7.4) at ~ 37°C. Read more
Neuronal Model With Distributed Delay: Emergence of Unimodal and Bimodal ISI Distributions
The empirically observed inter-spike interval (ISI) patterns in neuronal dynamics exhibit unimodal and bimodal behavior. The widely studied IF and LIF models are known to display only unimodal ISI distribution. A challenging problem in modeling of neuronal dynamics is to understand mechanism which can generate the empirically observed ISI patterns. A new neuronal model incorporating distributed delay (NMDD), proposed by Karmeshu, Varun, and Kadambari has been investigated in greater details for gamma distributed memory kernels with weak and strong delays. The underlying dynamics of membrane potential in subthreshold regime may result in bimodality of ISI distribution. It is found as the mean of the delay kernel exceeds a critical value, the ISI distribution makes a transition from unimodal to bimodal. Extensive simulation studies reveal that different empirically observed ISI patterns can be generated and interesting behavior is observed when excitatory and inhibitory rates of EPSP and IPSP processes are close to each other. This investigation suggests the important role played by distributed delays in neuronal dynamics. Read more
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On Modeling and State Estimation for Genetic Regulatory Networks With Polytopic Uncertainties
It is widely believed that gene expression data contains rich information that could discover the higher-order structures of an organism and even interpret its behavior. The modeling problem of gene regulatory networks (GRNs) from the experimental data has recently received increasing research attention. In this paper, we investigate the uncertainty quantification and state estimation issues. The polytopic uncertainty model (PUM) is exploited for describing the GRNs where the parameter uncertainties are constrained in a convex polytope domain. To cope with the high-dimension problem for GRN models, the principal component plane (PCP) algorithm is proposed to construct a pruned polytope in order to use as less vertices as possible to maintain the essential information from original polytope. The so-called system equivalence transformation is developed to transform the original system into a simpler canonical form and therefore facilitate the subsequent state estimation problem. For the state estimation problem, a robust stability condition is incorporated with guaranteed H2 performance via the semi-definite programme method, and then a new sufficient condition is derived for the desired H2 estimators with several free slack matrices. Such a condition is vertex-dependent and therefore possesses less conservatism. It is shown, via simulation from real-world microarray time-series data, that the designed H2 estimators have strong capability of dealing with modeling and estimation problems for short but high-dimensional gene expression time series. Read more
Multi-Hop Conjugation Based Bacteria Nanonetworks
Molecular communication is a new paradigm for nanomachines to exchange information, by utilizing biological mechanism and/or components to transfer information (e.g., molecular diffusion, neuronal networks, molecular motors). One possible approach for molecular communication is through the use of bacteria, which can act as carriers for DNA-based information, i.e., plasmids. This paper analyzes multi-hop molecular nanonetworks that utilize bacteria as a carrier. The proposed approach combines different properties of bacteria to enable multi-hop transmission, such as conjugation and chemotaxis-based motility. Various analyses have been performed, including the correlation between the success rate of plasmid delivery to the destination node, and the role of conjugation in enabling this; as well as analyses on the impact of large topology shapes (e.g., Grid, Random, and Scale-free) on the success rate of plasmid delivery for multiple source-destination nanonetworks. A further solution proposed in this paper is the application of antibiotics to act as filters on illegitimate messages that could be delivered by the bacteria. Our evaluation, which has been conducted through a series of simulations, has shown that numerous bacteria properties fit to properties required for communication networking (e.g., packet filtering, routing, addressing). Read more
In this article, the targeting of dye molecules as an important goal is probed and simulated by quantum dots and through the particle swarm optimization algorithm and fluorescence resonance energy transfer mechanism. At first, we design a nano-bio sensor, based on the fluorescence resonance energy transfer mechanism, which operates in a wide range of wavelength and is very sensitive to fluorescence resonance energy transfer parameters such as overlapping between donor and acceptor, Föster radius, and energy transfer rate from donor to acceptor. In fact, the alteration of nano-bio sensor parameters acts as the heart of our sensor. The target is detected if the attained parameters of the sensors fulfilled the critical conditions and therefore, by the use of the particle swarm optimization algorithm which simulates the signaling and communication among quantum dots, other agents are called toward the target site. In this simulation, the positions of quantum dots as sensor agents and of the target are randomly considered. Moreover, to attain high targeting efficiency, the two different structures are introduced to maximum coverage of operational wavelength. Read more
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Performance Analysis and Design of Position-Encoded Microsphere Arrays Using the Ziv-Zakai Bound
Position-encoded microsphere arrays are a promising technology for identifying biological targets and quantifying their concentrations. In this paper we analyze the statistical performance of these arrays in imaging targets at typical low signal-to-noise ratio (SNR) levels. We compute the Ziv-Zakai bound (ZZB) on the errors in estimating the unknown parameters, including the target concentrations. We find the SNR level below which the ZZB provides a more accurate prediction of the error than the posterior Cramér-Rao bound (PCRB), through numerical examples. We further apply the ZZB to select the optimal design parameters of the microsphere array device and investigate the effects of the experimental variables such as microscope point-spread function. An imaging experiment on microspheres with protein targets verifies the optimal design parameters using the ZZB. Read more
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