Biological evaluation of partially stabilized zirconia added HA/HDPE composites with osteoblast and fibroblast cell lines

In the present study, the biocompatibility of partially stabilized zirconia (PSZ) added hydroxyapatite (HA)––high density polyethylene (HDPE) composites was evaluated by proliferation and cell attachment assays on two osteoblast cell lines (G-292, Saos-2) and a type of fibroblast cell isolated from bone tissue namely HBF in different time intervals. Cell-material interactions on the surface of the composites were observed by scanning electron microscopy (SEM). The effect of composites on the behavior of osteoblast and fibroblast cells was compared with those of HDPE and Tissue Culture Poly Styrene (TPS) (as negative control) samples. Results showed that the composite samples supported a higher proliferation rate of osteoblast cells in the presence of composite samples as compared to the HDPE and TPS samples after 3, 7 and 14 days of incubation period. It was showed that an equal or in some cases an even higher proliferation rate of G-292 and Saos-2 osteoblast cells on composite samples in compare to negative controls in culture period (P < 0.05). The number of adhered cells on the composite samples was equal and in some cases higher than the number adhered on the HDPE and TPS samples after the above mentioned incubation periods (P < 0.05). Adhered cells presented a normal morphology by SEM and many of the cells were seen to be undergoing cell division.     

Linear Viscoelastic Characteristics of Poly(trimethylene terephthalate)/Polycarbonate Blends in the Melt State

Summary: Blends of poly(trimethylene terephthalate) (PTT) and polycarbonate (PC) over full composition range were prepared using a twin‐screw extruder. A glycidyl methacrylate‐based terpolymer was used to modify the interface of the blends. Morphological examinations were carried out using transmission electron microscopy (TEM) and confirmed the biphasic structure of the blends. Dynamic rheological response of the blends was recorded in the linear viscoelastic region. It was observed that addition of the terpolymer to the system increases the dynamic shear moduli and complex viscosity of the blends, which is attributed to interactions of the terpolymer at the interface of two phases leading to a restricted chain mobility of the blend components. The Veenstra model was found to be able to describe dynamic shear modulus of the PTT/PC 50/50 blend; however, for the compatibilized blend of PTT/PC 50/50, the fit is not as good as that of uncompatibilized system, which is believed to be due to formation of micelles in this system.

Dynamic storage modulus of the compatibilized and uncompatibilized PTT/PC blends.     

Predicting turbulent flow friction coefficient using ANFIS technique

The friction coefficient is widely used for technical and economical design of pipes in irrigation, land drainage, urban sewage systems and intake structures. In the present study, the friction factor in pipes is estimated by using adaptive neuro-fuzzy inference system (ANFIS) and grid partition method. The data derived from the Colebrook’s equation were considered for ascertaining the neuro-fuzzy model. Present approach developed an ANFIS technique to predict the friction coefficient as output variable based on pipe relative roughness and Reynold’s number as input variables. The performance of the ANFIS model was evaluated against conventional procedures. Correlation coefficient (R2), root mean squared error and mean absolute error were used as comparing statistical indicators for the assessment of the proposed approach’s performance. It was found that the adaptive neuro-fuzzy inference system model is more accurate than other empirical equations in modeling friction factor.     

Suprascapular nerve entrapment in a basketball player

A basketball player was shown to have a suprascapular nerve lesion without any history of shoulder girdle trauma. This acute neuropathy, never previously described in basketball players, is a result of repeated micro-trauma, due to nerve traction over the coracoid notch during violent movement ("dunking" most probably). Clinically, he was unable to abduct his arm and had some difficulty in external rotation. He developed atrophy in both the supra- and the infraspinatus muscles. Nerve conduction latency to the supraspinatus muscle was 8.0 ms, and to the infraspinatus, 8.5 ms. The compound muscle action potential registered in the supraspinatus was 1.224 mV, and in the infraspinatus, 1.237 mV. After 3 weeks of inactivity, recovery was spontaneous and practically complete.     

A Framework for Enabling Internet Access Using Wi-Fi Peer-to-Peer Links

Wireless Personal Communications - To realize the vision of ubiquitous computing and reachability, major technological advances have been achieved to make smart portable devices both highly capable...     

Hybrid paper-based microfluidics: combination of paper-based analytical device (µPAD) and digital microfluidics (DMF) on a single substrate

Microfluidics found its place in point of care diagnostics. Microfluidic devices on paper substrate are proposed on both channel-based and digital microfluidics (DMF). But fluid flow controlling on microfluidics paper-based analytical devices (µPADs) and post-processing on DMF devices have limitations. In this work a new hybrid paper-based device is proposed with the aim of resolving these limitations and expanding the microfluidics capabilities in point of care diagnostics. The hybrid paper-based microfluidics (HPMF) device is composed of a DMF device following a µPAD in a single substrate, in which the DMF part performs the preprocessing steps of the test on droplets and transfers the resulting droplet to the µPAD part of the device for post-processing steps. The fabrication process of the device is rapid and very low cost due to use of paper substrate and out of clean-room processes. The results show that the proposed HPMF device can perform droplet operations: moving, mixing, and splitting.     

Intelligent control of photovoltaic system using BPSO-GSA-optimized neural network and fuzzy-based PID for maximum power point tracking

The maximum power point tracking (MPPT) technique is applied in the photovoltaic (PV) systems to achieve the maximum power from a PV panel in different atmospheric conditions and to optimize the efficiency of a panel. A proportional-integral-derivative (PID) controller was used in this study for tracking the maximum power point (MPP). A fuzzy gain scheduling system with optimized rules by subtractive clustering algorithm was employed for tuning the PID controller parameters based on error and error-difference in an online mode. In addition, an Elman-type recurrent neural network (RNN) was used for inverse identification of the PV system and for estimating the solar radiation intensity to determine the MPP voltage. The optimum number of neurons in the single hidden-layer of the RNN was determined by binary particle swarm optimization algorithm. The weights of this RNN were also optimized by using a hybrid method based on the Levenberg-Marquardt algorithm and gravitational search algorithm (GSA). In the proposed fitness function for optimization, both the RNN size and its convergence accuracy were considered. Thus, the algorithm for RNN optimization attempts to minimize both the structural complexity and the mean square error. Simulation results revealed superior performance of GSA in comparison with particle swarm, cuckoo, and grey wolf optimization algorithms. The performance of the proposed MPPT method was evaluated under four different ambient conditions. Our experimental results show that the proposed MPPT method is more efficient than the three competitive methods presented in recent years.     

Structural,Magnetic, Optical and Electrochemical Properties of a New Class of α-Fe2O3-Mx-NiFe2O4+δ (M = None,Co2+, Eu3+, Ho3+ and Yb3+) Nanocomposites

Journal of Superconductivity and Novel Magnetism - Synthesis of α-Fe2O3-Mx-NiFe2O4+δ (M?=?None, Co2+, Eu3+, Ho3+ and Yb3+) nanocomposites is reported for the first time by a...