Synthesis and thermal stability of potassium substituted hydroxyapatites and hydroxyapatite/β-tricalciumphosphate mixtures

Hydroxyapatite (HAP) and biphasic ceramics of two different HAP and β-tricalcium phosphate (β-TCP) proportions with substituted potassium were prepared through the aqueous precipitation method. The prepared powders were characterized using XRD, FT-IR and elemental analysis. The results have shown that potassium added during the synthesis was found present in the apatite structure even after calcination at 1300 °C without showing any significant change in the phase behaviour of resultant apatites. The substitution of potassium in the calcium deficient apatites was accompanied by the formation of biphasic mixture of HAP and β-TCP ceramics, upon calcination beyond 700 °C and the resultant mixtures were dependent on the initial Ca/P ratios of the precursors. The calculated cell constant values for potassium substituted apatites have shown contraction in a-axis and irregular changes in the c-axis relative to those of pure HAP prepared under the same experimental conditions.     

Knowledge networking to support medical new product development

New product development (NPD) in the pharmaceutical industry is very knowledge intensive. Knowledge generated and used during medical NPD processes is fragmented and distributed across various phases and artifacts. Many challenges in medical NPD can be addressed by the integration of this fragmented knowledge. We propose the creation and use of knowledge networks to address these challenges. Based on a case study conducted in a leading pharmaceutical company, we have developed a knowledge framework that represents knowledge fragments that need to be integrated to support medical NPD. We have also developed a prototype system that supports knowledge integration using knowledge networks. We illustrate the capabilities of the system through scenarios drawn from the case study. Qualitative validation of our approach is also presented.     

Deep Learning with Optimal Hierarchical Spiking Neural Network for Medical Image Classification

Medical image classification becomes a vital part of the design of computer aided diagnosis (CAD) models. The conventional CAD models are majorly dependent upon the shapes, colors, and/or textures that are problem oriented and exhibited complementary in medical images. The recently developed deep learning (DL) approaches pave an efficient method of constructing dedicated models for classification problems. But the maximum resolution of medical images and small datasets, DL models are facing the issues of increased computation cost. In this aspect, this paper presents a deep convolutional neural network with hierarchical spiking neural network (DCNN-HSNN) for medical image classification. The proposed DCNN-HSNN technique aims to detect and classify the existence of diseases using medical images. In addition, region growing segmentation technique is involved to determine the infected regions in the medical image. Moreover, NADAM optimizer with DCNN based Capsule Network (CapsNet) approach is used for feature extraction and derived a collection of feature vectors. Furthermore, the shark smell optimization algorithm (SSA) based HSNN approach is utilized for classification process. In order to validate the better performance of the DCNN-HSNN technique, a wide range of simulations take place against HIS2828 and ISIC2017 datasets. The experimental results highlighted the effectiveness of the DCNN-HSNN technique over the recent techniques interms of different measures. Please type your abstract here.     

Computing Diameter in the Streaming and Sliding-Window Models

We investigate the diameter problem in the streaming and sliding-window models. We show that, for a stream of nn points or a sliding window of size nn, any exact algorithm for diameter requires W(n)\Omega(n) bits of space. We present a simple e\epsilon-approximation algorithm for computing the diameter in the streaming model. Our main result is an e\epsilon-approximation algorithm that maintains the diameter in two dimensions in the sliding-window model using O((1/e^3/2) log³n(logR+loglogn + log(1/e)))O(({1}/{\epsilon^{3/2}}) \log^{3}n(\log R+\log\log n + \log ({1}/{\epsilon}))) bits of space, where RR is the maximum, over all windows, of the ratio of the diameter to the minimum non-zero distance between any two points in the window.     

Recent Advances in Electrochemical Performances of Graphene Composite (Graphene-Polyaniline/Polypyrrole/Activated Carbon/Carbon Nanotube) Electrode Materials for Supercapacitor: A Review

The latest trend in the direction of miniaturized portable electronic devices has brought up necessitate for rechargeable energy sources. Among the various non conventional energy devices, the supercapacitor is the promising candidate for gleaning the energy. Supercapacitor, as a new energy device that colligates the gap between conventional capacitors and batteries, it has attracted more attention due to its high power density and long cycle life. Many researchers work on, synthesizing new electrode material for the development of supercapacitor. The electrode material possesses salient structure and electrochemical properties exhibit the efficient performance of the supercapacitor. Graphene has high carrier mobility, thermal conductivity, elasticity and stiffness and also has a theoretical specific capacitance of 2630 m²g^??1 corresponds to a specific capacitance of 550 Fg^??1. This article summarizes and reviews the electrochemical performance and applications of various graphene composite materials such as graphene/polyaniline, graphene/polypyrrole, graphene/metal oxide, graphene/activated carbon, graphene/carbon nanotube as an electrode materials towards highly efficient supercapacitors and also dealt with symmetric, asymmetric and hybrid nature of the graphene based supercapacitor.     

Supercritical carbon dioxide (scCO2) dispersion of poly(ethylene terephthalate)/clay nanocomposites: Structural,mechanical, thermal,and barrier properties

Dispersed poly(ethylene terephthalate) (PET)/clay nanocomposites can lead to materials with superior barrier and mechanical properties. PET/clay nanocomposites were prepared by melting extrusion of PET with as‐received or supercritical carbon dioxide (scCO₂) predispersed Cloisite^® 30B (30B). The predispersion of 30B was assessed by WAXD, SEM, and TGA, and results indicated that scCO₂ processing could predisperse 30B and the surface modification of the clay was preserved after processing. The structure of PET/30B nanocomposites was investigated by WAXD and TEM confirming that PET has penetrated into the clays inter‐galleries and the predispersed clays lead to improved interfacial interaction and homogenous clay dispersion. Both tensile strength and Young's modulus were improved by 12.1% and 24.9% respectively, as incorporating of 3 wt % of scCO₂ processed clay. Differential scanning calorimetry (DSC) results indicated that clay particles served as nucleation agent could increase the crystallinity whereas had no impact on melting process. In addition, with the addition of 1 wt % of predispersed clay, a significant reduction of oxygen permeation (～33%) was achieved at 23 °C and the maximum reduction (44%) was achieved by adding 3 wt % processed clay. Moreover, we confirmed the effect of temperature on the permeation of PET/30B nanocomposites depended both on the Arrhenius behavior of the organic phases and tortuous path effects, where improved clay dispersion resulted in a higher effective activation energy. Moreover, the transparency of PET matrix was preserved for all nanocomposites. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44779.     

Investigations of Fe-Ru bimetallic catalysts by in situ Mössbauer and EXAFS studies

In situ Mössbauer and EXAFS investigations have shown that the reduction of iron in the monometallic Fe/SiO₂ catalyst is only partial, the reduction being mostly to a ferrous silicate phase. In the bimetallic Fe-Ru/SiO₂ catalysts, the proportion of the FeRu alloy formed on reduction increases markedly with the increase in Ru content; clearly, Ru significantly enhances the reduction of iron on SiO₂. In the Ru-rich compositions (Ru/Fe 1.0), most of the iron is present in the alloy phase and there is no segregation of -Fe. A comparative study of the different supports has shown that -Al₂O₃ and SiO₂ interact with iron strongly at low reduction temperatures while the TiO₂ support interacts at higher temperatures. The presence of traces of Fe³⁺ often found in reduced Fe-Ru catalysts is shown to arise from the oxidation of fine segregated iron particles on the support.Contribution No. 831 from the Solid State and Structural Chemistry Unit.     

Widespread occurrence of perchlorate in water,foodstuffs and human urine collected from Kuwait and its contribution to human exposure

Perchlorate is a thyroid hormone-disrupting compound and is reported to occur widely in the environment. Little is known on human exposure to perchlorate in Kuwait. In this study, 218 water samples, 618 commonly consumed foodstuffs and 532 urine samples collected from Kuwait were analysed to assess the exposure of the Kuwaiti population to perchlorate. For the estimation of daily intake of perchlorate, food consumption rates were obtained from the National Nutrition Survey in the State of Kuwait (NNSSK). The results showed that leafy vegetables accounted for a major share of perchlorate exposure among the Kuwaiti population at 0.062 µg kg^–1 bw day^–1 (36.2%), followed by fruits at 0.026 µg kg^–1 bw day^–1 (15.3%) and non-leafy vegetables at 0.017 µg kg^–1 bw day^–1 (10.1%). The urinary perchlorate geometric mean (GM) concentrations ranged from 8.51 to 17.1 µg l^–1 for the five age groups, which were higher than those reported in other countries. The estimated urinary perchlorate exposure for the Kuwaiti general population was 0.42 µg kg^–1 bw day^–1, which was higher than that reported for the United States. The dietary intake of perchlorate for the Kuwaiti population ranged from 0.14 to 0.67 µg kg^–1 bw day^–1 for the five age groups, with a mean total daily intake of 0.17 µg kg^–1 bw day^–1 for the general population. The highest estimated dietary mean daily intake of perchlorate (0.67 µg kg^–1 bw day^–1) was found for children at 3–5 years. The estimated dietary perchlorate exposure in Kuwait is higher than the recommended mean reference dose (RfD) but lower than that of provisional maximum tolerable daily intake (PMTDI) set by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).     

Cross-layer based multiclass intrusion detection system for secure multicast communication of MANET in military networks

Wireless Networks - Multicast communication of mobile ad hoc networks (MANET), rather than multiple unicast communication, delivers common content to more than one receiver at a time. Due to...