Eggshell derived mesoporous biphasic calcium phosphate for biomedical applications using rapid thermal processing

Biphasic calcium phosphate (BCP) has received much interest for making various bone substitutes since its physicochemical properties can be easily tailored by tuning its phase composition. Due to high temperature processing, it is hard to prepare BCP with nanoscale characteristics. In the present study, we have made an attempt to optimize the heat treatment parameters for the synthesis of BCP with nanoscale characteristics from eggshell derived hydroxyapatite (HA) through rapid thermal processing (RTP). To accomplish this, eggshell derived HA was prepared by wet precipitation method and subjected to RTP at 750°C and 1150°C for 3 and 10 minutes. For comparison we have also studied conventional calcination at 750°C and 1150°C for 3 hours. XRD, FTIR, SEM, EDX, HRTEM, and BET analyses were used to understand the effect of RTP and conventional calcination on eggshell derived HA. Our results indicate that eggshell derived HA on RTP at 1150°C for 3 minutes and 10 minutes can offer nanoscale BCP with good dissolution, bioactivity, cytocompatibility, and mesoporous nature. Hence, RTP can be a potential method to prepare BCP with nanoscale features for biomedical applications.     

Hybrid supercapacitor based on poly(aniline-co-m-anilicacid) and activated carbon in non-aqueous electrolyte

A hybrid asymmetrical super capacitor has been fabricated based on p-doped poly(aniline-co-m-anilicacid) and activated carbon coated on SS electrodes. The characterization of material, electrode and performance of the super capacitor has been studied by FTIR, Cyclic Voltammetry, TGA/DTA, AC Impedance spectroscopy, and galvanostatic charge-discharge tests. The super capacitor showed a maximum specific capacitance of 102 F/g at a scan rate of 10 mV/s. The normalized active-reactive power behavior of the capacitor has been determined. The time constant calculated for the super capacitor is 6 milliseconds, indicating the suitability of the system for efficient use at low frequency range.     

Optimal tolerance design of assembly for minimum quality loss and manufacturing cost using metaheuristic algorithms

Tolerance allocation is a design tool for reducing overall cost of manufacturing while meeting target levels for quality. An important consideration in product design is the assignment of design and manufacturing tolerances to individual component dimensions so that the product can be produced economically and functions properly. The allocation of tolerances among the components of a mechanical assembly can significantly affect the resulting manufacturing costs. In this work, the tolerance allocation problem is formulated as a non-linear integer model by considering both the manufacturing cost of each component by alternate processes and the quality loss of assemblies so as to minimise the manufacturing cost. Metaheuristics techniques such as genetic algorithm and particle swarm optimisation are used to solve the model and obtain the global optimal solution for tolerance design. An example for illustrating the optimisation model and the solution procedure is provided. Results are compared with conventional technique and the performances are analysed.     

Financial Modeling and Prediction as a Service

This paper describes our proposal for Quality of Service (QoS) for Financial Modeling and Prediction as a Service (FMPaaS), since a majority of papers does not focus on SaaS level. We focus on two factors for delivering successful QoS, which are performance and accuracy for FMPaaS. The design process, theories and models behind the FMPaaS service have been explained. To support our FMPaaS service, two APIs have been developed to improve on performance and accuracy. Two major experiments have been illustrated and results show that each API processing can be completed in 2.12 seconds and 100,000 simulations can be completed in an acceptable period of time. Accuracy tests have been performed while using Facebook as an example. Three points of comparisons between actual and predicted prices have been undertaken. Results support accuracy since results are between 93.72 % and 99.63 % for Facebook. Three case studies have been used and results can support the accuracy and validity of the high level of accuracy offered by FMPaaS.     

Prediction of Heat of Vapourization of Moisture from Cereal Grains - A Modelling Approach

ABSTRACT

The Henderson's EMC model in modified form was used to fit the EMC data given by Engels et al (1987) for brown, parboiled rice. The constants in the model were related to temperature. A method to find an expression for heat of vapourization of moisture from grain was developed and demonstrated using the EMC data of brown, parboiled rice. The heat of vapourization of moisture from rice was high at low moisture contents. For moisture contents above 25% (db), the moisture inside the grain behaved almost like free water.     

Certain Investigation on Visible Light Communication with OFDM Modulated White LED Using Optisystem Simulation

Wireless Personal Communications - Visible light communication (VLC) has drawn more attention in recent years. It is due to the reason that the existing light sources for lighting application in...     

Landslide-Hazard Mapping Using an Expert System and a GIS

This paper presents a rule-based expert system used to create landslide warning and alert maps using as input change of landuse data from Earth observation, as well as geological, rainfall, and earthquake data stored in a Geographic Information System. The difference with other systems is in the use of change (differential) input data. The system is tested with 16 documented landslides. It can predict 11 of the 16 landslides to be among the 10% most at risk pixels in the area of study, which covers 100 km²