This paper presents a new correlation approach to predict total formation volume factor below the bubble point pressure for oil and gas mixtures. This correlation is obtained by using more than 450 experimental data points which are collected from samples of Iranian oil reservoirs. The important factors of influencing parameters are determined using an artificial neural network. Then an appropriate form of correlation is developed by multivariable regression. Finally by use of nonlinear optimization, the correlation coefficients are adjusted in an optimum level to minimize average absolute relative error. This new correlation is valid in a broad range of pressure and temperature and is more accurate than other ones for Iranian oil mixtures.

Wireless body area networks (WBANs) present a new solution to remote health monitoring. In a non-invasive WBAN deployment, the sensor nodes are implanted on the human body. These devices monitor health parameters such as body temperature, pressure, insulin levels, etc. A coordinator node is placed on body surface that collects information. The sensor nodes communicate monitored health parameters to the coordinator and the coordinator collects the data and forms an interface to other networks. An important concern here is the issue of network topology reorganization due to movement of body parts that enables sensor nodes to be mobile. A network topology reorganization scheme for WBANs is presented here that employs a tree based routing scheme wherein sensor nodes form a tree topology to communicate with the coordinator using one or more hops. In each hop, a node transfers the data with its immediate parent, and the data reaches the coordinator (root of the tree) in a finite number of hops. Here, the position of the mobile sensor nodes placed on body-parts (example, limbs- arms or legs), changes with respect to other nodes. This results in disruptions in communication or deterioration of received signal quality and therefore there is a need to reorganize the network topology. The proposed mechanism adapts the Zigbee network repair technique that accounts for the network topology restructuring. The proposed scheme ensures freedom from loops with reduced network repair time. It also accommodates dynamic changes in the network topology and thereby enables the network to scale in.

In an effort to develop new classes of NHC (N-heterocyclic carbenes) complexes, two imidazoline-anchored quat and bis-quat ligand systems have been synthesized. The process is superior owing to two approaches: (i) a new synthesized phase transfer catalyst, namely, 1,1’-benzene-1,4-diyldipyridinium dibromide (BDPDB) used to catalyze the phase-transfer hoffmann reaction of two structurally varied amines, dodecylamine and 1-amino-9, 10-anthraquinone. The reaction successfully gave the corresponding isocyanides that display the highest reactivity in reasonable to good yields. (ii) a cycloaddition-rearrangement reaction between imine and isocyanides based on chloroform gives easy access to a diverse range of highly substituted 4- and 2-imidazolines. Furthermore, imidazoline based bis-NHC (N-heterocyclic carbenes) precursors have been prepared and complexed to copper cation (4-L and 2-L, Figure 1). The molecular structures of the representative metal-NHC and metal-carbene bonds of these complexes have been elucidated and proved by elemental analyses, FT-IR, 1H & 13C NMR, and atomic adsorption spectroscopy. In contrast to the common assumption that NHCs are pure a-donors, the prepared complexes revealed a significant p-backbonding in electron-rich metal NHC complexes.

Skarns hosting fluid inclusions including melt inclusions, fluid-melt inclusions and vapor-liquid inclusions were found in skarn minerals from 29 main Fe, (Cu-Fe), (Au) and Au(Cu) Mo and Mo-Cu skarn deposits of China and 7 skarn deposits from the five Western countries. The fluid inclusions are many and varied in shape. Their sizes are commonly (10-46) × (6-15) µm2. They mainly consist of crystallized silicate phases such as garnet or pyroxene then calcite, hematite, magnetite, rutile, gypsum, anhydrite and/or water, together with other vapor phases. Results of Laser Raman spectrum analyses, microthermometric studies of the fluid inclusions, analyses of Sr, Nd, C-H-O isotopic compositions for skarns containing fluid inclusions and simulated experiments of magmatic skarns at high temperatures and high pressures are presented in this paper. An assimilation model of the formation mechanism of magmatic skarns has been advanced in this way: aliuminosilicate magmas intruded into limestone or marble first, then assimilated them to form high-T (P)-modified silicate melts, generating magmatic skarns. Based on the preceding data, we have reached some important conclusions: skarns studied in this paper are of magmatic genesis, rather than contact–metasomatic or metamophic origin. They are large in size and are wide in spatial distribution. Our conclusions are the same as that reached by Zhao Bin et al. in 2003 for study on characteristics of melt inclusions in skarn minerals from Fe. Cu(Au) and Au(Cu) ore deposits in the region from Daye to Jiujiang