Anti-CD4 activity of normal human immunoglobulin G for therapeutic use. (Intravenous immunoglobulin, IVIg)

The effects of intravenously administered normal immunoglobulin G (IVIg) in autoimmune diseases are dependent on the ability of IVIg to interact with surface molecules of lymphocytes. In the present study, we demonstrate the presence of anti-CD4 activity in IVIg by showing the ability of IVIg to bind to CD4 and to inhibit CD4-dependent cellular functions. Binding of IVIg to recombinant soluble human CD4 was assessed by ELISA, immunoblotting and real time analysis of complex formation. Anti-CD4 antibodies isolated from IVIg by affinity-chromatography bound to human CD4+ T cells. These anti-CD4 antibodies inhibited proliferative responses in MLR and infection of CD4+ human T cells with HIV. These results indicate that IVIg contains antibodies reactive with human CD4 and that these anti-CD4 antibodies exhibit biological functions. The presence of anti-CD4 antibodies in IVIg may be relevant to the immunoregulatory effects of normal polyspecific immunoglobulin G.     

Structural Investigation of Catalytically Grown Carbon Nanotubes

Carbon nanotubes (CNTs) having diameters in the range of 30–50 nm and few micrometers in length were synthesized in one step through a chemical-reduction route under autogenous pressure of H₂/CO₂. The synthesized materials prepared under different experimental conditions were characterized using different techniques. Results showed that V₂O₅ used as a catalyst for the nucleation of CNTs become carburized to vanadium carbide (V₈C₇) and provides a site for growth of CNTs. At high temperature, carbide particles thus formed become encapsulated at the tip of nanotube followed by the growth of CNTs through the tip-growth mechanism. Thermogravimetric analysis results showed that the CNTs obtained after the longer reaction time are more stable at high temperatures. Raman analysis showed a well-ordered graphite structure.     

Pyrolysis and combustion kinetics of Fosterton oil using thermogravimetric analysis

Thermogravimetric analysis (TGA) was used to examine the thermal behavior of Fosterton oil mixed with reservoir sand. TGA experiments were performed in nitrogen and air atmospheres at the heating rate of 10 °C/min up to 800 °C. In this study, four sets of TGA runs were performed to examine the thermal behavior of Fosterton whole oil, and the coke sample derived from the whole oil. Similar to previous studies in the literature, we also observed low-temperature oxidation (LTO), fuel deposition (FD), and high-temperature oxidation (HTO) in the non-isothermal combustion experiment. Higher activation energy values were obtained in reaction regions at higher temperatures. The mean activation energy for whole oil in nitrogen and air atmospheres was 33 and 126 kJ/mol, respectively. Fresh coke samples derived from whole oil were subjected to isothermal combustion at different temperatures from 375 to 500 °C. Arrhenius model was used to obtain the kinetic parameters from the TGA data. From the model, the Arrhenius parameters such as activation energy (E = 127 kJ/mol) and the pre-exponential factor (A = 1.6 × 10⁸/min) were determined for the coke combustion. The results showed a close agreement between the kinetic model and experimental data for different combustion temperatures. It was observed that the apparent order of combustion reaction for different temperatures approach unity.     

Random field finite elements

The probabilistic finite element method (PFEM) is formulated for linear and non-linear continua with inhomogeneous random fields. Analogous to the discretization of the displacement field in finite element methods, the random field is also discretized. The formulation is simplified by transforming the correlated variables to a set of uncorrelated variables through an eigenvalue orthogonalization. Furthermore, it is shown that a reduced set of the uncorrelated variables is sufficient for the second-moment analysis. Based on the linear formulation of the PFEM, the method is then extended to transient analysis in non-linear continua. The accuracy and efficiency of the method is demonstrated by application to a one-dimensional, elastic/plastic wave propagation problem and a two-dimensional plane-stress beam bending problem. The moments calculated compare favourably with those obtained by Monte Carlo simulation. Also, the procedure is amenable to implementation in deterministic FEM based computer programs.     

Radio-Frequency Coils in Implantable Devices: Misalignment Analysis and Design Procedure

Radio-frequency (RF) coils are used extensively in the design of implantable devices for transdermal power and data transmission. The practical issues of coil misalignments and configurations have not been investigated, and this paper presents a detailed theoretical analysis of misalignment effects in RF coil systems, including lateral and angular misalignments. Formulas are derived for the mutual inductance and, whenever possible, simplified upper bounds and lower bounds of the coupling coefficient are provided. A design procedure is established to maximize coil coupling for a given configuration, and a companion paper [1] discusses a circuit design technique to reduce the effects of misalignment on transmission efficiency.     

Real-coded genetic algorithm for machining condition optimization

In this paper, we consider the machining condition optimization models presented in earlier studies. Finding the optimal combination of machining conditions within the constraints is a difficult task. Hence, in earlier studies standard optimization methods are used. The non-linear nature of the objective function, and the constraints that need to be satisfied makes it difficult to use the standard optimization methods for the solution. In this paper, we present a real coded genetic algorithm (RCGA), to find the optimal combination of machining conditions. We present various issues related to real coded genetic algorithm such as solution representation, crossover operators, and repair algorithm in detail. We also present the results obtained for these models using real coded genetic algorithm and discuss the advantages of using real coded genetic algorithm for these problems. From the results obtained, we conclude that real coded genetic algorithm is reliable and accurate for solving the machining condition optimization models.