Pulsed laser surface treatment of magnesium alloy: Correlation between thermal model and experimental observations

The effect of deposition of Al +Al2O3 on MRI 153 M Mg alloy processed using a pulsed Nd:YAG laser is presented in this study. A composite coating with metallurgical joint to the substrate was formed. The microstructure and phase constituents were characterized and correlated with the thermal predictions. The laser scan speed had an effect on the average melt depth and the amount of retained and/or reconstituted alumina in the final coating. The coating consisted of alumina particles and highly refined dendrites formed due to the extremely high cooling rates (of the order of 10(8) K/s). The microhardness of the coating was higher and several fold improvement of wear resistance compared to the substrate was observed for the coatings. These microstructural features and physical properties were correlated with the effects predicted by a thermal model.

Catalyzed air oxidation for treatment of thiosalt effulents

Continuous slurry reactor runs of two to four weeks duration were carried out for catalyzed air oxidation of thiosalts under a variety of conditions using poly (4-vinylpyridine) - Cu (II) and quaternized poly (4-vinylpyridine) - Cu (II) catalysts. Results obtained indicate that these catalysts have high activity and relatively long-term catalyst stability for thiosalt waste streams of < 1000 ppm thiosalt level. Using 2% (w/w) slurries of the poly (4-vinylpyridine) Cu (II) catalyst, effective oxidation of 700 ppm S2O32− influent to an effluent of < 100 ppm total thio-salts can be carried out continuously for at least one month when operating at 20 to 30°C with solution flow rates of$˜1l/h and aeration of 1300 XXX/h using a two-stage reactor system comprised of 12 l reactors. At higher thiosalt influent levels (i.e. > 1600 ppm) increased reaction temperatures enable depletion to < 100 ppm thiosalt effluent levels for up to one week of continuous operation. The catalysts deactivate much more readily at these higher influent levels as a result of greater copper losses and appreciable adsorption of S2O32− and S4O62−. The behaviour of continuous slurry reactors employed in the experimental studies, by use of batch reaction data for the poly (4-vinylpyridine) Cu (II) catalyzed oxidation of thiosalts, can be modelled successfully. Quaternized poly (4-vinylpyridine) Cu (II) catalyst has good long-term stability and copper losses are very low. The poly (4-vinylpyridine) Cu (II) catalyst, however, is susceptible to appreciable oxidation of the polymer matrix on long-term usage. This oxidation of the polymer matrix results in a substantial loss in the activity of the regenerated catalyst.

Miconazole in the treatment of superficial mycoses

Miconazole nitrate (2%) cream was evaluated in the treatment of superficial mycoses. Out of 116 patients having multiple clinical diagnoses, 66 cases were found to be positive by culture. Species of Trichophyton were the predominant etiological agents (in over 60%) followed by Candida species (20%) and Epidermophyton floccosum (15%). All the cases selected for study were followed up to a period of 4–18 months. A cure rate of 94.6 per cent was observed in all the cases where causal organisms were isolated. Significantly high cure rate (66%) was also seen in cases where causal organisms could not be isolated, including cases of tinea versicolor. Results of mycological examination were in confirmity with the clinical results

The perturbational treatment of the process of hydrogen abstraction by ketones

The change in energy during hydrogen abstraction by ketones is estimated for different electronic states as a function of the intermolecular orbital overlap employing perturbation theory. The results suggest that ketones preferentially undergo the in-plane reaction and abstract a hydrogen atom in their triplet nπ* state. For ketones where the triplet ππ* state lies below the triplet nπ* state, hydrogen abstraction can take place in the ππ* state owing to the crossing of the zero order reaction surfaces of the nπ* and ππ* states.

In vivo treatment of Heymann's Nephritis using a cytotoxic protein-toxin conjugate

In this study we investigated the possibility of treating Heymann's Nephritis (HN) by destroying antibody producing cells by targetting a toxin, gelonin - conjugated to gp330, the renal brush border antigen. HN was induced in rats by immunizing them with purified gp330. The gelonin-gp330 conjugate was administered 12 days after the antigenic challenge. Serum was screened for circulating antibodies. Proteinurea was estimated. The gp330-gelonin conjugate-treated animals had a circulating antibody titre in the serum much lower than that of diseased (untreated) animals. Proteinurea seen in diseased animals was not observed in treated animals. This work suggests the possibility of using a toxin-antigen conjugate for immunomodulating antibody mediated autoimmune renal disease.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

A general treatment of two dimensional plane flows, for a micropolar fluid

In this paper we have studied the flow of a micropolar fluid, whose constitutive equations were given by Eringen, in two dimensional plane flow. In two notes, we have discussed the validity of the boundary condition v=a ω and its effect on the entire flow field. We have restricted our study to the case when Stokes' approximation is valid, i. e. slow motion for it is difficult to uncouple the equations in the most general case.

Effective treatment of infectious diseases: A nonlinear adaptive control theoretic approach

A nonlinear adaptive system theoretic approach is presented in this paper for effective treatment of infectious diseases that affect various organs of the human body. The generic model used does not represent any specific disease. However, it mimics the generic immunological dynamics of the human body under pathological attack, including the response to external drugs. From a system theoretic point of view, drugs can be interpreted as control inputs. Assuming a set of nominal parameters in the mathematical model, first a nonlinear controller is designed based on the principle of dynamic inversion. This treatment strategy was found to be effective in completely curing "nominal patients". However, in some cases it is ineffective in curing "realistic patients". This leads to serious (sometimes fatal) damage to the affected organ. To make the drug dosage design more effective, a model-following neuro-adaptive control design is carried out using neural networks, which are trained (adapted) online. From simulation studies, this adaptive controller is found to be effective in killing the invading microbes and healing the damaged organ even in the presence of parameter uncertainties and continuing pathogen attack.

A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

Supramolecular insulin assembly II for a sustained treatment of type 1 diabetes mellitus

Diabetes is a chronic disease requiring continuous medical supervision and patient education to prevent acute secondary complications. In this study, we have harnessed the inherent property of insulin to aggregate into an oligomeric intermediate on the pathway to amyloid formation, to generate a form that exhibits controlled and sustained release for extended periods. Administration of a single dose of the insulin oligomer, defined here as the supramolecular insulin assembly II (SIA-II), to experimental animals rendered diabetic by streptozotocin or alloxan, released the hormone capable of maintaining physiologic glucose levels for > 120 days for bovine and > 140 days for recombinant human insulin without fasting hypoglycemia. Moreover, the novel SIA-II described here not only improved the glycemic control, but also reduced the extent of secondary diabetic complications.

In situ surface modification of molybdenum-doped organic-inorganic hybrid TiO2 nanoparticles under hydrothermal conditions and treatment of pharmaceutical effluent

Molybdenum-doped TiO2 organic-inorganic hybrid nanoparticles were synthesized under mild hydrothermal conditions by in situ surface modification using n-butylamine. This was carried out at 150 degrees C at autogeneous pressure over 18 h. n-Butylamine was selected as a surfactant since it produced nanoparticles of the desired size and shape. The products were characterized using powder X-ray diffraction, Fourier transform infrared spectrometry, dynamic light-scattering spectroscopy, UV-Vis spectroscopy and transmission electron microscopy. Chemical oxygen demand was estimated in order to determine the photodegradation efficiency of the molybdenum-doped TiO2 hybrid nanoparticles in the treatment of pharmaceutical effluents. It was found that molybdenum-doped TiO2 hybrid nanoparticles showed higher photocatalytic efficiency than untreated TiO2 nanoparticles.

Theoretical Treatment of Interaction Parameters in Multicomponent Metallic Solutions

A new theoretical equation for interaction parameter in multicomponent metallic solutions is developed using the pseudopotential formalism coupled with the free energy of the hard sphere system. The approximate expression for the pseudopotential term is given in terms of the heat of solution at infinite dilution, to allow easy evaluation of the interaction parameter in various multicomponent systems. This theory has been applied to 23 non-ferrous alloys based on Pb, Sn, Bi and indium. Comparison with the results of previous theoretical calculations using only the hard sphere model suggests that the inclusion of the pseudopotential term yields a quantitatively more correct prediction of interaction parameters in multicomponent metallic solutions. Numerical calculations were also made for 320 Fe-base solutions relevant to steelmaking and the agreement between calculation and experimental data appears reasonable, with 90% reliability in predicting the correct sign.

Desensitization to ATP-Mg inhibition of 3-hydroxy-3-methylglutarylCoA reductase by heat treatment of microsomes

HMGCoA reductase is found to be inhibited by palmitylCoA and free CoA. The inhibition of this enzyme by ATP-Mg, but not by palmityl CoA, is lost on preincubation of microsomes at 50°C for 15 min.