Slow release polymer–iodine tablets for disinfection of untreated surface water

Simple water treatment devices are designed to treat small amounts of drinking water for home use. This study was undertaken to develop an iodine‐releasing polymeric formulation and examine its potential as a domestic water purifier for untreated surface water. The antimicrobial tablet formulation was made from gum arabic (GA), poly(vinylalcohol) (PVA), ethyl cellulose (EC), and poly(vinylpyrrolidone)‐iodine (PVP‐I). The formulation consisted of a dispersible core tablet surrounded by a hydrophilic coating of EC and poly(ethylene glycol) mixture. These stable, non‐vaporizing, and water‐insoluble tablets slowly release iodine through diffusion over 48 h when suspended in water. The swelling behavior and release were observed to be the functions of excipient composition, iodine loading, and coating materials. Iodine release was determined by UV–VIS spectroscopy and volumetric titrations. The tablets were also assessed for antimicrobial activity against Escherichia coli, Staphylococcus aureus, Listeria monocytogenes Scott A, and Salmonella typhimurium. The disinfection efficiency of the developed tablets was compared with a commercial formulation (Potable Aqua®) as both contain iodine‐releasing active compounds and work on the antimicrobial property of released iodine. The difference between the two formulations is that water‐dispersible Potable Aqua® has a higher amount of free iodine quickly available in water thereby making it a fast‐action emergency water purifier, whereas the developed water‐insoluble polymer–iodine tablets act slowly and require 24 h to show the same disinfection efficacy with lower content of iodine in water. Overnight release of iodine in water from polymer–iodine tablets was effective in 99.9% reduction of an initial cell count of ～ 10⁷ colony forming units (cfu)/mL. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Supervised inductive learning with Lotka–Volterra derived models

We present a classification algorithm built on our adaptation of the Generalized Lotka–Volterra model, well-known in mathematical ecology. The training algorithm itself consists only of computing several scalars, per each training vector, using a single global user parameter and then solving a linear system of equations. Construction of the system matrix is driven by our model and based on kernel functions. The model allows an interesting point of view of kernels’ role in the inductive learning process. We describe the model through axiomatic postulates. Finally, we present the results of the preliminary validation experiments.     

Residual analysis in random regressions using SAS and S-PLUS

A program package RRAP: Random Regression Residual Analysis Program using SAS [1] and S-PLUS [2] is available for performing random regression residual analysis. The PROCEDURE MIXED from SAS is used for statistical inference. Both elementary-level and individual-level residuals are used. The S-PLUS programs provide: (1) a transformation to orthogonalize the elementary-level correlated residuals for standard regression residual analyses; and (2) several statistics and plots for checking model assumptions, assessing model fitting and detecting outlying individuals. RRRAP starts with a SAS Macro RRRAPMAC on the data followed by a S-PLUS Program DoRRRAP on a UNIX system.     

Effect of aspect ratio on bed expansion in pirticulate fluidization

The effect of aspect ratio on the degree of bed expansion in particulate fluidization has been studied. For unicomponent solid systems of crushed particles with water as the fluidizing medium, the degree of bed expansion is independent of aspect ratio. Coal and limestone have been taken as the solid while aspect ratio has been varied from 1.10 to 4.67. The result is in full conformity with previous work with steel balls.     

Physical and mathematical modelling of flow and residence time distributions in different tundish designs

A steady state, three‐dimensional, turbulent flow model has been developed in‐house for analysis of melt flow and residence time distribution phenomena in steelmaking tundish system. The governing equations of flow, turbulence and tracer dispersion were derived in terms of the Cartesian co‐ordinate systems and solved numerically with their associated boundary conditions adapting a control volume based finite difference procedure. In the numerical solution scheme, the pressure‐velocity coupling was treated via the popular Simple (semi implicit method for pressure linked equations) algorithm. Prior to carrying out elaborate numerical predictions for tundish geometry, the model was applied to several standard test problems and evaluated against corresponding bench mark results. Thus, several typical test problems such as, flows in a cubic cavity, flows in ducts of rectangular cross‐section, flow over flat plate and so on were simulated numerically to assess the adequacy and appropriateness of the computational procedure developed. Results thus obtained together with the bench mark solutions indicated that the mathematical model is internally consistent and sufficiently robust. Accordingly, the turbulent flow model was applied to simulate flow and Residence Time Distributions (RTD) in four different tundish designs . These included, a single strand and a two strand slab casting tundish systems, a six strand rectangular shaped tundish and a six strand delta shaped billet casting tundish. Various RTD parameters (e.g., minimum break through time, t_min, time at which peak concentration occurs, t_peak and average residence time, t_av) were computed numerically in the four tundish systems and these were subsequently compared with corresponding experimental measurements derived from equivalent water model tundish systems. Except for the single strand tundish system, large differences between measurements and prediction (particularly on t_min and t_peak) were noted for the other three tundish geometries. Furthermore, the extent of such discrepancy was found to be relatively more pronounced for the multi‐strand tundish system. The possible reasons for such discrepancy is discussed in the text and it was shown computationally that relatively better agreement between theory and measurement can be achieved if, instead of the high Reynolds number k‐ε turbulence model, a low Reynolds number turbulence model is applied in the computational procedure.     

Numerical computation of flow phenomena in gas-stirred ladle systems

Quasi-single-phase mathematical models as applied to the ladle hydrodynamics have been analysed rigorously. It is shown that choice of convergence criteria, nodal configuration and differencing schemes all influence the computed results significantly and consequently, results independent of these numerical parameters must first be established to draw any useful conclusion. Several quasi-single-phase computational procedures reported in the literature to study the gas-injection-induced flow phenomena have been critically examined. To this end, experimentally measured bulk flow-fields, plume-rise velocity and gas voidages have been compared with those predicted numerically. Such comparisons indicate that the bottom injection phenomena (viz., bulk flow, plume-rise velocity, and gas volume fraction within the plume etc.) can be adequately represented by assuming bubble slippage and considering a constant rise velocity in the two-phase region in the numerical solution scheme.     

A Comparison of Several Component-Testing Plans For A Parallel System

We consider a parallel (1-out-of-n:G) system of n components with constant failure rates and treat three different classes of component testing procedures all of which guarantee that the given consumer and producer risks are not exceeded. It is necessary to impose certain restrictions on the magnitude of the unknown failure rates for guaranteeing the producer risk. The three classes of component test procedures use Type-I censoring and use decision rules based on: A) the total number of component failures during the testing periods, B) the number of failures for each individual component, and C) the maximum likelihood estimate of system reliability. Based on the requirement that both the consumer and producer risks lie within specified levels, class A plans exhibit lower testing costs in the selected numerical examples.