Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

The Skill of ECMWF Medium-Range Forecasts during the Year of Tropical Convection 2008

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains. For shorter lead times (less than 4-5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air-sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with ``zero'' precipitation and heavy (>40 mm day(-1)) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets. Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2-4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

Multicomponent self-sorting of a Pd-7 molecular boat and its use in catalytic Knoevenagel condensation

Unique three-component self-assembly of a cis-blocked 90 degrees Pd(II) acceptor with amixture of tri- and tetra-imidazole donors led to the self-sorting of a Pd-7 molecular boat with an internal nanocavity, which catalyses the Knoevenagel condensation of a series of aromatic aldehydes with 1,3-dimethylbarbituric acid and Meldrum's acid in aqueous media.

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

Novel derivatives of spirohydantoin induce growth inhibition followed by apoptosis in leukemia cells

Hydantoin derivatives possess a variety of biochemical and pharmacological properties and consequently are used to treat many human diseases. However, there are only few studies focusing on their potential as cancer therapeutic agents. In the present study, we have examined anticancer properties of two novel spirohydantoin compounds, 8-(3,4-difluorobenzyl)-1'-(pent-4-enyl)-8-azaspiro[bicyclo[3.2.1] octane-3,4'-imidazolidine]-2',5'-dione (DFH) and 8-(3,4-dichlorobenzyl)-1'-(pent-4-enyl)-8-azaspiro[bicyclo[3.2.1]octane-3,4'-imidazolidine]-2',5'-dione (DCH). Both the compounds exhibited dose- and time-dependent cytotoxic effect on human leukemic cell lines, K562, Reh, CEM and 8ES. Incorporation of tritiated thymidine ([H-3) thymidine) in conjunction with cell cycle analysis suggested that DFH and DCH inhibited the growth of leukemic cells. Downregulation of PCNA and p-histone H3 further confirm that the growth inhibition could be at the level of DNA replication. Flow cytometric analysis indicated the accumulation of cells at subG1 phase suggesting induction of apoptosis, which was further confirmed and quantified both by fluorescence-activated cell sorting (FACS) and confocal microscopy following annexin V-FITC/propidium iodide (PI) staining. Mechanistically, our data support the induction of apoptosis by activation of the mitochondrial pathway. Results supporting such a model include, elevated levels of p53, and BAD, decreased level of BCL2, activation and cleavage of caspase 9, activation of procaspase 3, poly (ADP-ribosyl) polymerase (PARP) cleavage, downregulation of Ku70, Ku80 and DNA fragmentation. Based on these results we discuss the mechanism of apoptosis induced by DFH and its implications in leukemia therapy. (C) 2008 Elsevier Inc. All rights reserved.

Probing into the role of conserved N-glycosylation sites in the Tyrosinase glycoprotein family

N-linked glycosylation has a profound effect on the proper folding, oligomerization and stability of glycoproteins. These glycans impart many properties to proteins that may be important for their proper functioning, besides having a tendency to exert a chaperone-like effect on them. Certain glycosylation sites in a protein however, are more important than other sites for their function and stability. It has been observed that some N-glycosylation sites are conserved over families of glycoproteins over evolution, one such being the tyrosinase related protein family. The role of these conserved N-glycosylation sites in their trafficking, sorting, stability and activity has been examined here. By scrutinizing the different glycosylation sites on this family of glycoproteins it was inferred that different sites in the same family of polypeptides can perform distinct functions and conserved sites across the paralogues may perform diverse functions.

Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management

Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting goals, which often leads to multi-objective optimization. In aid of effective decision-making to the water managers, apart from developing effective multi-objective mathematical models, there is a greater necessity of providing efficient Pareto optimal solutions to the real world problems. This study proposes a swarm-intelligence-based multi-objective technique, namely the elitist-mutated multi-objective particle swarm optimization technique (EM-MOPSO), for arriving at efficient Pareto optimal solutions to the multi-objective water resource management problems. The EM-MOPSO technique is applied to a case study of the multi-objective reservoir operation problem. The model performance is evaluated by comparing with results of a non-dominated sorting genetic algorithm (NSGA-II) model, and it is found that the EM-MOPSO method results in better performance. The developed method can be used as an effective aid for multi-objective decision-making in integrated water resource management.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Specificity for the Exchange of Phospholipids Through Polymyxin B Mediated Intermembrane Molecular Contacts

Structural specificity for the direct vesicle−vesicle exchange of phospholipids through stable molecular contacts formed by the antibiotic polymyxin B (PxB) is characterized by kinetic and spectroscopic methods. As shown elsewhere [Cajal, Y., Rogers, J., Berg, O. G., & Jain, M. K. (1996) Biochemistry 35, 299−308], intermembrane molecular contacts between anionic vesicles are formed by a small number of PxB molecules, which suggests that a stoichiometric complex may be responsible for the exchange of phospholipids. Larger clusters containing several vesicles are formed where each vesicle can make multiple contacts if sterically allowed. In this paper we show that the overall process can be dissected into three functional steps: binding of PxB to vesicles, formation of stable vesicle−vesicle contacts, and exchange of phospholipids. Polycationic PxB binds to anionic vesicles. Formation of molecular contacts and exchange of monoanionic phospholipids through PxB contacts does not depend on the chain length of the phospholipid. Only monoanionic phospholipids (with methanol, serine, glycol, butanol, or phosphatidylglycerol as the second phosphodiester substituent in the head group) exchange through these contacts, whereas dianionic phosphatidic acid does not. Selectivity for the exchange was also determined with covesicles of phosphatidylmethanol and other phospholipids. PxB does not bind to vesicles of zwitterionic phosphatidylcholine, and its exchange in covesicles is not mediated by PxB. Vesicles of dianionic phospholipids, like phosphatidic acid, bind PxB; however, this phospholipid does not exchange. The structural features of the contacts are characterized by the spectroscopic and chemical properties of PxB at the interface. PxB in intermembrane contacts is readily accessible from the aqueous phase to quenchers and reagents that modify amino groups. Results show that PxB at the interface can exist in two forms depending on the lipid/PxB ratio. Additional studies show that stable PxB-mediated vesicle−vesicle contacts may be structurally and functionally distinct from “stalks”, the putative transient intermediate for membrane fusion. The phenomenon of selective exchange of phospholipids through peptide-mediated contacts could serve as a prototype for intermembrane targeting and sorting of phospholipids during their biosynthesis and trafficking in different compartments of a cell. The protocols and results described here also extend the syllogistic foundations of interfacial equilibria and catalysis.

Optimal design of multiproduct batch chemical plant using NSGA-II

The optimal design of a multiproduct batch chemical plant is formulated as a multiobjective optimization problem, and the resulting constrained mixed-integer nonlinear program (MINLP) is solved by the nondominated sorting genetic algorithm approach (NSGA-II). By putting bounds on the objective function values, the constrained MINLP problem can be solved efficiently by NSGA-II to generate a set of feasible nondominated solutions in the range desired by the decision-maker in a single run of the algorithm. The evolution of the entire set of nondominated solutions helps the decision-maker to make a better choice of the appropriate design from among several alternatives. The large set of solutions also provides a rich source of excellent initial guesses for solution of the same problem by alternative approaches to achieve any specific target for the objective functions

Max-Coloring Paths: Tight Bounds and Extensions

The max-coloring problem is to compute a legal coloring of the vertices of a graph G = (V, E) with a non-negative weight function w on V such that Sigma(k)(i=1) max(v epsilon Ci) w(v(i)) is minimized, where C-1, ... , C-k are the various color classes. Max-coloring general graphs is as hard as the classical vertex coloring problem, a special case where vertices have unit weight. In fact, in some cases it can even be harder: for example, no polynomial time algorithm is known for max-coloring trees. In this paper we consider the problem of max-coloring paths and its generalization, max-coloring abroad class of trees and show it can be solved in time O(vertical bar V vertical bar+time for sorting the vertex weights). When vertex weights belong to R, we show a matching lower bound of Omega(vertical bar V vertical bar log vertical bar V vertical bar) in the algebraic computation tree model.

Turbulent flow computations on a hybrid cartesian point distribution using meshless solver LSFD-U

This paper may be considered as a sequel to one of our earlier works pertaining to the development of an upwind algorithm for meshless solvers. While the earlier work dealt with the development of an inviscid solution procedure, the present work focuses on its extension to viscous flows. A robust viscous discretization strategy is chosen based on positivity of a discrete Laplacian. This work projects meshless solver as a viable cartesian grid methodology. The point distribution required for the meshless solver is obtained from a hybrid cartesian gridding strategy. Particularly considering the importance of an hybrid cartesian mesh for RANS computations, the difficulties encountered in a conventional least squares based discretization strategy are highlighted. In this context, importance of discretization strategies which exploit the local structure in the grid is presented, along with a suitable point sorting strategy. Of particular interest is the proposed discretization strategies (both inviscid and viscous) within the structured grid block; a rotated update for the inviscid part and a Green-Gauss procedure based positive update for the viscous part. Both these procedures conveniently avoid the ill-conditioning associated with a conventional least squares procedure in the critical region of structured grid block. The robustness and accuracy of such a strategy is demonstrated on a number of standard test cases including a case of a multi-element airfoil. The computational efficiency of the proposed meshless solver is also demonstrated. (C) 2010 Elsevier Ltd. All rights reserved.

Biomass gasification: Environmentally sound technology for decentralized power generation, a case study from India

This study aims at understanding the need for decentralized power generation systems and to explore the potential, feasibility and environmental implications of biomass gasifier-based electricity generation systems for village electrification. Electricity needs of villages are in the range of 5–20 kW depending on the size of the village. Decentralized power generation systems are desirable for low load village situations as the cost of power transmission lines is reduced and transmission and distribution losses are minimised. A biomass gasifier-based electricity generation system is one of the feasible options; the technology is readily available and has already been field tested. To meet the lighting and stationary power needs of 500,000 villages in India the land required is only 16 Mha compared to over 100 Mha of degraded land available for tree planting. In fact all the 95 Mt of woody biomass required for gasification could be obtained through biomass conservation programmes such as biogas and improved cook stoves. Thus dedication of land for energy plantations may not be required. A shift to a biomass gasifier-based power generation system leads to local benefits such as village self reliance, local employment and skill generation and promotion of in situ plant diversity plus global benefits like no net CO2 emission (as sustainable biomass harvests are possible) and a reduction in CO2 emissions (when used to substitute thermal power and diesel in irrigation pump sets).

Seasonal prediction of the Indian monsoon

Under the project `Seasonal Prediction of the Indian Monsoon' (SPIM), the prediction of Indian summer monsoon rainfall by five atmospheric general circulation models (AGCMs) during 1985-2004 was assessed. The project was a collaborative effort of the coordinators and scientists from the different modelling groups across the country. All the runs were made at the Centre for Development of Advanced Computing (CDAC) at Bangalore on the PARAM Padma supercomputing system. Two sets of simulations were made for this purpose. In the first set, the AGCMs were forced by the observed sea surface temperature (SST) for May-September during 1985-2004. In the second set, runs were made for 1987, 1988, 1994, 1997 and 2002 forced by SST which was obtained by assuming that the April anomalies persist during May-September. The results of the first set of runs show, as expected from earlier studies, that none of the models were able to simulate the correct sign of the anomaly of the Indian summer monsoon rainfall for all the years. However, among the five models, one simulated the correct sign in the largest number of years and the second model showed maximum skill in the simulation of the extremes (i.e. droughts or excess rainfall years). The first set of runs showed some common bias which could arise either from an excessive sensitivity of the models to El Nino Southern Oscillation (ENSO) or an inability of the models to simulate the link of the Indian monsoon rainfall to Equatorial Indian Ocean Oscillation (EQUINOO), or both. Analysis of the second set of runs showed that with a weaker ENSO forcing, some models could simulate the link with EQUINOO, suggesting that the errors in the monsoon simulations with observed SST by these models could be attributed to unrealistically high sensitivity to ENSO.