Spin populations in one-dimensional alternant spin systems: A theoretical approach

Spin-density maps, deduced from polarized neutron diffraction experiments, for both the pair and chain compounds of the system Mn2+Cu2+ have been reported recently. These results have motivated us to investigate theoretically the spin populations in such alternant mixed-spin systems. In this paper, we report our studies on the one-dimensional ferrimagnetic systems (S-A,S-B)(N) where hi is the number of AB pairs. We have considered all cases in which the spin Sri takes on allowed values in the range I to 7/2 while the spin S-B is held fixed at 1/2. The theoretical studies have been carried out on the isotropic Heisenberg model, using the density matrix renormalization group method. The effect of the magnitude of the larger spin SA On the quantum fluctuations in both A and B sublattices has been studied as a function of the system size N. We have investigated systems with both periodic and open boundary conditions, the latter with a view to understanding end-of-chain effects. The spin populations have been followed as a function of temperature as well as an applied magnetic field. High-magnetic fields are found to lead to interesting re-entrant behavior. The ratio of spin populations P-A-P-B is not sensitive to temperature at low temperatures.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Understanding solvent effects on structure and reactivity of organic intermediates: a Raman study

The effect of solvent on chemical reactivity has generally been explained on the basis of the dielectric constant and viscosity. However a number of spectroscopic studies, including UV-VIS, IR and Raman, has led to numerous empirical parameters to define solvent effect based on either solvating ability or polarity scale. These parameters include solvent polarizability, dipolarity, Lewis acidity and Lewis basicity, E-T(30), pi*, alpha, beta etc. However, from a structural point of view, we can separate solvation as static and dynamic processes. The static solvation basically relates to stabilization of the molecular structure by the solvent to attain the equilibrium structure, both in the intermediate and ground state. Dynamic solvation relates to solvent reorganization-induced dynamics prior to the structural reorganization to reach the equilibrium state. In this paper, we present (a) structural distortions induced by the solvent due to preferential solvation of the triplet excited state, and (b) the importance of dynamic solvation induced by vibronic coupling (pseudo-Jahn-Teller coupling). The examples include the effect of solvent on structure and reactivity of excited states of 2,2,2-trifluoroacetophenone (TFA). Based on the comparison of time resolved resonance Raman (TR3) data of TFA and other substituted acetophenone systems, it was found that change in solvent polarity indeed results in electronic state switching and structural changes in the excited state, which explains the trend in reactivity. Further, a TR3 study of fluoranil (FA) in the triplet excited state in solvents of varying polarities indicates that the structure of FA in the triplet excited state is determined by vibronic coupling effects and thus distorted structure. These experimental results have been well supported by density functional theoretical computational studies.

Understanding Membranes through the Molecular Design of Lipids

Lipids are amphiphilic molecules that are composed of hydrophilic and hydrophobic regions. A typical membranous aggregate (vesicles, water-filled lipid nanospheres) is formed upon the self-organization of lipids in water from a diverse collection of amphiphiles producing a dynamic supramolecular structure that shows phase behavior and ordering as required for specific biological functions. The determination of various physical properties of lipid aggregates is the key to determining structure-function relationships. Over the years, we have designed and synthesized a wide variety of lipid molecular systems for the investigation of their membrane-forming properties and have used them for purposes such as gene delivery and enzyme activation. In this feature article, we focus on our work on various types of lipids including ion-paired amphiphiles, cholesterol-based lipids, aromatic lipids, macrocyclic lipids containing disulfide tethers; cationic dimeric lipids, and so forth. The emphasis is oil experimental design and bottom-line conclusions.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

Dynamic scheduling in manufacturing systems using brownian approximations

Recently, Brownian networks have emerged as an effective stochastic model to approximate multiclass queueing networks with dynamic scheduling capability, under conditions of balanced heavy loading. This paper is a tutorial introduction to dynamic scheduling in manufacturing systems using Brownian networks. The article starts with motivational examples. It then provides a review of relevant weak convergence concepts, followed by a description of the limiting behaviour of queueing systems under heavy traffic. The Brownian approximation procedure is discussed in detail and generic case studies are provided to illustrate the procedure and demonstrate its effectiveness. This paper places emphasis only on the results and aspires to provide the reader with an up-to-date understanding of dynamic scheduling based on Brownian approximations.

Orientational relaxation in dipolar systems: How much do we understand the role of correlations

Dipolar systems, both liquids and solids, constitute a class of naturally abundant systems that are important in all branches of natural science. The study of orientational relaxation provides a powerful method to understand the microscopic properties of these systems and, fortunately, there are many experimental tools to study orientational relaxation in the condensed phases. However, even after many years of intense research, our understanding of orientational relaxation in dipolar systems has remained largely imperfect. A major hurdle towards achieving a comprehensive understanding is the long range and complex nature of dipolar interactions which also made reliable theoretical study extremely difficult. These difficulties have led to the development of continuum model based theories, which although they provide simple, elegant expressions for quantities of interest, are mostly unsatisfactory as they totally neglect the molecularity of inter-molecular interactions. The situation has improved in recent years because of renewed studies, led by computer simulations. In this review, we shall address some of the recent advances, with emphasis on the work done in our laboratory at Bangalore. The reasons for the failure of the continuum model, as revealed by the recent Brownian dynamics simulations of the dipolar lattice, are discussed. The main reason is that the continuum model predicts too fast a decay of the torque-torque correlation function. On the other hand, a perturbative calculation, based on Zwanzig's projection operator technique, provides a fairly satisfactory description of the single particle orientational dynamics for not too strongly polar dipolar systems. A recently developed molecular hydrodynamic theory that properly includes the effects of intermolecular orientational pair correlations provides an even better description of the single-particle orientational dynamics. We also discuss the rank dependence of the dielectric friction. The other topics reviewed here includes dielectric relaxation and solvation dynamics, as they are intimately connected with orientational relaxation. Recent molecular dynamics simulations of the dipolar lattice are also discussed. The main theme of the present review is to understand the effects of intermolecular interactions on orientational relaxation. The presence of strong orientational pair correlation leads to a strong coupling between the single particle and the collective dynamics. This coupling can lead to rich dynamical properties, some of which are detailed here, while a major part remains yet unexplored.

Thermodynamic constraints along isograms in ternary systems: application to three-phase equilibria

Thermodynamic constraints on component chemical potentials in three-phase fields introduced by the various isograms suggested in the literature are derived for a ternary system containing compounds. When compositions of two compounds lie on an isogram, it is associated with specific characteristics which can be used to obtain further understanding of the interplay of thermodynamic factors that determine phase equilibria. When two compounds are shared by adjacent three-phase fields, the constraints are dictated by binary compositions generated by the intersection of a line passing through the shared compounds with the sides of the ternary triangle. Generalized expressions for an arbitrary line through the triangle are presented. These are consistent with special relations obtained along Kohler, Colinet and Jacob isograms. Five axioms are introduced and proved. They provide valuable tools for checking consistency of thermodynamic measurements and for deriving thermodynamic properties from phase diagrams. (C) 1997 Elsevier Science S.A.

Charge Density Analysis of a Pentaborate Ion in an Ammonium Borate: Toward the Understanding of Topological Features in Borate Minerals

Structural and charge density distribution studies have been carried out on a single crystal data of an ammonium borate, [C(10)H(26)N(4)][B(5)O(6)(OH)(4)](2), synthesized by solvothermal method. Further, the experimentally observed geometry is used for the theoretical charge density calculations using the B3LYP/6-31G** level of theory, and the results are compared with the experimental values. Topological analysis of charge density based on the Atoms in Molecules approach for B-O bonds exhibit mixed covalent/ionic character. Detailed analysis of the hydrogen bonds in the crystal structure in the ammonium borate provides insights into the understanding of the reaction pathways that net atomic charges and electrostatic potential isosurfaces also give additional such systems. could result in the formation of borate minerals. The input to evaluate chemical and physical properties in such systems.

The R-x, R2-x Planes; Some New Ideas for the Study of Nonlinear Systems

Use of some new planes such as the R-x, R2-x (where R represents in the n-dimensional phase space, the radius vector from the origin to any point on the trajectory described by the system) is suggested for analysis of nonlinear systems of any kind. The stability conditions in these planes are given. For easy understanding of the method, the transformation from the phase plane to the R-x, R2-x planes is brought out for second-order systems. In general, while these planes serve as useful as the phase plane, they have proved to be simpler in determining quickly the general behavior of certain classes of second-order nonlinear systems. A chart and a simple formula are suggested to evaluate time easily from the R-x and R2-x trajectories, respectively. A means of solving higher-order nonlinear systems is also illustrated. Finally, a comparative study of the trajectories near singular points on the phase plane and on the new planes is made.

Understanding the Magnetization Reversal in Six-Fold Anisotropic Hexagonal Networks

Isolated magnetic nanowires have been studied extensively and the magnetization reversal mechanism is well understood in these systems. But when these nanowires are joined together in different architectures, they behave differently and can give novel properties. Using this approach, one can engineer the network architectures to get artificial anisotropy. Here, we report six-fold anisotropy by joining the magnetic nanowires into hexagonal network. For this study, we also benchmark the widely used micromagnetic packages: OOMMF, Nmag, and LLG-simulator. Further, we propose a local hysteresis method by post processing the spatial magnetization information. With this approach we obtained the hysteresis of nanowires to understand the six-fold anisotropy and the reversal mechanism within the hexagonal networks.

Review of Geohazard Warning Systems toward Development of a Popular Usage Geohazard Warning Communication System

The advent and evolution of geohazard warning systems is a very interesting study. The two broad fields that are immediately visible are that of geohazard evaluation and subsequent warning dissemination. Evidently, the latter field lacks any systematic study or standards. Arbitrarily organized and vague data and information on warning techniques create confusion and indecision. The purpose of this review is to try and systematize the available bulk of information on warning systems so that meaningful insights can be derived through decidable flowcharts, and a developmental process can be undertaken. Hence, the methods and technologies for numerous geohazard warning systems have been assessed by putting them into suitable categories for better understanding of possible ways to analyze their efficacy as well as shortcomings. By establishing a classification scheme based on extent, control, time period, and advancements in technology, the geohazard warning systems available in any literature could be comprehensively analyzed and evaluated. Although major advancements have taken place in geohazard warning systems in recent times, they have been lacking a complete purpose. Some systems just assess the hazard and wait for other means to communicate, and some are designed only for communication and wait for the hazard information to be provided, which usually is after the mishap. Primarily, systems are left at the mercy of administrators and service providers and are not in real time. An integrated hazard evaluation and warning dissemination system could solve this problem. Warning systems have also suffered from complexity of nature, requirement of expert-level monitoring, extensive and dedicated infrastructural setups, and so on. The user community, which would greatly appreciate having a convenient, fast, and generalized warning methodology, is surveyed in this review. The review concludes with the future scope of research in the field of hazard warning systems and some suggestions for developing an efficient mechanism toward the development of an automated integrated geohazard warning system. DOI: 10.1061/(ASCE)NH.1527-6996.0000078. (C) 2012 American Society of Civil Engineers.

The problem of clear air turbulence: Changing perspectives in the understanding of the phenomenon

Due to rapid improvements in on-board instrumentation and atmospheric observation systems, in most cases, aircraft are able to steer clear of regions of adverse weather. However, they still encounter unexpected bumpy flight conditions in regions away from storms and clouds. This is the phenomenon of clear air turbulence (CAT), which has been a challenge to our understanding as well as efforts at prediction. While most of such cases result in mild discomfort, a few cases can be violent leading to serious injuries to passengers and damage to the aircraft. The underlying physical mechanisms have been sought to be explained in terms of fluid dynamic instabilities and waves in the atmosphere. The main mechanisms which have been proposed are: (i) Kelvin-Helmholtz instability of shear layers, (ii) waves generated from flow over mountains, (iii) inertia-gravity waves from clouds and other sources, (iv) spontaneous imbalance theory and (v) horizontal vortex tubes. This has also undergone a change over the years. We present an overview of the mechanisms proposed and their implications for prediction.