Host-Assisted Delivery of a Model Drug to Genomic DNA: Key Information from Ultrafast Spectroscopy and in silico Study

Drug delivery to a target without adverse effects is one of the major criteria for clinical use. Herein, we have made an attempt to explore the delivery efficacy of SDS surfactant in a monomer and micellar stage during the delivery of the model drug, Toluidine Blue (TB) from the micellar cavity to DNA. Molecular recognition of pre-micellar SDS encapsulated TB with DNA occurs at a rate constant of k₁ ∼652 s⁻¹. However, no significant release of encapsulated TB at micellar concentration was observed within the experimental time frame. This originated from the higher binding affinity of TB towards the nano-cavity of SDS at micellar concentration which does not allow the delivery of TB from the nano-cavity of SDS micelles to DNA. Thus, molecular recognition controls the extent of DNA recognition by TB which in turn modulates the rate of delivery of TB from SDS in a concentration-dependent manner.     

Some Observations of Diatoms Under Turbulence

The effect of turbulence on several freshwater diatom taxa was investigated and our findings are described herein. We have compared diatom morphology in shallow natural systems that experience turbulence due to wind and in river/waterfall systems where turbulence is due to high flow rates. We have also introduced turbulence into diatom laboratory cultures by mechanical shaking and by forcing air into the media. In particular, we have studied diatoms in five independent environments or cultures: the freshwater diatoms Tabellaria and Eunotia in equatorial lakes experiencing extreme seasonal variability in depth; two freshwater diatom monocultures of Aulacoseira granulata var angustissima and Melosira varians in the laboratory; and a freshwater diatom community possessing equal amounts (by number) of elongated and non-elongated diatoms (mostly Nitzschia and mostly Cyclotella, respectively) in the laboratory. We have demonstrated the effect of turbulence on freshwater diatom frustule morphologies and, perhaps more importantly, the effect of turbulence on freshwater diatom species population after controlled perturbation of the organisms’ environment. It has been widely reported that symmetry is often preferred in biological evolution, however here we have observed a preference towards asymmetry for the survival of diatoms in the presence of environmental stress (in particular, turbulence). We also note that to date there have been no systematic attempts to manipulate diatom frustules using external stimuli. We therefore present a proof-of-concept study in order to demonstrate: (i) that diatom morphologies can be manipulated by controlled simple external triggers (chemical and physical) (ii) that population balance (i.e. natural selection) can be controlled via simple external triggers (chemical and physical). This approach could open up an entire new field of future studies wherein controlled environmental perturbations are used to manipulate the structure, form, growth and reproduction of biological species.     

Structural Evolution of Q-Carbon and Nanodiamonds

This article provides insights pertaining to the first-order phase transformation involved in the growth of densely packed Q-carbon and nanodiamonds by nanosecond laser melting and quenching of diamond-like carbon (DLC) thin films. DLC films with different sp³ content were melted rapidly in a controlled way in super-undercooled state and quenched, leading to formation of distinct nanostructures, i.e., nanodiamonds, Q-carbon, and Q-carbon nanocomposites. This analysis provides direct evidence of the dependence of the super-undercooling on the structural evolution of Q-carbon. Finite element heat flow calculations showed that the super-undercooling varies monotonically with the sp³ content. The phenomenon of solid–liquid interfacial instability during directional solidification from the melt state is studied in detail. The resulting lateral segregation leads to formation of cellular filamentary Q-carbon nanostructures. The dependence of the cell size and wavelength at the onset of instability on the sp³ content of DLC thin films was modeled based on perturbation theory.     

Delineation of Groundwater Potential Zones of Coastal Groundwater Basin Using Multi-Criteria Decision Making Technique

Delineation of groundwater potential zones (GWPZ) has been performed for a coastal groundwater basin of eastern India. The groundwater potential zone index (GWPZI) map is generated by using Analytic Hierarchy Process (AHP) from different influencing features, e.g., Land Use/Land Cover (LU/LC), soil (S), geomorphology (GM), hydrogeology (HG), surface geology (SG), recharge rate (RR), drainage density (DD), rainfall (RF), slope (Sl), surface water bodies (SW), lineament density (LD), and Normalized Difference Vegetative Index (NDVI). Recharge rate values are estimated from hydrological water balance model. Overlay weighted sum method is used to integrate all thematic feature maps to generate GWPZ map of the study area. Four zones have been identified for the coastal groundwater basin [very good: 36.39 % (273.53 km², good: 43.57 % (327.47 km²), moderate: 18.27 % (137.30 km²), and poor: 1.77 % (13.27 km²)]. Areas in north to south-west and south-east direction show very good GWPZ due to the presence of low drainage density. GWPZ map and well yield values show good agreement. Sensitivity analysis reveals that exclusion/absence of rainfall and lineament density increases the poor groundwater potential zones. Omission of hydrogeology, soils, surface geology, and NDVI show maximum increase in good GWPZ. Obtained GWPZ map can be utilized effectively for planning of sustainable agriculture. This analysis demonstrates the potential applicability of the methodology for a general coastal groundwater basin.     

Modeling and simulation of enhancement mode p-GaN Gate AlGaN/GaN HEMT for RF circuit switch applications

An enhancement mode p-GaN gate AlGaN/GaN HEMT is proposed and a physics based virtual source charge model with Landauer approach for electron transport has been developed using Verilog-A and simulated using Cadence Spectre, in order to predict device characteristics such as threshold voltage, drain current and gate capacitance. The drain current model incorporates important physical effects such as velocity saturation, short channel effects like DIBL (drain induced barrier lowering), channel length modulation (CLM), and mobility degradation due to self-heating. The predicted I_d-V_ds, I_d-V_gs, and C-V characteristics show an excellent agreement with the experimental data for both drain current and capacitance which validate the model. The developed model was then utilized to design and simulate a single-pole single-throw (SPST) RF switch.     

High speed multiplier using Nikhilam Sutra algorithm of Vedic mathematics

This article presents the design of a new high-speed multiplier architecture using Nikhilam Sutra of Vedic mathematics. The proposed multiplier architecture finds out the compliment of the large operand from its nearest base to perform the multiplication. The multiplication of two large operands is reduced to the multiplication of their compliments and addition. It is more efficient when the magnitudes of both operands are more than half of their maximum values. The carry save adder in the multiplier architecture increases the speed of addition of partial products. The multiplier circuit is synthesised and simulated using Xilinx ISE 10.1 software and implemented on Spartan 2 FPGA device XC2S30-5pq208. The output parameters such as propagation delay and device utilisation are calculated from synthesis results. The performance evaluation results in terms of speed and device utilisation are compared with earlier multiplier architecture. The proposed design has speed improvements compared to multiplier architecture presented in the literature.     

Multi-objective evolutionary algorithm for SSSC-based controller design

In this paper, an evolutionary multi-objective optimization approach is employed to design a static synchronous series compensator (SSSC)-based controller. The design objective is to improve the transient performance of a power system subjected to a severe disturbance by damping the multi-modal oscillations namely; local mode, inter-area mode and inter-plant mode. A genetic algorithm (GA)-based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented and compared with a PI controller under various disturbances namely; three-phase fault, line outage, loss of load and unbalanced faults to show the effectiveness and robustness of the proposed approach.     

Computer-aided design of chiral ligands. Part I. Database search methods to identify chiral ligand types for asymmetric reactions

The utility of database searching to identify chiral ligand motifs is outlined. The key elements of three known chiral ligands have been described as bond vectors. The CAVEAT program was then used to screen the Cambridge Structural Database (CSD), portions of the Chemical Abstracts Services three-dimensional database (CAS-3D), and the TRIAD tricyclic structure database for scaffolds containing these elements. Scaffolds corresponding to the known starting points were identified indicating that this method can be used to identify chiral ligand structural motifs. In addition, alternate structural motifs were found that suggested alternative possible ligands.     

Automatic clustering algorithm based on multi-objective Immunized PSO to classify actions of 3D human models

Multi-objective clustering algorithms are preferred over its conventional single objective counterparts as they incorporate additional knowledge on properties of data in the from of objectives to extract the underlying clusters present in many datasets. Researchers have recently proposed some standardized multi-objective evolutionary clustering algorithms based on genetic operations, particle swarm optimization, clonal selection principles, differential evolution and simulated annealing, etc. In many cases it is observed that hybrid evolutionary algorithms provide improved performance compared to that of individual algorithm. In this paper an automatic clustering algorithm MOIMPSO (Multi-objective Immunized Particle Swarm Optimization) is proposed, which is based on a recently developed hybrid evolutionary algorithm Immunized PSO. The proposed algorithm provides suitable Pareto optimal archive for unsupervised problems by automatically evolving the cluster centers and simultaneously optimizing two objective functions. In addition the algorithm provides a single best solution from the Pareto optimal archive which mostly satisfy the users' requirement. Rigorous simulation studies on 11 benchmark datasets demonstrate the superior performance of the proposed algorithm compared to that of the standardized automatic clustering algorithms such as MOCK, MOPSO and MOCLONAL. An interesting application of the proposed algorithm has also been demonstrated to classify the normal and aggressive actions of 3D human models.