Two-storage inventory model with lot-size dependent fuzzy lead-time under possibility constraints via genetic algorithm

Multi-item inventory models with stock dependent demand and two storage facilities are developed in a fuzzy environment where processing time of each unit is fuzzy and the processing time of a lot is correlated with its size. These are order-quantity reorder-point models with back-ordering if required. Here possibility and crisp constraints on investment and capacity of the small storehouse respectively are considered. The models are formulated as fuzzy chance constrained programming problem and is solved via generalized reduced gradient (GRG) technique when crisp equivalent of the constraints are available. A genetic algorithm (GA) is developed based on fuzzy simulation and entropy where region of search space gradually decreases to a small neighborhood of the optima and it is used to solve the models whenever the equivalent crisp form of the constraint is not available. The models are illustrated with some numerical examples and some sensitivity analyses have been done. For some particular cases results observed via GRG and GA are compared.     

Palladium(II)‐Catalyzed meta‐CH Olefination: Constructing Multisubstituted Arenes through Homo‐Diolefination and Sequential Hetero‐Diolefination

Divinylbenzene derivatives represent an important class of molecular building blocks in organic chemistry and materials science. Reported herein is the palladium‐catalyzed synthesis of divinylbenzenes by meta‐C? H olefination of sulfone‐based arenes. Successful sequential olefinations in a position‐selective manner provided a novel route for the synthesis of hetero‐dialkenylated products, which are difficult to access using conventional methods. Additionally, 1,3,5‐trialkenylated compounds can be generated upon successful removal of the directing group.     

Phenanthroline-fluorescein molecular hybrid as a ratiometric and selective fluorescent chemosensor for Cu2+ via FRET strategy: synthesis,computational studies and in vitro applications

A FRET-based chemosensor L containing donor phenanthroline and acceptor fluorescein moiety was designed, synthesised and characterised for the ratiometric fluorescent detection of Cu²⁺ in organo-aqueous solution. Probe L showed high selectivity and excellent sensitivity towards Cu²⁺ ions by exhibiting both colorimetric and fluorometric changes due to opening of the spirolactum ring of fluorescein upon complexation with Cu²⁺. In presence of Cu²⁺ ions, probe L formed L-Cu²⁺ complex in 1:1 stoichiometric fashion which is established on the basis of Job’s plot and mass spectroscopy. We also performed DFT computational studies to know the binding nature and coordination feature of the complex. Furthermore, fluorescence imaging studies revealed that probe L was cell permeable and could be used to detect intracellular Cu²⁺ in living cells.     

Atomistic modeling toward high‐efficiency carbon capture: A brief survey with a few illustrative examples

With the negative environmental implications of the anthropogenic emission of greenhouse gases like CO₂ having been scientifically established, emphasis is being placed on a concerted global effort to prevent such gases from reaching the atmosphere. Especially important are capture efforts at large point emission sources like fossil fuel power generation, natural gas processing, and various industrial plants. Given the importance and scale of such activities, it is a significant priority to optimize the capture process in terms of speed, energy requirements, and cost efficiency. For CO₂ capture, in particular, multiple systems are being pursued both with near‐term retrofitting and medium‐ to long‐term designs in mind, including: (1) liquid solvents like amines, carbonates, and ionic liquids (ILs); (2) microporous sorbents like zeolites, activated carbon, and metal‐organic frameworks; (3) solid sorbents like metal‐oxides and ionic clays; and (4) polymeric and inorganic membrane separators. Each system is unique in its molecular‐level guest–host interactions, chemistry, heats of adsorption/desorption, and equilibrium thermodynamic and transport properties as a function of loading, temperature, and pressure. This opens up exciting opportunities for molecular modeling in the design and optimization of materials systems. Here, we offer a brief survey of molecular modeling applications in the field of carbon capture, with a few illustrative examples from our own work primarily involving amine solutions and ILs. Important molecular dynamics, Monte Carlo, and correlations‐based work in the literature relevant to CO₂ capture in other systems are also discussed. © 2013 Wiley Periodicals, Inc.     

Thermodynamics of water entry in hydrophobic channels of carbon nanotubes

Experiments and computer simulations demonstrate that water spontaneously fills the hydrophobic cavity of a carbon nanotube. To gain a quantitative thermodynamic understanding of this phenomenon, we use the recently developed two phase thermodynamics method to compute translational and rotational entropies of confined water molecules inside single-walled carbon nanotubes and show that the increase in energy of a water molecule inside the nanotube is compensated by the gain in its rotational entropy. The confined water is in equilibrium with the bulk water and the Helmholtz free energy per water molecule of confined water is the same as that in the bulk within the accuracy of the simulation results. A comparison of translational and rotational spectra of water molecules confined in carbon nanotubes with that of bulk water shows significant shifts in the positions of the spectral peaks that are directly related to the tube radius.     

Chitosan nanoparticles of 5-fluorouracil for ophthalmic delivery: characterization, in-vitro and in-vivo study

The aim of this investigation was to develop 5-fluorouracil (5-FU) loaded chitosan nanoparticles (CH-DNPs) for ophthalmic delivery. CH-DNPs were fabricated by ionotropic gelation mechanism using chitosan (CH) and a polyanion (TPP). The nanoparticles were smooth and spherical, confirmed by scanning electron microscopy (SEM) and atomic force microscope (AFM). CH/TPP mass ratio and TPP significantly changed the particles size morphology and encapsulation efficiency. The nanoparticles size ranged from approximately 114 to 192 nm and had a positive zeta potential (30±4 mV). The encapsulation efficiency, loading capacity and recovery of DNPs were 8.12-34.32%, 3.14-15.24% and 24.22 to 67% respectively. Physical characterization was done by Fourier transform infrared (FT-IR) and X-ray diffraction (XRD). No interaction was observed in between drug and polymer and crystallinity of drug was not changed in drug loaded nanoparticles. In-vitro release study of DNPs showed diffusion controlled release. Bioavailability study of batch CS9 was studied in rabbit eye and compare to 5-FU solution. 5-FU level was significantly higher in aqueous humor of rabbit eye. Ocular tolerance was studied in the eye of New Zealand rabbits and tested formulation was non-irritant with no sign of inflammation.     

Multiplex cancer cell detection by SERS nanotags with cyanine and triphenylmethine Raman reporters

SERS nanotags have been prepared to accomplish the multiplex detection of cancer cells. Herein we evaluated the adequacy of lipoic acid-containing cyanine derivatives (Cy3LA and Cy5LA) to function as multiplex partners with a triphenylmethine Raman reporter (B2LA) under a single excitation wavelength. SERS experiments enabled the multiplex recognition of two different cancer cells with antibody-conjugated nanotags that were derivatized with optimized cyanine and triphenylmethine reporters.     

Chemoselectivity in the Cu-catalyzed O-arylation of phenols and aliphatic alcohols

An orthogonal set of Cu-catalysts for the selective mono-arylation of alkyl aryl diols using aryl iodides is presented. Picolinic acid ligated copper catalyst provided phenol O-arylation only, while alkyl aryl ethers are generated by ligand-free copper catalyst in the presence of 2 equivalents NaOt-Bu.     

Two storage inventory model in a mixed environment

Multi-item inventory models with two storage facility and bulk release pattern are developed with linearly time dependent demand in a finite time horizon under crisp, stochastic and fuzzy-stochastic environments. Here different inventory parameters—holding costs, ordering costs, purchase costs, etc.—are assumed as probabilistic or fuzzy in nature. In particular cases stochastic and crisp models are derived. Models are formulated as profit maximization principle and three different approaches are proposed for solution. In the first approach, fuzzy extension principle is used to find membership function of the objective function and then it’s Graded Mean Integration Value (GMIV) for different optimistic levels are taken as equivalent stochastic objectives. Then the stochastic model is transformed to a constraint multi-objective programming problem using Stochastic Non-linear Programming (SNLP) technique. The multi-objective problems are transferred to single objective problems using Interactive Fuzzy Satisfising (IFS) technique. Finally, a Region Reducing Genetic Algorithm (RRGA) based on entropy has been developed and implemented to solve the single objective problems. In the second approach, the above GMIV (which is stochastic in nature) is optimized with some degree of probability and using SNLP technique model is transferred to an equivalent single objective crisp problem and solved using RRGA. In the third approach, objective function is optimized with some degree of possibility/necessity and following this approach model is transformed to an equivalent constrained stochastic programming problem. Then it is transformed to an equivalent single objective crisp problem using SNLP technique and solved via RRGA. The models are illustrated with some numerical examples and some sensitivity analyses have been presented.