A PVC Plasticized Sensor for Ni(II) Ion Based on a Simple Ethylenediamine Derivative

new PVC membrane ion selective electrode which is highly selective towards Ni(II) ions was constructed using a Schiff base containing a binaphthyl moiety as the ionophore. The sensor exhibited a good Nernstian response for nickel ions over the concentration range 1.0 × 10–1 – 5.0 × 10–6 M with a lower limit of detection of 1.3 × 10–6 M. It has a fast response time and can be used for a period of 4 months with a good reproducibility. The sensor is suitable for use in aqueous solutions in a wide pH range of 3.6 – 7.4 and works satisfactorily in the presence of 25% (v/v) methanol or ethanol. The sensor shows high selectivity to nickel ions over a wide variety of cations. It has been successfully used as an indicator electrode in the potentiometric titration of nickel ions against EDTA and also for the direct determination of nickel content in real samples: effluent samples, chocolates and hydrogenated oils.

A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks

We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991.

Synthesis and Aggregation Behavior of Pluronic F87/Poly(acrylic acid) Block Copolymer with Doxorubicin

Poly(acrylic acid) (PAA) was grafted onto both termini of Pluronic F87 (PEO₆₇-PPO₃₉-PEO₆₇) via atom transfer radical polymerization to produce a novel muco-adhesive block copolymer PAA₈₀-b-F₈₇-b-PAA₈₀. It was observed that PAA₈₀-F₈₇-PAA₈₀ forms stable complexes with weakly basic anti-cancer drug, Doxorubicin. Thermodynamic changes due to the drug binding to the copolymer were assessed at different pH by isothermal titration calorimetry (ITC). The formation of the polymer/drug complexes was studied by turbidimetric titration and dynamic light scattering. Doxorubicin and PAA-b-F87-b-PAA block copolymer are found to interact strongly in aqueous solution via non-covalent interactions over a wide pH range. At pH>4.35, drug binding is due to electrostatic interactions. Hydrogen-bond also plays a role in the stabilization of the PAA₈₀-F₈₇-PAA₈₀/DOX complex. At pH 7.4 (α=0.8), the size and stability of polymer/drug complex depend strongly on the doxorubicin concentration. When CDOX <0.13mM, the PAA₈₀-F₈₇-PAA₈₀ copolymer forms stable inter-chain complexes with DOX (110 ~ 150 nm). When CDOX >0.13mM, as suggested by the light scattering result, the reorganization of the polymer/drug complex is believed to occur. With further addition of DOX (CDOX >0.34mM), sharp increase in the turbidity indicates the formation of large aggregates, followed by phase separation. The onset of a sharp enthalpy increase corresponds to the formation of a stoichiometric complex.

Targeted Stimuli-Responsive Dextran Conjugates for Doxorubicin Delivery to Hepatocytes

A targeted, stimuli-responsive, polymeric drug delivery vehicle is being developed in our lab to help alleviate severe side-effects caused by narrow therapeutic window drugs. Targeting specific cell types or organs via proteins, specifically, lectin-mediated targeting holds potential due to the high specificity and affinity of receptor-ligand interactions, rapid internalization, and relative ease of processing. Dextran, a commercially available, biodegradable polymer has been conjugated to doxorubicin and galactosamine to target hepatocytes in a three-step, one-pot synthesis. The loading of doxorubicin and galactose on the conjugates was determined by absorbance at 485 nm and elemental analysis, respectively. Conjugation efficiency based on the amount loaded of each reactant varies from 20% to 50% for doxorubicin and from 2% to 20% for galactosamine. Doxorubicin has also been attached to dextran through an acid-labile hydrazide bond. Doxorubicin acts by intercalating with DNA in the nuclei of cells. The fluorescence of doxorubicin is quenched when it binds to DNA. This allows a fluorescence-based cell-free assay to evaluate the efficacy of the polymer conjugates where we measure the fluorescence of doxorubicin and the conjugates in increasing concentrations of calf thymus DNA. Fluorescence quenching indicates that our conjugates can bind to DNA. The degree of binding increases with polymer molecular weight and substitution of doxorubicin. In cell culture experiments with hepatocytes, the relative uptake of polymer conjugates was evaluated using flow cytometry, and the killing efficiency was determined using the MTT cell proliferation assay. We have found that conjugate uptake is much lower than that of free doxorubicin. Lower uptake of conjugates may increase the maximum dose of drug tolerated by the body. Also, non-galactosylated conjugate uptake is lower than that of the galactosylated conjugate. Microscopy indicates that doxorubicin localizes almost exclusively at the nucleus, whereas the conjugates are present throughout the cell. Doxorubicin linked to dextran through a hydrazide bond was used to achieve improved killing efficiency. Following uptake, the doxorubicin dissociates from the polymer in an endosomal compartment and diffuses to the nucleus. The LC₅₀ of covalently linked doxorubicin is 7.4 μg/mL, whereas that of hydrazide linked doxorubicin is 4.4 μg/mL.

General derivative relations for anharmonic force fields

The brace notation, introduced by Allen and Csaszar (1993, J. chem. Phys., 98, 2983), provides a simple and compact way to deal with derivatives of arbitrary non-tensorial quantities. One of its main advantages is that it builds the permutational symmetry of the derivatives directly into the formalism. The brace notation is applied to formulate the general nth-order Cartesian derivatives of internal coordinates, and to provide closed forms for general, nth-order transformation equations of anharmonic force fields, expressed as Taylor series, from internal to Cartesian or normal coordinate spaces.

X-ray crystallographic study of DNA duplex cross-linking: simultaneous binding to two d(CGTACG)(2) molecules by a bis(9-aminoacridine-4-carboxamide) derivative

Acridine-4-carboxamides form a class of known DNA mono-intercalating agents that exhibit cytotoxic activity against tumour cell lines due to their ability to inhibit topoisomerases. Previous studies of bis-acridine derivatives have yielded equivocal results regarding the minimum length of linker necessary between the two acridine chromophores to allow bis-intercalation of duplex DNA. We report here the 1.7 angstrom resolution X-ray crystal structure of a six-carbon-linked bis(acridine-4-carboxamide) ligand bound to d(CGTACG)(2) molecules by non-covalent duplex cross-linking. The asymmetric unit consists of one DNA duplex containing an intercalated acridine-4-carboxamide chromophore at each of the two CG steps. The other half of each ligand is bound to another DNA molecule in a symmetry-related manner, with the alkyl linker threading through the minor grooves. The two crystallographically independent ligand molecules adopt distinct side chain interactions, forming hydrogen bonds to either O6 or N7 on the major groove face of guanine, in contrast to the semi-disordered state of mono-intercalators bound to the same DNA molecule. The complex described here provides the first structural evidence for the non-covalent cross-linking of DNA by a small molecule ligand and suggests a possible explanation for the inconsistent behaviour of six-carbon linked bis-acridines in previous assays of DNA bis-intercalation.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Electronic energy transfer in a dinuclear Ru/Os complex containing a photoresponsive dithienylethene derivative as bridging ligand

In order to build up a multicomponent system able to perform useful light-induced functions, a dithienylethene-bridged heterodinuclear metal complex (Ru/Os) has been prepared. The compound was characterized and its photophysical properties studied in detail.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Eliminativism about derivative prima facie duties

Ross divides prima facie duties into derivative and foundational ones, but seems to understand the notion of a derivative prima facie duty in two very different ways. Sometimes he understands them in a non-eliminativist way. According to this understanding, basic prima facie duties ground distinct derivative ones. According to the eliminativist understanding, basic duties do not ground distinct derivative duties, but replace (eliminate) them. On the eliminativist view, discovering that a prima facie duty is derivative is discovering that it is not genuine. The genuine one is the basic one. I argue that Ross is best understood as an eliminativist.

The synthesis of dicobalt and dinickel complexes of trimethylsilylethynyl-1, 2-dihydrofullerene; characterisation by n.m.r. and structure of the first acyclic metal fullerene derivative: molecular structure of [η2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2(η-C5H5)2]

The synthesis and characterisation of the complexes [η2-{2-H-1-(Me3SiC ≡ C)-C60}Co2(CO)6] (2)} and [η-2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2η-C5H5)2] (3)} is reported, together with a single-crystal molecular structure for (3). This provides the first structural data for an acyclic metal derivative of [60]-fullerene.

Regularization of Descriptor Systems by Derivative and Proportional State Feedback

For linear multivariable time-invariant continuous or discrete-time singular systems it is customary to use a proportional feedback control in order to achieve a desired closed loop behaviour. Derivative feedback is rarely considered. This paper examines how derivative feedback in descriptor systems can be used to alter the structure of the system pencil under various controllability conditions. It is shown that derivative and proportional feedback controls can be constructed such that the closed loop system has a given form and is also regular and has index at most 1. This property ensures the solvability of the resulting system of dynamic-algebraic equations. The construction procedures used to establish the theory are based only on orthogonal matrix decompositions and can therefore be implemented in a numerically stable way. The problem of pole placement with derivative feedback alone and in combination with proportional state feedback is also investigated. A computational algorithm for improving the “conditioning” of the regularized closed loop system is derived.