Tuning excited-state electron transfer from an adiabatic to nonadiabatic type in donor-bridge-acceptor systems and the associated energy-transfer process

Through design and synthesis of a new series of dyads I-III composed of 2,3-dimethoxynaphthalene as an electron donor (D) and 2,3-dicyanonaphthalene as an acceptor (A) bridged by n-norbornadiene (n = 1-3) we demonstrate an excellent prototype to switch the excited-state electron-transfer dynamics from an adiabatic to a nonadiabatic process. I reveals a remarkable excitonic effect and undergoes an adiabatic type of electron transfer (ET), resulting in a unique charge-transfer emission, of which the peak wavelength exhibits strong solvatochromism. Conversely, upon exciting the donor moiety, a fast D --> A energy transfer takes place for II (approximately 3 ps) and III (< or =30 ps), followed by a nonadiabatic type, weak coupled electron transfer with a relatively slow ET rate, giving rise to dual emission in polar solvents. Further detailed temperature-dependent studies of the ET rate deduced reaction barriers of 2.7 kcal/mol (for II) and 1.3 kcal/mol (for III) in diethyl ether and CH2Cl2, respectively. The results lead to a deduction of the reaction free energy and reorganization energy for both II (in diethyl ether) and III (in CH2Cl2). Theoretical (for I) and experimental (for II and III) approaches estimate the electronic coupling to be 860, 21.9, and 3.2 cm(-1) for I, II, and III, respectively, supporting the adiabatic versus nonadiabatic switching mechanism.     

Simulating physiological conditions to evaluate nanoparticles for magnetic fluid hyperthermia (MFH) therapy applications

Magnetite nanoparticles with high self-heating capacity and low toxicity characteristics are a promising candidate for cancer hyperthermia treatment. In order to achieve minimum dosage to a patient, magnetic nanoparticles with high heating capacity are needed. In addition, the influence of physiological factors on the heat capacity of a material should be investigated in order to determine the feasibility. In this study, magnetite nanoparticles coated with lauric acid were prepared by co-precipitation of Fe³⁺:Fe²⁺ in a ratio of 2:1, 5:3, 3:2, and 4:3, and the pH was controlled using NaOH. Structural and magnetization characterization by means of X-ray diffractometry (XRD) and a superconducting quantum interference device (SQUID) revealed that the main species was Fe₃O₄ and further showed that most of the nanoparticles exhibited superparamagnetic properties. All of the magnetic nanoparticles showed a specific absorption rate (SAR) increase that was linear with the magnetic field strength and frequency of the alternating magnetic field. Among all, the magnetic nanoparticles prepared in a 3:2 ratio showed the highest SAR. To further test the influence of physiological factors on the 3:2 ratio magnetic nanoparticles, we simulated the environment with protein (bovine serum albumin, BSA), blood sugar (dextrose), electrolytes (commercial norm-saline) and viscosity (glycerol) to examine the heating capacity under these conditions. Our results showed that the SAR value was unaffected by the protein and blood sugar environments. On the other hand, the SAR value was significantly reduced in the electrolyte environment, due to precipitation and aggregation with sodium ions. For the simulated viscous environment with glycerol, the result showed that the SAR values reduced with increasing glycerol concentration. We have further tested the heating capacity contribution from the Néel mechanism by trapping the magnetic nanoparticles in a solid form of polydimethylsiloxane (PDMS) to eliminate the heating pathway due to a Brownian motion. We measured the heating capability and determined that 47% of the total heat generated by the magnetic nanoparticles was from the Néel mechanism contribution. For evaluating magnetic nanoparticles, this method provides a fast and low cost method for determining qualitative and quantitative information measurement for the effect of physiological interference and could greatly reduce the cost and time by in vitro or animal test.     

Deviations from linearity in statistical evaluation of linearity in assay validation

Linearity and linear range are the key evaluations of the accuracy in assay validation. The average deviation from linearity (ADL) and the sum of squares of deviations from linearity (SSDL) have been proposed for assessment of the linearity. However, both ADL and SSDL do no consider the variability of the assay for evaluation of linearity. Therefore, we proposed the coefficient of variation of deviations from linearity (CVDL) as an alternative measure for the linearity assessment. For the inference of evaluation of linearity, we proposed testing procedures based on generalized pivotal quantities (GPQ) of ADL and CVDL for evaluation of linearity. The simulation studies were conducted to empirically investigate the size and power between the three methods. The simulation results show that all three methods adequately control size. However, the ADL method is uniformly more powerful than the other two methods. A numeric example illustrates the proposed methods. Copyright © 2009 John Wiley & Sons, Ltd.     

A Lyapunov functional for a stage-structured predator–prey model with nonlinear predation rate

We consider the dynamics of a general stage-structured predator–prey model which generalizes several known predator–prey, SEIR, and virus dynamics models, assuming that the intrinsic growth rate of the prey, the predation rate, and the removal functions are given in an unspecified form. Using the Lyapunov method, we derive sufficient conditions for the local stability of the equilibria together with estimations of their respective domains of attraction, while observing that in several particular but important situations these conditions yield global stability results. The biological significance of these conditions is discussed and the existence of the positive steady state is also investigated.     

Optimal ordering and pricing policy for an inventory system with trial periods

It is a business practice that home shopping companies offer a free trial period for their products with a goal of increasing sales. Under this policy, if for any reason customers are not satisfied with the purchase, they can return the product for a refund within the trial period. To develop inventory strategies in such environment, home shopping companies should take the return phenomenon into account so as to increase their profit. This paper considers this phenomenon and develops a seasonal inventory model to deal with the problem. Two scenarios are analyzed. In the first scenario, demand is assumed to be linearly price-dependent while in the second one, it is assumed to be exponentially price-dependent. The purpose of this research is to maximize the total profit over a given planning period by determining the optimal ordering quantity and price. The analytical results demonstrate that the optimal ordering quantity and prices are obtained using closed-form formulas.     

Mathematical modeling of interrelationships among cutting angles,setting angles and working angles of single-point cutting tools

The angles of a cutting tool play a key role in determining its cutting efficiency. However, once the tool has been mounted on a machine tool, setting errors inevitably cause the working angles of the tool to deviate slightly from the designed cutting angles. Accordingly, this study develops mathematical models to analyze the interrelationships among the tool angles, the setting angles and the working angles. In the proposed approach, a process of homogeneous coordinate transformation is employed to develop a kinematic model of the cutting tool such that the working angles can be derived given the tool angles and setting angles. Mathematical formulae are then developed to inversely derive the tool angles required to generate the specified working angles given prior knowledge of the setting angles. An illustrative numerical example is presented to demonstrate the validity of the proposed approach. Overall, the numerical results confirm that the methodology presented in this study provides a comprehensive, simple and versatile means of modeling a variety of conventional single-point cutting tools.     

Robustness of Tail Index Estimation

Abstract

The implementation of the Hill estimator, which estimates the heaviness of the tail of a distribution, requires a choice of the number of extreme observations in the tails, r from a sample of size n where 2 ≤ r + 1 ≤ n. This article is concerned with a robust procedure of choosing an optimal r. Thus, an estimation procedure, δ _s , based on the idea of spacing statistics, H^(r) is developed. The proposed decision rule for choosing r under the squared error loss is found to be a simple function of the sample size. The proposed rule is then illustrated across a wide range of data, including insurance claims, currency exchange rate returns, and city size.     

On multidimensional discrete-time Beverton–Holt competition models

Following Ackleh et al. (2005), we study the multidimensional discrete-time competitive Beverton–Holt equations with equal interspecific competition coefficients. It is shown that competitive exclusion occurs if only one species has the largest carrying capacity. Otherwise, all the species with the largest carrying capacity coexist. In the former case, the system is globally asymptotically stable. In the latter case, the system has a linear stable manifold.     

A particle swarm optimization for solving lot-sizing problem with fluctuating demand and preservation technology cost under trade credit

In this paper, we consider the effect of preservation technology cost investing on preservation equipment for reducing deterioration rate under two-level trade credit. The preservation technology cost is allowed for periodical upward or downward adjustments due to the time varying demand and the strategy of trade credit within the planning horizon. We establish a deterministic economic order quantity model for a retailer to determine his/her optimal preservation technology cost per replenishment cycle, the trade credit policies, the replenishment number and replenishment schedule that will maximize the present value of total profit. A particle swarm optimization with constriction factor is coded and used to solve the mixed-integer nonlinear programming problem by employing the properties derived from this paper. Some numerical examples are used to illustrate the features of the proposed model.     

A theoretical study of the photoelectron spectra of dichloroketene with accurate computation of ionization energies via complete basis set limit extrapolation

We calculated the equilibrium geometries and harmonic vibrational frequencies of the ground state and five cationic states of dichloroketene using (TD-)B3LYP, PBE0, and M06/M06-2X approaches. The photoelectron spectra of dichloroketene were simulated by computing Franck-Condon factors. The ionization energies were computed using the CCSD(T) approach with extrapolation to the complete basis set (CBS) limit. We propose two new CBS energy formulas (E = E_CBS + Aexp(-x) + B/(x−1) ⁿ, n = 2 or 3) and compare the performance of different CBS approaches. A new ionic state of dichloroketene belonging to the C_s point group is reported. This state is identified as the first excited state of Cl₂CCO⁺ having a double-well potential-energy curve along the CCO bending mode with a barrier height of 1.335 eV. The simulated photoelectron spectra are in agreement with the experiment. The vertical ionization energies calculated via spectral simulation are more accurate compared with those obtained at the ground-state structure. Among the CBS formulas used, the proposed ansatz with n = 2 performs best, with a mean absolute error of 0.021 and 0.012 eV for the adiabatic and vertical ionization energies, respectively.