Chemical Oxidative Degradation of Acridine Orange Dye in Aqueous Solution by Fenton's Reagent

Degradation of acridine orange (AO) in aqueous solution by Fenton's reagent (Fe²⁺ and H₂O₂) was investigated. The effects of different reaction parameters such as initial AO concentration, pH value of solution, ferrous concentration, hydrogen peroxide concentration, and the presence of chloride ion on the oxidative degradation of AO were investigated. Under optimum conditions, 2 mM H₂O₂, 0.4 mM Fe²⁺ and pH 3.0, the initial 0.2 mM AO solution was reduced by 95.8% within 10 min. The primary intermediates of the degradation reaction of AO were identified. The analytical results indicated that the N‐de‐methylation degradation of AO dye took place in a stepwise manner to yield mono‐, di‐, tri‐, and tetra‐N‐de‐methylated AO species generated during the Fenton process. The probable degradation pathways were proposed and discussed.     

Alkali-hydroxide-doped matrices for structural characterization of neutral underivatized oligosaccharides by MALDI time-of-flight mass spectrometry

We report new approaches using alkali-hydroxide-doped matrices to facilitate structural characterization of neutral underivatized oligosaccharides by matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) MS. The approaches involved pretreatment of the analytes with NaOH or LiOH in aqueous solution, followed by mixing them with MALDI matrices prior to MS analysis. It was found that for open-ended neutral underivatized oligosaccharides partial alkaline degradation occurred upon laser desorption and ionization of the hydroxide-pretreated analytes in 2,5-dihydroxybenzoic acid (DHBA). The effect intensified when nonacidic compounds such as 2,4,6-trihydroxyacetophenone (THAP) and 5-amino-2-mercapto-1,3,4-thiadiazole (AMT) were used as matrix. The degradation allowed facile identification of the reducing end residue of the analyte and facilitated its structural characterization by postsource decay TOF-MS. Applying the same technique using matrices composed of LiOH and THAP or AMT led to the production of singly as well as multiple lithiated ions of oligosaccharides containing hexoses with free 3-OH groups. Extensive lithiation through multiple hydrogen-lithium exchanges up to 6 Li atoms was observed for maltoheptaose, beta-cyclodextrin, and dextran 1500. Such a 'lithium tagging' technique makes it possible to differentiate positional isomers of milk-neutral oligosaccharides, lacto-N-difucohexaose I and II (LNDFH-I and LNDFH-II), without the need of chemical derivatization or tandem MS analysis.     

The minimum norm method for the determination of the charge density from elastic electron scattering data

Unphysical behavior in the QR algorithm based least squares determination of the expansion coefficients of the charge density obtained from limited information about the charge form factor occurs when the spread of the singular values in the matrix relating these quantities becomes too large. Setting the smallest singular values equal to zero in the singular value decomposition used in the minimum norm method yields a much more reasonable determination of the charge density. Increasing the size of the basis without increasing the range of the prior information about the charge form factor leads to ambiguities in the determination of the charge density. Numerical results in an analytic model are presented.     

Exchange bias dependence on interface spin alignment in a Ni80Fe20/(Ni,Fe)O thin film

A Ni80Fe20/(Ni,Fe)O thin film exhibits a positive exchange bias when cooled in a zero field and a negative exchange bias when field cooled. With transmission electron microscopy and electron energy loss spectrometry, the composition and magnetic structure has been ascertained and a distribution of magnetization easy axes about the interface extrapolated. The results indicate that the positive exchange bias is from antiferromagnetic interface moments perpendicular to their ferromagnetic counterparts. With field cooling the alignment is put into a parallel configuration resulting in a negative exchange bias.     

Friction and forced convective heat transfer in a sintered porous channel with obstacle blocks

This work experimentally studies the flow characteristics and forced convective heat transfer in a sintered porous channel that filled with sintered copper beads of three average diameters ( 0.830, and 1.163 mm). The pressure drop and the local temperature measurements can be applied to figure out the distributions of the friction coefficient and the heat transfer coefficient. Three sintered porous channels differ in the arrangement of obstacle blocks. Model A has no obstacle. Models B and C have five obstacle blocks facing down and up, respectively, in a sintered porous channel. The range of experimental parameters, porosity, heat flux, and effect of forced convection are 0.370 ≤ ɛ ≤ 0.385, q=0.228, 0.872, 1.862 W/cm², and 200 ≤ Re _d ≤ 800. The permeability and inertia coefficient of each of the three sintered porous channels are analyzed. The results for Model A agree with those obtained by previous investigations in C _f distribution. The heat transfer of Model C exceeds that of Model A by approximately 20%. Finally, a series of empirical correlation equations were obtained for practical applications and engineering problems.     

Choosing best alliance partners and allocating optimal alliance resources using the fuzzy multi-objective dummy programming model

Synergy effects are the motives to enter into strategic alliances; however due to lack of adequate preparation or planning, these alliances often fail. It is of no doubt that a successful strategic alliance depends on choosing the correct alliance partners and appropriate resource allocation. In this paper, the fuzzy multi-objective dummy programming model is proposed to overcome the above-mentioned problems. Two types of strategic alliances, joint ventures and mergers and acquisitions (M&A), are demonstrated to choose the best alliance partners and allocate the optimal alliance resources in a numerical example. Based on the results, our method can provide the optimal alliance cluster and satisfaction in strategic alliances.     

Modeling single-frequency laser-plasma acceleration usingparticle-in-cell simulations: the physics of beam breakup

We investigate electron acceleration from space-charge waves driven by single-frequency lasers using a fully explicit particle-in-cell (PIC) model. The two dimensional (2-D) simulations model ~100 fs pulses at densities near n=4×10¹⁹ cm^-3 for 1-μm lasers. The pulses are found to break up due to a combination of longitudinal and transverse bunching of the laser intensity via Raman forward scattering type instabilities. The ponderomotive force of these intensity modulations generates large amplitude plasma waves. Large numbers of self-trapped electrons and multiple Raman forward scattering satellites are observed. The relevance of these simulations to experiments is discussed     

A Public-Key Traitor Tracing Scheme with Revocation Using Dynamic Shares

We proposed a new public-key traitor tracing scheme with revocation capability using dynamic shares and entity revocation techniques. Our schemes traitor tracing and revocation programs cohere tightly. The size of the enabling block of our scheme is independent of the number of receivers. Each receiver holds one decryption key only. The distinct feature of our scheme is that when traitors are found, we can revoke their private keys (up to some threshold z) without updating the private keys of other receivers. In particular, no revocation messages are broadcast and all receivers do nothing. Previously proposed revocation schemes need update existing keys and entail large amount of broadcast messages. Our traitor tracing algorithm works in a black-box way. It is conceptually simple and fully k-resilient, that is, it can find all traitors if the number of them is k or less. The encryption algorithm of our scheme is semantically secure assuming that the decisional Diffie-Hellman problem is hard.AMS Classification: 11T71, 68P30     

On the optimal product mix in life insurance companies using conditional value at risk

This paper proposes a Conditional Value-at-Risk Minimization (CVaRM) approach to optimize an insurer’s product mix. By incorporating the natural hedging strategy of Cox and Lin (2007) and the two-factor stochastic mortality model of Cairns et al. (2006b), we calculate an optimize product mix for insurance companies to hedge against the systematic mortality risk under parameter uncertainty. To reflect the importance of required profit, we further integrate the premium loading of systematic risk. We compare the hedging results to those using the duration match method of Wang et al. (forthcoming), and show that the proposed CVaRM approach has a narrower quantile of loss distribution after hedging—thereby effectively reducing systematic mortality risk for life insurance companies.