A Schiff base complex of Zn(II) as a neutral carrier for highly selective PVC membrane sensors for the sulfate ion

Novel polymeric membrane (PME) and coated graphite (CGE) sulfate-selective electrodes based on a recently synthesized Schiff base complex of Zn(II) were prepared. The electrodes reveal a Nernstian behavior over wide SO4(2-) ion concentration ranges (5.0 x 10(-5)-1.0 x 10(-1) M for PME and 1.0 x 10(-7)-1.0 x 10(-1) M for CGE) and very low detection limits (2.8 x 10(-5) M for PME and 8.5 x 10(-8) M for CGE). The potentiometric response is independent of the pH of the solution in the pH range 3.0-7.0. The electrodes manifest advantages of low resistance, very fast response, and, most importantly, good selectivities relative to a wide variety of other anions. In fact, the selectivity behavior of the proposed SO4(2) ion-selective electrodes shows a great improvement compared to the previously reported electrodes for sulfate ion. The electrodes can be used for at least 3 months without any appreciable divergence in potentials. The electrodes were used as an indicator electrode in the potentiometric titration of sulfate and barium ions and in the determination of iron in ferrous sulfate tablets.     

Heat Treatment of Ni-Ti Alloy for Improvement of Shape Memory Effect

Nickel-Titanium alloys with stoichiometric single phase and non-stoichiometric dual phase structures of NiTi and NiTi+Ni3Ti are produced through high speed induction melting and combustion synthesis of pure Ti/Ni elements. Both alloys are homogenized at 1273 K for two hours, rolled into thin strips of 0.3 mm thickness, solution treated at 1273 K for two hours under vacuum and finally quenched in water. Effect of ageing on austenite/martensite and intermediate phase transformation temperatures are investigated. Results show that transformation temperatures and reversible shape memory properties comparable with those required for bioengineering applications such as manufacturing of artificial hand prostheses can be obtained through careful control of the chemical composition and the heating processes.     

Strontium-selective membrane electrodes based on some recently synthesized benzo-substituted macrocyclic diamides

Eight different recently synthesized macrocyclic diamides were studied to characterize their abilities as strontium ion carriers in PVC membrane electrodes. The electrode based on 1,13-diaza-2,3;11,12-dibenzo-4,7,10-trioxacyclopentadecane-14,15-dione exhibits a Nernstian response for Sr(2+) ions over a wide concentration range (1.0 × 10(-)(1)-3.2 × 10(-)(5) M) with a limit of detection of 8.0 × 10(-)(6) M (0.7 ppm). The response time of the sensor is ～10 s, and the membrane can be used for more than three months without observing any deviation. The electrode revealed comparatively good selectivities with respect to many alkali, alkaline earth, and transition metal ions. It was used as an indicator electrode in potentiometric titration of carbonate ions with a strontium ion solution.     

Solid phase extraction and determination of sub-ppb levels of hazardous Hg2+ ions

A simple, rapid and reliable method has been developed to selectively separate and concentrate ultra trace amounts of mercury(II) ions from aqueous samples for its highly sensitive measurement by cold vapor atomic absorption spectrometry (CV-AAS). The Hg(2+) ions were adsorbed selectively and quantitatively during the passage of aqueous samples through octadecyl silica membrane disks modified by isopropyl 2-[(isopropoxycarbothiolyl)disulfanyl]ethane thioate (IIDE). The retained Hg(2+) ions were then stripped from the disk with minimal amounts of 0.5 M hydrobromic acid (two 8 ml portions) as eluent, and determined by CV-AAS. The break-through volume of the method is greater than 3000 ml, which results in enrichment factors >150. Maximum capacity of the membrane disks modified with 10mg of the ligand was found to be 350+/-30 microg of mercury(II), and the limit of detection is 0.005 ng ml(-1). The effect of various cationic interferences on the recovery of mercury in binary mixtures was studied. The method was applied to the recovery of Hg(2+) ions from different synthetic and tap water samples, as well as the determination of mercury in human hair samples.     

Carbon nanotube composite coated platinum electrode for detection of Ga(III)

This study demonstrates the application of composite multi-walled carbon nanotube (MWCNT) polyvinylchloride (MWNT-PVC) based on 7-(2-hydroxy-5-methoxybenzyl)-5,6,7,8,9,10-hexahydro-2H benzo [b][1,4,7,10,13] dioxa triaza cyclopentadecine-3,11(4H,12H)-dione ionophore for gallium sensor. The sensor shows a good Nernstian slope of 19.68 ± 0.40 mV/decade in a wide linear range concentration of 7.9 × 10(-7) to 3.2 × 10(-2)M of Ga(NO(3))(3). The detection limit of this electrode is 5.2 × 10(-7)M of Ga(NO(3))(3). This proposed sensor is applicable in a pH range of 2.7-5.0. It has a short response time of about 10s and has a good selectivity over nineteen various metal ions. The practical analytical utility of this electrode is demonstrated by measurement of Ga(III) in river water.     

Emotional ANN (EANN) and Wavelet-ANN (WANN) Approaches for Markovian and Seasonal Based Modeling of Rainfall-Runoff Process

The hydrological time series have three principle components (autoregressive, seasonality and trend) and the performance of the models is strongly related to the nature of these components. The current research examines the accuracy of two Artificial Neural Network (ANN) based approaches for rainfall-runoff (r-r) modeling of two catchments with different geomorphological conditions at monthly and daily time scales. The techniques proposed here are hybrid wavelet-ANN (WANN) model, as a multi-resolution forecasting tool and Emotional Artificial Neural Network (EANN) (a new generation of ANN based models) which serves artificial emotional factors as well as classic bias and weights parameters. The obtained results for monthly modeling show that WANN could perform better than the simple feed forward neural network (FFNN) model up to 40% and 35% in terms of verification and training efficiency criteria due to significant seasonality involved in the monthly time series of the process. On the other hand, the obtained results for daily modeling via FFNN and EANN, both as Markovian models, indicates the superiority of EANN over FFNN because of EANN capability to better learning of extraordinary and extreme conditions of the process in the training phase.     

Development of Sulfide‐Selective Optode Membranes Based on Immobilization of Methylene Blue on Optically Transparent Triacetylcellulose Film

Abstract

The development of reversible sulfide‐selective optode membranes, based on immobilization of methylene blue (MB) on optically transparent triacetylcellulose film, is described. The sensing scheme of the sulfide‐selective optode membranes is based on the decreasing absorbance of the membrane at 654 nm in the presence of sulfide, which can be related to the sulfide concentration in solution. The dynamic working range, detection limit, sensitivity, selectivity, and effect of pH are discussed in detail.

Under optimum experimental conditions, the membrane system shows a calibration response range from 3.1×10^?5 to 6.1×10^?4 M in a phosphate buffer of pH 7.5. Typical response times in the samples are 15–20 min. The lifetime of the system was about 30 days, with a relative standard deviation of <2%. The sensing membrane showed a good selectivity to sulfide over other anions. The optode membrane was applied to the determination of sulfide in real samples.     

An expressive event-based language for representing user behavior patterns

In-depth analysis of user interactions with applications in large systems is widely adopted as a means to understand user’s behavior for strategic purposes such as fraud detection, system security, weblog analysis, social networking, and customer relationship management. Overall, the user behavior presents characteristics, relationships, structures, and effects of a sequence of actions in a specific application domain. The interaction of users with applications at the business-level generates events that make the elements of the user behavior. Formal modelling and representation of complex patterns of user actions using expressive languages are critical aspects of behavior analysis. We present a model to describe the behavior elements and their relationships. The model also provides a systematic mechanism for describing and presenting events, sequence of events, and complex behavior patterns. A behavior pattern can be defined as a sequence of typed events that occur during specific time intervals. An event consists of a tuple of attributes whose values represent an observation of the behavior. In this paper, first we define a semantic model of the user behavior to address the issues around the user behavior representation, and then we present syntax and semantics of a generic Behavior Pattern Language (BPL), which enables the analysts to define a variety of complex behavior patterns in a declarative manner. We present the feasibility of the approach through several examples of complex behavior patterns expressed using the proposed language.