Use of adsorptive square-wave anodic stripping voltammetry at carbon paste electrode for the determination of amlodipine besylate in pharmaceutical preparations

The antihypertensive drug amlodipine has been characterized voltammetrically in a carbon paste electrode by means of anodic stripping voltammetry. An adsorptive stripping method in a carbon paste electrode for trace determination of amlodipine has been described. Cyclic voltammetric studies indicated the oxidation of amlodipine besylate at the electrode surface through a single two-electron irreversible step fundamentally controlled by adsorption. A study of the variation in the peak current with solution variables such as pH, ionic strength, concentration of amlodipine, possible interference, and instrumental variables, such as preconcentration time and accumulation potential, has resulted in the optimization of the oxidation signal for analytical purposes. By anodic adsorptive anodic stripping voltammetry, the calibration plot was linear in the range 9.9 × 10^?9 ? 1.4 × 10^?7 M with a detection limit of 2 × 10^?10 M in a carbon paste electrode at pH 11.0. The procedure was successfully applied to the assay of amlodipine besylate in some commercial products in the market (Amlopres®, Amlodipine, and Norvasc®). The percentage recoveries were in agreement with those obtained by the reference method.     

A new model for automatic normalization of multitemporal satellite images using Artificial Neural Network and mathematical methods

Relative Radiometric Normalization is often required in remote sensing image analyses particularly in the land cover change detection process. Normalization process minimizes the radiometric differences between two images caused by inequalities in the acquisition conditions rather than changes in surface reflectance. A wide range of RRN methods have been developed to adjust linear models. This paper proposes an automated Relative Radiometric Normalization (RRN) method to adjust a non-linear model based on an Artificial Neural Network (ANN) and unchanged pixels. The proposed method includes the following stages: (1) automatic detection of unchanged pixels based on a new idea that uses CVA (Change Vector Análysis) method, PCA (Principal Component Analysis) transformation and K-means clustering technique, (2) evaluation of different architectures of perceptron neural networks to find the best architecture for this specific task and (3) use of the aforementioned network for normalizing the subject image. The method has been implemented on two images taken by the TM sensor. Experimental results confirm the effectiveness of the presented technique in the automatic detection of unchanged pixels and minimizing imaging condition effects (i.e., atmosphere and other effective parameters).     

Removal and preconcentration of lead(II), cadmium(II) and chromium(III) ions from wastewater samples using surface functionalized magnetite nanoparticles

The potential removal and preconcentration of lead(II), cadmium(II), and chromium(III) ions from wastewaters were investigated and explored. Magnetite nanoparticles were chemically modified with p-nitro aniline. The aniline-coated magnetite nanoparticles (ANMNPs) were fully characterized by FT-IR, XRD, SEM, and TEM measurements. Batch studies were performed to address various experimental parameters for the removal and determination of these ions. ANMNPs showed high tendency to investigated metal ions, in this order: Cr(III) > Cd(II) > Pb(II), owing to the strong contribution of surface loaded aniline. The potential applications of ANMNPs adsorbent for removal and preconcentration of Pb(II), Cr(III), and Cd(II) from wastewaters as well as drinking tap water samples were successfully accomplished giving recovery values of (98–101 %), without any noticeable interference of the wastewater or drinking tap water matrices.     

A Review on Machine Learning Approaches for Network Malicious Behavior Detection in Emerging Technologies

Network anomaly detection systems (NADSs) play a significant role in every network defense system as they detect and prevent malicious activities. Therefore, this paper offers an exhaustive overview of different aspects of anomaly-based network intrusion detection systems (NIDSs). Additionally, contemporary malicious activities in network systems and the important properties of intrusion detection systems are discussed as well. The present survey explains important phases of NADSs, such as pre-processing, feature extraction and malicious behavior detection and recognition. In addition, with regard to the detection and recognition phase, recent machine learning approaches including supervised, unsupervised, new deep and ensemble learning techniques have been comprehensively discussed; moreover, some details about currently available benchmark datasets for training and evaluating machine learning techniques are provided by the researchers. In the end, potential challenges together with some future directions for machine learning-based NADSs are specified.     

Cu-based atom transfer radical polymerization of methyl methacrylate using a novel tridentate ligand with mixed donor atoms

This study is aimed at atom transfer radical polymerization (ATRP) of methyl methacrylate (MMA) using a novel catalyst. The bis-(2-dodecylsulfanyl-ethyl)-amine (SNS) tridentate ligand with mixed donor atoms was synthesized in high purity using inexpensive reagents and was reacted with copper(I) bromide to produce the CuBr/SNS catalyst. The catalyst mediated living polymerization of MMA yielding polymers with controlled molecular masses and narrow molecular mass distributions (PDI < 1.25). Also, the kinetic plot exhibited a linear increase of ln([M]₀/[M]) versus time, indicating constant concentration of propagating radicals during the polymerization. The products were characterized by ¹H NMR, ¹³C NMR, FT-IR, UV-VIS, GC and elemental analyses (CHNS) and by GPC.     

Preparation and biodistribution study of technetium-99m-labeled quercetin as a potential radical scavenging agent

Free radicals and oxidative stress are the primary causes of several chronic diseases such as cancer and heart disease. Quercetin is a natural compound with potent antioxidant activity. We have prepared and evaluated technetium-99m (^99mTc)-labeled quercetin as a potential radical scavenging radiotracer. A ^99mTc-quercetin complex was prepared using quercetin, SnCl₂ and Na^99mTcO₄ in a buffered solution over 30 min. The participation coefficient was measured in octanol and queues solutions. The stability was determined in phosphate buffered saline and serum. The biodistribution in normal mice was evaluated at 0.5, 2, 6 and 24 h post-injection. The radiochemical purity (>99%) was determined by thin layer chromatography (TLC) in normal saline solution as the mobile phase. It has a log P of 0.204. It was mainly cleared by the kidneys and showed negligible brain uptake at four time points measured post-injection. The pharmacological properties of quercetin, mainly its free radical scavenging, may potentially cat as a radiopharmaceutical agent for radical-targeted imaging of tissue with high levels of reactive oxygen species.     

A novel organocatalytic multi-component reaction: an efficient synthesis of polysubstituted pyrano-fused spirooxindoles

A practical, simple, and efficient method for the synthesis of pyrano-fused spirooxindoles via an organocatalytic three-component reaction of isatins, malononitrile, and dialkyl acetylenedicarboxylate in the presence of 3,4-dimethylaniline as an organocatalyst in ethanol is reported. The structures of these products are confirmed by IR, ¹H NMR and ¹³C NMR spectroscopy, mass spectrometry, and single-crystal X-ray diffraction studies.     

Erratum: Investigation of drug release and 1H‐NMR analysis of the in situ forming systems based on poly(lactide‐co‐glycolide)

This paper was published online on 10 October 2008 (DOI: 10.1002/pat.1279 ) and appears in the January 2009 issue (Vol. 20, No. 1, pp. 48‐57). The following changes should be recognized: The second corresponding author should be changed to M. Rafiena. ** Correspondence to: M. Rafienia, Medical Physics and Medical Engineering Department, Isfahan University of Medical Sciences (IUMS), P.O. Box 81744‐176, Isfahan, Iran. E‐mail: m_rafienia@med.mui.ac.ir