Molecularly imprinted polymer based potentiometric sensor for the determination of hydroxyzine in tablets and biological fluids

Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. In this work, a biomimetic potentiometric sensor, based on a non-covalent imprinted polymer, was fabricated for the recognition and determination of hydroxyzine in tablets and biological fluids. The molecularly imprinted polymer (MIP) was synthesized by precipitation polymerization, using hydroxyzine dihydrochloride as a template molecule, methacrylic acid (MAA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensor showed a high selectivity and a sensitive response to the template in aqueous system. The MIP-modified electrode exhibited a Nernstian response (29.4 ± 1.0 mV decade⁻¹) in a wide concentration range of 1.0 × 10⁻⁶ to 1.0 × 10⁻¹ M with a lower detection limit of 7.0 × 10⁻⁷ M. The electrode demonstrated a response time of ∼15 s, a high performance and a satisfactory long-term stability (more than 5 months). The method has the requisite accuracy, sensitivity and precision to assay hydroxyzine in tablets and biological fluids.     

Biomimetic electrochemical sensor based on molecularly imprinted polymer for dicloran pesticide determination in biological and environmental samples

Dicloran pesticide is used to inhibit the fungal spore germination for different crops. Because of the increasing application of pesticides, reliable and accurate analytical methods are necessary. The aim of this work is designing the highly selective sensor to determine the dicloran in biological and environmental samples. Multi-walls carbon nanotubes and a molecularly imprinted polymer (MIP) were used as modifiers in the sensor composition. A dicloran MIP and a nonimprinted polymer (NIP) were synthesized and applied in the carbon paste electrode. After the optimization of electrode composition, it was used to determine the concentration of analyte. Parameters affecting the sensor response were optimized, such as sample pH, electrolyte concentration and its pH, and the instrumental parameters of square wave voltammetry. The MIP-CP electrode showed very high recognition ability in comparison with NIP-CP. The obtained linear range was 1 × 10^?6 to 1 × 10^?9 mol L^?1. The detection limit was 4.8 × 10^?10 mol L^?1. This sensor was used to determine the dicloran in real samples (human urine, tap and river water samples) without special sample preparation before analysis. All important parameters were optimized, improving the sensor response considerably.     

Synthesis of Novel 2‐Oxoquinoline Derivatives via Ugi‐Four‐Component‐Heck Reaction

The present study provides an efficient strategy for the preparation of novel N‐substituted‐4‐methyl‐quinolin‐1(2H)‐one derivatives via two‐step Ugi/Heck reaction. The procedure is based on the Ugi coupling between 2‐bromoanilines, various aromatic aldehydes, vinylacetic acid, and isocyanides, and then intramolecular Heck reaction, which leads to the formation of the title compounds in good yields.     

LDC-CNTFET: A carbon nanotube field effect transistor with linear doping profile channel

In this paper, a novel carbon nanotube field effect transistor with linear doping profile channel (LDC-CNTFET) is presented. The channel impurity concentration of the proposed structure is at maximum level at source side and linearly decreases toward zero at drain side. The simulation results show that the leakage current, on-off current ratio, subthreshold swing, drain induced barrier lowering, and voltage gain of the proposed structure improve in comparison with conventional CNTFET. Also, due to spreading the impurity throughout the channel region, the proposed structure has superior performance compared with a single halo CNTFET structure with equal saturation current. Design considerations show that the proposed structure enhances the device performance all over a wide range of channel lengths.     

Method/basis set dependence of NICS values among metallic nano-clusters and hydrocarbons

The influence of various all-electron basis sets and effective core potentials employed along with several DFT functionals (B3LYP, B3PW91, BLYP, BP86 and M06) on the magnitude of nucleus independent chemical shift (NICS) values in different metallic nano-clusters and hydrocarbons is studied. In general, it is demonstrated that the NICS values are very sensitive to the applied method/basis set; however, the method/basis set dependence is more prominent for computed NICS values in transition metal clusters. In hydrocarbons, medium-size basis sets perform roughly similar to large basis sets in most cases. It is also found that NICS(0) values are more sensitive to the method/basis set variation compared to the NICS values computed at 1 or 2 ? above the ring plane. However, in many cases, no broad-spectrum regulation is found for the effect of basis set/method on the magnitude of NICS values. A detailed study showed that bond length alternation in a molecule has an insignificant effect on the magnitude of NICS values so the influence of method/basis sets on the magnitude of NICS values mostly arises from the different predicted ring current intensities at various computational levels.     

A robust optimization model for multi-product two-stage capacitated production planning under uncertainty

Production planning (PP) is one of the most important issues carried out in manufacturing environments which seeks efficient planning, scheduling and coordination of all production activities that optimizes the company’s objectives. In this paper, we studied a two-stage real world capacitated production system with lead time and setup decisions in which some parameters such as production costs and customer demand are uncertain. A robust optimization model is developed to formulate the problem in which minimization of the total costs including the setup costs, production costs, labor costs, inventory costs, and workforce changing costs is considered as performance measure. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. A mixed-integer programming (MIP) model is developed to formulate the related robust production planning problem. In fact the robust proposed model is presented to generate an initial robust schedule. The performance of this schedule could be improved against of any possible occurrences of uncertain parameters. A case from an Iran refrigerator factory is studied and the characteristics of factory and its products are discussed. The computational results display the robustness and effectiveness of the model and highlight the importance of using robust optimization approach in generating more robust production plans in the uncertain environments. The tradeoff between solution robustness and model robustness is also analyzed.     

Minimizing the total completion time on a single machine with the learning effect and multiple availability constraints

This paper considers a single machine scheduling problem with the learning effect and multiple availability constraints that minimizes the total completion time. To solve this problem, a new binary integer programming model is presented, and a branch-and-bound algorithm is also developed for solving the given problem optimally. Since the problem is strongly NP-hard, to find the near-optimal solution for large-sized problems within a reasonable time, two meta-heuristics; namely, genetic algorithm and simulated annealing are developed. Finally, the computational results are provided to compare the result of the binary integer programming, branch-and-bound algorithm, genetic algorithm and simulated annealing. Then, the efficiency of the proposed algorithms is discussed.     

Possibility for mode-locked operation of a femtosecond UV storage ring free-electron laser using a low-loss Fabry–Perot resonator

A storage ring free-electron laser (SR-FEL) is inherently a self-mode-locked optical system. The gain broadening due to electron energy spread affects the small signal gain in order to determine the output coupling. Here, the dependence of the small signal gain, the optimum output coupling, and pulse duration on both electron energy spread and loss of a Fabry–Perot resonator in UV SR-FEL were investigated. It was shown that the output coupling strongly affects the mode-locked pulse duration and the present picosecond pulses can be shortened to femtosecond ones using a proper low-loss resonator.     

Antibacterial activity and comparison of the volatile constituents obtained by several extraction methods from the flowers, stems and leaves of Astrodaucus orientalis

The oils of the flowers, stems and leaves of Astrodaucus orientalis L. were separately extracted using hydrodistillation (HD), head-space solid-phase microextraction (HS-SPME) and microwave assisted head-space solid-phase microextraction (MA-HS-SPME). The volatile constituents were analyzed by GC and GC/MS. Temperature and time of extraction, microwave power and exposure time of extraction were optimized. Polydimethylsiloxane (PDMS) fiber was used as the solid phase for SPME methods. The main constituents of the flower, stem and leaf oils isolated by HD, HS-SPME and MA-HS-SPME are as follows, respectively: beta-pinene (20.5%, 13.9% and 30.4%), alpha-thujene (8.7%, 16.2% and 10.9%) and alpha-pinene (7.6%, 14.3% and 10.9%) for the flowers, sabinene (11.8%, 32.3% and 11.8%), alpha-pinene (8.7%, 28.8% and 6.1%) and p-mycrene (2.5%, 12% and 8.5%) for the stem, and alpha-pinene (9.4%, 37.1% and 22.5%), sabinene (13.5%, 26.3% and 23.5%), beta-pinene (6.3%, 9.8% and 10%) and p-mycrene (3.2%, 2.5% and 15.6%) for the leaf. The minimum inhibitory concentrations (MIC) were determined for all essential oils obtained by HD against both Gram-positive (Bacillus subtilis) and Gram-negative (Escherichia coli) bacteria using the agar dilution method. These oils showed the good activities against the both bacteria (0.5 - 1.5 mg/mL).