Palladium nanoparticles as reusable catalyst for the synthesis of N-aryl sulfonamides under mild reaction conditions

An efficient palladium nanoparticles-catalyzed N-arylation of sulfonamides and sulfonyl azides is described. This procedure serves as an active protocol for intermolecular C–N bond formation using Pd(OAc)₂ in PEG-400 under air. Aryl bromides and triflates react at 35°C, while aryl chlorides require heating to 50°C and give the desired products only in low yields. This reaction proceeds smoothly in acceptable yields using low catalyst loading.     

Cadmium adsorption on modified chitosan‐coated bentonite: batch experimental studies

BACKGROUND: Several researchers have investigated the use of chitosan as an adsorbent for removal of heavy metals from aqueous streams. Chitosan flake or powder swells and crumbles making it unsuitable for use in an adsorption column. Chitosan also has a tendency to agglomerate or form a gel in aqueous media. The adsorption capacity can be enhanced by spreading chitosan on physical supports that can increase the accessibility of the metal binding sites. Although several attempts have been made to enhance the adsorption capacity of chitosan, using various chemicals, the sorption capacity for metal ions decreased after cross‐linking of chitosan. RESULTS: Bentonite was coated with chitosan (Chi) and its derivative, 3,4‐dimethoxy‐benzaldehyde (Chi/DMB). The product was then used as adsorbent for the removal of Cd²⁺ from aqueous solutions. The presence of imine groups resulting from chemical modification was confirmed using IR, DRS and SEM. The adsorption followed the Langmuir isotherm and could be described by pseudo‐second order kinetics. CONCLUSION: Chi/DMB coated on bentonite increased the accessibility of metal binding sites. The Chi/DMB/bentonite showed no significant pH dependence in the pH range 2–9, but bentonite coated with chitosan revealed very intensive pH dependence, which had a considerable effect on cadmium removal. As expected adsorption of Cd²⁺ by Chi/bentonite and Chi/DMB/bentonite is dependent on contact time and adsorbent dose. In addition, an EDTA solution is suitable for desorption of cadmium ions, and the reusability of Chi/DMB/bentonite is quite good. © 2012 Society of Chemical Industry     

An optimal algorithm for rectilinear steiner trees for channels with obstacles

The channel rectilinear Steiner tree problem is to construct an optimal rectilinear Steiner tree interconnecting n terminals on the upper shore and the lower shore of a channel without crossing any obstacles inside the channel. However, intersecting boundaries of obstacles is allowed. We present an algorithm that computes an optimal channel rectilinear Steiner tree in O(F₁(k)n + F₂(k)) time, where k is the number of obstacles inside the channel and F₁ and F₂ are exponential functions of k. For any constant k the proposed algorithm runs in O(n) time.     

Intrarenal nitric oxide activity and pressure natriuresis in anesthetized dogs

In the course of an ongoing cohort study on constitutional and occupational risk factors for the development of irritant hand dermatitis in hairdressing apprentices, an increased prevalence of irritant skin changes was noted in a subgroup examined during particularly cold winter months. Prompted by this observation, the importance of several meteorological factors (day means of temperature, relative and absolute humidity) was assessed in extensive statistical analyses based on data of 742 participants, supplemented by meteorological information obtained from the German Meteorological Service (DWD). There were significant associations of existing hand dermatitis with low temperature and low absolute humidity (Mann-Whitney U-test, P < 0.0001), but not with relative humidity (P = 0.38). Logistic regression analysis, including known determinants of irritant hand dermatitis in this setting, showed that low temperature and low relative humidity tended to be risk factors (OR = 1.66 and 1.57, respectively, for the lower quartiles, P = 0.07 in both cases), and confirmed that absolute humidity significantly influenced the occurrence of irritant hand dermatitis (OR = 2.06 for < 4.8 mg/L, P < 0.01). Thus, these environmental factors must be regarded as possible confounders in the analysis of future epidemiological studies on irritant hand dermatitis and should be considered in multifactorial analyses.     

In situ synthesis of hydroxyapatite-grafted titanium nanotube composite

ABSTRACT

The present study is an investigation to demonstrate the effectiveness of in situ approach in the synthesis of hydroxyapatite-grafted titanium nanotube composite (HA-TNT). This method involves combining the process of HA sol–gel and rapid breakdown anodisation of titanium in a novel solution consisting of NaCl and N₃PO₄. This new synthesis approach produced a uniform dispersion of Anatase and Rutile phases of TiO₂ nanotubes with minimal agglomeration in the matrix of crystalline HA. The characterisation of homogenised HA-TNT composite was investigated via field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), transmission electron microscope (TEM) and X-ray diffraction (XRD). FESEM and TEM images indicated the nanostructure of composite with TiO₂ nanotube diameter of approximately 10 nm. XRD and EDS analyses confirmed the formation of HA crystalline with the Ca/P ratio of 1.58 and formation of Anatase and Rutile phase of TiO₂ nanotubes.     

Robust group fused lasso for multisample copy number variation detection under uncertainty

One of the most important needs in the post‐genome era is providing the researchers with reliable and efficient computational tools to extract and analyse this huge amount of biological data, in which DNA copy number variation (CNV) is a vitally important one. Array‐based comparative genomic hybridisation (aCGH) is a common approach in order to detect CNVs. Most of methods for this purpose were proposed for one‐dimensional profiles. However, slightly this focus has moved from one‐ to multi‐dimensional signals. In addition, since contamination of these profiles with noise is always an issue, it is highly important to have a robust method for analysing multi‐sample aCGH profiles. In this study, the authors propose robust group fused lasso which utilises the robust group total variations. Instead of l _2,1 norm, the l ₁ − l ₂ M‐estimator is used which is more robust in dealing with non‐Gaussian noise and high corruption. More importantly, Correntropy (Welsch M‐estimator) is also applied for fitting error. Extensive experiments indicate that the proposed method outperforms the state‐of‐the art algorithms and techniques under a wide range of scenarios with diverse noises.Inspec keywords: genomics, DNA, molecular biophysics, Gaussian noise, entropyOther keywords: robust group fused lasso, multisample copy number variation detection, post‐genome era, computational tools, biological data, DNA copy number variation, array‐based comparative genomic hybridisation, one‐dimensional profiles, one‐dimensional signals, multidimensional signals, profile contamination, multisample aCGH profiles, robust group total variations, l₁ ‐l₂ M‐estimator, nonGaussian noise, correntropy, Welsch M‐estimator, fitting error, diverse noises     

Experimental and numerical results of dynamics behavior of a nonlinear piezoelectric beam

This article presents a numerical formulation and experimental implementation for the dynamics behavior verification of the nonlinear piezoelectric beam through harmonic excitation. The nonlinear piezoelectric beam dynamic analysis program is developed with MATLAB software. To verify the nonlinear piezoelectric beam dynamic analysis results, the experimental results are used for the vibration analysis of a piezoelectric beam to the harmonic excitation of the base of the beam. Then, the piezoelectric effect on the output voltage, velocity, acceleration values, and the time response are obtained. Afterwards, the effects of the excitation velocity and the position of concentrated mass on the output voltage are verified.     

Optimum lipid production using agro-industrial wastewater treated microalgae as biofuel substrate

Abundant wastewater discharges from palm oil industries in tropical nations being a valuable resource of biodiesel need proper exploration. Research hinted that such wastewater as economical nutrient source or substrate can support the cultivation of microalgae. In this experiment, we have tested the growth and lipid production of five different microalgal strains in palm oil mill effluent (POME). POME as a biofuel substrate is demonstrated to be lucrative for microalgae-assisted lipids production. POME is rich in macro- and micronutrients can be used as a growth medium for algal growth in order to reduce the growth medium cost and environmental pollutions. Among the five microalgal strains tested, Chlorella sorokiniana revealed optimum biomass and lipid production. The productivity was evaluated in terms of chlorophyll content, growth rate, biomass, and lipid content, which discerned to be 0.099/day, 8.0 mg/L day and 2.68 mg/mg cell dry weight (CDW). Furthermore, in this study, an optimization study was carried out to enhance the microalgae to produce high lipid content using carbon-to-nitrogen ratio and different light/dark periods. The presence of nitrogen combined glucose (with a carbon-to-nitrogen ratio 100:7) as an alternative source to carbon displayed higher lipid production of 2.68 (mg/mg CDW) by C. sorokiniana. This study confirms that 8:16 h light/dark condition at C:TN ratio of 100:7 supported to produce high lipid content of 17 mg lipid/mg CDW. The above results revealed that POME could be a suitable growth media for the alga C. sorokiniana to improve the maximum lipid yield for biofuels production.     

SIMULTANEOUS STATE ESTIMATION AND LEARNING IN REPEATED COURNOT GAMES

The aim of this article is to propose that an intelligent agent can be able to decide properly in an incomplete information repeated Cournot game. The market model and the competitors’ decision models are not known to the players. The proposed agent employs a combination of the k-nearest neighbor (KNN) method and the Bayes classifier to predict the next action of its rivals, using the market decision history. The agent takes the predicted actions as an estimate of its next state and learns the expected payoff of its state-action pairs interactively using the reinforcement learning (RL) algorithm. The results of the proposed agent's competition with two benchmark competitors in different simulated Cournot games are presented. The simulation results show that the proposed agent can significantly earn more payoffs in comparison with the two benchmark agents.