Application of a New Functionalized Nanoporous Silica for Simultaneous Trace Separation and Determination of Cd(II), Cu(II), Ni(II), and Pb(II) in Food and Agricultural Products

A novel sorbent for simultaneous separation of cadmium, copper, nickel, and lead was prepared by functionalizing SBA-15 nanoporous silica with dithizone. A solid-phase extraction method using the above sorbent was developed to separate and preconcentrate trace amounts of cadmium, copper, nickel, and lead ions from food and agricultural products by flame atomic absorption spectrometry measurements. The optimum experimental conditions such as pH; flow rates; type, concentration, and volume of the eluent; breakthrough volume; and effect of coexisting ions on the separation and determination of these heavy metals were evaluated. The extraction efficiencies for the mentioned heavy metals were greater than 97 %, and the limits of detection were 0.09, 0.16, 0.21, and 0.45 μg?L^?1 for cadmium, copper, nickel, and lead, respectively. The preconcentration factor for simultaneous analysis of the four heavy metals was found to be 100 approximately. The relative standard deviations of the method were <5 % for 10 separate column experiments for the determination of 5.0 μg of cadmium, copper, nickel, and lead ions. The adsorption capacity of the dithizone-SBA-15 was 189 mg?g^?1 for cadmium, 102 mg?g^?1 for copper, 91 mg?g^?1 for nickel, and 208 mg?g^?1 for lead.     

Digestive proteolytic and amylolytic activities in Trogoderma granarium Everts (Dermestidae: Coleoptera)

The Khapra beetle, Trogoderma granarium is a serious post-harvest pest of wheat. Digestive proteinase and amylase activities of larvae and adult insects were investigated using general and specific substrates and inhibitors. Gut pH in larvae was determined to be slightly acidic in the midgut and more acidic in the hindgut. However, midgut extracts from larvae showed an optimum activity for proteolysis against azocasein and haemoglobin at alkaline pH (broad optimum in the range 8–11). Proteinase extracted from larval guts hydrolyzed the synthetic substrates BApNA(N–benzoyl–L–arginine–p–nitroanilide) and SAAPPpNA (N–succinyl–alanine–alanine–proline–phenylalanine–p–nitroanilide) for trypsin- and chymotrypsin-like activities, respectively. The specific substrate for elastase-like activity SAAApNA (N–succinyl–alanine–alanine–alanine–p–nitroanilide) was not hydrolyzed by midgut extract of larvae. The most effective inhibitors of azocaseinolytic hydrolysis were trypsin and chymotrypsin-like serine proteinase inhibitors. Casein zymogram analysis revealed at least six proteinase bands in the larval midgut extract and showed the presence of trypsin-like serine proteinases. No cysteine proteinases were detected in larval midgut extract using specific cysteine proteinase substrates, inhibitors and activators. Carboxypeptidase A activity also was detected in larval midgut extract using FAPP(N-(3-(2-furyl) acryloyl)-l-phenylalanyl-l-phenylalanine) and showed optimal activity at alkaline pH. Activity of -amylase using starch as substrate, was determined to be maximal around neutral pH (pH 6–8), which is correlated with the pH prevailing in the midgut. No proteolytic and amylolytic activities were detected using conventional substrates in the digestive system of the adult suggesting no significant protein and carbohydrate digestion occurs in the adult beetle which does not need to feed.     

Effect of iron on Ni–Mo–Fe composite as a low-cost bifunctional electrocatalyst for overall water splitting

By increasing demand for hydrogen and oxygen gas for energy and industrial applications, designing a cheap, high-efficiency, and bifunctional electrocatalyst for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) seems necessary. For this purpose Ni–Mo–Fe as a bifunctional electrocatalyst was synthesized by one-step electrodeposition. From this electrocatalyst with optimal composition and current density, a small overpotential of 65, 161 mV for delivering 10, 100 mA/cm² on HER in alkaline media was achieved. As-fabricated electrode exhibited 344,408 mV for delivering 10, 100 mA/cm² in OER. Furthermore, this electrocatalyst shows high stability and negligible degradation in overpotential for HER and OER under long term stability tests in alkaline media. The notable function of As-fabricated Ni–Mo–Fe is due to the synergism effect between Ni, Mo, and Fe element and binder-free structure. Owing to the high-performance and high-stability of Ni–Mo–Fe electrocatalyst under Hydrogen and Oxygen evolution reactions is a candidate for industrial uses in the alkaline electrolyzer.     

Non-destructive Evaluation of Bread Staling Using Gray Level Co-occurrence Matrices

The potential application of image texture processing for non-destructive evaluation of bread staling was investigated by monitoring the changes in gray level co-occurrence matrix (GLCM) features (energy, contrast, homogeneity, correlation, and entropy) of baguette bread over a 5-day storage period. Energy experienced a significant reduction after 2 days of storage and increased significantly afterwards. However, contrast tended to increase dramatically over the entire storage time. While homogeneity and correlation showed a decreasing trend during the storage period, no meaningful trend was observed for changes of entropy. The GLCM texture features contrast, homogeneity, and correlation showed high correlations with the instrumental texture parameters and physicochemical properties of the bread during storage; in fact, the breads with firmer and less springy crumbs and higher crust moisture contents (the stale breads) had noticeably higher contrast and lower homogeneity and correlation values compared to the freshly baked samples. The results suggested that the GLCM texture features are promising indices for non-destructively assessing bread staling progress.     

Phase equilibrium modelling of natural gas hydrate formation conditions using LSSVM approach

The formation of gas hydrates in industries and chemical plants, especially in natural gas production and transmission, is an important factor that can lead to operational and economic risks. Hence, if the hydrate conditions are well addressed, it is possible overcome hydrate-related problems. To that end, evolving an accurate and simple-to-apply approach for estimating gas hydrate formation is vitally important. In this contribution, the least square support vector machine (LSSVM) approach has been developed based on Katz chart data points to estimate natural gas hydrate formation temperature as function of the pressure and gas gravity. In addition, a genetic algorithm has been employed to optimize hyper parameters of the LSSVM. Moreover, the present model has been compared with five popular correlations and was concluded that the LSSVM approach has fewer deviations than these correlations so to estimate hydrate formation temperature. According to statistical analyses, the obtained values of MSE and R² were 0.278634 and 0.9973, respectively. This predictive tool is simple to apply and has great potential for estimating natural gas hydrate formation temperature and can be of immense value for engineers who deal with the natural gas utilities.     

Behavior of channel shear connectors, Part II: Analytical study

In this second part of the two companion papers an effective numerical model is proposed using finite element method to simulate the push-out test of channel shear connectors. The focus is on the shear capacity of channel shear connectors embedded in a solid reinforced concrete slab under monotonic loading. The model has been validated against test results presented in Part (I) and compared with data given in North American design codes. Parametric studies using this nonlinear model are performed to investigate the variations in concrete strength, channel dimensions and the orientation of the channel. The results show that the concrete strength, web and flange thicknesses of the channel and the length of the channel are significant parameters in determining the ultimate strength of channel shear connectors, whereas the height of the channel section is not a significant parameter. Also, changing the orientation of the channel causes a change in the stiffness and the ultimate strength of the shear connector.     

Reservoir Inflow Modeling Using Temporal Neural Networks with Forgetting Factor Approach

In this paper, a recursive training procedure with forgetting factor is proposed for on-line calibration of temporal neural networks. The forgetting factor discounts old measurements through an on-line model calibration. The forgetting factor approach enables the recursive algorithm to reduce the effect of the older error data by multiplying the error data by a discounting factor. The proposed procedure is used to calibrate a temporal neural network for reservoir inflow modeling. The mean monthly inflow of the Karoon-III reservoir dam in the south-western part of Iran is used to test the performance of the proposed approach. An autoregressive moving average (ARMA) model is also applied to the same data. The temporal neural network, which is trained with the proposed approach, has shown a significant improvement in the forecast accuracy in comparison with the network trained by the conventional method. It is also demonstrated that the neural network trained with forgetting factor results in better forecasts compared to the statistical ARMA model, which has been calibrated through this approach.     

Evaluating the durability,microstructure and mechanical properties of a clayey-sandy soil stabilized with copper slag-based geopolymer against wetting-drying cycles

Bulletin of Engineering Geology and the Environment - This study was conducted on durability of the clayey-sand stabilized using the copper slag (CS)-based geopolymer against wetting-drying (W-D)...     

The effect of the change in the amount of Sb doping in ZnO nanorods for hydrogen gas sensors

In this study, pure and variable content Sb doped ZnO nanorods (NRs) were grown by a simple spray pyrolysis method successfully. Structural analysis has showed that all the films are indicating preferential dominant c-axis (002) plane from x-ray diffraction (XRD) measurements. It is observed that Sb doping does not result in changes in lattice parameter indicating no lattice distortion. Raman measurements has indicated Sb doping related modes in ZnO NRs especially defect related. SEM images has shown uniform hexagonal close packing NR structures uniformly distributed throughout the film. X-ray photoelectron spectroscopy (XPS) has displayed lower incorporation of the Sb from the precursor to the Sb doped NRs. Hydrogen gas sensor performances of these NRs has investigated. 5.0 wt% Sb doped ZnO NR sample has showed outstanding response with 23-fold response to 10 ppm hydrogen gas level at 250 °C.     

Maximizing Network Lifetime in Many-to-One Wireless Sensor Networks (WSNs)

Wireless Personal Communications - In many-to-one patterns of wireless sensor networks, the energy hole problem is a crucial issue that ultimately causes to reduce the network lifetime...