Characterization and Sorptivity of the Plesiomonas shigelloides Strain and Its Potential Use to Remove Cd2+ from Wastewater

In this study, the ability of adsorbing Cd2+ ions of Plesiomonas shigelloides was discovered. Herein, the method and mechanisms of adsorbing Cd2+ ions from aqueous solutions is discussed. The cadmium-resistant bacterium was collected from the sediment of Harbin section of the Songhua River in China, and then isolated, identified and characterized. The isolated strain was identified as Plesiomonas shigelloides H5 on the basis of morphological and biochemical characteristics, the sequencing of the 16SrDNA gene, and phylogeny analysis. P. shigelloides H5 was Gram-negative and bacillus. Maximum tolerance concentration (MTC) of the strain was 150 mg/L. The maximum adsorption rate and adsorption amounts was 42.71% ± 0.88% and 106.775 ± 2.325 mg/g when dried biomass was presented in a 50 mg/L Cd2+ solution. Dried biomass was in accordance with Lagergren pseudo-second-order models. A field emission scanning electron microscope (FE-SEM), an energy dispersive X-ray spectrometer (EDX), and Fourier transform infrared spectroscopy (FTIR) analyses were applied to identify the surface morphology and functional groups. Transmission electron microscope (TEM) results showed that Cd2+ was also absorbed into cells to form precipitates. The results revealed that the surface functional groups of P. shigelloides H5 can bind to heavy metal ions. To sum up, the ability of adsorbing cadmium ions of Plesiomonas shigelloides was discovered, which might be helpful in wastewater treatment in the future

Erratum: Xue, C., et al. Characterization and Sorptivity of the Plesiomonas shigelloides Strain and Its Potential Use to Remove Cd2+ from Wastewater. Water 2016, 8, 241

The authors wish to make the following corrections to their paper [1].[...

Fe3O4 Nanoparticles Embedded Sodium Alginate/PVP/Calcium Gel Composite for Removal of Cd2+

Magnetic ferroferric oxide (Fe3O4) nanoparticles embedded sodium alginate (SA)/polyvinylpyrrolidone (PVP)/calciumgel composites (MSPC) were synthesized for the removal of Cd2+. The physicochemical properties of the composite gel ball were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), power X-ray diffraction patterns (XRD), and vibrating sample magnetometer (VSM). Quantitative adsorptions experiments were performed in view of sorbent dosage, pH, contact time, and temperature. Results showed that the optimum quantity of particles was 1.2 g·L−1, when the Cd2+ concentration was fixed at 150 mg/L. The optimum pH for adsorption is 6.2. When the initial Cd2+ concentration was from 50 to 200 mg·L−1, the adsorption equilibrium time was 80–120 minutes. The isotherms results showed the maximum sorption was 97.8 mg/g calculated from the Langmuir isotherm. The pseudo-second-order kinetic model could be well described by the sorption of Cd2+ in the sediment. The correlation coefficients (R2) were all higher than 0.96. Results showed that MSPC was a practical and low-cost material for heavy metal removal from the river sediment and simultaneously solves the problems in convenient separation under additional magnetic field

Rapid Identification of Waste Cooking Oil with Near Infrared Spectroscopy Based on Support Vector Machine

International audienceThe qualitative model for rapidly discriminating the waste oil and four normal edible vegetable oils is developed using near infrared spectroscopy combined with support vector machine (SVM). Principal component analysis (PCA) has been carried out on the base of the combination of spectral pretreatment of vector normalization, first derivation and nine point smoothing, and seven principal components are selected. The radial basis function (RBF) is used as the kernel function; the penalty parameter C and kernel function parameter γ are optimized by K-fold Cross Validation (K-CV), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), respectively. The result shows that the best classification model is developed by GA optimization when the parameters C = 911.33, γ= 2.91. The recognition rate of the model for 208 samples in training set and 85 samples in prediction set is 100% and 90.59%, respectively. By comparison with K-means and Linear Discriminant Analysis (LDA), the result indicates that the SVM recognition rate is higher, well generalization, can quickly and accurately identify the waste cooking oil and normal edible vegetable oils

Direct-Ink-Writing Printed Strain Rosette Sensor Array with Optimized Circuit Layout

Abstract The full-field multiaxial strain measurement is highly desired for application of structural monitoring but still challenging, especially when the manufacturing and assembling for large-area sensing devices is quite difficult. Compared with the traditional procedure of gluing commercial strain gauges on the structure surfaces for strain monitoring, the recently developed Direct-Ink-Writing (DIW) technology provides a feasible way to directly print sensors on the structure. However, there are still crucial issues in the design and printing strategies to be probed and improved. Therefore, in this work, we propose an integrated strategy from layered circuit scheme to rapid manufacturing of strain rosette sensor array based on the DIW technology. Benefit from the innovative design with simplified circuit layout and the advantages of DIW for printing multilayer structures, here we achieve optimization design principle for strain rosette sensor array with scalable circuit layout, which enable a hierarchical printing strategy for multiaxial strain monitoring in large scale or multiple domains. The strategy is highly expected to adapt for the emerging requirement in various applications such as integrated soft electronics, nondestructive testing and small-batch medical devices