Removal of E. coli from water using surface-modified activated carbon filter media and its performance over an extended use

Modification of activated carbon (AC) by aluminum hydroxychloride (AHC), and diatomaceous earth by zinc hydroxide changed the zeta potentials of these filter media from negative to positive. The modification method is amenable to room temperature, and eliminates the essential requirement of strong base treatment for making metal hydroxide coated filter media. Solid-state MAS 27Al NMR spectra suggested the presence of Al13-mer in the AHC-treated AC. AHC-modified AC samples were further treated with silver halide, and two antibacterial compounds to prevent microbial growth on filter media. In situ precipitation of silver bromide on AC resulted in formation of nanosized AgBr crystals. Bacteria removal performances of the modified media were tested in columns. For the first time, we demonstrated that only 30 g of either AHC-treated AC (60 x 200 mesh) or nano AgBr supported AC could provide >6 log E. coli removal over approximately 1000 L when the input water had a bacterial load of 10(7) CFU/mL. The filter media were robust enough to perform even when water was passed at superficial velocities 3-10 times the typical velocity (6 cm/min) of water treatment processes. Metal leaching from the modified media was found to be less than the USEPA specified Maximum Contaminant Level.     

Vertically aligned ZnO nanowire arrays in Rose Bengal-based dye-sensitized solar cells

We fabricate dye-sensitized solar cells (DSSC) using vertically oriented, high density, and crystalline array of ZnO nanowires, which can be a suitable alternative to titanium dioxide nanoparticle films. The vertical nanowires provide fast routes or channels for electron transport to the substrate electrode. As an alternative to conventional ruthenium complex, we introduce Rose Bengal dye, which acts as a photosensitizer in the dye-sensitized solar cells. The dye energetically matches the ZnO with usual KII₂ redox couple for dye-sensitized solar cell applications.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Land Use Effect on the CN Model Parameters in a Tropical Dry Environment

Dry tropical forests account for over 1,000,000 km², and there is still lack of knowledge on their hydrologic processes. The curve number (CN) hydrologic model developed by the Natural Resources Conservation Service (NRCS) is widely applied for runoff determination in various parts of the world, but not so in tropical semiarid regions. This study analyzes the impact of land use changes on the CN model in a tropical semiarid environment, in two catchments of native dry tropical forest and thinned dry tropical forest land use from 2009 to 2012. The CN model was calibrated and validated for the NRCS recommended initial abstraction ratio λ = 0.2, and for λ evaluated from rainfall and runoff data. A reliability analysis was performed using Monte Carlo simulation. Model goodness-of-fit was assessed with statistical criteria. A total of 42 and 40 rainfall-runoff events were analyzed for the native and thinned dry tropical forest, respectively. Characteristic λ values of 0.15 and 0.11 were determined for the two respective catchments. Although CN values were similar for both land uses, CN_λ=0.20 = 80 and CN_{median λ} = 77, the thinned catchment showed a higher CN model parameters variability. The CN model was more sensitive to variations of CN values than to those of λ. This study showed that no matter the vegetation management in a dry tropical forest environment, modeled runoff is not affected by λ, but rather affected by CN, which represents soil, landuse and management.     

Effect of Thermal Cycling on Creep Behavior of Powder-Metallurgy-Processed and Hot-Rolled Al and Al-SiC Particulate Composites

The tensile creep behavior of powder metallurgy (P/M)–processed and hot-rolled commercially pure Al and Al-5 or Al-10 vol pct SiC particulate composites has been evaluated after subjecting to 0, 2, and 8 thermal cycles between 500 °C and 0 °C with rapid quenching. The images of microstructures obtained using scanning and transmission electron microscopy as well as changes in the electrical resistivity, Young’s modulus, and microhardness have been examined in the samples subjected to thermal cycling, in order to compare the effects of structural damage and strengthening by dislocation generation. The damage is caused by voids formed by vacancy coalescence, and is more severe in pure Al than in Al-SiC_p composites, because the particle-matrix interfaces in the composites act as effective sinks for vacancies. Creep tests have shown that the application of 2 thermal cycles lowers the creep strain rates in both pure Al and Al-SiC_p composites. However, the creep resistance of pure Al gets significantly deteriorated, unlike the mild deterioration in the Al-5 SiC_p composite, while the time to rupture for the Al-10 SiC_p composite is increased. The dislocation structure and subgrain sizes in the Al and in the matrices of the Al-SiC_p composites in the as-rolled condition, after thermal cycling, and after creep tests, have been compared and related to the creep behavior. The dimple sizes of the crept fracture surfaces appear to be dependent on the void density, tertiary component of strain, and time to rupture.     

Immobilization and the conformational study of phospholipid and phospholipid-protein vesicles

The present work demonstrates the immobilization of phospholipids and phospholipids-protein vesicles on solid substrate by simple drop-cast technique. We have also studied the structural and conformational transition of protein (OVA) molecules when they are loaded in immobilized vesicles of DPPC. High-resolution FE-SEM imaging is used to study the structural aspects of the immobilized vesicles of DPPC and OVA loaded DPPC. FTIR analyses of amide bands are being used to inspect the extent of the conformational transitions of β-sheet to α-helix of OVA in immobilized DPPC vesicles. Immobilized OVA-DPPC vesicles provide the structure of individual OVA molecule attached with DPPC, without aggregation amongst them.     

Generalized Rough Sets, Entropy, and Image Ambiguity Measures

Quantifying ambiguities in images using fuzzy set theory has been of utmost interest to researchers in the field of image processing. In this paper, we present the use of rough set theory and its certain generalizations for quantifying ambiguities in images and compare it to the use of fuzzy set theory. We propose classes of entropy measures based on rough set theory and its certain generalizations, and perform rigorous theoretical analysis to provide some properties which they satisfy. Grayness and spatial ambiguities in images are then quantified using the proposed entropy measures. We demonstrate the utility and effectiveness of the proposed entropy measures by considering some elementary image processing applications. We also propose a new measure called average image ambiguity in this context.     

High-speed target tracking by fuzzy hostility-induced segmentation of optical flow field

A time efficient technique for real-time tracking of high-speed objects in a video sequence is presented in this article. The technique is primarily based on the segmentation of the optical flow field computed between the successive image frames of a video sequence, followed by the tracking of a detected point of interest (POI) within the segmented flow field. In the initial phase of the technique, the optical flow field between the first two successive image frames acquired from a video sequence, is computed. A fuzzy hostility index indicative of the degree of coherence of the moving objects in the image frames, is used to segment the optical flow field. This yields different coherent regions of interest (ROIs) in the segmented flow field. A POI is then detected in the different ROIs obtained. Tracking of the moving object is then carried out by computing the flow fields between predefined ROIs in the neighborhood of the detected POI in the subsequent image frames.Since the selected ROIs are smaller than the image frames, a fair amount of reduction in the time required for the computation of the optical flow field is achieved, thereby facilitating real-time operation. An application of the proposed technique is demonstrated on three video sequences of high-speed flying fighter aircrafts.     

Microwave‐assisted facile and convenient synthesis of fatty acid amide (erucamide): Chemical‐catalyzed rapid method

The present investigation explores a process for the production of erucamide, utilizing microwave irradiation as the heating element for the reaction between erucic acid and gaseous ammonia liberated by urea in the presence of catalyst (di‐ammonium hydrogen ortho‐phosphate) at atmospheric pressure and high temperature. In this process, the time of reaction is very short (25 min) and the yield is also good (92%).     

Comparison of culture media for enrichment and isolation of Salmonella spp. from frozen Channel catfish and Vietnamese basa fillets

Frozen fillets of Channel catfish and Vietnamese basa fish were used to compare Salmonella spp. recovery effectiveness of selective enrichment in Rappaport–Vassiliadis (RV) broth and tetrathionate broth (TT) and selective isolation on Hekteon enteric (HE) agar, xylose lysine deoxycholate (XLD) agar, and bismuth sulfite (BS) agar. Isolate confirmation was through fatty acid methyl ester analysis. Of 60 samples analyzed, 25 were found contaminated with Salmonella (42% incidence). Salmonella spp. recovery after enrichment in RV medium was 35% on HE agar, 30% on XLD agar, and 42% on BS agar. Similarly, after enrichment in TT broth, HE and XLD agars recovered 22% each and BS agar recovered 37%. No performance difference (p > 0.05) was observed in the recovery of Salmonella using the combinations of BS, HE, and XLD agars with RV broth and BS agar with TT broth. The combination of selective enrichment in RV and selective isolation on BS gave numerically greatest isolation of Salmonella from Channel catfish and Vietnamese basa fish compared to other isolation combinations.