Novel tiO2 nanocatalysts for wastewater purification: tapping energy from the sun.

Water treatment using TiO2 semiconductor as a durable heterogeneous photocatalyst has been the focus of environmentalists in recent years. Currently, we developed an inexpensive and highly efficient approach for synthesizing nitrogen-doped TiO2 with lower band-gap energy that can respond to visible light. Doping on the molecular scale led to an enhanced nitrogen concentration of up to 21.8%. Reflectance measurements showed the synthesized N-doped TiO2 nanoparticles are catalytically active with the absorbance that extends into the visible region up to 600 nm. The water purification potential of this new class of compound was evaluated by studying the photodegradation of Acid Orange 7 (AO7) and E. coli. Experiments were conducted to compare the photocatalytic activities of N-doped TiO2 nanocatalysts and commercially available Degussa P25 power under identical solar light exposure. N-doped TiO2 demonstrated superior photocatalytic activities in both chemical compound degradation and bactericidal reactions. The result of this study shows the potential of applying new generations of catalyst for wastewater purification and disinfection.     

Modelling and simulation of KNbO3 ceramics dispersion

The dispersion of potassium niobate (KNbO₃) ceramics is analysed using the multiple-arc approach. This has revealed a high frequency arc that is unattainable by the Cole-Cole single arc analysis. The temperature dependence of the new arc is derived through the spread parameter of the relaxation distribution and interpreted in terms of the ferroelectric property of the KNbO₃ ceramics. It is shown that the overall dispersion behaviour of the ceramics is mainly due to the existence of two distinctly different polarisation mechanisms. The arc approach has also provided an effective tool for network simulation of dispersion whereby the ceramics are modelled by nine parallel R-C branches over the frequency range 10²-10⁵ Hz used     

Evaluation of image similarity by histogram intersection

Colour is the most widely used attribute in image retrieval and object recognition. A technique known as histogram intersection has been widely studied and is considered to be effective for color‐image indexing. The key issue of this algorithm is the selection of an appropriate color space and optimal quantization of the selected color space. The goal of this article is to measure the model performance in predicting human judgment in similarity measurement for various images, to explore the capability of the model with a wide set of color spaces, and to find the optimal quantization of the selected color spaces. Six color spaces and twelve quantization levels are involved in evaluating the performance of histogram intersection. The categorical judgment and rank order experiments were conducted to measure image similarity. The CIELAB color space was found to perform at least as good as or better than the other color spaces tested, and the ability to predict image similarity increased with the number of bins used in the histograms, for up to 512 bins (8 per channel). With more than 512 bins, further improvement was negligible for the image datasets used in this study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 265–274, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20122     

Factors affecting cloud point analysis of palm oleins

Some of the factors affecting cloud point determination of palm oleins are described. These are the type of container used, method of stirring, rate of stirring and bath temperature. The repeatability and reproducibility standard deviations of the method are determined from collaborative trials. Recommendations for the test are made to reduce the large variations among laboratories.     

Anaerobic biodecolorization of textile reactive anthraquinone and phthalocyanine dyebaths under hypersaline conditions.

The biological decolorization of two industrial, spent textile reactive dyebaths was investigated using a suspended-growth, halophilic mixed culture fed with glucose. Dyebath I contained mainly Reactive Blue 19 (RB19), an anthraquinone dye, whereas dyebath II contained mainly Reactive Blue 21 (RB21), a phthalocyanine dye. Batch assays under anaerobic conditions with the two neutralized dyebaths resulted in 87 and 37% extent of decolorization for dyebaths I and II, respectively. The rate of glucose utilization and the extent of acetate production were impacted in the presence of each dyebath as compared to the control culture. However, dyebath decolorization occurred despite moderate culture inhibition. Reuse of a biologically renovated RB19-containing dyebath in the dyeing process resulted in reproducible but not identical cotton fabric shades as compared to a standard dyeing (i.e., control) using fresh water. This difference is attributed to a variable degree of RB19 aggregation during the dyeing process and is not related to the efficiency of the biodecolorization process. Further improvement of the redyeing efficiency will lead to the development of an in-plant, closed-loop decolorization system resulting in significant water conservation and minimization of textile pollutants such as salt and dyes.     

The architecture of the Sure System 2000 communications processor

Sure System 2000, a fault-tolerant computer that couples multiprocessors to offer low-priced, high-performance systems that deal effectively with faults and failures, is presented. The architecture is based on the local redundancy technique, ensuring that no hardware or software fault can cause a system crash. Software errors can be fixed, and hardware can be replaced, upgraded, or added dynamically. Existing fault-tolerant computers are briefly reviewed, and the logic hardware system configuration of the Sure System 2000 is described. The multiprocessor and I/O architecture are examined. The SXO Sure System 2000 expandable operating system is described