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.     

Evaluating software reuse alternatives: a model and its application to an industrial case study

We propose a model that enables software developers to systematically evaluate and compare all possible alternative reuse scenarios. The model supports the clear identification of the basic operations involved and associates a cost component with each basic operation in a focused and precise way. The model is a practical tool that assists developers to weigh and evaluate different reuse scenarios, based on accumulated organizational data, and then to decide which option to select in a given situation. The model is currently being used at six different companies for cost-benefit analysis of alternative reuse scenarios; we give a case study that illustrates how it has been used in practice.     

Effect of broaching on high-temperature fatigue behavior in notched specimens of INCONEL 718

Notches were machined in specimens of INCONEL 718 by a broaching process, where differing broaching runs led to differing extents of subsurface deformation and surface roughness. Fatigue tests were carried out at 600 °C with a trapezoidal loading waveform at 0.25 Hz. The broaching process that led to the more severe subsurface deformation (but lower surface roughness) showed the worst fatigue performance. Analysis of total strain amplitude in the notch root with the aid of an elastoplastic finite-element (FE) model showed that the work hardening related to the subsurface deformation caused by the different broaching can account for the difference in fatigue lives. Differences in initiation and growth behavior were seen for the two broached finishes as well as for broached and subsequently polished samples. These differences are discussed in terms of a change in crack growth initiation and growth mechanisms due to the presence of the work-hardened layer.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Thermal Transformations of an Aluminoborophosphate Binder

Thermal transformations of a commercial aluminoborophosphate binder are studied in a broad temperature range by optical microscopy, x-ray diffraction, IR spectroscopy, and thermal analysis. The introduction of B₂O₃ reduces the temperature of phosphate polycondensation, enhances the stability of cyclometaphosphates in a broad temperature range (180–1100°C), and reduces the stability of hydrogen phosphates.     

A test for the statistical significance of DNA sequence similarities for application in databank searches

A method is developed, based on word-searching, which provides a rapid test for the statistical significance of DNA sequence similarities for use in databank searching. The method makes allowance for the lengths and dinucleotide compositions of the sequences being compared. A way is also described to calculate the power of the test, i.e. the probability of detecting a given similarity as being statistically significant. The effects on the power of the test of the scoring method, word length, sequence length, and sequence composition are examined. A novel scoring method is shown to be superior to the method currently used in most word-searching algorithms.     

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.