Simultaneous monitoring of the destruction of stearic acid and generation of carbon dioxide by self-cleaning semiconductor photocatalytic films

The destruction of stearic acid (SA), the SA test, is a popular approach used to evaluate the activities of photocatalytic films. The destruction of SA via semiconductor photocatalysis is monitored simultaneously, using FT-IR spectroscopy, via the disappearance of SA and the appearance of CO2, Sol-gel and P25 films of titania are used as the semiconductor photocatalytic self-cleaning films. A conversion factor is used of 9.7 x 1015 molecules of SA cm(-2) 1 Cru-1 integrated areas of the peaks in the Fr-IR of SA over the range 2700-3000 cm(-1), which is three times that reported previously by others. As the SA disappeared the concomitant amount of CO2 generated was > 90% that expected throughout the photomineralisation process for the sol-gel titania film. In contrast, the slightly more active, and scattering, P25 fitania films generated CO2 levels that dipped as low as 69% during the course of the photoreaction, but eventually recovered to congruent to 100% that expected based on the amount of SA present. The importance of these results with respect to SA test and the evaluation of new and existing self-cleaning films are discussed briefly. (c) 2006 Elsevier B.V. All rights reserved.

Self-cleaning perovskite type catalysts for the dry reforming of methane

Gas-to-liquid processes are generally used to convert natural gas or other gaseous hydrocarbons into liquid fuels via an intermediate syngas stream. This includes the production of liquid fuels from biomass-derived sources such as biogas. For example, the dry reforming of methane is done by reacting CH4 and CO2, the two main components of natural biogas, into more valuable products, i.e., CO and H2. Nickel containing perovskite type catalysts can promote this reaction, yielding good conversions and selectivities; however, they are prone to coke laydown under certain operating conditions. We investigated the addition of high oxygen mobility dopants such as CeO2, ZrO2, or YSZ to reduce carbon laydown, particularly using reaction conditions that normally result in rapid coking. While doping with YSZ, YDC, GDC, and SDC did not result in any improvement, we show that a Ni perovskite catalyst (Na0.5La0.5Ni0.3Al0.7O2.5) doped with 80.9 ZrO2 15.2 CeO2 gave the lowest amount of carbon formation at 800 °C and activity was maintained over the operating time.

Correlation between ΔAbs, ΔRGB (red) and stearic acid destruction rates using commercial self-cleaning glass as the photocatalyst

A resazurin (Rz) based photocatalyst indicator ink is used to test the activity of a commercial self-cleaning glass, using UV–vis spectroscopy and digital photography to monitor the photocatalyst-driven change in colour of the ink. UV–vis spectroscopy allows the change in film absorbance, ΔAbs, to be monitored as a function of irradiation time, whereas digital photography is used to monitor the concomitant change in the red component of the RGB values, i.e. ΔRGB (red). Initial work reveals the variation in ΔAbst and ΔRGB (red)t as a function of irradiation time, t, are linearly correlated. The rates of change of these parameters are also linearly correlated to the rates of oxidative destruction of stearic acid on self-cleaning glass under different irradiances. This work demonstrates that a measure of photocatalyst activity of self-cleaning glass, i.e. the time taken to change the colour of an Rz photocatalyst indicator ink, can be obtained using inexpensive digital photography, as alternative to more expensive lab-based techniques, such as UV–vis spectrophotometry.

Smart, Reusable labels for assessing self-cleaning films

Novel, reversible (reusable) photocatalyst activity indicator labels, which undergo a rapid colour change when in contact with a photocatalytic film via the photoreduction of methylene blue contained within the label’s adhesive, are explored as a method for assessing the activity of self-cleaning glass in situ and the laboratory, using digital photography.

Data Cleaning and Outlier Removal: Application in Human Skin Detection

An outlier removal based data cleaning technique is proposed to
clean manually pre-segmented human skin data in colour images.
The 3-dimensional colour data is projected onto three 2-dimensional
planes, from which outliers are removed. The cleaned 2 dimensional
data projections are merged to yield a 3D clean RGB data. This data
is finally used to build a look up table and a single Gaussian classifier
for the purpose of human skin detection in colour images.

SmartClean: an incremental data cleaning tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the data quality problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool's validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.

Ontologies for reusing data cleaning knowledge

The emergence of new business models, namely, the establishment of partnerships between organizations, the chance that companies have of adding existing data on the web, especially in the semantic web, to their information, led to the emphasis on some problems existing in databases, particularly related to data quality. Poor data can result in loss of competitiveness of the organizations holding these data, and may even lead to their disappearance, since many of their decision-making processes are based on these data. For this reason, data cleaning is essential. Current approaches to solve these problems are closely linked to database schemas and specific domains. In order that data cleaning can be used in different repositories, it is necessary for computer systems to understand these data, i.e., an associated semantic is needed. The solution presented in this paper includes the use of ontologies: (i) for the specification of data cleaning operations and, (ii) as a way of solving the semantic heterogeneity problems of data stored in different sources. With data cleaning operations defined at a conceptual level and existing mappings between domain ontologies and an ontology that results from a database, they may be instantiated and proposed to the expert/specialist to be executed over that database, thus enabling their interoperability.

Multi-Enzymatic Systems for Cleaning-up Synthetic Dyes from the Environment

Environmental pollution is one of the major and most important problems of the modern world. In order to fulfill the needs and demands of the overgrowing human population, developments in agriculture, medicine, energy sources, and all chemical industries are necessary (Ali 2010). Over the last century, the increased industrialization and continued population growth led to an augmented production of environmental pollutants that are released into air, water, and soil, with significant impact in the degradation of various ecosystems (Ali 2010, Khan et al. 2013).(...)

Hazardous substances in frequently used professional cleaning products.

A growing number of studies have identified cleaners as a group at risk for adverse health effects of the skin and the respiratory tract. Chemical substances present in cleaning products could be responsible for these effects. Currently, only limited information is available about irritant and health hazardous chemical substances found in cleaning products. We hypothesized that chemical substances present in cleaning products are known health hazardous substances that might be involved in adverse health effects of the skin and the respiratory tract. We performed a systematic review of cleaning products used in the Swiss cleaning sector. We surveyed Swiss professional cleaning companies (n = 1476) to identify the most used products (n = 105) for inclusion. Safety data sheets (SDSs) were reviewed and hazardous substances present in cleaning products were tabulated with current European and global harmonized system hazard labels. Professional cleaning products are mixtures of substances (arithmetic mean 3.5 +/- 2.8), and more than 132 different chemical substances were identified in 105 products. The main groups of chemicals were fragrances, glycol ethers, surfactants, solvents; and to a lesser extent, phosphates, salts, detergents, pH-stabilizers, acids, and bases. Up to 75% of products contained irritant (Xi), 64% harmful (Xn) and 28% corrosive (C) labeled substances. Hazards for eyes (59%) and skin (50%), and hazards by ingestion (60%) were the most reported. Cleaning products potentially give rise to simultaneous exposures to different chemical substances. As professional cleaners represent a large workforce, and cleaning products are widely used, it is a major public health issue to better understand these exposures. The list of substances provided in this study contains important information for future occupational exposure assessment studies.

County of Welland estimate (copy) of work done on the main drain, and cleaning of fallen timber by Andrew Mains, signed by S.D. Woodruff

County of Welland estimate (copy) of work done on the main drain, and cleaning of fallen timber by Andrew Mains, signed by S.D. Woodruff. Estimate no.1, Oct., 1856.

County of Welland estimate of work done on section no.1 and cleaning below the culvert of the tap drain at Marshville by Edward Henderson

County of Welland estimate of work done on section no.1 and cleaning below the culvert of the tap drain at Marshville by Edward Henderson, signed by S.D. Woodruff. Estimate no.2, Oct., 1856.

Receipt from Chatfield and Neelon, St. Catharines for cleaning out boilers

Receipt from Chatfield and Neelon, St. Catharines for cleaning out boilers, Oct. 1, 1887.