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I By adding an impaction plate in a graphite furnace it is possible to separate and collect 6µm particles which are found in cigarette smoke. This allows for the quantitative detection of Cd, Cr, Pb and Mn in air in a direct fashion and quasi real time. It is important to monitor not only direct inhalation of cigarette smoke, but also “second‐hand” smoking by innocent by‐standers.

Many factors affect the print quality and ink transfer. These are either machine factors, paper factors, or Ink factors. The aim of this work was to find out to what extent are the amount of ink transferred influenced by the previously mentioned factors. Atomic absorption was used for quantitatively measuring the amount of ink transferred. Copper phthalocyanine pigment was chosen. The amount of copper detected is taken as an indication of the amount of ink transferred. The results indicated that the amount of ink transferred decreased as the printing speed increased. It was expected to be increased with increasing printing pressure. But It was found that the amount of ink transferred to supercalendered paper decreased with increasing printing pressure. The amount of ink transferred increased as the ink viscosity increased. The type of ink resin was found to have a considerable effect on the amount of ink transferred.

The quality of groundwater in the vicinity of petroleum products retailing stations in Ile-Ife, Nigeria was investigated with a view to providing valuable information on the organic and other physico-chemical parameters associated with the contamination of the groundwaters by petroleum products. The paper aims to discuss these issues.

Three sets of samples were collected per season from artesian wells within petroleum products retailing stations for polycyclic aromatic hydrocarbons (PAHs), trace metals and other physico-chemical parameters analysis. Extraction, cleaned-up and concentration of the PAHs were done using certified analytical methods. Levels of the PAHs and metals were determined using gas chromatography coupled with flame ionization detector and bulk scientific atomic absorption spectrophotometer, respectively, while other pollution indicators were measured using standard analytical procedures.

The groundwaters contained elevated levels of PAHs, Cu, Zn, Mn, Pb, Cr, V, Ni, Fe and total dissolved solids than their maximum allowable limits for drinking water. Analysis of variance (ANOVA) results confirmed that both seasonal variation and location had much influence on the levels of most of the analyzed parameters. Some of the parameters showed strong positive correlation with each other, while Cr/Pb and Na/Pb displayed strong negative correlation with each other, indicating similar source(s) and/or chemical affinity and vice versa, respectively. Cross-plot analysis results using metals and PAHs concentrations as variables showed significant positive correlations (R2=0.99) and (R2=0.60), respectively, suggesting similar source(s) of contamination of the two sets of samples.

The level of the groundwater contamination was an indication of indiscriminate discharge of petroleum products and/or underground tank leakage within the study areas.

The dependency on human expertise for analysis and interpretation is the main reason for wear debris analysis not being used in industry to its full potential and becoming one of the most powerful machine condition monitoring strategies. The dependency on human expertise makes the interpretation and result subjective in nature, costly and time consuming. The purpose of this paper is to review work being done to develop an automatic, reliable and objective wear particle classification system as a solution to the above problem. At the same time it also aims to discuss some common off line test methods being practiced for wear debris analysis.

Computer image analysis is a solution for some of the problems associated with the conventional techniques. First it is tried to efficiently describe the characteristics of computer images of different types of wear debris using a few numerical parameters. Then using some Artificial Intelligence tools, the wear particle classification system can be developed.

Many shape, size and surface parameters are discussed in the paper. Out of these, nine numerical parameters are selected to describe and distinguish six common type of wear debris. Once the type of debris is identified, the mode of wear and hence the machine condition can be assessed.

The present process of fault and condition monitoring of an equipment by wear debris analysis involves human judgment of debris formations. A set‐up standard for comparison of debris will enable the maintenance team to diagnose faults in a comparatively better way.

The aim of this paper is to discuss the difficulties in identifying wear particles and finding out the exact health of equipment, which, due to its subjective nature, is influenced by human errors. An objective method with certain standards for classification of wear particles compatible with an artificial intelligence system will yield some flawless results of wear debris analysis, which has not been attempted in the past as per available literature.

Studies samples of different used lubricating oils. Details how their physico‐chemical characteristics were determined by the use of modern instrumental analytical techniques; and how different standard separation techniques were used to separate the unused base oil and other components from the collected samples for characterization. Discusses the different re‐refining procedures available in the literature and highlights the merits and demerits of different re‐refining techniques. Concludes that re‐refining of used oil will conserve resources and help to preserve the environment.

Elemental analysis of these medicinal plants was performed by employing Instrumental Neutron Activation Analysis (INAA) and Atomic Absorption Spectroscopy (AAS) techniques. The samples were irradiated with thermal neutrons in a nuclear reactor and the induced radio activity was counted by gamma ray spectrometry using an efficiency calibrated high resolution High Purity Germanium (HPGe) detector. Most of the medicinal plants were found to be rich in one or more of the elements under study. The variation in elemental concentration in same medicinal plant samples collected from different regions was studied and the biological effects of these elements on human beings are discussed. The study was also extended further to estimate the level of toxic elements like Cr, Cd, Ni, Pb and Hg in medicinal plants which arises due to environmental pollution. The results were discussed with careful reference to established role of essential and rare elements to the physiology and pathology of plant and human life.

The innovation process is not homogeneous, but highly variable according to industrial sector and the level of abstraction of the innovation itself. This level of abstraction from existing products while not precisely measurable, can be graded, thus giving some guidance as to the probability of success according to the size of investment and the risk involved. The complexity of the new product and its technological level (the monograph confines the argument to product innovation) will also determine how the innovating organisation handles the innovation. Much research has now been done into the innovation process, and some of the leading projects and their findings are analysed. Supporting the basic argument there are two case histories, one of a successful scientific instrument, together with reference to an unsuccessful attempt to launch it, and one of a failure with a new material, in spite of highly successful technology.

Nutritional and medicinal properties of black sesame seeds (Sesamum indicum) make it very valuable in traditional system of food. Minerals in Sesamum indicum play an important role to enhance its nutritional value. The present research comprises on proximate and chemical analysis of Sesamum indicum. This study is also based on the development of ashing methods for extraction of metals in black sesame seeds. The paper aims to discuss these issues.

Black sesame seeds were taken from local market at Karachi-Pakistan. Proximate analysis of seeds comprises of moisture content, ash content and total metal content by EDTA titration. Digestion of this herb was done in different medium, i.e. HNO₃, HCl, H₂SO₄ and simple ash (ash was prepared without using any acid). Atomic absorption spectroscopy was used for the analysis of metals, i.e. Fe, Zn, Cu and Mg in all these ashes.

From the results it is concluded that best medium for ashing is H₂SO₄, by which maximum ash (5.39±0.0021 per cent) produced. Qualitative analysis (based on Ksp values) also confirmed the presence of maximum number of metals in H₂SO₄ medium. Complexometric titration also revealed that maximum metal content was found to be in HCl and H₂SO₄ ash. Results from atomic absorption spectroscopy revealed that H₂SO₄ is the best method for copper (0.399±0.0001 mg/g) and iron (0.3993±0.0015 mg/g), while simple ash can extract zinc and magnesium at their maximum level.

This research demonstrates the best ashing method for the extraction of micronutrients, present in Sesamum indicum. These micronutrients are very beneficial for human health.

Standardised solutions of 30 commonly determined metals are listed with compositions, catalogue numbers and prices in a product data sheet published by Fisher Scientific Co. The Fisher certified atomic absorption standards are 1000ppm solutions which have a shelf life of at least 24 months. Each standard is checked against microchemical standards obtained from the National Bureau of Standards and against spectro‐graphically pure metals, using both classic analytical methodology and atomic absorption techniques to define the concentration of each solution.

Because the discontinuous and uncertain characteristics of knowledge-based innovation cannot be reasonably interpreted by conventional management approaches, quantum mechanics which begins with uncertainty and concerns with a dynamic process of the complex system, has been exploratorily used in the management field. Although the theoretical new insights are provided by pioneering studies, quantitative research is in short supply. This paper aims to propose a quantum mechanics-based framework for quantitative research, thus extending the application of quantum mechanics in the knowledge management area from a dynamic system evolutionary standpoint.

Based on the similarity comparison between knowledge-based system evolution and atomic motion, the authors construct the atom-like structure of the knowledge-based system and elaborate the evolutionary mechanism of the knowledge-based system, thereby establishing the quantitative model. Apple and Zhongxing Telecom Equipment were selected for an empirical study to demonstrate the usefulness of the models for research on knowledge-based innovation and explore the unique knowledge-based innovation characteristics of the two firms.

First, the transition force of dynamic knowledge shows an inverted U shape; accumulating dynamic knowledge to a moderate degree not only facilitates transforming dynamic knowledge into static knowledge but also balances the relationship between the influence of knowledge force range and dynamic knowledge transformation. Second, existing knowledge is gradually substituted by new knowledge and knowledge density at a high knowledge energy level distinctly increases with a narrower bandwidth. Third, the investment loss is associated with resource configuration, resource utilization and the amount of accumulative dynamic knowledge before investment. Knowledge loss is negatively correlated with the knowledge compatibility coefficient.

The authors use the advanced method in quantum mechanics to legitimately unveil the emergence mechanism of knowledge-based innovation. Meanwhile, the authors capture the non-linear transformation relationship of heterogeneous knowledge and expose the change in ways of both investment loss and knowledge loss that cannot be quantified by conventional models. In doing so, the authors not only reveal the principle of qualitative knowledge change but also offer practical implications for developing flexible and targeted innovation strategies.

First, by proposing a complete quantum mechanics-based framework, the authors not only supplement the quantitative research contents to knowledge-based innovation literature which proposed calls to conduct research in way of quantum mechanics but also overcome the difficulties of knowledge-based system conceptualization and measurement. Second, the authors reveal the uncertain change of knowledge transformation and measure the loss of investment and knowledge, which contribute to identifying defects of firms in knowledge-based innovation. Third, the authors explore the internal mechanism that led to knowledge-based innovation exhibits non-linear characteristics and capture unique dynamic relationships between different variables which affect the emergence of knowledge-based innovation.