Advanced Fenton processing of aqueous phenol solutions: a continuous system study including sonication effects.

Our previous report based on a batch reactor system for the Advanced Fenton Process (AFP) showed that pH, hydrogen peroxide and the organic substances treated are among the most important factors affecting the oxidation efficiency. As an extended study towards its potential commercialisation, this paper reports the effects of the main process parameters including those relating to a new laboratory scale AFP flow-through system. In order to systemise and correlate the results, the Taguchi experimental design method was used. Total organic carbon (TOC) removal was utilised as the measure of the oxidation efficiency and it was found that the removal of phenol from aqueous solution at pH 2.0 and 2.5 was very similar but hydrogen peroxide supply significantly affected the TOC removal with the change of flow rate from 14.4 ml/h to 60 ml/h. Also, the initial concentration of phenol was a highly significant factor, with higher concentrations resulting in a lower TOC removal rate. The temperature effects in the range of 14-42 degrees C were investigated and it was found that there was accelerated oxidation of phenol in the early stages but after 90 min there was no significant difference between the results. Sonication with a bath type sonicator resulted in relatively small enhancements of TOC removal but further studies with cup-horn sonication showed that TOC removal increased with higher intensity of sonication.

A modified advanced Fenton process for industrial wastewater treatment.

For the first time hydrodynamic cavitation induced by a liquid whistle reactor (LWR) has been used in conjunction with the advanced Fenton process (AFP) for the treatment of industrial wastewater. Semi-batch experiments in the LWR were designed to investigate the performance of the process by optimising various parameters such as pressure, pH, H2O2 concentration and the concentration of industrial wastewater samples on the mineralisation of the total organic carbon (TOC). It was found that higher pressures are more favourable for a rapid TOC mineralisation.

A Fenton-like oxidation process using corrosion of iron metal sheet surfaces in the presence of hydrogen peroxide: a batch process study using model pollutants.

This study evaluates a new method for chemically destroying organic pollutants in wastewater using spontaneous corrosion of iron metal sheet surfaces in the presence of hydrogen peroxide. Model pollutants (phenol and benzoic acid) were degraded in batch experiments to investigate which parameters affected the process performance. Iron metal sheet surfaces spontaneously corrode under acidic conditions producing iron species (mainly ferrous ions) dissolved in aqueous solution, which react with hydrogen peroxide via the Fenton reaction. In order to optimise the oxidation system, several factors (pH, H2O2 dosage, initial concentration of organic substances) affecting corrosion of the iron metal sheet surface were investigated. Total iron concentration in solution was investigated with different dosages of H2O2 (100 mg l(-1), 1000 mg l(-1) and 1900 mg l(-1)) at different pH values (1.5, 2.5 and 3.0). Iron corrosion increased with the decrease of pH. The addition of H2O2 resulted in a significant increase of iron corrosion. Organic substances also had a marked effect with, for instance, the presence of phenol or benzoic acid resulting in a considerable increase of iron corrosion. In contrast, the absence of either hydrogen peroxide or iron metal brought no change in total organic carbon (TOC). In order to obtain the most effective combination of parameters for TOC removal of phenol solution, experiments were conducted under varied conditions. The experimental results showed that there is an optimum pH requirement (in this work, 2.5). The factors affecting the TOC removal are discussed and the oxidation mechanisms leading to mineralization of organic substances are proposed.

Human observer detection experiments with mammograms and power-law noise.

We determined contrast thresholds for lesion detection as a function of lesion size in both mammograms and filtered noise backgrounds with the same average power spectrum, P(f)=B/f3. Experiments were done using hybrid images with digital images of tumors added to digitized normal backgrounds, displayed on a monochrome monitor. Four tumors were extracted from digitized specimen radiographs. The lesion sizes were varied by digital rescaling to cover the range from 0.5 to 16 mm. Amplitudes were varied to determine the value required for 92% correct detection in two-alternative forced-choice (2AFC) and 90% for search experiments. Three observers participated, two physicists and a radiologist. The 2AFC mammographic results demonstrated a novel contrast-detail (CD) diagram with threshold amplitudes that increased steadily (with slope of 0.3) with increasing size for lesions larger than 1 mm. The slopes for prewhitening model observers were about 0.4. Human efficiency relative to these models was as high as 90%. The CD diagram slopes for the 2AFC experiments with filtered noise were 0.44 for humans and 0.5 for models. Human efficiency relative to the ideal observer was about 40%. The difference in efficiencies for the two types of backgrounds indicates that breast structure cannot be considered to be pure random noise for 2AFC experiments. Instead, 2AFC human detection with mammographic backgrounds is limited by a combination of noise and deterministic masking effects. The search experiments also gave thresholds that increased with lesion size. However, there was no difference in human results for mammographic and filtered noise backgrounds, suggesting that breast structure can be considered to be pure random noise for this task. Our conclusion is that, in spite of the fact that mammographic backgrounds have nonstationary statistics, models based on statistical decision theory can still be applied successfully to estimate human performance.

The Rose model, revisited.

In 1946 and 1948, three very important papers by Albert Rose [J. Soc. Motion Pict. Eng. 47, 273 (1946); J. Opt. Soc. Am. 38, 196 (1948); L. Marton, ed. (Academic, New York, 1948)] were published on the role that photon fluctuations have in setting fundamental performance limits for both human vision and electronic imaging systems. The papers were important because Rose demonstrated that the performance of imaging devices can be evaluated with an absolute scale (quantum efficiency). The analysis of human visual signal detection used in these papers (developed before the formal theory of signal detectability) was based on an approach that has come to be known as the Rose model. In spite of its simplicity, the Rose model is a very good approximation of a Bayesian ideal observer for the carefully and narrowly defined conditions that Rose considered. This simple model can be used effectively for back-of-the-envelope calculations, but it needs to be used with care because of its limited range of validity. One important conclusion arising from Rose's investigations is that pixel signal-to-noise ratio is not a good figure of merit for imaging systems or components, even though it is still occasionally used as such by some researchers. In the present study, (1) aspects of signal detection theory are presented, (2) Rose's model is described and discussed, (3) pixel signal-to-noise ratio is discussed, and (4) progress on modeling human noise-limited performance is summarized. This study is intended to be a tutorial with presentation of the main ideas and provision of references to the (dispersed) technical literature.

Visual signal detection with two-component noise: low-pass spectrum effects.

Detection of signals in natural images and scenes is limited by both noise and structure. The purpose of this study is to investigate phenomenological issues of signal detection in two-component noise. One component had a broadband (white) spectrum designed to simulate image noise. The other component was filtered to simulate two classes of low-pass background structure spectra: Gaussian-filtered noise and power-law noise. Measurements of human and model observer performance are reported for several aperiodic signals and both classes of background spectra. Human results are compared with two classes of observer models and are fitted very well by suboptimal prewhitening matched filter models. The nonprewhitening model with an eye filter does not agree with human results when background-noise-component power spectrum bandwidths are less than signal energy bandwidths.

Visual signal detectability with two noise components: anomalous masking effects.

We measured human observers' detectability of aperiodic signals in noise with two components (white and low-pass Gaussian). The white-noise component ensured that the signal detection task was always noise limited rather than contrast limited (i.e., image noise was always much larger than observer internal noise). The low-pass component can be considered to be a statistically defined background. Contrast threshold elevation was not linearly related to the rms background contrast. Our results gave power-law exponents near 0.6, similar to that found for deterministic masking. The Fisher-Hotelling linear discriminant model assessed by Rolland and Barrett [J. Opt. Soc. Am. A 9, 649 (1992)] and the modified nonprewhitening matched filter model suggested by Burgess [J. Opt. Soc. Am. A 11, 1237 (1994)] for describing signal detection in statistically defined backgrounds did not fit our more precise data. We show that it is not possible to find any nonprewhitening model that can fit our data. We investigated modified Fisher-Hotelling models by using spatial-frequency channels, as suggested by Myers and Barrett [J. Opt. Soc. Am. A 4, 2447 (1987)]. Two of these models did give good fits to our data, which suggests that we may be able to do partial prewhitening of image noise.

Comparison of receiver operating characteristic and forced choice observer performance measurement methods.

The receiver operating characteristic (ROC) method has been successfully used in medical imaging for 20 years. It has been so successful that many people think of it as an end in itself rather than just one of several ways to assess human observer performance of image based decision tasks. Studies of human and ideal observer decision performance are designed to estimate a measure of observer performance (e.g., efficiency, d' or da). The experimenter would like to obtain accurate and precise estimates using a relatively small number of images or decision trials because of a variety of constraints. One purpose of this paper is to introduce medical physicists to another effective psychophysical measurement technique, the forced choice method. The second purpose is to present a comparison of the forced choice and ROC methods, with particular attention to sampling statistics considerations. In brief, the rating scale ROC method is preferable when the limiting constraint is the number of images and at the same time it is not feasible to use the forced choice with more than four alternatives. The forced choice method can be superior for experiments using synthetic images, under some conditions.

A method of using noise as a test pattern for determining image enhancement filters.

Many digitally based medical imaging systems include both reconstruction algorithms and additional image filters designed to enhance certain image features. However, the manufacturers usually consider these algorithms and filters to be proprietory information. The purpose of this note is to describe a simple procedure for determining the spatial frequency response of these proprietary enhancement filters. The technique uses image noise as a test pattern. The procedure consists of acquiring a small number of noise-only data sets (say 10) of a uniform phantom and reconstructing the images using the different filters with repeated use of the noise data sets. A straightforward analysis then yields the enhancement filter frequency responses.

Statistically defined backgrounds: performance of a modified nonprewhitening observer model.

Research on human-observer performance for noise-limited tasks (such as those found in medical imaging) has recently progressed to investigations in which some signal or image parameters are statistically defined. In these cases the ideal-observer procedure is usually nonlinear, and analysis is mathematically intractable. Two suboptimal but linear observer models have been proposed for mathematical convenience. The Hotelling observer is the optimal linear model and has been found to give a good fit to most human results. The nonprewhitening (NPW) matched filter also has been useful for explanation of some human results. Rolland and Barrett [J. Opt. Soc. Am. A 9, 649 (1992)] recently reported human results for detection of signals in white noise superimposed on statistically defined (lumpy) backgrounds in experiments that simulated nuclear medicine imaging systems. They found that the Hotelling model gave a good fit, whereas the simple NPW matched filter gave a poor fit. It is shown that the NPW model can also fit their data if a spatial frequency filter of a shape similar to the human contrast-sensitivity function is added to the NPW observer model. The best fit is achieved by use of an eye-filter model E(f) = f1.3 exp(-cf2), with c selected to yield a peak at 4 cycles/deg.

Spinal bone loss and ovulatory disturbances.

BACKGROUND: Osteoporosis develops in women with estrogen deficiency and amenorrhea who lose bone at an accelerated rate. It is not known to what extent bone loss differs between ovulatory women with regular menstrual cycles who are training intensely and those who are sedentary. METHODS: We measured the density of cancellous spinal bone from the 12th thoracic vertebra to the 3rd lumbar vertebra by quantitative computed tomography on two occasions one year apart in 66 premenopausal women 21 to 42 years of age. All the women had two consecutive ovulatory cycles immediately before entering the study. Twenty-one women were training for a marathon, 22 ran regularly but less intensively, and 23 had normal levels of activity. The lengths of the women's menstrual cycles and luteal phases, diet, exercise levels, and hormonal levels were also determined. We defined ovulatory disturbances as anovulatory cycles and cycles with short luteal phases. RESULTS: The mean (+/- SD) spinal bone density in the 66 women decreased 3.0 +/- 4.8 mg per cubic centimeter per year (2.0 percent per year) (P less than 0.001). Amenorrhea did not develop in any woman during the year of observation (only 2.7 percent of the cycles were greater than 36 days long). Ovulatory disturbances occurred in 29 percent of all cycles, however. Bone loss was strongly associated with these disturbances (r = 0.54, 24 percent of the variance). The 13 women who had anovulatory cycles lost bone mineral at a rate of 6.4 +/- 3.8 mg per cubic centimeter per year (4.2 percent per year). The women training for a marathon had menstrual cycles similar to those of the women in the other two groups. CONCLUSION: Decreases in spinal bone density among women with differing exercise habits correlated with asymptomatic disturbances of ovulation (without amenorrhea) and not with physical activity.

Visual signal detection. IV. Observer inconsistency.

Historically, human signal-detection responses have been assumed to be governed by external determinants (nature of the signal, the noise, and the task) and internal determinants. Variability in the internal determinants is commonly attributed to internal noise (often vaguely defined). We present a variety of experimental results that demonstrate observer inconsistency in performing noise-limited visual detection and discrimination tasks with repeated presentation of images. Our results can be interpreted by using a model that includes an internal-noise component that is directly proportional to image noise. This so-called induced internal-noise component dominates when external noise is easily visible. We demonstrate that decision-variable fluctuations lead to this type of internal noise. Given this induced internal-noise proportionality (sigma i/sigma 0 = 0.75 +/- 0.1), the upper limit to human visual signal-detection efficiency is 64% +/- 6%. This limit is consistent with a variety of results presented in earlier papers in this series.

Vertebral trabecular bone: comparison of single and dual-energy CT measurements with chemical analysis.

We have done detailed analysis of 50 excised L1 vertebral bones including single-energy CT, preprocessing dual-energy CT, as well as a number of physical and chemical analyses to determine the amount of fat and the elemental composition. We found a good correlation (0.91) between single-energy CT measurements and mineral element content and excellent correlation (0.95) between dual-energy CT measurements and mineral element content. The SEEs of the CT mineral were 14 and 10 mg (K2HPO4 equivalent) per cm3 for single and dual energy, respectively. We also report on the variation of fat and mineral content with respect to age, the quantitative effect of fat variation on CT values, and the relationship between calcium and phosphorus content.

Contrast discrimination in noise.

Even the highest contrast sensitivities that humans can achieve for the detection of targets on uniform fields fall far short of ideal values. Recent theoretical formulations have attributed departures from ideal performance to two factors--the existence of internal noise within the observer and suboptimal stimulus information sampling by the observer. It has been postulated that the contributions of these two factors can be evaluated separately by measuring contrast-detection thresholds as a function of the level of externally added visual noise. We wished to determine whether a similar analysis could be applied to contrast discrimination and whether variation of the increment threshold with pedestal contrast is due to changes in internal noise or sampling efficiency. We measured contrast-increment thresholds as a function of noise spectral density for near-threshold and suprathreshold pedestal contrasts. The experiments were conducted separately for static and dynamic noise. Our findings indicate that the same formulation can be applied to contrast discrimination and that changes in the estimated values of internal noise, rather than changes in sampling efficiency, play the major role in determining properties of contrast discrimination. Implications for models of contrast coding in vision are discussed.

Scatter radiation from abdominal CT examinations.

Several water phantoms were scanned under a number of conditions and radiation exposure due to scatter was measured at the center of one end. The decrease of the scatter radiation exposure is nearly exponential with distance from the slice plane. The half-value distance is a function of the slice cross-sectional area. An empirical equation is presented to relate exposure to the pertinent variables.

Physical measurements of heavy metal filter performance.

Contrast, relative tube loading, and relative entrance exposure have been measured for a number of heavy metal filters (Gd, Ho, Yb, and W) at several filter thicknesses, tube voltages (70-100 kV), and phantom thicknesses (1.5-2.5 cm of aluminum). The rare-earth filters consistently gave higher contrast (relative to water) for air, CaCl2, iodine, and oil than the standard 2 mm of added aluminum, at a given tube voltage. It was found that the best filter choices gave a constant product of relative exposure and relative tube loading.

Visual signal detection. II. Signal-location identification.

We have measured the effect of signal-location uncertainty on the detectability of simple visual signals in uncorrelated image noise. An M-alternative forced-choice signal-location identification technique was used with values of M ranging from 2 to 1800. We find high statistical efficiency (50% for aperiodic signals), and results from one value of M can be used to predict all others. The results are consistent with the view that humans can act as suboptimal maximum a posteriori probability observers.