Application of multiple modified fouling index (MFI) measurements at full-scale SWRO plant

Several potential growth methods have been developed to monitor biological/organic fouling potential in seawater reverse osmosis (SWRO), but to date the correlation between these methods and biofouling of SWRO has not been demonstrated. In this research, the relation between a new adenosine triphosphate (ATP)-based bacterial growth potential (BGP) test of SWRO feed water and SWRO membrane performance is investigated. For this purpose, the pre-treatment of a full-scale SWRO plant including dissolved air flotation (DAF) and two stage dual media filtration (DMF) was monitored for 5 months using BGP, orthophosphate, organic fractions by liquid chromatography coupled with organic carbon detection (LC-OCD), silt density index (SDI), and modified fouling index (MFI). Results showed that particulate fouling potential was well controlled through the SWRO pre-treatment as the measured SDI and MFI in the SWRO feed water were below the recommended values. DAF in combination with coagulation (1–5 mg-Fe3+/L) consistently achieved 70% removal of orthophosphate, 50% removal of BGP, 25% removal of biopolymers, and 10% removal of humic substances. Higher BGP (100–950 µg-C/L) in the SWRO feed water corresponded to a higher normalized pressure drop in the SWRO, suggesting the applicability of using BGP as a biofouling indicator in SWRO systems. However, to validate this conclusion, more SWRO plants with different pre-treatment systems need to be monitored for longer periods of time.

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Relation of Statistically Significant, Abnormal, and Typical WAIS-R VIQ-PIQ Discrepancies to Full Scale IQs

European Journal of Psychological Assessment ◽

10.1027//1015-5759.16.2.107 ◽

2000 ◽

Vol 16 (2) ◽

pp. 107-114 ◽

Cited By ~ 3

Author(s):

Louis M. Hsu ◽

Judy Hayman ◽

Judith Koch ◽

Debbie Mandell

Keyword(s):

Graphical Method ◽

The United States ◽

Full Scale ◽

True Score ◽

Absolute Value ◽

Normative Population ◽

The Us ◽

The Mean ◽

And Performance ◽

Quadratic Models

Summary: In the United States' normative population for the WAIS-R, differences (Ds) between persons' verbal and performance IQs (VIQs and PIQs) tend to increase with an increase in full scale IQs (FSIQs). This suggests that norm-referenced interpretations of Ds should take FSIQs into account. Two new graphs are presented to facilitate this type of interpretation. One of these graphs estimates the mean of absolute values of D (called typical D) at each FSIQ level of the US normative population. The other graph estimates the absolute value of D that is exceeded only 5% of the time (called abnormal D) at each FSIQ level of this population. A graph for the identification of conventional “statistically significant Ds” (also called “reliable Ds”) is also presented. A reliable D is defined in the context of classical true score theory as an absolute D that is unlikely (p < .05) to be exceeded by a person whose true VIQ and PIQ are equal. As conventionally defined reliable Ds do not depend on the FSIQ. The graphs of typical and abnormal Ds are based on quadratic models of the relation of sizes of Ds to FSIQs. These models are generalizations of models described in Hsu (1996) . The new graphical method of identifying Abnormal Ds is compared to the conventional Payne-Jones method of identifying these Ds. Implications of the three juxtaposed graphs for the interpretation of VIQ-PIQ differences are discussed.

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A Modification of the Payne-Jones Method of Identifying Abnormal Differences in WISC-R Performance and Verbal IQ's

European Journal of Psychological Assessment ◽

10.1027/1015-5759.12.1.27 ◽

1996 ◽

Vol 12 (1) ◽

pp. 27-32 ◽

Cited By ~ 1

Author(s):

Louis M. Hsu

Keyword(s):

Full Scale ◽

True Score ◽

Verbal Iq ◽

Score Difference ◽

The Difference ◽

And Performance

The difference (D) between a person's Verbal IQ (VIQ) and Performance IQ (PIQ) has for some time been considered clinically meaningful ( Kaufman, 1976 , 1979 ; Matarazzo, 1990 , 1991 ; Matarazzo & Herman, 1985 ; Sattler, 1982 ; Wechsler, 1984 ). Particularly useful is information about the degree to which a difference (D) between scores is “abnormal” (i.e., deviant in a standardization group) as opposed to simply “reliable” (i.e., indicative of a true score difference) ( Mittenberg, Thompson, & Schwartz, 1991 ; Silverstein, 1981 ; Payne & Jones, 1957 ). Payne and Jones (1957) proposed a formula to identify “abnormal” differences, which has been used extensively in the literature, and which has generally yielded good approximations to empirically determined “abnormal” differences ( Silverstein, 1985 ; Matarazzo & Herman, 1985 ). However applications of this formula have not taken into account the dependence (demonstrated by Kaufman, 1976 , 1979 , and Matarazzo & Herman, 1985 ) of Ds on Full Scale IQs (FSIQs). This has led to overestimation of “abnormality” of Ds of high FSIQ children, and underestimation of “abnormality” of Ds of low FSIQ children. This article presents a formula for identification of abnormal WISC-R Ds, which overcomes these problems, by explicitly taking into account the dependence of Ds on FSIQs.

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