Do teacher rating forms reveal as much about students as about teachers?

417 students in a multisection introductory psychology course responded to a questionnaire on reasons for section selection at the beginning of the course and evaluated their instructors at the end. Ss using teacher's reputation or ability to select sections congregated in certain sections and rated instructors more favorably than classmates using other criteria ( p     

Gray-level corner detection

Besides reducing thick responses to thin, the application of non-maximum suppression to digital gradient magnitudes also improves the form of the edge response histogram, making the choice of thresholds easier.     

Primacy/recency effects in student ratings of instruction: A reinterpretation of gain–loss effects.

Examined how the side effects of initial and final lecture quality on end-of-course student ratings can be predicted from seemingly unrelated gain–loss theory. Also investigated was the effect on ratings of student belief that the instructor will use midterm rating feedback to improve teaching. Using videotaped lectures in a 2?×?2?×?2 laboratory analog study, the present authors manipulated Lecture 1 (good, poor), Lecture 2 (good, poor), and whether 131 college students were told that feedback to the instructor about Lecture 1 would be used to improve teaching (yes, no). With Lecture 2 ratings as the principal measure, ratings varied moderately and inversely with Lecture 1 quality (negative primacy effect), greatly and directly with Lecture 2 quality (positive recency effect), and trivially with feedback. The primacy/recency findings confirm gain–loss predictions and illustrate how gain–loss theory can be interpreted as primacy/recency effects. Implications for expectancy research and field research on instructors using midterm ratings to improve instruction in the final portion of the course are discussed. (32 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Faecal pollution source identification in an urbanising catchment using antibiotic resistance profiling, discriminant analysis and partial least squares regression

Increasing urbanisation and changes in land use lead to adverse impacts on the quality of natural water resources. The specific sources of contamination are often difficult to identify using conventional water quality monitoring techniques. This acts as a significant constraint to the development of appropriate management techniques to protect natural water resources. Consequently, alternative means of identifying pollutant sources and their locality are necessary. In this study, Antibiotic Resistance Patterns (ARP) were established for a library of 1005 known Escherichia coli source isolates obtained from human and non-human (domesticated animals, livestock and wild) sources in an urbanising catchment in Queensland State, Australia. Discriminant Analysis (DA) was used to differentiate between the ARP of source isolates and to identify the sources of faecal contamination. Partial Least Square (PLS) regression was then utilised on identified human source isolates to correlate their locality with specified sampling locations within the catchment. The resulting ARP DA indicated that a majority of the faecal contamination in the rural areas was non-human. However, the percentage of human isolates increased significantly in urbanised areas using onsite systems for wastewater treatment. The PLS regression was able to develop predictive models which indicated a high correlation of human source isolates from the urban area. The study results confirm the feasibility of using ARP for source tracking faecal contamination in surface waters, as well as predicting their point of origin.     

Review of the mathematical background to the development of realistic load histories for fatigue testing relevant to tubular structures in the North Sea

Following the discovery of oil and gas, fixed welded tubular steel platforms were first installed in the North Sea in 1966. They are subjected to significant fatigue loads due to wave action. A report on proposed standard load histories was published in 1976. These were based on theoretical calculations. In 1979, increasing interest led to the formation of the Wave Action Standards History (WASH) Working Group. Strain gauge data for platforms in the North Sea were made available to the Working Group so later standard load histories were based on service data rather than theoretical calculations. Mathematical techniques used are reviewed, and some load histories are described as case studies. A framework was developed that could be used to formulate a particular standard load history but left open the option of incorporating alternative features, with relatively little additional work.     

The relative positions of alanine residues in the hydrophobic core control the formation of two-stranded or four-stranded {alpha}-helical coiled-coils

The objective of this study was to investigate the positionaleffect of hydrophobic interactions in the -helical interfacein controlling the formation of two-stranded and four-strandedcoiled-coils. Two disulfide-bridged antiparallel coiled-coilswere designed which differ only in the position of a singleAla residue in the middle heptad: in peptide 2H the Ala residuesare in register (in the same rung), while in peptide 4H theyare not. Data from size-exclusion chromatography and sedimentationequilibrium experiments showed that under benign conditionspeptides 2H and 4H were two-stranded and four-stranded coiled-coilsrespectively. These results, in conjunction with molecular modelingstudies, suggest that when four Ala residues are in the sameplane of a potential four-stranded coiled-coil, the small sidechains of Ala would create a large cavity in the hydrophobicinterface of the potential four-stranded structure which isdestabilizing and favors the two-stranded, disulfide-bridgedcoiled-coil. In contrast, an alternating Leu-Ala hydrophobicpacking in the two planes distributes the potential cavity overa larger region, which may be partially filled by minor adjustmentsof the neighboring Leu side chains. As a result, there is stillsufficient hydrophobic contact to maintain the four-strandedstructure.     

Predicting phytoplankton composition in the River Thames,England

Phytoplankton were sampled fortnightly in summer and monthly in winter for 33 months to determine temporal and spatial variations in taxonomic structure and relate these to the physical and chemical environment. Using canonical correspondence analysis, environmental variables selected by stepwise regression were found to be correlated with the major variable(s) determining phytoplankton composition. An improved proportion of explained variance was achieved by classifying data into three seasonal subsets. The highest percentage of explained variance in phytoplankton composition was achieved for the months March to May (36·5%), the lowest variance explained was for the period June to September (28·6%). Within each season, general linear modelling was used to predict taxa responses to variations in particular environmental variables. Taxa responses to discharge are presented as examples for determining river management policies. The rationale of conceptual models and the empirical models used for this study are discussed. © 1997 John Wiley & Sons, Ltd.     

Extraction of parameters and their error distributions from cyclic voltammograms using bootstrap resampling enhanced by solution maps: Computational study

The conventional determination of model parameter errors in least-squares regression of experimental cyclic voltammetric data assumes validity of local approximations (e.g., linearization) in the parameter space and normal distributions of the data and parameter errors. Such assumptions may not always be satisfied in practice. Bootstrap resampling techniques present a more universally applicable approach to error estimation, which until now has not been used in cyclic voltammetric studies, owing to the high costs of the required voltammogram simulations. We demonstrate that the burden of computing voltammograms can be significantly reduced by the use of high-dimensional model representation (HDMR) solution mapping techniques, thereby making it feasible to apply the bootstrap data analysis in cyclic voltammetry. We perform computational experiments with bootstrap resampling, enhanced by HDMR maps, for a typical cyclic voltammetric model (i.e., the Eqrev Cirr Eqrev reaction mechanism at a planar macroelectrode under semi-infinite, pure diffusion transport conditions). The experiments reveal that the bootstrap distributions of the estimated parameters provide a satisfactory quantification of the parameter errors and can also be used for detecting statistical correlations of the parameters.