Application of central composite rotatable design to modelling the effect of some operating variables on the performance of the three-product cyclone

The central composite rotatable design (CCRD) was used to design an experimental program to model the effects of inlet pressure, feed density, and length and diameter of the inner vortex finder on the operational performance of a 150-min three-product cyclone. The ranges of values of the variables used in the design were: inlet pressure: 80-130 kPa, feed density: 30 60%; length of IVF below the OVF: 50-585 mm; diameter of IVF: 35-50 mm. A total of 30 tests were conducted, which is 51 less; an that required for a three-level full factorial design. Because the model allows confident performance prediction by interpolation over the range of data in the database, it was used to construct response surface graphs to describe the effects of the variables on the performance of the three-product cyclone. To obtain a simple and yet a realistic model, it was refitted using only the variable terms that are significant at greater than or equal to 90% confidence level. Considering the selected operating variables, the resultant model is significant and predicts the experimental data well. (c) 2005 Elsevier B.V. All rights reserved.

Relationship between work performance and personality traits in Hong Kong organizational settings

Four hundred and thirty-seven employees from four Hong Kong organizations completed the Traditional Chinese versions of the Fifteen Factor Personality Questionnaire Plus (15FQ+) and the Cross-Cultural Personality Assessment Inventory (CPAI-2) (indigenous scales) and provided objective and memory-based recent performance appraisal scores. A number of significant bivariate correlations were found between personality and performance scores. Hierarchical multiple regression analyses revealed that a number of the scales from the 15FQ+ contributed to significantly predicting four of the performance competency dimensions, but that the CPAI-2 indigenous scales contributed no incremental validity in performance prediction over and above the 15FQ+. Results are discussed in the light of previous research and a call made for continued research to further develop and increase the reliability of the Chinese instruments used in the study and to enable generalization of the findings with confidence.

Evaluation of the indirect measures of rock brittleness and fracture toughness in rock cutting

Performance prediction models for partial face mechanical excavators, when developed in laboratory conditions, depend on relating the results of a set of rock property tests and indices to specific cutting energy (SE) for various rock types. There exist some studies in the literature aiming to correlate the geotechnical properties of intact rocks with the SE, especially for massive and widely jointed rock environments. However, those including direct and/or indirect measures of rock fracture parameters such as rock brittleness and fracture toughness, along with the other rock parameters expressing different aspects of rock behavior under drag tools (picks), are rather limited. With this study, it was aimed to investigate the relationships between the indirect measures of rock brittleness and fracture toughness and the SE depending on the results of a new and two previous linear rock cutting programmes. Relationships between the SE, rock strength parameters, and the rock index tests have also been investigated in this study. Sandstone samples taken from the different fields around Ankara, Turkey were used in the new testing programme. Detailed mineralogical analyses, petrographic studies, and rock mechanics and rock cutting tests were performed on these selected sandstone specimens. The assessment of rock cuttability was based on the SE. Three different brittleness indices (B1, B2, and B4) were calculated for sandstones samples, whereas a toughness index (T-i), being developed by Atkinson et al.(1), was employed to represent the indirect rock fracture toughness. The relationships between the SE and the large amounts of new data obtained from the mineralogical analyses, petrographic studies, rock mechanics, and linear rock cutting tests were evaluated by using bivariate correlation and curve fitting techniques, variance analysis, and Student's t-test. Rock cutting and rock property testing data that came from well-known studies of McFeat-Smith and Fowell(2) and Roxborough and Philips(3) have also been employed in statistical analyses together with the new data. Laboratory tests and subsequent analyses revealed that there were close correlations between the SE and B4 whereas no statistically significant correlation has been found between the SE and T-i. Uniaxial compressive and Brazilian tensile strengths and Shore scleroscope hardness of sandstones also exhibited strong relationships with the SE. NCB cone indenter test had the greatest influence on the SE among the other engineering properties of rocks, confirming the previous studies in rock cutting and mechanical excavation. Therefore, it was recommended to employ easy-to-use index tests of NCB cone indenter and Shore scleroscope in the estimation of laboratory SE of sandstones ranging from very low to high strengths in the absence of a rock cutting rig to measure it until the easy-to-use universal measures of the rock brittleness and especially the rock fracture toughness, being an intrinsic rock property, are developed.

Moderating effect of ear preference on personality in the prediction of sales performance

This study examined the relationship between ear preference, personality, and performance ratings on 203 telesales staff. Social desirability scores were a significant predictor of two relatively independent sets of supervisor ratings (actual performance and developmental potential) in interaction with ear preference. It was found that the social desirability scale was a significant positive predictor for staff preferring a right ear headset, but a negative predictor for staff preferring a left ear headset. These results were interpreted in terms of different strategies used to achieve successful sales.

Hemispheric asymmetry of neuroticism in the prediction of disinhibited work performance

Disinhibition is usually defined as a combination of high extraversion and high neuroticism or high extraversion and low neuroticism. The hypothesis that neuroticism interacts with aural preference (preferred-ear for listening) in the prediction of everyday types of disinhibited behaviour is tested. The importance of aural preference rests on the assumption that it is a readily available proxy measure of contra-hemispheric preference such that a left aural preference is indicative of right hemispheric preference and vice versa. Since the left hemisphere acts to initiate approach behaviour, the hypothesis investigates a model in which preference for the left hemisphere, together with high neuroticism, provides an alternative mechanism of disinhibition. This study provides evidence of the mechanism in the predicdon of disinhibited telesales performance.

The effects of work control and job demands on employee adjustment and work performance

The present study examined the effects of work control and job demands on employee adjustment and work performance using a multidimensional measure of work control (assessing levels of task control, decision control and work scheduling control). It was proposed that the negative effects of job demands and employee adjustment would be moderated by high levels of task control. It was also proposed that there would be evidence of main effects of both job demands and work control (particularly task-related levels of control) on employee adjustment. To test these predictions, a study of 135 university employees holding administrative positions was undertaken. Methodological improvements over previous research included the use of both self-reported adjustment measures and supervisor ratings of work performance as outcome variables, and the assessment of the predictor and outcome measures at different points in time (self-reported adjustment was assessed at both Times 1 and 2). The results revealed some support for the proposal that the effects of job demands would be buffered by high levels of task control, but not more peripheral aspects of work control. There were also significant main effects of task control on job satisfaction.

Evaluation of a new bioelectrical impedance instrument for the prediction of body cell mass independently of height or weight

The objective of the present study was to evaluate the performance of a new bioelectrical impedance instrument, the Soft Tissue Analyzer (STA), which predicts a subject's body composition. A cross-sectional population study in which the impedance of 205 healthy adult subjects was measured using the STA. Extracellular water (ECW) volume (as a percentage of total body water, TBW) and fat-free mass (FFM) were predicted by both the STA and a compartmental model, and compared according to correlation and limits of agreement analysis, with the equivalent data obtained by independent reference methods of measurement (TBW measured by D2O dilution, and FFM measured by dual-energy X-ray absorptiometry). There was a small (2.0 kg) but significant (P < 0.02) difference in mean FFM predicted by the STA, compared with the reference technique in the males, but not in the females (-0.4 kg) or in the combined group (0.8 kg). Both methods were highly correlated. Similarly, small but significant differences for predicted mean ECW volume were observed. The limits of agreement for FFM and ECW were -7.5-9.9 and -4.1-3.0 kg, respectively. Both FFM and ECW (as a percentage of TBW) are well predicted by the STA on a population basis, but the magnitude of the limits of agreement with reference methods may preclude its usefulness for predicting body composition in an individual. In addition, the theoretical basis of an impedance method that does not include a measure of conductor length requires further validation. (C) Elsevier Science Inc. 2000.

The role of cognitive vulnerability and stress in the prediction of postpartum depressive symptomatology

Objectives. The present study was designed to test the diathesis-stress components of Beck's cognitive theory of depression and the reformulated learned helplessness model of depression in the prediction of postpartum depressive symptomatology. Design and methods. The research used a two-wave longitudinal design-data were collected from 65 primiparous women during their third trimester of pregnancy and then 6 weeks after the birth. Cognitive vulnerability and initial depressive symptomatology were assessed at Time 1, whereas stress and postpartum depressive symptomatology were assessed at Time 2. Results. There was some support for the diathesis-stress component of Beck's cognitive theory, to the extent that the negative relationship between both general and maternal-specific dysfunctional attitudes associated with performance evaluation and Time 2 depressive symptomatology was strongest for women who reported high levels of parental stress. In a similar vein, the effects of dysfunctional attitudes (general and maternal-specific) associated with performance evaluation and need for approval (general measure only) on partner ratings of emotional distress were evident only among those women whose infants were rated as being temperamentally difficult. Conclusion. There was no support for the diathesis-stress component of the reformulated learned helplessness model of depression; however, there was some support for the diathesis-stress component of Beck's cognitive theory.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Larval activity levels and delayed metamorphosis affect post-larval performance in the colonial, ascidian Diplosoma listerianum

It is becoming widely recognized that extending the larval period of marine invertebrates, especially of species with non-feeding larvae, can affect post-larval performance. As these carry-over effects are presumed to be caused by the depletion of larval energy reserves, we predicted that the level of larval activity would also affect post-larval performance. This prediction was tested with the cosmopolitan colonial ascidian Diplosoma listerianum in field experiments in southern Australia. Diplosoma larvae, brooded in the parent colony, are competent to settle immediately after spawning, and they remain competent to metamorphose for > 15 h. Some larvae were induced to metamorphose 0 to 6 h after release, whilst others were induced to swim actively by alternating light and dark periods for up to 3 h prior to metamorphosis. Juvenile colonies were then transplanted to a subtidal field site in Port Phillip Bay and left to grow for up to 3 wk. Extending the larval period and increasing the amount of swimming both produced carry-over effects on post-larval performance. Colonies survived at different rates among experiments, but larval experience did not affect survival rates. Delays in metamorphosis and increased swimming activity did, however, reduce colony growth rates dramatically, resulting in 50% fewer zooids per colony. Moreover, such colonies produced initial zooids with smaller feeding structures, with the width of branchial baskets reduced by 10 to 15%. These differences in branchial basket size persisted and were still apparent in newly budded zooids 3 wk after metamorphosis. Our results suggest that, for D. listerianum, larval maintenance, swimming, and metamorphosis all use energy from a common pool, and increases in the allocation to maintenance or swimming come at the expense of post-larval performance.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

PREDBALB/c: a system for the prediction of peptide binding to H2(d) molecules, a haplotype of the BALB/c mouse

PREDBALB/c is a computational system that predicts peptides binding to the major histocompatibility complex-2 (H2(d)) of the BALB/c mouse, an important laboratory model organism. The predictions include the complete set of H2(d) class I ( H2-K-d, H2-L-d and H2-D-d) and class II (I-E-d and I-A(d)) molecules. The prediction system utilizes quantitative matrices, which were rigorously validated using experimentally determined binders and non-binders and also by in vivo studies using viral proteins. The prediction performance of PREDBALB/c is of very high accuracy. To our knowledge, this is the first online server for the prediction of peptides binding to a complete set of major histocompatibility complex molecules in a model organism (H2(d) haplotype). PREDBALB/c is available at http://antigen.i2r.a-star.edu.sg/predBalbc/.

Axial Young's modulus prediction of single-walled carbon nanotube arrays with diameters from nanometer to meter scales

Based on a self-similar array model, we systematically investigated the axial Young's modulus (Y-axis) of single-walled carbon nanotube (SWNT) arrays with diameters from nanometer to meter scales by an analytical approach. The results show that the Y-axis of SWNT arrays decreases dramatically with the increases of their hierarchy number (s) and is not sensitive to the specific size and constitution when s is the same, and the specific Young's modulus Y-axis(s) is independent of the packing configuration of SWNTs. Our calculations also show that the Y-axis of SWNT arrays with diameters of several micrometers is close to that of commercial high performance carbon fibers (CFs), but the Y-axis(s) of SWNT arrays is much better than that of high performance CFs. (C) 2005 American Institute of Physics.