Similarity not favourability : the role of donor prototypes in predicting willingness to donate organs while living

Using an extended Prototype/Willingness Model, we examined the predictors of willingness to donate an organ to a partner/family member and a stranger while living. A questionnaire assessed university students’ (N = 284) attitudes, subjective norm, prototype favourability, prototype similarity, moral norm, and willingness to donate organs in each recipient scenario. All variables, except prototype favourability, predicted willingness to donate organs in both situations. Future strategies should emphasise perceived approval from important others for living donation, the consistency of living donation with one’s own morals, and encourage perceptions of similarity between oneself and living donors to increase acceptance of living donation.

Predicting driver's hypovigilance on monotonous roads: literature review.

Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Particularly, highway design reduces the driving task mainly to a lane-keeping one. It contributes to hypovigilance and road crashes as drivers are often not aware that their driving behaviour is impaired. Monotony increases fatigue, however, the fatigue community has mainly focused on endogenous factors leading to fatigue such as sleep deprivation. This paper focuses on the exogenous factor monotony which contributes to hypovigilance. Objective measurements of the effects of monotonous driving conditions on the driver and the vehicle's dynamics is systematically reviewed with the aim of justifying the relevance of the need for a mathematical framework that could predict hypovigilance in real-time. Although electroencephalography (EEG) is one of the most reliable measures of vigilance, it is obtrusive. This suggests to predict from observable variables the time when the driver is hypovigilant. Outlined is a vision for future research in the modelling of driver vigilance decrement due to monotonous driving conditions. A mathematical model for predicting drivers’ hypovigilance using information like lane positioning, steering wheel movements and eye blinks is provided. Such a modelling of driver vigilance should enable the future development of an in-vehicle device that detects driver hypovigilance in advance, thus offering the potential to enhance road safety and prevent road crashes.

Modulation of the SHBG signalling axis

Sex hormone-binding globulin (SHBG) is a homodimeric plasma glycoprotein that is the major sex steroid carrier-protein in the bloodstream and functions also as a key regulator of steroid bioavailability within target tissues, such as the prostate. Additionally, SHBG binds to prostatic cell membranes via the putative and unidentified SHBG receptor (RSHBG), activating a signal transduction pathway implicated in stimulating both proliferation and expression of prostate specific antigen (PSA) in prostate cell lines in vitro. A yeast-two hybrid assay suggested an interaction between SHBG and kallikrein-related protease (KLK) 4, which is a serine protease implicated in the progression of prostate cancer. The potential interaction between these two proteins was investigated in this PhD thesis to determine whether SHBG is a proteolytic substrate of KLK4 and other members of the KLK family including KLK3/PSA, KLK7 and KLK14. Furthermore, the effects from SHBG proteolytic degradation on SHBG-regulated steroid bioavailability and the activation of the putative RSHBG signal transduction pathway were examined in the LNCaP prostate cancer cell line. SHBG was found to be a proteolytic substrate of the trypsin-like KLK4 and KLK14 in vitro, yielding several proteolysis fragments. Both chymotrypsin-like PSA and KLK7 displayed insignificant proteolytic activity against SHBG. The kinetic parameters of SHBG proteolysis by KLK4 and KLK14 demonstrate a strong enzyme-substrate binding capacity, possessing a Km of 1.2 ± 0.7 µM and 2.1 ± 0.6 µM respectively. The catalytic efficiencies (kcat/Km) of KLK4 and KLK14 proteolysis of SHBG were 1.6 x 104 M-1s-1 and 3.8 x 104 M-1s-1 respectively, which were comparable to parameters previously reported for peptide substrates. N-terminal sequencing of the fragments revealed cleavage near the junction of the N- and C-terminal laminin globulin-like (G-like) domains of SHBG, resulting in the division of the two globulins and ultimately the full degradation of these fragments by KLK4 and KLK14 over time. Proteolytic fragments that may retain steroid binding were rapidly degraded by both proteases, while fragments containing residues beyond the steroid binding pocket were less degraded over the same period of time. Degradation of SHBG was inhibited by the divalent metal cations calcium and zinc for KLK4, and calcium, zinc and magnesium for KLK14. The human secreted serine protease inhibitors (serpins), α1-antitrypsin and α2-antiplasmin, inhibited KLK4 and KLK14 proteolysis of SHBG; α1-antichymotrypsin inhibited KLK4 but not KLK14 activity. The inhibition by these serpins was comparable and in some cases more effective than general trypsin protease inhibitors such as aprotinin and phenylmethanesulfonyl fluoride (PMSF). The binding of 5α-dihydrotestosterone (DHT) to SHBG modulated interactions with KLK4 and KLK14. Steroid-free SHBG was more readily digested by both enzymes than DHT-bound SHBG. Moreover, a binding interaction exists between SHBG and pro-KLK4 and pro-KLK14, with DHT strengthening the binding to pro-KLK4 only. The inhibition of androgen uptake by cultured prostate cancer cells, mediated by SHBG steroid-binding, was examined to assess whether SHBG proteolysis by KLK4 and KLK14 modulated this process. Proteolytic digestion eliminated the ability of SHBG to inhibit the uptake of DHT from conditioned media into LNCaP cells. Therefore, the proteolysis of SHBG by KLK4 and KLK14 increased steroid bioavailability in vitro, leading to an increased uptake of androgens by prostate cancer cells. Interestingly, different transcriptional responses of PSA and KLK2, which are androgen-regulated genes, to DHT-bounsd SHBG treatment were observed between low and high passage number LNCaP cells (lpLNCaP and hpLNCaP respectively). HpLNCaP cells treated with DHT-bound SHBG demonstrated a significant synergistic upregulation of PSA and KLK2 above DHT or SHBG treatment alone, which is similar to previously reported downstream responses from RSHBG-mediated signaling activation. As this result was not seen in lpLNCaP cells, only hpLNCaP cells were further investigated to examine the modulation of potential RSHBG activity by KLK4 and KLK14 proteolysis of SHBG. Contrary to reported results, no increase in intracellular cAMP was observed in hpLNCaP cells when treated with SHBG in the presence and absence of either DHT or estradiol. As a result, the modulation of RSHBG-mediated signaling activation could not be determined. Finally, the identification of the RSHBG from both breast (MCF-7) and prostate cancer (LNCaP) cell lines was attempted. Fluorescently labeled peptides corresponding to the putative receptor binding domain (RBD) of SHBG were shown to be internalized by MCF-7 cells. Crosslinking of the RBD peptide to the cell surfaces of both MCF-7 and LNCaP cells, demonstrated the interaction of the peptide with several targets. These targets were then captured using RBD peptides synthesized onto a hydrophilic scaffold and analysed by mass spectrometry. The samples captured by the RBD peptide returned statistically significantly matches for cytokeratin 8, 18 and 19 as well as microtubule-actin crosslinking factor 1, which may indicate a novel interaction between SHBG and these proteins, but ultimately failed to detect a membrane receptor potentially responsible for the putative RSHBG-mediated signaling. This PhD project has reported the proteolytic processing of SHBG by two members of the kallikrein family, KLK4 and KLK14. The effect of SHBG proteolysis by KLK4 and KLK14 on RSHBG-mediated signaling activation was unable to be determined as the reported signal transduction pathway was not activated after treatment with SHBG, in combination with either DHT or estradiol. However, the digestion of SHBG by these two proteases positively regulated androgen bioavailability to prostate cancer cells in vitro. The increased uptake of androgens is deleterious in prostate cancer due to the promotion of proliferation, metastasis, invasion and the inhibition of apoptosis. The increased bioavailability of androgens, from SHBG proteolysis by KLK4 and KLK14, may therefore promote both carcinogenesis and progression of prostate cancer. Finally, this information may contribute to the development of therapeutic treatment strategies for prostate cancer by inhibiting the proteolysis of SHBG, by KLK4 and KLK14, to prevent the increased uptake of androgens by hormone-dependent cancerous tissues.

Predicting query reformulation during web searching

This paper reports results from a study in which we automatically classified the query reformulation patterns for 964,780 Web searching sessions (composed of 1,523,072 queries) in order to predict what the next query reformulation would be. We employed an n-gram modeling approach to describe the probability of searchers transitioning from one query reformulation state to another and predict their next state. We developed first, second, third, and fourth order models and evaluated each model for accuracy of prediction. Findings show that Reformulation and Assistance account for approximately 45 percent of all query reformulations. Searchers seem to seek system searching assistant early in the session or after a content change. The results of our evaluations show that the first and second order models provided the best predictability, between 28 and 40 percent overall, and higher than 70 percent for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance in real time.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Ghrelin gene-related peptides : multifunctional endocrine/autocrine modulators in health and disease

Ghrelin is a multi-functional peptide hormone which affects various processes including growth hormone and insulin release, appetite regulation, gut motility, metabolism and cancer cell proliferation. Ghrelin is produced in the stomach and in other normal and pathological cell types. It may act as an endocrine or autocrine/paracrine factor. The ghrelin gene encodes a precursor protein, preproghrelin, from which ghrelin and other potentially active peptides are derived by alternative mRNA splicing and/or proteolytic processing. The metabolic role of the peptide obestatin, derived from the preproghrelin C-terminal region, is controversial. However, it has direct effects on cancer cell proliferation. The regulation of ghrelin expression and the mechanisms through which the peptide products arise are unclear. We have recently re-examined the organisation of the ghrelin gene and identified several novel exons and transcripts. One transcript, which lacks the ghrelin-coding region of preproghrelin, contains the coding sequence of obestatin. Furthermore, we have identified an overlapping gene on the antisense strand of ghrelin, GHRLOS, which generates transcripts that may function as non-coding regulatory RNAs or code for novel, short bioactive peptides. The identification of these novel ghrelin-gene related transcripts and peptides raises critical questions regarding their physiological function and their role in obesity, diabetes and cancer.

Examining the use of bid information in predicting the contractor’s performance

Purpose – The purpose of this paper is to examine the use of bid information, including both price and non-price factors in predicting the bidder’s performance. Design/methodology/approach – The practice of the industry was first reviewed. Data on bid evaluation and performance records of the successful bids were then obtained from the Hong Kong Housing Department, the largest housing provider in Hong Kong. This was followed by the development of a radial basis function (RBF) neural network based performance prediction model. Findings – It is found that public clients are more conscientious and include non-price factors in their bid evaluation equations. With the input variables used the information is available at the time of the bid and the output variable is the project performance score recorded during work in progress achieved by the successful bidder. It was found that past project performance score is the most sensitive input variable in predicting future performance. Research limitations/implications – The paper shows the inadequacy of using price alone for bid award criterion. The need for a systemic performance evaluation is also highlighted, as this information is highly instrumental for subsequent bid evaluations. The caveat for this study is that the prediction model was developed based on data obtained from one single source. Originality/value – The value of the paper is in the use of an RBF neural network as the prediction tool because it can model non-linear function. This capability avoids tedious ‘‘trial and error’’ in deciding the number of hidden layers to be used in the network model. Keywords Hong Kong, Construction industry, Neural nets, Modelling, Bid offer spreads Paper type Research paper

Predicting project performance through neural networks

Successful project delivery of construction projects depends on many factors. With regard to the construction of a facility, selecting a competent contractor for the job is paramount. As such, various approaches have been advanced to facilitate tender award decisions. Essentially, this type of decision involves the prediction of a bidderÕs performance based on information available at the tender stage. A neural network based prediction model was developed and presented in this paper. Project data for the study were obtained from the Hong Kong Housing Department. Information from the tender reports was used as input variables and performance records of the successful bidder during construction were used as output variables. It was found that the networks for the prediction of performance scores for Works gave the highest hit rate. In addition, the two most sensitive input variables toward such prediction are ‘‘Difference between Estimate’’ and ‘‘Difference between the next closest bid’’. Both input variables are price related, thus suggesting the importance of tender sufficiency for the assurance of quality production.

Establishment of a mouse model of colitis and its use to evaluate the anti-inflammatory effects of two ghrelin peptides

Ghrelin is a gut-brain peptide hormone that induces appetite, stimulates the release of growth hormone, and has recently been shown to ameliorate inflammation. Recent studies have suggested that ghrelin may play a potential role in inflammation-related diseases such as inflammatory bowel diseases (IBD). A previous study with ghrelin in the TNBS mouse model of colitis demonstrated that ghrelin treatment decreased the clinical severity of colitis and inflammation and prevented the recurrence of disease. Ghrelin may be acting at the immunological and epithelial level as the ghrelin receptor (GHSR) is expressed by immune cells and intestinal epithelial cells. The current project investigated the effect of ghrelin in a different mouse model of colitis using dextran sodium sulphate (DSS) – a luminal toxin. Two molecular weight forms of DSS were used as they give differing effects (5kDa and 40kDa). Ghrelin treatment significantly improved clinical colitis scores (p=0.012) in the C57BL/6 mouse strain with colitis induced by 2% DSS (5kDa). Treatment with ghrelin suppressed colitis in the proximal colon as indicated by reduced accumulative histopathology scores (p=0.03). Whilst there was a trend toward reduced scores in the mid and distal colon in these mice this did not reach significance. Ghrelin did not affect histopathology scores in the 40kDa model. There was no significant effect on the number of regulatory T cells or TNF-α secretion from cultured lymph node cells from these mice. The discovery of C-terminal ghrelin peptides, for example, obestatin and the peptide derived from exon 4 deleted proghrelin (Δ4 preproghrelin peptide) have raised questions regarding their potential role in biological functions. The current project investigated the effect of Δ4 peptide in the DSS model of colitis however no significant suppression of colitis was observed. In vitro epithelial wound healing assays were also undertaken to determine the effect of ghrelin on intestinal epithelial cell migration. Ghrelin did not significantly improve wound healing in these assays. In conclusion, ghrelin treatment displays a mild anti-inflammatory effect in the 5kDa DSS model. The potential mechanisms behind this effect and the disparity between these results and those published previously will be discussed.

Role of self-efficacy in predicting outcomes from a programme for controlled drinking

Predicted the outcomes of 40 men and 20 women who attended a controlled drinking program in a general hospital. Measures included a behavioral interview, the Alcohol Dependence Scale (ADS), the Severity of Alcohol Dependence Questionnaire (SADQ) described by T. Stockwell et al (1979), and a problem drinking self-efficacy scale (PDSES). Substantial reductions in drinking appeared after the program and appeared to be sustained over a 6-mo follow-up. Intake dropped from 11.3 drinks per day to 2.2 drinks during follow-up. Drinking history and alcohol dependence (as measured by the SADQ, but not the ADS) were significant predictors of alcohol consumption during follow-up. Predictive utility of the PDSES was confirmed. PDSES administered at the end of the program significantly predicted alcohol consumption over the next 6 mo.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing

Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush-tailed rock-wallaby petrogale penicillata

Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.