Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state. J Appl Physiol 112: 1805-1813, 2012. First published March 1, 2012; doi:10.1152/japplphysiol.00170.2012.- We made sex-based comparisons of rates of myofibrillar protein synthesis (MPS) and anabolic signaling after a single bout of high-intensity resistance exercise. Eight men (20 ± 10 yr, BMI = 24.3 ± 2.4) and eight women (22 ± 1.8 yr, BMI = 23.0 ± 1.9) underwent primed constant infusions of L-[ring-13C6]phenylalanine on consecutive days with serial muscle biopsies. Biopsies were taken from the vastus lateralis at rest and 1, 3, 5, 24, 26, and 28 h after exercise. Twenty-five grams of whey protein was ingested immediately and 26 h after exercise. We also measured exercise-induced serum testosterone because it is purported to contribute to increases in myofibrillar protein synthesis (MPS) postexercise and its absence has been hypothesized to attenuate adaptative responses to resistance exercise in women. The exercise-induced area under the testosterone curve was 45-fold greater in men than women in the early (1 h) recovery period following exercise (P < 0.001). MPS was elevated similarly in men and women (2.3- and 2.7-fold, respectively) 1-5 h postexercise and after protein ingestion following 24 h recovery. Phosphorylation of mTORSer2448 was elevated to a greater extent in men than women acutely after exercise (P = 0.003), whereas increased phosphorylation of p70S6K1Thr389 was not different between sexes. Androgen receptor content was greater in men (main effect for sex, P = 0.049). Atrogin-1 mRNA abundance was decreased after 5 h recovery in both men and women (P < 0.001), and MuRF-1 expression was elevated in men after protein ingestion following 24 h recovery (P = 0.003). These results demonstrate minor sex-based differences in signaling responses and no difference in the MPS response to resistance exercise in the fed state. Interestingly, our data demonstrate that exerciseinduced increases in MPS are dissociated from postexercise testosteronemia and that stimulation of MPS occurs effectively with low systemic testosterone concentrations in women.

The valuation accuracy of multiples in mergers and acquisitions, and their association with firm misvaluation

This study explores the accuracy and valuation implications of the application of a comprehensive list of equity multiples in the takeover context. Motivating the study is the prevalent use of equity multiples in practice, the observed long-run underperformance of acquirers following takeovers, and the scarcity of multiplesbased research in the merger and acquisition setting. In exploring the application of equity multiples in this context three research questions are addressed: (1) how accurate are equity multiples (RQ1); which equity multiples are more accurate in valuing the firm (RQ2); and which equity multiples are associated with greater misvaluation of the firm (RQ3). Following a comprehensive review of the extant multiples-based literature it is hypothesised that the accuracy of multiples in estimating stock market prices in the takeover context will rank as follows (from best to worst): (1) forecasted earnings multiples, (2) multiples closer to bottom line earnings, (3) multiples based on Net Cash Flow from Operations (NCFO) and trading revenue. The relative inaccuracies in multiples are expected to flow through to equity misvaluation (as measured by the ratio of estimated market capitalisation to residual income value, or P/V). Accordingly, it is hypothesised that greater overvaluation will be exhibited for multiples based on Trading Revenue, NCFO, Book Value (BV) and earnings before interest, tax, depreciation and amortisation (EBITDA) versus multiples based on bottom line earnings; and that multiples based on Intrinsic Value will display the least overvaluation. The hypotheses are tested using a sample of 147 acquirers and 129 targets involved in Australian takeover transactions announced between 1990 and 2005. The results show that first, the majority of computed multiples examined exhibit valuation errors within 30 percent of stock market values. Second, and consistent with expectations, the results provide support for the superiority of multiples based on forecasted earnings in valuing targets and acquirers engaged in takeover transactions. Although a gradual improvement in estimating stock market values is not entirely evident when moving down the Income Statement, historical earnings multiples perform better than multiples based on Trading Revenue or NCFO. Third, while multiples based on forecasted earnings have the highest valuation accuracy they, along with Trading Revenue multiples for targets, produce the most overvalued valuations for acquirers and targets. Consistent with predictions, greater overvaluation is exhibited for multiples based on Trading Revenue for targets, and NCFO and EBITDA for both acquirers and targets. Finally, as expected, multiples based Intrinsic Value (along with BV) are associated with the least overvaluation. Given the widespread usage of valuation multiples in takeover contexts these findings offer a unique insight into their relative effectiveness. Importantly, the findings add to the growing body of valuation accuracy literature, especially within Australia, and should assist market participants to better understand the relative accuracy and misvaluation consequences of various equity multiples used in takeover documentation and assist them in subsequent investment decision making.

Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

Gene expression analysis of diagnostic biopsies predicts pathological response to neoadjuvant chemoradiotherapy of esophageal cancer

OBJECTIVE: This study explored gene expression differences in predicting response to chemoradiotherapy in esophageal cancer. PURPOSE:: A major pathological response to neoadjuvant chemoradiation is observed in about 40% of esophageal cancer patients and is associated with favorable outcomes. However, patients with tumors of similar histology, differentiation, and stage can have vastly different responses to the same neoadjuvant therapy. This dichotomy may be due to differences in the molecular genetic environment of the tumor cells. BACKGROUND DATA: Diagnostic biopsies were obtained from a training cohort of esophageal cancer patients (13), and extracted RNA was hybridized to genome expression microarrays. The resulting gene expression data was verified by qRT-PCR. In a larger, independent validation cohort (27), we examined differential gene expression by qRT-PCR. The ability of differentially-regulated genes to predict response to therapy was assessed in a multivariate leave-one-out cross-validation model. RESULTS: Although 411 genes were differentially expressed between normal and tumor tissue, only 103 genes were altered between responder and non-responder tumor; and 67 genes differentially expressed >2-fold. These included genes previously reported in esophageal cancer and a number of novel genes. In the validation cohort, 8 of 12 selected genes were significantly different between the response groups. In the predictive model, 5 of 8 genes could predict response to therapy with 95% accuracy in a subset (74%) of patients. CONCLUSIONS: This study has identified a gene microarray pattern and a set of genes associated with response to neoadjuvant chemoradiation in esophageal cancer. The potential of these genes as biomarkers of response to treatment warrants further investigation. Copyright © 2009 by Lippincott Williams & Wilkins.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Accuracy of weight status perception in contemporary Australian children and adolescents

Aim: To explore weight status perception and its relation to actual weight status in a contemporary cohort of 5- to 17-year-old children and adolescents. Methods: Body mass index (BMI), derived from height and weight measurements, and perception of weight status (‘too thin’, ‘about right’ and ‘too fat’) were evaluated in 3043 participants from the Healthy Kids Queensland Survey. In children less than 12 years of age, weight status perception was obtained from the parents, whereas the adolescents self-reported their perceived weight status. Results: Compared with measured weight status by established BMI cut-offs, just over 20% of parents underestimated their child's weight status and only 1% overestimated. Adolescent boys were more likely to underestimate their weight status compared with girls (26.4% vs. 10.2%, P < 0.05) whereas adolescent girls were more likely to overestimate than underestimate (11.8% vs. 3.4%, P < 0.05). Underestimation was greater by parents of overweight children compared with those of obese children, but still less than 50% of parents identified their obese child as ‘too fat’. There was greater recognition of overweight status in the adolescents, with 83% of those who were obese reporting they were ‘too fat’. Conclusion: Whilst there was a high degree of accuracy of weight status perception in those of healthy weight, there was considerable underestimation of weight status, particularly by parents of children who were overweight or obese. Strategies are required that enable parents to identify what a healthy weight looks like and help them understand when intervention is needed to prevent further weight gain as the child gets older.

Agrobacterium-mediated transformation of Australian rice cultivars Jarrah and Amaroo using modified promoters and selectable markers

We report the first successful Agrobacterium-mediated transformation of Australian elite rice cultivars, Jarrah and Amaroo, using binary vectors with our improved promoters and selectable markers. Calli derived from mature embryos were used as target tissues. The binary vectors contained hph (encoding hygromycin resistance) or bar (encoding herbicide resistance) as the selectable marker gene and uidA (gus) or sgfpS65T as the reporter gene driven by different promoters. Use of Agrobacterium strain AGL1 carrying derivatives of an improved binary vector pWBVec8, wherein the CaMV35S driven hph gene is interrupted by the castor bean catalase 1 intron, produced a 4-fold higher number of independent transgenic lines compared to that produced with the use of strain EHA101 carrying the binary vector pIG121-Hm wherein the CaMV35S driven hph is intronless. The Ubiquitin promoter produced 30-fold higher β-glucuronidase (GUS) activity (derivatives of binary vector pWBVec8) in transgenic plants than the CaMV35S promoter (pIG121-Hm). The two modified SCSV promoters produced GUS activity comparable to that produced by the Ubiquitin promoter. Progeny analysis (R1) for hygromycin resistance and GUS activity with selected lines showed both Mendelian and non-Mendelian segregation. Lines showing very high levels of GUS activity in T0 showed a reduced level of GUS activity in their T1 progeny, while lines with moderate levels of GUS activity showed increased levels in T1 progeny. Stable heritable green fluorescent protein (GFP) expression was also observed in few transgenic plants produced with the binary vector pTO134 which had the CaMV35S promoter-driven selectable marker gene bar and a modified CaMV35S promoter-driven reporter gene sgfpS65T.

Ghrelin O-acyltransferase (GOAT) is expressed in prostate cancer tissues and cell lines and expression is differentially regulated in vitro by ghrelin

Background Ghrelin is a 28 amino acid peptide hormone that is expressed in the stomach and a range of peripheral tissues, where it frequently acts as an autocrine/paracrine growth factor. Ghrelin is modified by a unique acylation required for it to activate its cognate receptor, the growth hormone secretagogue receptor (GHSR), which mediates many of the actions of ghrelin. Recently, the enzyme responsible for adding the fatty acid residue (octanoyl/acyl group) to the third amino acid of ghrelin, GOAT (ghrelin O-acyltransferase), was identified. Methods We used cell culture, quantitative real-time reverse transcription (RT)-PCR and immunohistochemistry to demonstrate the expression of GOAT in prostate cancer cell lines and tissues from patients. Real-time RT-PCR was used to demonstrate the expression of prohormone convertase (PC)1/3, PC2 and furin in prostate cancer cell lines. Prostate-derived cell lines were treated with ghrelin and desacyl ghrelin and the effect on GOAT expression was measured using quantitative RT-PCR. Results We have demonstrated that GOAT mRNA and protein are expressed in the normal prostate and human prostate cancer tissue samples. The RWPE-1 and RWPE-2 normal prostate-derived cell lines and the LNCaP, DU145, and PC3 prostate cancer cell lines express GOAT and at least one other enzyme that is necessary to produce mature, acylated ghrelin from proghrelin (PC1/3, PC2 or furin). Finally, ghrelin, but not desacyl ghrelin (unacylated ghrelin), can directly regulate the expression of GOAT in the RWPE-1 normal prostate derived cell line and the PC3 prostate cancer cell line. Ghrelin treatment (100nM) for 6 hours significantly decreased GOAT mRNA expression two-fold (P < 0.05) in the PC3 prostate cancer cell line, however, ghrelin did not regulate GOAT expression in the DU145 and LNCaP prostate cancer cell lines. Conclusions This study demonstrates that GOAT is expressed in prostate cancer specimens and cell lines. Ghrelin regulates GOAT expression, however, this is likely to be cell-type specific. The expression of GOAT in prostate cancer supports the hypothesis that the ghrelin axis has autocrine/paracrine roles. We propose that the RWPE-1 prostate cell line and the PC3 prostate cancer cell line may be useful for investigating GOAT regulation and function.

Association between xenobiotic gene polymorphisms and non-Hodgkin's lymphoma risk

The last four decades have seen a significant increase in the incidence of non-Hodgkin's lymphoma (NHL) as a possible result of increasing environmental carcinogen exposure, particularly pesticides and solvents. Based on the increasing evidence for an association between carcinogen exposure-related cancer risk and xenobiotic gene polymorphisms, we have undertaken a case-control study of xenobiotic gene polymorphisms in individuals with a diagnosis of NHL. Polymorphisms of six xenobiotic genes (CYP1A1, GSTT1, GSTM1, PON1, NAT1, NAT2) were characterized in 169 individuals with NHL and 205 normal controls using polymerase chain reaction-based methods. Polymorphic frequencies were compared using Fisher's exact tests, and odds ratios for NHL risk were calculated. Among the NHL group, the incidence of GSTT1 null and PON1 BB genotypes were significantly increased compared with controls, 34% vs 14%, and 24% vs 11% respectively. Adjusted odds ratios calculated from multivariate analyses demonstrated that GSTT1 null conferred a fourfold increase in NHL risk (OR = 4.27; 95% CI, 2.40-7.61, P < 0.001) and PON1 BB a 2.9-fold increase (OR = 2.92; 95% CI, 1.49-5.72, P = 0.002). Furthermore, GSTT1 null combined with PON1 BB or GSTM1 null conferred an additional risk of NHL. This is the first time that a PON1 gene polymorphism has been shown to be associated with cancer risk. We conclude that the two polymorphisms, GSTT1 null and PON1 BB, are common genetic traits that pose low individual risk but may be important determinants of overall population NHL risk, particularly among groups exposed to NHL-related carcinogens.

Efficient top-k retrieval with signatures

This paper describes a new method of indexing and searching large binary signature collections to efficiently find similar signatures, addressing the scalability problem in signature search. Signatures offer efficient computation with acceptable measure of similarity in numerous applications. However, performing a complete search with a given search argument (a signature) requires a Hamming distance calculation against every signature in the collection. This quickly becomes excessive when dealing with large collections, presenting issues of scalability that limit their applicability. Our method efficiently finds similar signatures in very large collections, trading memory use and precision for greatly improved search speed. Experimental results demonstrate that our approach is capable of finding a set of nearest signatures to a given search argument with a high degree of speed and fidelity.

Higher-order non-linear analysis of steel structures. Part I : elastic second-order formulation

This paper presents a higher-order beam-column formulation that can capture the geometrically non-linear behaviour of steel framed structures which contain a multiplicity of slender members. Despite advances in computational frame software, analyses of large frames can still be problematic from a numerical standpoint and so the intent of the paper is to fulfil a need for versatile, reliable and efficient non-linear analysis of general steel framed structures with very many members. Following a comprehensive review of numerical frame analysis techniques, a fourth-order element is derived and implemented in an updated Lagrangian formulation, and it is able to predict flexural buckling, snap-through buckling and large displacement post-buckling behaviour of typical structures whose responses have been reported by independent researchers. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. The higher-order element forms a basis for augmenting the geometrically non-linear approach with material non-linearity through the refined plastic hinge methodology described in the companion paper.

Higher-order non-linear analysis of steel structures. Part II : refined plastic hinge formulation

In the companion paper, a fourth-order element formulation in an updated Lagrangian formulation was presented to handle geometric non-linearities. The formulation of the present paper extends this to include material non-linearity by proposing a refined plastic hinge approach to analyse large steel framed structures with many members, for which contemporary algorithms based on the plastic zone approach can be problematic computationally. This concept is an advancement of conventional plastic hinge approaches, as the refined plastic hinge technique allows for gradual yielding, being recognized as distributed plasticity across the element section, a condition of full plasticity, as well as including strain hardening. It is founded on interaction yield surfaces specified analytically in terms of force resultants, and achieves accurate and rapid convergence for large frames for which geometric and material non-linearity are significant. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. In addition to the numerical efficiency, the present versatile approach is able to capture different kinds of material and geometric non-linearities on general applications of steel structures, and thereby it offers an efficacious and accurate means of assessing non-linear behaviour of the structures for engineering practice.