155 resultados para Pan-Germanism


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This paper presents an approach for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera’s optical center and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. Previous methods for auto-calibration of cameras based on pure rotations fail to work in these two degenerate cases. In addition, our approach includes a modified RANdom SAmple Consensus (RANSAC) algorithm, as well as improved integration of the radial distortion coefficient in the computation of inter-image homographies. We show that these modifications are able to increase the overall efficiency, reliability and accuracy of the homography computation and calibration procedure using both synthetic and real image sequences

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Pan et al. claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al. contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.

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Findings from an online survey conducted by Queensland University of Technology (QUT) shows that Australia is suffering from a lack of data reflecting trip generation for use in Traffic Impact Assessments (TIAs). Current independent variables for trip generation estimation are not able to create robust outcomes as well. It is also challenging to account for the impact of the new development on public and active transport as well as the effect of trip chaining behaviour in Australian TIA studies. With this background in mind, research is being implemented by QUT to find a new approach developing a combined model of trip generation and mode choice with consideration of trip chaining effects. It is expected that the model will provide transferable outcomes as it is developed based on socio-demographic parameters. Child Care Centres within the Brisbane area have been nominated for model development. At the time, the project is in the data collection phase. Findings from the pilot survey associated with capturing trip chaining and mode choice information reveal that applying questionnaire is able to capture required information in an acceptable level. The result also reveals that several centres within an area should be surveyed in order to provide sufficient data for trip chaining and modal split analysis.

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Dhaka, the capital of Bangladesh, is facing severe traffic congestion. Owing to the flaws in past land use and transport planning decisions, uncontrolled population growth and urbanization, Dhaka’s traffic condition is worsening. Road space is widely regarded in the literature as a utility, so a common view of transport economists is that its usage ought to be charged. Road pricing policy has proven to be effective in managing travel demand, in order to reduce traffic congestion from road networks in a number of cities including London, Stockholm and Singapore. Road pricing as an economic mechanism to manage travel demand can be more effective and user-friendly when revenue is hypothecated into supply alternatives such as improvements to the transit system. This research investigates the feasibility of adopting road pricing in Dhaka with respect to a significant Bus Rapid Transit (BRT) project. Because both are very new concepts for the population of Dhaka, public acceptability would be a principal issue driving their success or failure. This paper explores the travel behaviour of workers in Dhaka and public perception toward Road Pricing with regards to work trips- based on worker’s travel behaviour. A revealed preference and stated preference survey has been conducted on sample of workers in Dhaka. They were asked limited demographic questions, their current travel behaviour and at the end they had been given several hypothetical choices of integrated BRT and road pricing to choose from. Key finding from the survey is the objective of integrated road pricing; subsidies Bus rapid Transit by road pricing to get reduced BRT fare; cannot be achieved in Dhaka. This is because most of the respondent stated that they would choose the cheapest option Walk-BRT-Walk, even though this would be more time consuming and uncomfortable as they have to walk from home to BRT station and also from BRT station to home. Proper economic analysis has to be carried out to find out the appropriate fare of BRT and road charge with some incentive for the low income people.

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Dhaka, Bangladesh faces chronic traffic congestion Funding for major infrastructure proves challenging This research is investigating feasibility of adopting: -Road Pricing -with significant Bus Rapid Transit (BRT) project

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Transport Impact Assessment (TIA) -Generally a short range transport planning activity -Assess transport impacts of new developments or expansions -Present solutions to mitigate impacts Problems with TIA Process -Private vehicles focus (i.e. Veh Trip Ends) -Proxy variables (e.g. 100sqm GFA) -Trip generation rates (e.g. VTE/proxy) -Little info/guidance on trip chaining effects -Little info/guidance on non-PV modes Requires significant professional judgment

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TOD: - A fully planned, mixed use development equipped with good quality transit service and infrastructure for walking and cycling Hypothesis: -TOD will help to reduce urban transport congestion Method: -Comparison of a TOD with non TOD urban environments -Residents’ trip characteristics

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OBJECTIVE: The fibroblast growth factor (FGF) family of signaling molecules has been associated with chemoresistance and poor prognosis in a number of cancer types, including lung, breast, ovarian, prostate, and head and neck carcinomas. Given the identification of activating mutations in the FGF receptor 2 (FGFR2) receptor tyrosine kinase in a subset of endometrial tumors, agents with activity against FGFRs are currently being tested in clinical trials for recurrent and progressive endometrial cancer. Here, we evaluated the effect of FGFR inhibition on the in vitro efficacy of chemotherapy in endometrial cancer cell lines. METHODS: Human endometrial cancer cell lines with wild-type or activating FGFR2 mutations were used to determine any synergism with concurrent use of the pan-FGFR inhibitor, PD173074, and the chemotherapeutics, doxorubicin and paclitaxel, on cell proliferation and apoptosis. RESULTS: FGFR2 mutation status did not alter sensitivity to either chemotherapeutic agent alone. The combination of PD173074 with paclitaxel or doxorubicin showed synergistic activity in the 3 FGFR2 mutant cell lines evaluated. In addition, although nonmutant cell lines were resistant to FGFR inhibition alone, the addition of PD173074 potentiated the cytostatic effect of paclitaxel and doxorubicin in a subset of FGFR2 wild-type endometrial cancer cell lines. CONCLUSIONS: Together these data suggest a potential therapeutic benefit to combining an FGFR inhibitor with standard chemotherapeutic agents in endometrial cancer therapy particularly in patients with FGFR2 mutation positive tumors.

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Aurora Kinase (AK) based therapy targeting AK-A & B is effective against some cancers. We have explored its potential against previously unreported incurable, metastatic androgen depletion independent Prostate Cancer (ADIPC). We used androgen sensitive (AS) and ADI lines derived from Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) mice. The relevance of this model was unequivocally established through focussed array, quantitative PCR and western blotting studies; significantly greater alteration of genes (fold change and number) representing major cancer pathways was shown in ADI cells compared to AS lines. A marked enhancement of in vivo growth of the ADI subline showing the greatest degree of gene modulations [TRAMP C1 (TC1)-T5: TC1-T5] reflected this. In contrast to the parental AS TC1 line, TC1-T5 cells grew with 100% incidence in the prostate, as lung pseudometastases and migrated to the bone and other soft tissues. The potential involvement of AKs in this transition was indicated by the significant upregulation of AK-A/B and their downstream regulators, survivin and phosphorylated-histone H3 in TC1-T5 cells compared to TC1 cells. This led to enhanced sensitivity of TC1-T5 cells to the pan-AK inhibitor, VX680 and to significant reduction in in vivo tumour growth rates when AK-A and/or B were downregulated in TC1-T5 cells. This cell growth inhibition was markedly enhanced when both AKs were downregulated and also led to substantially greater sensitivity of these cells to docetaxel, the only chemotherapeutic with activity against ADI PC. Finally, use of VX680 with docetaxel led to impressive synergies suggesting promise for treating clinical ADI metastatic PC.

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Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.

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In this issue of Cancer Discovery, Guagnano and colleagues use a large and diverse annotated collection of cancer cell lines, the Cancer Cell Line Encyclopedia, to correlate whole-genome expression and genomic alteration datasets with cell line sensitivity data to the novel pan-fibroblast growth factor receptor (FGFR) inhibitor NVP-BGJ398. Their findings underscore not only the preclinical use of such cell line panels in identifying predictive biomarkers, but also the emergence of the FGFRs as valid therapeutic targets, across an increasingly broad range of malignancies.

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The Chinese Ministry of Education (MOE) initiatives to improve the English competence of college students, as well as increased proficiency level of entering college students (Cheng, 2002) have contributed to greater demands on Teaching English as a Foreign Language (TEFL) academics (MOE, 2004), as “the upgrading of national English proficiency, then, is predicated largely on the professional competence of the teaching force” (Hu, 2005, p. 655). For TEFL academics, one component of this competence is the capacity to conduct research (Shu, 2002), which also reflects other changes in Chinese higher education. The aspirations of higher education institutions at all levels have led to more rigorous recruitment policies and promotion requirements (Che, 2004; Wang, 2007), stressing research as an important indicator of academics’ performance (Shi, 2002; Pan, 2006). These changes highlight the role of research in higher education institutions’ efforts to raise their national status and world ranking (Zhang, Wang, & He, 2006), and have exerted influences on faculty’s academic role. Academics are obliged to engage in research activities, and this has posed challenges to teaching-oriented institutions and disciplines.

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Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.