Can We Model Driver Perceptions? An In-Situ Experiment in Real-World Conditions

ABSTRACTIt is clear that perceptions play a significant role in traveler decisions. Consequently, traveler perceptions are a corner stone in the feasibility of traveler information systems; for traveler information systems are only valuable if the drivers are incapable of accurately acquiring the provided information on their own, and if the provided information is relevant for the drivers' decision criteria. Accuracy of traveler perceptions has been repeatedly researched in public transportation, and has been found to vary according to different reasons. However, in spite of the clear significance of traveler perceptions, minimal effort has been put into modeling it. Almost all travel behavior models are based on traveler experiences, which are assumed to reflect traveler perceptions via the addition of some random error component. This works introduces an alternative approach: instead of adding an error component to represent driver perceptions, it proposes to model driver perceptions. This work is based on a real-world route choice experiment of a sample of 20 drivers who made more than 2,000 real-world route choices. Each of the drivers' experiences, perceptions, and choices were recorded, analyzed and cross examined. The paper demonstrates that: i) driver experiences are different from driver perceptions, ii) driver perceptions explain driver choices better than driver experiences, iii) it is possible to model and predict driver perceptions of travel distance, time and speed

On an Extension of Kummer's Second Theorem

The aim of this paper is to establish an extension of Kummer's second theorem in the form   e-x/2F22[a,2+d;x2a+2,d;]=F10[-;x2/16a+3/2;]+((a/d-1/2)/(a+1))x F10[-;x2/16a+3/2;]+(cx2/2(2a+3))F10[-;x2/16a+5/2;], where  c=1/a+11/2-a/d+a/d(d+1),  d≠0,-1,-2,…. For d=2a, we recover Kummer's second theorem. The result is derived with the help of Kummer's second theorem and its contiguous results available in the literature. As an application, we obtain two general results for the terminating F23(2) series. The results derived in this paper are simple, interesting, and easily established and may be useful in physics, engineering, and applied mathematics

Prognostic factors in metaplastic carcinoma of the breast: A multi-institutional study

Background: Metaplastic breast carcinoma (MBC) is a rare type of breast cancer that has basal-like characteristics and is perceived to have poorer prognosis when compared with conventional no specific type/ductal carcinomas (ductal/NST). However, current data on MBC are largely derived from small case series or population-based reports. This study aimed to assess the clinicopathological features and outcome of MBC identified through an international multicentre collaboration. Methods: A large international multicentre series of MBC (no=405) with histological confirmation and follow-up information has been included in this study. The prognostic value of different variables and outcome has been assessed and compared with grade, nodal status and ER/HER2 receptor-matched ductal/NST breast carcinoma. Results: The outcome of MBC diagnosed in Asian countries was more favourable than those in Western countries. The outcome of MBC is not different from matched ductal/NST carcinoma but the performance of the established prognostic variables in MBC is different. Lymph node stage, lymphovascular invasion and histologic subtype are associated with outcome but tumour size and grade are not. Chemotherapy was associated with longer survival, although this effect was limited to early-stage disease. In this study no association between radiotherapy and outcome was identified. Multivariate analysis of MBC shows that histologic subtype is an independent prognostic feature. Conclusions: This study suggests that MBC is a heterogeneous disease. Although the outcome of MBC is not different to matched conventional ductal/NST breast carcinoma, its behaviour is dependent on the particular subtype with spindle cell carcinoma in particular has an aggressive biological behaviour. Management of patients with MBC should be based on validated prognostic variables

Simulations of Alfvénic modes in TJ-II Stellarator

Alfvénic modes are one of the subclass of instabilities prevalent in burning plasmas due to interaction of energetic particles with background plasma. In this paper we investigate the properties of these modes with 3D simulations using modeling tools STELLGAP [1] and AE3D [2] of Neutral Beam Injection (NBI) heated H-plasmas in TJ-II low-magnetic-shear flexible heliac (B0 = 0.95 T, = 1.5 m, = 0.22 m). These simulations focus on modelling the experimental observations [3] for prominent modes in TJ-II plasmas. Our simulations show consistency in frequency and radial location with the measured Alfvén Eigenmodes [3]. These simulations are performed for chirping and steady modes in TJ-II discharge # 29839 at t = 1150 and 1160ms respectively

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

<p>Abstract</p> <p>Background</p> <p>Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.</p> <p>Methods</p> <p>Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).</p> <p>Results</p> <p>Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.</p> <p>Conclusion</p> <p>Factor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.</p> <p>Virtual Slides</p> <p>The virtual slide(s) for this article can be found here: <url>http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949</url></p