Some Contributions to the Class of Two-Sex Branching Processes Depending on the Number of Couples in the Population

2000 Mathematics Subject Classification: 60J80We consider the class of two-sex branching processes with offspring and mating depending on the number of couples in the population introduced in Molina et al. (2008). In addition to its theoretical interest, this class also has clear practical implications, especially in population dynamics. We investigate its extinction probability and limiting behavior. By considering different probabilistic approaches, necessary and sufficient conditions for its almost sure extinction are determined. Assuming the nonextinction, some limiting results are derived.This research has been supported by the Ministerio de Ciencia e Innovaci´on of Spain, the Junta de Extremadura, and the FEDER (grants MTM2009-13248 and GR10118) and by the Natural Sciences Foundation of China (grant 10971048)

Pricing Options with Credit Risk in Markovian Regime-Switching Markets

This paper investigates the valuation of European option with credit risk in a reduced form model when the stock price is driven by the so-called Markov-modulated jump-diffusion process, in which the arrival rate of rare events and the volatility rate of stock are controlled by a continuous-time Markov chain. We also assume that the interest rate and the default intensity follow the Vasicek models whose parameters are governed by the same Markov chain. We study the pricing of European option and present numerical illustrations

Proteomic resistance biomarkers for PI3K inhibitor in triple negative breast cancer patient-derived xenograft models

PI3K pathway activation is frequently observed in triple negative breast cancer (TNBC). However, single agent PI3K inhibitors have shown limited anti-tumor activity. To investigate biomarkers of response and resistance mechanisms, we tested 17 TNBC patient-derived xenograft (PDX) models representing diverse genomic backgrounds and varying degrees of PI3K pathway signaling activities for their tumor growth response to the pan-PI3K inhibitor, BKM120. Baseline and post-treatment PDX tumors were subjected to reverse phase protein array (RPPA) to identify protein markers associated with tumor growth response. While BKM120 consistently reduced PI3K pathway activity, as demonstrated by reduced levels of phosphorylated AKT, percentage tumor growth inhibition (%TGI) ranged from 35% in the least sensitive to 84% in the most sensitive model. Several biomarkers showed significant association with resistance, including elevated baseline levels of growth factor receptors (EGFR, pHER3 Y1197), PI3Kp85 regulatory subunit, anti-apoptotic protein BclXL, EMT (Vimentin, MMP9, IntegrinaV), NFKB pathway (IkappaB, RANKL), and intracellular signaling molecules including Caveolin, CBP, and KLF4, as well as treatment-induced increases in the levels of phosphorylated forms of Aurora kinases. Interestingly, increased AKT phosphorylation or PTEN loss at baseline were not significantly correlated to %TGI. These results provide important insights into biomarker development for PI3K inhibitors in TNBC

Travelable Area Detection Fusing Superpixel 3D and Apperance Feature

For automatic driving and advanced driving assistance task based on computer vision,the real-time detection of travelable area in front of the vehicle is necessary.The travelable area detection is an image segmentation problem,and the mainstream Scene Parsing scheme is based on deep learning model.In general,the deep learning framework is not real-time and cannot be applied in automatic driving task or advanced driving assistance task until now.Aiming at this problem,in this paper,an Appearance and 3D feature fusion detection framework is proposed,which implements two-stage process from coarse-grained segmentation to fine-grained segmentation.The coarse-grained segmentation is the fast estimation based on RANSAC fast plane,and the fine-grained segmentation is the conditional random field model based on the road estimation probability from coarse-grained segmentation,which uses super pixels to accelerate.Experimental result in the Cityscape data sets shows that the proposed framework achieves more than 90% accuracy and recall rate,which is comparable to SegNet and FCN 16 Scene Parsing framework.Its real-time applications can be achieved both in X86 and ARM platform

Comparison of laparoscopic and traditional abomasal cannulation in sheep

Introduction: The objective of this study was to describe a laparoscopic abomasal cannulation (LAC) technique, and compare the extent of the surgical trauma after LAC and open abomasal cannulation (OAC) by examining postoperative visual analog scale (VAS) pain scores and serum values of interleukin-6 and tumour necrosis factor-α in sheep. Material and Methods: Twelve healthy ewes, weighing 38-43 kg, were used. Three-portal laparoscopic techniques were used for LAC procedures. OAC was performed by a right flank laparotomy. Results: Abomasal cannulation was accomplished in all sheep without major intraoperative and postoperative complications. The abomasal contents were collected easily in both groups. Comparative studies found that open procedures exhibit a more pronounced short-term increase in cytokines and significantly higher VAS pain scores than the corresponding laparoscopic procedures. Conclusion: The laparoscopic technique proved to be less traumatic than the conventional open technique