A hidden Markov reduced-form risk model

In this paper, we propose a reduced-form credit risk model with a hidden state process. The hidden state process is adopted to model the underlying economic environment with an observable state revealing the delayed and noisy information of the underlying economic state. Our model is a generalization of the work in Gu et al. [1]. Under this framework, we give a computational method to extract the underlying economic state and to find the distribution of multiple default times. Numerical experiment is conducted to illustrate the impact of change in observable state and the contagion effect of defaults.published_or_final_versio

On infectious models for dependent default risk

Modeling dependent defaults is a key issue in risk measurement and management. In this paper, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit entities. The key idea of the proposed model is based on the concept of common shocks adopted in the insurance industry. We compare the proposed model to both one-sector and two-sector models considered in the credit literature using real default data. A log-likelihood ratio test is applied to compare the goodness-of- fit of the proposed model. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models. © 2011 IEEE.published_or_final_versionThe 4th International Joint Conference on Computational Sciences and Optimization (CSO 2011), Yunnan, China, 15-19 April 2011. In Proceedings of the 4th CSO, 2011, p. 1196-120

On Modeling Credit Defaults: A Probabilistic Boolean Network Approach

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Distributions of colorectal cancer in two chinese cities with contrasting colorectal cancer epidemiology

BACKGROUND AND AIM: The incidence of colorectal cancer (CRC) is rising rapidly in Chinese. We studied the anatomic distributions and characteristics of CRC in Hong Kong (HK) and Chongqing (CQ) with different CRC epidemiology. METHODS: It was a retrospective study conducted in three large regional hospitals of the two cities. We identified all patients newly diagnosed with CRC between 2003 and 2012. The distribution and characteristics of CRC of the two cities were compared. RESULTS: 3,664 new cases of CRC were diagnosed within the study period. CRC was more common in men (>56%) in both cities. The mean age at diagnosis was significantly younger in CQ, the lower prevalence area, than in HK (62.1 vs 70.4 years; P <0.001). Rectal cancer was the predominant (61.3%) cancer in CQ, but only 18% of cancers in HK were rectal cancer (P = 0.0001). Right-sided colonic cancer, however, was more common in HK than CQ (27.2% vs 17.4%; P <0.001). Women had more right-sided colonic cancer than men in both cities (P < 0.002), and there was an age-related increase in right-sided colonic cancer in HK but not in CQ. Multivariate analysis showed that older age, female and living in HK were independent risk factors associated with right-sided colonic cancer. CONCLUSIONS: There are significant differences in the distribution of CRC between HK and CQ. The discrepancy may be partly accounted by older population and an increase in proximal colonic cancer, particularly in women, in HK.preprin

Selection for Replicases in Protocells

PMCID: PMC3649988This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with $n$ current particles, a new particle is born with instantaneous rate $\lambda_n$ and a particle dies with instantaneous rate $\mu_n$. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics

Accurate Strand-Specific Quantification of Viral RNA

The presence of full-length complements of viral genomic RNA is a hallmark of RNA virus replication within an infected cell. As such, methods for detecting and measuring specific strands of viral RNA in infected cells and tissues are important in the study of RNA viruses. Strand-specific quantitative real-time PCR (ssqPCR) assays are increasingly being used for this purpose, but the accuracy of these assays depends on the assumption that the amount of cDNA measured during the quantitative PCR (qPCR) step accurately reflects amounts of a specific viral RNA strand present in the RT reaction. To specifically test this assumption, we developed multiple ssqPCR assays for the positive-strand RNA virus o'nyong-nyong (ONNV) that were based upon the most prevalent ssqPCR assay design types in the literature. We then compared various parameters of the ONNV-specific assays. We found that an assay employing standard unmodified virus-specific primers failed to discern the difference between cDNAs generated from virus specific primers and those generated through false priming. Further, we were unable to accurately measure levels of ONNV (−) strand RNA with this assay when higher levels of cDNA generated from the (+) strand were present. Taken together, these results suggest that assays of this type do not accurately quantify levels of the anti-genomic strand present during RNA virus infectious cycles. However, an assay permitting the use of a tag-specific primer was able to distinguish cDNAs transcribed from ONNV (−) strand RNA from other cDNAs present, thus allowing accurate quantification of the anti-genomic strand. We also report the sensitivities of two different detection strategies and chemistries, SYBR® Green and DNA hydrolysis probes, used with our tagged ONNV-specific ssqPCR assays. Finally, we describe development, design and validation of ssqPCR assays for chikungunya virus (CHIKV), the recent cause of large outbreaks of disease in the Indian Ocean region

Visual and olfactory associative learning in the malaria vector Anopheles gambiae sensu stricto

<p>Abstract</p> <p>Background</p> <p>Memory and learning are critical aspects of the ecology of insect vectors of human pathogens because of their potential effects on contacts between vectors and their hosts. Despite this epidemiological importance, there have been only a limited number of studies investigating associative learning in insect vector species and none on Anopheline mosquitoes.</p> <p>Methods</p> <p>A simple behavioural assays was developed to study visual and olfactory associative learning in <it>Anopheles gambiae</it>, the main vector of malaria in Africa. Two contrasted membrane qualities or levels of blood palatability were used as reinforcing stimuli for bi-directional conditioning during blood feeding.</p> <p>Results</p> <p>Under such experimental conditions <it>An. gambiae </it>females learned very rapidly to associate visual (chequered and white patterns) and olfactory cues (presence and absence of cheese or Citronella smell) with the reinforcing stimuli (bloodmeal quality) and remembered the association for up to three days. Associative learning significantly increased with the strength of the conditioning stimuli used. Importantly, learning sometimes occurred faster when a positive reinforcing stimulus (palatable blood) was associated with an innately preferred cue (such as a darker visual pattern). However, the use of too attractive a cue (e.g. Shropshire cheese smell) was counter-productive and decreased learning success.</p> <p>Conclusions</p> <p>The results address an important knowledge gap in mosquito ecology and emphasize the role of associative memory for <it>An. gambiae</it>'s host finding and blood-feeding behaviour with important potential implications for vector control.</p

Differential gene expression between wild-type and Gulo-deficient mice supplied with vitamin C

The aim of this study was to test the hypothesis that hepatic vitamin C (VC) levels in VC deficient mice rescued with high doses of VC supplements still do not reach the optimal levels present in wild-type mice. For this, we used a mouse scurvy model (sfx) in which the L-gulonolactone oxidase gene (Gulo) is deleted. Six age- (6 weeks old) and gender- (female) matched wild-type (WT) and sfx mice (rescued by administering 500 mg of VC/L) were used as the control (WT) and treatment (MT) groups (n = 3 for each group), respectively. Total hepatic RNA was used in triplicate microarray assays for each group. EDGE software was used to identify differentially expressed genes and transcriptomic analysis was used to assess the potential genetic regulation of Gulo gene expression. Hepatic VC concentrations in MT mice were significantly lower than in WT mice, even though there were no morphological differences between the two groups. In MT mice, 269 differentially expressed transcripts were detected (≥ twice the difference between MT and WT mice), including 107 up-regulated and 162 down-regulated genes. These differentially expressed genes included stress-related and exclusively/predominantly hepatocyte genes. Transcriptomic analysis identified a major locus on chromosome 18 that regulates Gulo expression. Since three relevant oxidative genes are located within the critical region of this locus we suspect that they are involved in the down-regulation of oxidative activity in sfx mice