Optimal reinsurance and dividend for a diffusion model with capital injection: variance premium principle

This paper considers the optimal dividend problem with proportional reinsurance and capital injection for a large insurance portfolio. In particular, the reinsurance premium is assumed to be calculated via the variance principle instead of the expected value principle. Our objective is to maximize the expectation of the discounted dividend payments minus the discounted costs of capital injection. This optimization problem is studied in four cases depending on whether capital injection is allowed and whether there exist restrictions on dividend policies. In all cases, closed-form expressions for the value function and optimal dividend and reinsurance policies are obtained. From the results, we see that the optimal dividend distribution policy is of threshold type with a constant barrier, and that the optimal ceded proportion of risk exponentially decreases with the initial surplus and remains constant when the initial surplus exceeds the dividend barrier. Furthermore, we show that the optimization problem without capital injection is the limiting case of the one with capital injection when the proportional transaction cost goes to infinity. © 2011 Elsevier B.V.postprin

Optimal proportional reinsurance with common shock dependence

In this paper, we consider the optimal proportional reinsurance strategy in a risk model with multiple dependent classes of insurance business, which extends the work of Liang and Yuen (2014) to the case with the reinsurance premium calculated under the expected value principle and to the model with two or more classes of dependent risks. Under the criterion of maximizing the expected exponential utility, closed-form expressions for the optimal strategies and value function are derived not only for the compound Poisson risk model but also for the diffusion approximation risk model. In particular, we find that the optimal reinsurance strategies under the expected value premium principle are very different from those under the variance premium principle in the diffusion risk model. The former depends not only on the safety loading, time and interest rate, but also on the claim size distributions and the counting processes, while the latter depends only on the safety loading, time and interest rate. Finally, numerical examples are presented to show the impact of model parameters on the optimal strategiespostprin

The Chinese classroom paradox: A cross-cultural comparison of teacher controlling behaviors

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Auction-based schemes for multipath routing in selfish networks

We study multipath routing with traffic assignment in selfish networks. Based on the Vickrey-Clarke-Groves (VCG) auction, an optimal and strategy-proof scheme, known as optimal auction-based multipath routing (OAMR), is developed. However, OAMR is computationally expensive and cannot run in real time when the network size is large. Therefore, we propose sequential auction-based multipath routing (SAMR). SAMR handles routing requests sequentially using some greedy strategies. In particular, with reference to the Ausubel auction, we develop a water-draining algorithm to assign the traffic of a request among its available paths and determine the payment of the transmission in approximately constant time. Our simulation results show that SAMR can rapidly compute the allocations and payments of requests with small sacrifice on the system cost. Moreover, various sequencing strategies for sequential auction are also investigated. © 2013 IEEE.published_or_final_versio

Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities

The Anatomical Therapeutic Chemical (ATC) classification system, recommended by the World Health Organization, categories drugs into different classes according to their therapeutic and chemical characteristics. For a set of query compounds, how can we identify which ATC-class (or classes) they belong to? It is an important and challenging problem because the information thus obtained would be quite useful for drug development and utilization. By hybridizing the informations of chemical-chemical interactions and chemical-chemical similarities, a novel method was developed for such purpose. It was observed by the jackknife test on a benchmark dataset of 3,883 drug compounds that the overall success rate achieved by the prediction method was about 73% in identifying the drugs among the following 14 main ATC-classes: (1) alimentary tract and metabolism; (2) blood and blood forming organs; (3) cardiovascular system; (4) dermatologicals; (5) genitourinary system and sex hormones; (6) systemic hormonal preparations, excluding sex hormones and insulins; (7) anti-infectives for systemic use; (8) antineoplastic and immunomodulating agents; (9) musculoskeletal system; (10) nervous system; (11) antiparasitic products, insecticides and repellents; (12) respiratory system; (13) sensory organs; (14) various. Such a success rate is substantially higher than 7% by the random guess. It has not escaped our notice that the current method can be straightforwardly extended to identify the drugs for their 2nd-level, 3rd-level, 4th-level, and 5th-level ATC-classifications once the statistically significant benchmark data are available for these lower levels

Functional MRI of postnatal visual development in normal rat superior colliculi

Theme: Engineering the Future of BiomedicineThis study employed blood oxygenation level-dependent functional MRI (BOLD-fMRI) to evaluate the visual responses in the superior colliculus of the developing rat brain from the time of eyelid opening to adulthood. Upon flash illumination to the contralateral eye, the regional BOLD response underwent a systematic increase in amplitude with age especially after the third postnatal week. However, no significant difference in BOLD signal increase was found between postnatal days 14 and 21. Our results constitute the first fMRI report in demonstrating the critical period of visual functions in the rat brain during maturation. This can be potentially useful in establishing the links between changes in relation to visual sensory development. ©2009 IEEE.published_or_final_versionThe 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), Minneapolis, MN., 3-6 September 2009. In Proceedings of the 31st EMBC, 2009, p. 4436-443

In vivo manganese-enhanced MRI and diffusion tensor imaging of developing and impaired visual brains

This study explored the feasibility of high-resolution Mn-enhanced MRI (MEMRI) and diffusion tensor imaging (DTI) for in vivo assessments of the development and reorganization of retinal and visual callosal pathways in normal neonatal rodent brains and after early postnatal visual impairments. Using MEMRI, intravitreal Mn 2+ injection into one eye resulted in maximal T1-weighted hyperintensity in neonatal contralateral superior colliculus (SC) 8 hours after administration, whereas in adult contralateral SC signal increase continued at 1 day post-injection. Notably, mild but significant Mn 2+ enhancement was observed in the ipsilateral SC in normal neonatal rats, and in adult rats after neonatal monocular enucleation (ME) but not in normal adult rats. Upon intracortical Mn 2+ injection to the visual cortex, neonatal binocularly-enucleated (BE) rats showed an enhancement of a larger projection area, via the splenium of corpus callosum to the V1/V2 transition zone of the contralateral hemisphere in comparison to normal rats. For DTI, the retinal pathways projected from the enucleated eyes possessed lower fractional anisotropy (FA) 6 weeks after BE and ME. Interestingly, in the optic nerve projected from the remaining eye in ME rats a significantly higher FA was observed compared to normal rats. The results of this study are potentially important for understanding the axonal transport, microstructural reorganization and functional activities in the living visual brain during early postnatal development and plasticity in a global and longitudinal setting. © 2011 IEEE.published_or_final_versionThe 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), Boston, MA., 30 August-3 September 2011. In IEEE Engineering in Medicine and Biology Society Conference Proceedings, 2011, p. 7005-700

Structural and Functional Brain Remodeling during Pregnancy with Diffusion Tensor MRI and Resting-State Functional MRI

Although pregnancy-induced hormonal changes have been shown to alter the brain at the neuronal level, the exact effects of pregnancy on brain at the tissue level remain unclear. In this study, diffusion tensor imaging (DTI) and resting-state functional MRI (rsfMRI) were employed to investigate and document the effects of pregnancy on the structure and function of the brain tissues. Fifteen Sprague-Dawley female rats were longitudinally studied at three days before mating (baseline) and seventeen days after mating (G17). G17 is equivalent to the early stage of the third trimester in humans. Seven age-matched nulliparous female rats served as non-pregnant controls and were scanned at the same time-points. For DTI, diffusivity was found to generally increase in the whole brain during pregnancy, indicating structural changes at microscopic levels that facilitated water molecular movement. Regionally, mean diffusivity increased more pronouncedly in the dorsal hippocampus while fractional anisotropy in the dorsal dentate gyrus increased significantly during pregnancy. For rsfMRI, bilateral functional connectivity in the hippocampus increased significantly during pregnancy. Moreover, fractional anisotropy increase in the dentate gyrus appeared to correlate with the bilateral functional connectivity increase in the hippocampus. These findings revealed tissue structural modifications in the whole brain during pregnancy, and that the hippocampus was structurally and functionally remodeled in a more marked manner.published_or_final_versio

NR-2L: A Two-Level Predictor for Identifying Nuclear Receptor Subfamilies Based on Sequence-Derived Features

Nuclear receptors (NRs) are one of the most abundant classes of transcriptional regulators in animals. They regulate diverse functions, such as homeostasis, reproduction, development and metabolism. Therefore, NRs are a very important target for drug development. Nuclear receptors form a superfamily of phylogenetically related proteins and have been subdivided into different subfamilies due to their domain diversity. In this study, a two-level predictor, called NR-2L, was developed that can be used to identify a query protein as a nuclear receptor or not based on its sequence information alone; if it is, the prediction will be automatically continued to further identify it among the following seven subfamilies: (1) thyroid hormone like (NR1), (2) HNF4-like (NR2), (3) estrogen like, (4) nerve growth factor IB-like (NR4), (5) fushi tarazu-F1 like (NR5), (6) germ cell nuclear factor like (NR6), and (7) knirps like (NR0). The identification was made by the Fuzzy K nearest neighbor (FK-NN) classifier based on the pseudo amino acid composition formed by incorporating various physicochemical and statistical features derived from the protein sequences, such as amino acid composition, dipeptide composition, complexity factor, and low-frequency Fourier spectrum components. As a demonstration, it was shown through some benchmark datasets derived from the NucleaRDB and UniProt with low redundancy that the overall success rates achieved by the jackknife test were about 93% and 89% in the first and second level, respectively. The high success rates indicate that the novel two-level predictor can be a useful vehicle for identifying NRs and their subfamilies. As a user-friendly web server, NR-2L is freely accessible at either http://icpr.jci.edu.cn/bioinfo/NR2L or http://www.jci-bioinfo.cn/NR2L. Each job submitted to NR-2L can contain up to 500 query protein sequences and be finished in less than 2 minutes. The less the number of query proteins is, the shorter the time will usually be. All the program codes for NR-2L are available for non-commercial purpose upon request