Optimal periodic dividend strategies for spectrally positive L\'evy risk processes with fixed transaction costs

We consider the general class of spectrally positive L\'evy risk processes, which are appropriate for businesses with continuous expenses and lump sum gains whose timing and sizes are stochastic. Motivated by the fact that dividends cannot be paid at any time in real life, we study $\textit{periodic}$ dividend strategies whereby dividend decisions are made according to a separate arrival process. In this paper, we investigate the impact of fixed transaction costs on the optimal periodic dividend strategy, and show that a periodic $(b_u,b_l)$ strategy is optimal when decision times arrive according to an independent Poisson process. Such a strategy leads to lump sum dividends that bring the surplus back to $b_l$ as long as it is no less than $b_u$ at a dividend decision time. The expected present value of dividends (net of transaction costs) is provided explicitly with the help of scale functions. Results are illustrated.Comment: Accepted for publication in Insurance: Mathematics and Economic

Towards a transparent, credible, evidence-based decision-making process of new drug listing on the Hong Kong Hospital Authority Drug Formulary: challenges and suggestions

The aim of this article is to describe the process, evaluation criteria, and possible outcomes of decision-making for new drugs listed in the Hong Kong Hospital Authority Drug Formulary in comparison to the health technology assessment (HTA) policy overseas. Details of decision-making processes including the new drug listing submission, Drug Advisory Committee (DAC) meeting, and procedures prior to and following the meeting, were extracted from the official Hong Kong Hospital Authority drug formulary management website and manual. Publicly-available information related to the new drug decision-making process for five HTA agencies [the National Institute of Health and Care Excellence (NICE), the Scottish Medicines Consortium (SMC), the Australia Pharmaceutical Benefits Advisory Committee (PBAC), the Canadian Agency for Drugs and Technologies in Health (CADTH), and the New Zealand Pharmaceutical Management Agency (PHARMAC)] were reviewed and retrieved from official documents from public domains. The DAC is in charge of systemically and critically appraising new drugs before they are listed on the formulary, reviewing submitted applications, and making the decision to list the drug based on scientific evidence to which safety, efficacy, and cost-effectiveness are the primary considerations. When compared with other HTA agencies, transparency of the decision-making process of the DAC, the relevance of clinical and health economic evidence, and the lack of health economic and methodological input of submissions are the major challenges to the new-drug listing policy in Hong Kong. Despite these challenges, this review provides suggestions for the establishment of a more transparent, credible, and evidence-based decision-making process in the Hong Kong Hospital Authority Drug Formulary. Proposals for improvement in the listing of new drugs in the formulary should be a priority of healthcare reforms

Interoperability Optimization and Service Enhancement in Vehicle Onboard Infortainment Systems

This paper presents an overview on optimizing interoperability between different applications for enhanced return-on-investment through utilization of business intelligence in conjunction with prognostics and health management methodology. Such implementation is particularly suitable for deployment in mass-produced vehicle onboard diagnostics system

A high-throughput screen identifies that CDK7 activates glucose consumption in lung cancer cells.

Elevated glucose consumption is fundamental to cancer, but selectively targeting this pathway is challenging. We develop a high-throughput assay for measuring glucose consumption and use it to screen non-small-cell lung cancer cell lines against bioactive small molecules. We identify Milciclib that blocks glucose consumption in H460 and H1975, but not in HCC827 or A549 cells, by decreasing SLC2A1 (GLUT1) mRNA and protein levels and by inhibiting glucose transport. Milciclib blocks glucose consumption by targeting cyclin-dependent kinase 7 (CDK7) similar to other CDK7 inhibitors including THZ1 and LDC4297. Enhanced PIK3CA signaling leads to CDK7 phosphorylation, which promotes RNA Polymerase II phosphorylation and transcription. Milciclib, THZ1, and LDC4297 lead to a reduction in RNA Polymerase II phosphorylation on the SLC2A1 promoter. These data indicate that our high-throughput assay can identify compounds that regulate glucose consumption and that CDK7 is a key regulator of glucose consumption in cells with an activated PI3K pathway

Understanding of User Preferences in Global Electronic Commerce Sites

This paper addresses issues of user preferences in web design of global e-commerce. Increasing attention to global e-commerce sites are not only global companies concerns but also an issue for users. This research is an attempt to identify issues of global web design and user preferences particularly from different culture backgrounds. An exploratory study relating to user preferences for design features in popular global sites is presented, and through it identifies a number of factors related to design in the B2C context and proposes a framework based on understanding of users preferences of these factors. Results indicate that users are more likely to use global web sites if they find their favorite features in it. Users form different culture groups and their preferences are likely to influence different levels of design content in a web site. Furthermore, a user with his/her favorite design features that promote user s attention and lead to purchase of goods through the global sites

Approximate Matching for Peer-to-Peer Overlays with Cubit

Keyword search is a critical component in most content retrieval systems. Despite the emergence of completely decentralized and efficient peer-to-peer techniques for content distribution, there have not been similarly efficient, accurate, and decentralized mechanisms for content discovery based on approximate search keys. In this paper, we present a scalable and efficient peer-to-peer system called Cubit with a new search primitive that can efficiently find the k data items with keys most similar to a given search key. The system works by creating a keyword metric space that encompasses both the nodes and the objects in the system, where the distance between two points is a measure of the similarity between the strings that the points represent. It provides a loosely-structured overlay that can efficiently navigate this space. We evaluate Cubit through both a real deployment as a search plugin for a popular BitTorrent client and a large-scale simulation and show that it provides an efficient, accurate and robust method to handle imprecise string search in filesharing applications.This work was supported in part by NSF-TRUST 0424422 and NSF-CAREER 0546568 grants