Maximal Entanglement, Collective Coordinates and Tracking the King

Maximal entangled states (MES) provide a basis to two d-dimensional particles Hilbert space, d=prime $\ne 2$. The MES forming this basis are product states in the collective, center of mass and relative, coordinates. These states are associated (underpinned) with lines of finite geometry whose constituent points are associated with product states carrying Mutual Unbiased Bases (MUB) labels. This representation is shown to be convenient for the study of the Mean King Problem and a variant thereof, termed Tracking the King which proves to be a novel quantum communication channel. The main topics, notions used are reviewed in an attempt to have the paper self contained.Comment: 8. arXiv admin note: substantial text overlap with arXiv:1206.3884, arXiv:1206.035

The properties of the Malin 1 galaxy giant disk: A panchromatic view from the NGVS and GUViCS surveys

Low surface brightness galaxies (LSBGs) represent a significant percentage of local galaxies but their formation and evolution remain elusive. They may hold crucial information for our understanding of many key issues (i.e., census of baryonic and dark matter, star formation in the low density regime, mass function). The most massive examples - the so called giant LSBGs - can be as massive as the Milky Way, but with this mass being distributed in a much larger disk. Malin 1 is an iconic giant LSBG, perhaps the largest disk galaxy known. We attempt to bring new insights on its structure and evolution on the basis of new images covering a wide range in wavelength. We have computed surface brightness profiles (and average surface brightnesses in 16 regions of interest), in six photometric bands (FUV, NUV, u, g, i, z). We compared these data to various models, testing a variety of assumptions concerning the formation and evolution of Malin 1. We find that the surface brightness and color profiles can be reproduced by a long and quiet star-formation history due to the low surface density; no significant event, such as a collision, is necessary. Such quiet star formation across the giant disk is obtained in a disk model calibrated for the Milky Way, but with an angular momentum approximately 20 times larger. Signs of small variations of the star-formation history are indicated by the diversity of ages found when different regions within the galaxy are intercompared.For the first time, panchromatic images of Malin 1 are used to constrain the stellar populations and the history of this iconic example among giant LSBGs. Based on our model, the extreme disk of Malin 1 is found to have a long history of relatively low star formation (about 2 Msun/yr). Our model allows us to make predictions on its stellar mass and metallicity.Comment: Accepted in Astronomy and Astrophysic

Commercializing Biomedical Research Through Securitization Techniques

Biomedical innovation has become riskier, more expensive and more difficult to finance with traditional sources such as private and public equity. Here we propose a financial structure in which a large number of biomedical programs at various stages of development are funded by a single entity to substantially reduce the portfolio's risk. The portfolio entity can finance its activities by issuing debt, a critical advantage because a much larger pool of capital is available for investment in debt versus equity. By employing financial engineering techniques such as securitization, it can raise even greater amounts of more-patient capital. In a simulation using historical data for new molecular entities in oncology from 1990 to 2011, we find that megafunds of $5–15 billion may yield average investment returns of 8.9–11.4% for equity holders and 5–8% for 'research-backed obligation' holders, which are lower than typical venture-capital hurdle rates but attractive to pension funds, insurance companies and other large institutional investors

Regularized fitted Q-iteration: application to planning

We consider planning in a Markovian decision problem, i.e., the problem of finding a good policy given access to a generative model of the environment. We propose to use fitted Q-iteration with penalized (or regularized) least-squares regression as the regression subroutine to address the problem of controlling model-complexity. The algorithm is presented in detail for the case when the function space is a reproducing kernel Hilbert space underlying a user-chosen kernel function. We derive bounds on the quality of the solution and argue that data-dependent penalties can lead to almost optimal performance. A simple example is used to illustrate the benefits of using a penalized procedure

Open access and open source in chemistry

Scientific data are being generated and shared at ever-increasing rates. Two new mechanisms for doing this have developed: open access publishing and open source research. We discuss both, with recent examples, highlighting the differences between the two, and the strengths of both

A systematic review and critical assessment of incentive strategies for discovery and development of novel antibiotics

Despite the growing threat of antimicrobial resistance, pharmaceutical and biotechnology firms are reluctant to develop novel antibiotics because of a host of market failures. This problem is complicated by public health goals that demand antibiotic conservation and equitable patient access. Thus, an innovative incentive strategy is needed to encourage sustainable investment in antibiotics. This systematic review consolidates, classifies and critically assesses a total of 47 proposed incentives. Given the large number of possible strategies, a decision framework is presented to assist with the selection of incentives. This framework focuses on addressing market failures that result in limited investment, public health priorities regarding antibiotic stewardship and patient access, and implementation constraints and operational realities. The flexible nature of this framework allows policy makers to tailor an antibiotic incentive package that suits a country’s health system structure and needs

Drug Repurposing: Far Beyond New Targets for Old Drugs

Repurposing drugs requires finding novel therapeutic indications compared to the ones for which they were already approved. This is an increasingly utilized strategy for finding novel medicines, one that capitalizes on previous investments while derisking clinical activities. This approach is of interest primarily because we continue to face significant gaps in the drug–target interactions matrix and to accumulate safety and efficacy data during clinical studies. Collecting and making publicly available as much data as possible on the target profile of drugs offer opportunities for drug repurposing, but may limit the commercial applications by patent applications. Certain clinical applications may be more feasible for repurposing than others because of marked differences in side effect tolerance. Other factors that ought to be considered when assessing drug repurposing opportunities include relevance to the disease in question and the intellectual property landscape. These activities go far beyond the identification of new targets for old drugs