On Optimality of Myopic Sensing Policy with Imperfect Sensing in Multi-channel Opportunistic Access

We consider the channel access problem under imperfect sensing of channel state in a multi-channel opportunistic communication system, where the state of each channel evolves as an independent and identically distributed Markov process. The considered problem can be cast into a restless multi-armed bandit (RMAB) problem that is of fundamental importance in decision theory. It is well-known that solving the RMAB problem is PSPACE-hard, with the optimal policy usually intractable due to the exponential computation complexity. A natural alternative is to consider the easily implementable myopic policy that maximizes the immediate reward but ignores the impact of the current strategy on the future reward. In this paper, we perform an analytical study on the optimality of the myopic policy under imperfect sensing for the considered RMAB problem. Specifically, for a family of generic and practically important utility functions, we establish the closed-form conditions under which the myopic policy is guaranteed to be optimal even under imperfect sensing. Despite our focus on the opportunistic channel access, the obtained results are generic in nature and are widely applicable in a wide range of engineering domains.Comment: 21 pages regular pape

On Optimality of Myopic Policy for Restless Multi-armed Bandit Problem with Non i.i.d. Arms and Imperfect Detection

We consider the channel access problem in a multi-channel opportunistic communication system with imperfect channel sensing, where the state of each channel evolves as a non independent and identically distributed Markov process. This problem can be cast into a restless multi-armed bandit (RMAB) problem that is intractable for its exponential computation complexity. A natural alternative is to consider the easily implementable myopic policy that maximizes the immediate reward but ignores the impact of the current strategy on the future reward. In particular, we develop three axioms characterizing a family of generic and practically important functions termed as $g$-regular functions which includes a wide spectrum of utility functions in engineering. By pursuing a mathematical analysis based on the axioms, we establish a set of closed-form structural conditions for the optimality of myopic policy.Comment: Second version, 16 page

Microgravimetric immunosensor for direct detection of aerosolized influenza A virus particles.

The development and characterization of a quartz crystal microbalance (QCM) sensor for the direct detection of aerosolized influenza A virions is reported. Self-assembled monolayers (SAMs) of mercaptoundecanoic acid (MUA) are formed on QCM gold electrodes to provide a surface amenable for the immobilization of anti-influenza A antibodies using NHS/EDC coupling chemistry. The surface-bound antibody provides a selective and specific sensing interface for the capture of influenza virions. A nebulizer is used to create aerosolized samples and is directly connected to a chamber housing the antibody-modified crystal ("immunochip"). Upon exposure to the aerosolized virus, the interaction between the antibody and virus leads to a dampening of the oscillation frequency of the quartz crystal. The magnitude of frequency change is directly related to virus concentration. Control experiments using aerosols from chicken egg allantoic fluid and an anti-murine antibody based immunosensor confirm that the observed signal originates from specific viral binding on the chip surface. Step-by-step surface modification of MUA assembly, antibody attachment, and antibody-virus interaction are characterized by atomic force microscopy (AFM) imaging analysis. Using the S/N = 3 principle, the limit of detection is estimated to be 4 virus particles/mL. The high sensitivity and real-time sensing scheme presented here can play an important role in the public health arena by offering a new analytical tool for identifying bio-contaminated areas and assisting in timely patient diagnosis

Photonic-plasmonic hybrid single-molecule nanosensor measures the effect of fluorescent labels on DNA-protein dynamics

Current methods to study molecular interactions require labeling the subject molecules with fluorescent reporters. However, the effect of the fluorescent reporters on molecular dynamics has not been quantified because of a lack of alternative methods. We develop a hybrid photonic-plasmonic antenna-in-a-nanocavity single-molecule biosensor to study DNA-protein dynamics without using fluorescent labels. Our results indicate that the fluorescein and fluorescent protein labels decrease the interaction between a single DNA and a protein due to weakened electrostatic interaction. Although the study is performed on the DNA-XPA system, the conclusion has a general implication that the traditional fluorescent labeling methods might be misestimating the molecular interactions

Deterministic Raman crosstalk effects in amplified wavelength division multiplexing transmission

We study the deterministic effects of Raman-induced crosstalk in amplified wavelength division multiplexing (WDM) optical fiber transmission lines. We show that the dynamics of pulse amplitudes in an N-channel transmission system is described by an N-dimensional predator-prey model. We find the equilibrium states with non-zero amplitudes and prove their stability by obtaining the Lyapunov function. The stability is independent of the exact details of the approximation for the Raman gain curve. Furthermore, we investigate the impact of cross phase modulation and Raman self and cross frequency shifts on the dynamics and establish the stability of the equilibrium state with respect to these perturbations. Our results provide a quantitative explanation for the robustness of differential-phase-shift-keyed WDM transmission against Raman crosstalk effects.Comment: 34 pages and 12 figures. Revised paper. Submitted to Optics Communication

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Moving towards a virtual world - A case study conducted at Gard

Master i økonomi og administrasjonIn this age, we are moving towards a virtual world, where Web 2.0 technologies can provide new possibilities for collaboration and knowledge sharing. Furthermore, in the 21th century, the global economy has become more knowledge-based. Companies in today's highly competitive markets, must utilize all available knowledge reasonably and practically. This leads to an emphasize on knowledge sharing and collaboration. The aim of this study was to explore the interrelationship - virtual phenomenon, knowledge sharing and collaboration. Thus, following problem statement was developed: “How does the virtual phenomenon affect collaboration and knowledge sharing in an organization.” To answer this problem statement, a qualitative single case study was conducted at Gard. Gard is a global knowledge-intensive firm and the leading actor within marine insurance. To gain an in-depth understanding of the unit of analysis, multiple evidence in the form of 17 interviews, two observations, documents and qualitative review of statistics, was collected. Multiple interesting results were discovered. First, this study suggest that various ICT platforms support a hybrid strategy. In addition, the results suggest that social technologies can support knowledge creation and conversion. However, challenges such as established working routines and lack of computer capabilities in individuals, need to be addressed to fully benefit from social technologies. Furthermore, this study suggest that collaboration is no longer limited by time, space and geographical distance since social technologies enable virtual collaboration. Lastly, a concept, based on the theoretical groundwork and results was proposed

Substrate protein folds while it is bound to the ATP-independent chaperone Spy

Chaperones assist the folding of many proteins in the cell. While the most well studied chaperones use cycles of ATP binding and hydrolysis to assist protein folding, a number of chaperones have been identified that promote protein folding in the absence of highenergy cofactors. Precisely how ATP-independent chaperones accomplish this feat is unclear. Here we have characterized the kinetic mechanism of substrate folding by the small, ATP-independent chaperone, Spy. Spy rapidly associates with its substrate, Immunity protein 7 (Im7), eliminating its potential for aggregation. Remarkably, Spy then allows Im7 to fully fold into its native state while remaining bound to the surface of the chaperone. These results establish a potentially widespread mechanism whereby ATP-independent chaperones can assist in protein refolding. They also provide compelling evidence that substrate proteins can fold while continuously bound to a chaperone

Mapping interactions with the chaperone network reveals factors that protect against tau aggregation.

A network of molecular chaperones is known to bind proteins ('clients') and balance their folding, function and turnover. However, it is often unclear which chaperones are critical for selective recognition of individual clients. It is also not clear why these key chaperones might fail in protein-aggregation diseases. Here, we utilized human microtubule-associated protein tau (MAPT or tau) as a model client to survey interactions between ~30 purified chaperones and ~20 disease-associated tau variants (~600 combinations). From this large-scale analysis, we identified human DnaJA2 as an unexpected, but potent, inhibitor of tau aggregation. DnaJA2 levels were correlated with tau pathology in human brains, supporting the idea that it is an important regulator of tau homeostasis. Of note, we found that some disease-associated tau variants were relatively immune to interactions with chaperones, suggesting a model in which avoiding physical recognition by chaperone networks may contribute to disease

Mapping an atlas of tissue-specific drosophila melanogaster metabolomes by high resolution mass spectrometry

Metabolomics can provide exciting insights into organismal function, but most work on simple models has focussed on the whole organism metabolome, so missing the contributions of individual tissues. Comprehensive metabolite profiles for ten tissues from adult Drosophila melanogaster were obtained here by two chromatographic methods, a hydrophilic interaction (HILIC) method for polar metabolites and a lipid profiling method also based on HILIC, in combination with an Orbitrap Exactive instrument. Two hundred and forty two polar metabolites were putatively identified in the various tissues, and 251 lipids were observed in positive ion mode and 61 in negative ion mode. Although many metabolites were detected in all tissues, every tissue showed characteristically abundant metabolites which could be rationalised against specific tissue functions. For example, the cuticle contained high levels of glutathione, reflecting a role in oxidative defence; the alimentary canal (like vertebrate gut) had high levels of acylcarnitines for fatty acid metabolism, and the head contained high levels of ether lipids. The male accessory gland uniquely contained decarboxylated S-adenosylmethionine. These data thus both provide valuable insights into tissue function, and a reference baseline, compatible with the FlyAtlas.org transcriptomic resource, for further metabolomic analysis of this important model organism, for example in the modelling of human inborn errors of metabolism, aging or metabolic imbalances such as diabetes