A Discrete and Bounded Envy-free Cake Cutting Protocol for Four Agents

We consider the well-studied cake cutting problem in which the goal is to identify a fair allocation based on a minimal number of queries from the agents. The problem has attracted considerable attention within various branches of computer science, mathematics, and economics. Although, the elegant Selfridge-Conway envy-free protocol for three agents has been known since 1960, it has been a major open problem for the last fifty years to obtain a bounded envy-free protocol for more than three agents. We propose a discrete and bounded envy-free protocol for four agents

Data Mining and Machine Learning in Astronomy

We review the current state of data mining and machine learning in astronomy. 'Data Mining' can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black-box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those where data mining techniques directly resulted in improved science, and important current and future directions, including probability density functions, parallel algorithms, petascale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm, and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.Comment: Published in IJMPD. 61 pages, uses ws-ijmpd.cls. Several extra figures, some minor additions to the tex

Multiple populations in Omega Centauri: a cluster analysis of spectroscopic data

Omega Cen is composed of several stellar populations. Their history might allow us to reconstruct the evolution of this complex object. We performed a statistical cluster analysis on the large data set provided by Johnson and Pilachowski (2010). Stars in Omega Cen divide into three main groups. The metal-poor group includes about a third of the total. It shows a moderate O-Na anticorrelation, and similarly to other clusters, the O-poor second generation stars are more centrally concentrated than the O-rich first generation ones. This whole population is La-poor, with a pattern of abundances for n-capture elements which is very close to a scaled r-process one. The metal-intermediate group includes the majority of the cluster stars. This is a much more complex population, with an internal spread in the abundances of most elements. It shows an extreme O-Na anticorrelation, with a very numerous population of extremely O-poor and He-rich second generation stars. This second generation is very centrally concentrated. This whole population is La-rich, with a pattern of the abundances of n-capture elements that shows a strong contribution by the s-process. The spread in metallicity within this metal-intermediate population is not very large, and we might attribute it either to non uniformities of an originally very extended star forming region, or to some ability to retain a fraction of the ejecta of the core collapse SNe that exploded first, or both. As previously noticed, the metal-rich group has an Na-O correlation, rather than anticorrelation. There is evidence for the contribution of both massive stars ending their life as core-collapse SNe, and intermediate/low mass stars, producing the s-capture elements. Kinematics of this population suggests that it formed within the cluster rather than being accreted.Comment: Accepted for publication in Astronomy and Astrophysic

The Fairness Challenge in Computer Networks

In this paper, the concept of fairness in computer networks is investigated. We motivate the need of examining fairness issues by providing example future application scenarios where fairness support is needed in order to experience sufficient service quality. Fairness definitions from political science and their application to computer networks are described and a state-of-the-art overview of research activities in fairness, from issues such a queue management and tcp-friendliness to issues like fairness in layered multi-rate multicast scenarios, is given. We contribute with this paper to the ongoing research activities by defining the fairness challenge with the purpose of helping direct future investigations to with spots on the map of research in fairness

From the discrete to the continuous - towards a cylindrically consistent dynamics

Discrete models usually represent approximations to continuum physics. Cylindrical consistency provides a framework in which discretizations mirror exactly the continuum limit. Being a standard tool for the kinematics of loop quantum gravity we propose a coarse graining procedure that aims at constructing a cylindrically consistent dynamics in the form of transition amplitudes and Hamilton's principal functions. The coarse graining procedure, which is motivated by tensor network renormalization methods, provides a systematic approximation scheme towards this end. A crucial role in this coarse graining scheme is played by embedding maps that allow the interpretation of discrete boundary data as continuum configurations. These embedding maps should be selected according to the dynamics of the system, as a choice of embedding maps will determine a truncation of the renormalization flow.Comment: 22 page

Quality evaluation of olive oil by statistical analysis of multicomponent stable isotope dilution assay data of aroma active compounds

An instrumental method for the evaluation of olive oil quality was developed. Twenty-one relevant aroma active compounds were quantified in 95 olive oil samples of different quality by headspace solid phase microextraction (HS-SPME) and dynamic headspace coupled to GC-MS. On the basis of these stable isotope dilution assay results, statistical evaluation by partial least-squares discriminant analysis (PLS-DA) was performed. Important variables were the odor activity values of ethyl isobutanoate, ethyl 2-methylbutanoate, 3-methylbutanol, butyric acid, E,E-2,4-decadienal, hexanoic acid, guaiacol, 2-phenylethanol, and the sum of the odor activity values of Z-3-hexenal, E-2-hexenal, Z-3-hexenyl acetate, and Z-3-hexenol. Classification performed with these variables predicted 88% of the olive oils? quality correctly. Additionally, the aroma compounds, which are characteristic for some off-flavors, were dissolved in refined plant oil. Sensory evaluation of these models demonstrated that the off-flavors rancid, fusty, and vinegary could be successfully simulated by a limited number of odorants

Characterisation of Dalmarnock Fire Test One

Journal paperThe Dalmarnock Tests comprise a set of fire experiments conducted in a real high-rise building in July 2006. The two main tests took place in identical flats, Test One allowing the fire to develop freely to post-flashover conditions while Test Two incorporated sensor-informed ventilation management. The test compartments were furnished with regular living room/office items and fully instrumented with high sensor densities. The furniture and objects acting as fuel were arranged to provide conditions that favour repeatability. A full description of the set up of the tests, including fire monitoring sensors, is provided. Focus is on the larger Test One fire for which the major events are reported together with a thorough characterisation of the fire using sensor information. The main aim of the experiments was to collect a comprehensive set of data from a realistic fire scenario that had a resolution compatible with the output of field models. The characterisation of Test One provides a platform with potential for analytical and computational fire model validation

AI-powered transmitted light microscopy for functional analysis of live cells

Transmitted light microscopy can readily visualize the morphology of living cells. Here, we introduce artificial-intelligence-powered transmitted light microscopy (AIM) for subcellular structure identification and labeling-free functional analysis of live cells. AIM provides accurate images of subcellular organelles; allows identification of cellular and functional characteristics (cell type, viability, and maturation stage); and facilitates live cell tracking and multimodality analysis of immune cells in their native form without labeling

Augmented Two-Channel Arrhythmia Detection: An Efficient Diagnostic Method for Implantable Devices

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75624/1/j.1540-8159.1996.tb03164.x.pd

EXPLORING ANTICORRELATIONS AND LIGHT ELEMENT VARIATIONS IN NORTHERN GLOBULAR CLUSTERS OBSERVED BY THE APOGEE SURVEY

We investigate the light-element behavior of red giant stars in northern globular clusters (GCs) observed by the SDSS-III Apache Point Observatory Galactic Evolution Experiment. We derive abundances of 9 elements (Fe, C, N, O, Mg, Al, Si, Ca, and Ti) for 428 red giant stars in 10 GCs. The intrinsic abundance range relative to measurement errors is examined, and the well-known C–N and Mg–Al anticorrelations are explored using an extreme-deconvolution code for the first time in a consistent way. We find that Mg and Al drive the population membership in most clusters, except in M107 and M71, the two most metal-rich clusters in our study, where the grouping is most sensitive to N. We also find a diversity in the abundance distributions, with some clusters exhibiting clear abundance bimodalities (for example M3 and M53) while others show extended distributions. The spread of Al abundances increases significantly as cluster average metallicity decreases as previously found by other works, which we take as evidence that low metallicity, intermediate mass AGB polluters were more common in the more metal-poor clusters. The statistically significant correlation of [Al/Fe] with [Si/Fe] in M15 suggests that 28Si leakage has occurred in this cluster. We also present C, N, and O abundances for stars cooler than 4500 K and examine the behavior of A(C+N+O) in each cluster as a function of temperature and [Al/Fe]. The scatter of A(C+N +O) is close to its estimated uncertainty in all clusters and independent of stellar temperature. A(C+N+O) exhibits small correlations and anticorrelations with [Al/Fe] in M3 and M13, but we cannot be certain about these relations given the size of our abundance uncertainties. Star-to-star variations of a-element (Si, Ca, Ti) abundances are comparable to our estimated errors in all clusters