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We present OpenDosimeter (https://opendosimeter.org/), an open hardware solution for real-time personal X-ray dose monitoring based on a scintillation counter. Using an X-ray sensor assembly (LYSO + SiPM) on a custom board powered by a Raspberry Pi Pico, OpenDosimeter provides real-time feedback (1 Hz), data logging (10 hours), and battery-powered operation. One of the core innovations is that we calibrate the device using $^{241}$Am found in ionization smoke detectors. Specifically, we use the $\gamma$-emissions to spectrally calibrate the dosimeter, then calculate the effective dose from X-ray exposure by compensating for the scintillator absorption efficiency and applying energy-to-dose coefficients derived from tabulated data in the ICRP 116 publication. We demonstrate that this transparent approach enables real-time dose rate readings with a linear response between 0.1-1000 $\mu$Sv/h at $\pm$25% accuracy, tested for energies up to 120 keV. The maximum dose rate readings are limited by pile-up effects when approaching count rate saturation ($\sim$77 kcps at $\sim$13 $\mu$s average pulse processing time). The total component cost for making an OpenDosimeter is <\$100, which, combined with its open design (both hardware and software), enables cost-effective local reproducibility on a global scale. This paper complements the open-source documentation by explaining the underlying technology, the algorithm for dose calculation, and areas for future improvement., Comment: 7 pages, 3 figures

We analyze call center data on properties such as agent heterogeneity, customer patience and breaks. Then we compare simulation models that are different in the ways these properties are modeled. We classify them according to the extend in which they approach the actual service level and average waiting times. We obtain a theoretical understanding on how to distinguish between the model error and other aspects such as random noise. We conclude that modeling explicitly breaks and agent heterogeneity is crucial for obtaining a precise model.

The astronomical detection of formamide (NH$_2$CHO) toward various star-forming regions and in cometary material implies that the simplest amide might have an early origin in dark molecular clouds at low temperatures. Laboratory studies have proven the efficient NH$_2$CHO formation in interstellar CO:NH$_3$ ice analogs upon energetic processing. However, it is still under debate, whether the proposed radical-radical recombination reactions forming complex organic molecules remain valid in an abundant H$_2$O environment. The aim of this work was to investigate the formation of NH$_2$CHO in H$_2$O- and CO-rich ices under conditions prevailing in molecular clouds. Therefore, different ice mixtures composed of H$_2$O:CO:NH$_3$ (10:5:1), CO:NH$_3$ (4:1), and CO:NH$_3$ (0.6:1) were exposed to vacuum ultraviolet photons in an ultra-high vacuum chamber at 10 K. Fourier-transform infrared spectroscopy was utilized to monitor in situ the initial and newly formed species as a function of photon fluence. The infrared spectral identifications are complementarily secured by a temperature-programmed desorption experiment combined with a quadrupole mass spectrometer. The energetic processing of CO:NH$_3$ ice mixtures mainly leads to the NH$_2$CHO formation, along with its chemical derivatives such as isocyanic acid (HNCO) and cyanate ion (OCN$^-$). The formation kinetics of NH$_2$CHO shows an explicit dependency on ice ratios and compositions; the highest yield is found in H$_2$O-rich ice. The astronomical relevance of the resulting reaction network is discussed., Comment: 16 pages, 6 figures, 2 tables

Fast Radio Bursts must be powered by uniquely energetic emission mechanisms. This requirement has eliminated a number of possible source types, but several remain. Identifying the physical nature of Fast Radio Burst (FRB) emitters arguably requires good localisation of more detections, and broadband studies enabled by real-time alerting. We here present the Apertif Radio Transient System (ARTS), a supercomputing radio-telescope instrument that performs real-time FRB detection and localisation on the Westerbork Synthesis Radio Telescope (WSRT) interferometer. It reaches coherent-addition sensitivity over the entire field of the view of the primary dish beam. After commissioning results verified the system performed as planned, we initiated the Apertif FRB survey (ALERT). Over the first 5 weeks we observed at design sensitivity in 2019, we detected 5 new FRBs, and interferometrically localised each of these to 0.4--10 sq. arcmin. All detections are broad band and very narrow, of order 1 ms duration, and unscattered. Dispersion measures are generally high. Only through the very high time and frequency resolution of ARTS are these hard-to-find FRBs detected, producing an unbiased view of the intrinsic population properties. Most localisation regions are small enough to rule out the presence of associated persistent radio sources. Three FRBs cut through the halos of M31 and M33. We demonstrate that Apertif can localise one-off FRBs with an accuracy that maps magneto-ionic material along well-defined lines of sight. The rate of 1 every ~7 days next ensures a considerable number of new sources are detected for such study. The combination of detection rate and localisation accuracy exemplified by the 5 first ARTS FRBs thus marks a new phase in which a growing number of bursts can be used to probe our Universe., Comment: Accepted version

With the development of new sensors and monitoring devices, more sources of data become available to be used as inputs for machine learning models. These can on the one hand help to improve the accuracy of a model. On the other hand, combining these new inputs with historical data remains a challenge that has not yet been studied in enough detail. In this work, we propose a transfer learning algorithm that combines new and historical data with different input dimensions. This approach is easy to implement, efficient, with computational complexity equivalent to the ordinary least-squares method, and requires no hyperparameter tuning, making it straightforward to apply when the new data is limited. Different from other approaches, we provide a rigorous theoretical study of its robustness, showing that it cannot be outperformed by a baseline that utilizes only the new data. Our approach achieves state-of-the-art performance on 9 real-life datasets, outperforming the linear DSFT, another linear transfer learning algorithm, and performing comparably to non-linear DSFT., Comment: Manuscript accepted for publication at the Journal of Computational Mathematics and Data Science. Code available at https://github.com/lpsilvestrin/incremental_input_tl

Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering, based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Demand forecasting is extremely important in revenue management. After all, it is one of the inputs to an optimisation method which aim is to maximize revenue. Most, if not all, forecasting methods use historical data to forecast the future, disregarding the "why". In this paper, we combine data from multiple sources, including competitor data, pricing, social media, safety and airline reviews. Next, we study five competitor pricing movements that, we hypothesize, affect customer behavior when presented a set of itineraries. Using real airline data for ten different OD-pairs and by means of Extreme Gradient Boosting, we show that customer behavior can be categorized into price-sensitive, schedule-sensitive and comfort ODs. Through a simulation study, we show that this model produces forecasts that result in higher revenue than traditional, time series forecasts.

We describe the models we built for hospital admissions and occupancy of COVID-19 patients in the Netherlands. These models were used to make short-term decisions about transfers of patients between regions and for long-term policy making. We motivate and describe the model we used for predicting admissions and how we use this to make predictions on occupancy.

Many models such as Long Short Term Memory (LSTMs), Gated Recurrent Units (GRUs) and transformers have been developed to classify time series data with the assumption that events in a sequence are ordered. On the other hand, fewer models have been developed for set based inputs, where order does not matter. There are several use cases where data is given as partially-ordered sequences because of the granularity or uncertainty of time stamps. We introduce a novel transformer based model for such prediction tasks, and benchmark against extensions of existing order invariant models. We also discuss how transition probabilities between events in a sequence can be used to improve model performance. We show that the transformer-based equal-time model outperforms extensions of existing set models on three data sets.

Forecasting demand is one of the fundamental components of a successful revenue management system in hospitality. The industry requires understandable models that contribute to adaptability by a revenue management department to make data-driven decisions. Data analysis and forecasts prove an essential role for the time until the check-in date, which differs per day of week. This paper aims to provide a new model, which is inspired by cubic smoothing splines, resulting in smooth demand curves per rate class over time until the check-in date. This model regulates the error between data points and a smooth curve, and is therefore able to capture natural guest behavior. The forecast is obtained by solving a linear programming model, which enables the incorporation of industry knowledge in the form of constraints. Using data from a major hotel chain, a lower error and 13.3% more revenue is obtained.

We give an overview of the practice and science of call center workforce planning, where we evaluate the commonly used methods by their quality and the theory by its applicability. As such this paper is useful for developers and consultants interested in the background and advanced methodology of workforce management, and for researchers interested in practically relevant science.

Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) architecture to generate synthetic samples for variable length, multi-feature sequence datasets. In this model, we develop a GAN architecture with an additional autoencoder component, where recurrent neural networks (RNNs) are used for each component of the model in order to generate synthetic data to improve classification accuracy for a highly imbalanced medical device dataset. In addition to the medical device dataset, we also evaluate the GAN-AE performance on two additional datasets and demonstrate the application of GAN-AE to a sequence-to-sequence task where both synthetic sequence inputs and sequence outputs must be generated. To evaluate the quality of the synthetic data, we train encoder-decoder models both with and without the synthetic data and compare the classification model performance. We show that a model trained with GAN-AE generated synthetic data outperforms models trained with synthetic data generated both with standard oversampling techniques such as SMOTE and Autoencoders as well as with state of the art GAN-based models.

One of the most celebrated results in mechanism design is Myerson's characterization of the revenue optimal auction for selling a single item. However, this result relies heavily on the assumption that buyers are indifferent to risk. In this paper we investigate the case where the buyers are risk-loving, i.e. they prefer gambling to being rewarded deterministically. We use the standard model for risk from expected utility theory, where risk-loving behavior is represented by a convex utility function. We focus our attention on the special case of exponential utility functions. We characterize the optimal auction and show that randomization can be used to extract more revenue than when buyers are risk-neutral. Most importantly, we show that the optimal auction is simple: the optimal revenue can be extracted using a randomized take-it-or-leave-it price for a single buyer and using a loser-pay auction, a variant of the all-pay auction, for multiple buyers. Finally, we show that these results no longer hold for convex utility functions beyond exponential., Comment: To appear in 14th Conference on Web and Internet Economics (WINE 2018)

When deciding where to place access points in a wireless network, it is useful to model the signal propagation loss between a proposed antenna location and the areas it may cover. The indoor dominant path (IDP) model, introduced by W\"{o}lfle et al., is shown in the literature to have good validation and generalization error, is faster to compute than competing methods, and is used in commercial software such as WinProp, iBwave Design, and CellTrace. Previously, the algorithms known for computing it involved a worst-case exponential-time tree search, with pruning heuristics to speed it up. We prove that the IDP model can be reduced to a parametric shortest path computation on a graph derived from the walls in the floorplan. It therefore admits a quasipolynomial-time (i.e., $n^{O(\log n)}$) algorithm. We also give a practical approximation algorithm based on running a small constant number of shortest path computations. Its provable worst-case additive error (in dB) can be made arbitrarily small via appropriate choices of parameters, and is well below 1dB for reasonable choices. We evaluate our approximation algorithm empirically against the exact IDP model, and show that it consistently beats its theoretical worst-case bounds, solving the model exactly (i.e., no error) in the vast majority of cases., Comment: 12 pages, 8 figures, accepted to MobiHoc 2018

We consider the stochastic bandit problem in the sublinear space setting, where one cannot record the win-loss record for all $K$ arms. We give an algorithm using $O(1)$ words of space with regret \[ \sum_{i=1}^{K}\frac{1}{\Delta_i}\log \frac{\Delta_i}{\Delta}\log T \] where $\Delta_i$ is the gap between the best arm and arm $i$ and $\Delta$ is the gap between the best and the second-best arms. If the rewards are bounded away from $0$ and $1$, this is within an $O(\log 1/\Delta)$ factor of the optimum regret possible without space constraints., Comment: AISTATS 2018

Distribution network reconfiguration (DNR) is a tool used by operators to balance line load flows and mitigate losses. As distributed generation and flexible load adoption increases, the impact of DNR on the security, efficiency, and reliability of the grid will increase as well. Today, heuristic-based actions like branch exchange are routinely taken, with no theoretical guarantee of their optimality. This paper considers loss minimization via DNR, which changes the on/off status of switches in the network. The goal is to ensure a radial final configuration (called a spanning tree in the algorithms literature) that spans all network buses and connects them to the substation (called the root of the tree) through a single path. We prove that the associated combinatorial optimization problem is strongly NP-hard and thus likely cannot be solved efficiently. We formulate the loss minimization problem as a supermodular function minimization under a single matroid basis constraint, and use existing algorithms to propose a polynomial time local search algorithm for the DNR problem at hand and derive performance bounds. We show that our algorithm is equivalent to the extensively used branch exchange algorithm, for which, to the best of our knowledge, we pioneer in proposing a theoretical performance bound. Finally, we use a 33-bus network to compare our algorithm's performance to several algorithms published in the literature., Comment: 10 pages, 6 figures, to appear in 51st Hawaii International Conference on System Sciences (HICSS), Hawaii, USA, Jan. 3-6, 2018

Selfish routing is a central problem in algorithmic game theory, with one of the principal applications being that of routing in road networks. Inspired by the emergence of routing technologies and autonomous driving, we revisit selfish routing and consider three possible outcomes of it: (i) $\theta$-Positive Nash Equilibrium flow, where every path that has non-zero flow on all of its edges has cost no greater than $\theta$ times the cost of any other path, (ii) $\theta$-Used Nash Equilibrium flow, where every used path that appears in the path flow decomposition has cost no greater than $\theta$ times the cost of any other path, and (iii) $\theta$-Envy Free flow, where every path that appears in the path flow decomposition has cost no greater than $\theta$ times the cost of any other path in the path flow decomposition. We first examine the relations of these outcomes among each other and then measure their possible impact on the network's performance. Afterwards, we examine the computational complexity of finding such flows of minimum social cost and give a range for $\theta$ for which this task is easy and a range for $\theta$ for which this task is NP-hard. Finally, we propose deterministic strategies which, in a worst case approach, can be used by a central planner in order to provide good such flows, and further introduce a natural idea for randomly routing players after giving them specific guarantees about their costs in the randomized routing, as a tool for the central planner to implement a desired flow.

Small changes to the parameters of a system can lead to abrupt qualitative changes of its behavior, a phenomenon known as bifurcation. Such instabilities are typically considered problematic, however, we show that their power can be leveraged to design novel types of mechanisms. Hysteresis mechanisms use transient changes of system parameters to induce a permanent improvement to its performance via optimal equilibrium selection. Optimal control mechanisms induce convergence to states whose performance is better than even the best equilibrium. We apply these mechanisms in two different settings that illustrate the versatility of bifurcation mechanism design. In the first one we explore how introducing flat taxation can improve social welfare, despite decreasing agent "rationality", by destabilizing inefficient equilibria. From there we move on to consider a well known game of tumor metabolism and use our approach to derive novel cancer treatment strategies.

It is demonstrated that the often observed broadness of the molecular weight distribution obtained from latex particles synthesized by means of surfactant-free emulsion polymerization results from the multistage kinetics. The initial stage of the polymerization, by which the primary particles are formed, is of the 01-kind which means that it can be assumed that the particles are so small that at any moment of time there is no more than one radical chain per particle. After the aggregation of primary particles into secondary particles, the so called coagulative nucleation step, the polymerization kinetics in the subsequently coalesced secondary particles is of the pseudo-bulk kind which means that there are so many radicals in the particles that the polymerization process proceeds as in bulk. The important consequence is that the molecular weight of the 01-process is about one order of magnitude larger than that of the pseudo-bulk process. Hence, each of these polymerization modes and the aggregation stage in-between leave their traces in the molecular weight distribution as is shown by experiments aimed at prolonging the initial formation kinetics. Bimodal molecular weight distributions are found both for ionic and non-ionic initiators.

We offer a brief overview of the solvent-based graphene production and summarize the current knowledge on the formation mechanism of graphite oxide that proceeds via graphite intercalation compounds. In addition, the results of our in situ X-ray diffraction investigation into this process are presented, discussed and contrasted to the findings by other authors, who employed the same oxidation protocol but examined the samples by ex situ X-ray diffraction. Our results suggest that, contrary to the numerous reports by other authors, no strong crystalline order, unique to graphite intercalation compounds as well as graphite oxide, develops if they remain in concentrated acid. Furthermore, it also appears that, depending on the concentration, sulfuric acid molecules significantly weaken graphene-graphene interactions in graphite. Consequently, concentrated sulfuric acid may be a good solvent for graphene dispersions, if only there is sufficient energy input to separate the layers of graphene.

We consider optimal route planning when the objective function is a general nonlinear and non-monotonic function. Such an objective models user behavior more accurately, for example, when a user is risk-averse, or the utility function needs to capture a penalty for early arrival. It is known that as nonlinearity arises, the problem becomes NP-hard and little is known about computing optimal solutions when in addition there is no monotonicity guarantee. We show that an approximately optimal non-simple path can be efficiently computed under some natural constraints. In particular, we provide a fully polynomial approximation scheme under hop constraints. Our approximation algorithm can extend to run in pseudo-polynomial time under a more general linear constraint that sometimes is useful. As a by-product, we show that our algorithm can be applied to the problem of finding a path that is most likely to be on time for a given deadline., Comment: 9 pages, 2 figures, main part of this paper is to be appear in AAAI'16

The aimed high sensitivities and large fields of view of the new generation of interferometers impose to reach high dynamic range of order $\sim$1:$10^6$ to 1:$10^8$ in the case of the Square Kilometer Array. The main problem is the calibration and correction of the Direction Dependent Effects (DDE) that can affect the electro-magnetic field (antenna beams, ionosphere, Faraday rotation, etc.). As shown earlier the A-Projection is a fast and accurate algorithm that can potentially correct for any given DDE in the imaging step. With its very wide field of view, low operating frequency ($\sim30-250$ MHz), long baselines, and complex station-dependent beam patterns, the Low Frequency Array (LOFAR) is certainly the most complex SKA precursor. In this paper we present a few implementations of A-Projection applied to LOFAR that can deal with non-unitary station beams and non-diagonal Mueller matrices. The algorithm is designed to correct for all the DDE, including individual antenna, projection of the dipoles on the sky, beam forming and ionospheric effects. We describe a few important algorithmic optimizations related to LOFAR's architecture allowing us to build a fast imager. Based on simulated datasets we show that A-Projection can give dramatic dynamic range improvement for both phased array beams and ionospheric effects. We will use this algorithm for the construction of the deepest extragalactic surveys, comprising hundreds of days of integration.

The Square Kilometre Array (SKA) will have a low frequency component (SKA-low) which has as one of its main science goals the study of the redshifted 21cm line from the earliest phases of star and galaxy formation in the Universe. This 21cm signal provides a new and unique window on both the formation of the first stars and accreting black holes and the later period of substantial ionization of the intergalactic medium. The signal will teach us fundamental new things about the earliest phases of structure formation, cosmology and even has the potential to lead to the discovery of new physical phenomena. Here we present a white paper with an overview of the science questions that SKA-low can address, how we plan to tackle these questions and what this implies for the basic design of the telescope., Comment: Accepted for publication in Experimental Astronomy, reformatted to 57 pages, some updated and improved figures and minor changes and updates to the text

Measuring radio waves at low frequencies offers a new window to study cosmic magnetism, and LOFAR is the ideal radio telescope to open this window widely. The LOFAR Magnetism Key Science Project (MKSP) draws together expertise from multiple fields of magnetism science and intends to use LOFAR to tackle fundamental questions on cosmic magnetism by exploiting a variety of observational techniques. Surveys will provide diffuse emission from the Milky Way and from nearby galaxies, tracking the propagation of long-lived cosmic-ray electrons through magnetic field structures, to search for radio halos around spiral and dwarf galaxies and for magnetic fields in intergalactic space. Targeted deep-field observations of selected nearby galaxies and suspected intergalactic filaments allow sensitive mapping of weak magnetic fields through Rotation Measure (RM) grids. High-resolution observations of protostellar jets and giant radio galaxies reveal structures on small physical scales and at high redshifts, whilst pulsar RMs map large-scale magnetic structures of the Galactic disk and halo in revolutionary detail. The MKSP is responsible for the development of polarization calibration and processing, thus widening the scientific power of LOFAR., Comment: Proceedings of "Magnetic Fields in the Universe: From Laboratory and Stars to Primordial Structures", 2011 Aug. 21-27 in Zakopane/Poland, eds. M. Soida et al

The Olkin-Baker functional equation is closely related to the celebrated Lukacs characterization of the gamma distribution. Its deeper understanding is essential to settle a challenging question of multivariate extensions of the Lukacs theorem. In this paper, first, we provide a new approach to the additive Olkin-Baker equation which holds almost everywhere on (0,\infinity)^2 (with respect to the Lebesgue measure on R^2) under measurability assumption. Second, this new approach is adapted to the case when unknown functions are allowed to be non-measurable and the complete solution is given in such a general case. Third, the Olkin-Baker equation holding outside of a set from proper linearly invariant ideal of subsets of R^2 is considered.

The Low Frequency Array (LOFAR) will operate between 10 and 250 MHz, and will observe the low frequency Universe to an unprecedented sensitivity and angular resolution. The construction and commissioning of LOFAR is well underway, with over 27 of the Dutch stations and five International stations routinely performing both single-station and interferometric observations over the frequency range that LOFAR is anticipated to operate at. Here, we summarize the capabilities of LOFAR and report on some of the early commissioning imaging of Cygnus A., Comment: 6 pages, 4 figures. 10th European VLBI Network Symposium and EVN Users Meeting: VLBI and the new generation of radio arrays, Manchester, UK, September 20-24, 2010

One of the science drivers of the new Low Frequency Array (LOFAR) is large-area surveys of the low-frequency radio sky. Realizing this goal requires automated processing of the interferometric data, such that fully calibrated images are produced by the system during survey operations. The LOFAR Imaging Pipeline is the tool intended for this purpose, and is now undergoing significant commissioning work. The pipeline is now functional as an automated processing chain. Here we present several recent LOFAR images that have been produced during the still ongoing commissioning period. These early LOFAR images are representative of some of the science goals of the commissioning team members., Comment: 11 pages, 6 figures. Accepted for publication in proceedings of "ISKAF2010 Science Meeting", PoS(ISKAF2010)057

Double-double radio galaxies (DDRGs) offer a unique opportunity for us to study multiple episodes of jet activity in large-scale radio sources. We use radio data from the Very Large Array and the literature to model two DDRGs, B1450+333 and B1834+620, in terms of their dynamical evolution. We find that the standard Fanaroff-Riley II model is able to explain the properties of the two outer lobes of each source, whereby the lobes are formed by ram-pressure balance of a shock at the end of the jet with the surrounding medium. The inner pairs of lobes, however, are not well-described by the standard model. Instead we interpret the inner lobes as arising from the emission of relativistic electrons within the outer lobes, which are compressed and re-accelerated by the bow-shock in front of the restarted jets and within the outer lobes. The predicted rapid progression of the inner lobes through the outer lobes requires the eventual development of a hotspot at the edge of the outer lobe, causing the DDRG ultimately to resemble a standard Fanaroff-Riley II radio galaxy. This may suggest that DDRGs are a brief, yet normal, phase of the evolution of large-scale radio galaxies., Comment: Accepted for publication in MNRAS. 17 pages; 15 figures, 2 of which are in colour

We present Hubble Space Telescope UV and optical imaging of the radio galaxy 3C 236, whose relic 4 Mpc radio jet lobes and inner 2 kpc CSS radio source are evidence of multiple epochs of AGN activity. Our data confirm the presence of four bright knots of FUV emission in an arc along the edge of the inner circumnuclear dust disk in the galaxy's nucleus, as well as FUV emission cospatial with the nucleus itself. We interpret these to be sites of recent or ongoing star formation. We present photometry of these knots, as well as an estimate for the internal extinction in the source using the Balmer decrement from SDSS spectroscopy. We estimate the ages of the knots by comparing our extinction-corrected photometry with stellar population synthesis models. We find the four knots cospatial with the dusty disk to be young, of order 10^7 yr old. The FUV emission in the nucleus is likely due to an episode of star formation triggered ~10^9 yr ago. We argue that the young 10^7 yr old knots stem from an episode of star formation that was roughly coeval with the event resulting in reignition of radio activity, creating the CSS source. The 10^9 yr old stars in the nucleus may be associated with the previous epoch of activity that generated the 4 Mpc relic source, before it was cut off by exhaustion or interruption. The ages of the knots, considered in context with the disturbed morphology of the nuclear dust and the double-double morphology of the "old" and "young" radio sources, present evidence for an episodic AGN/starburst connection. We suggest that the AGN fuel supply was interrupted for ~10^7 yr due to a minor merger event and has now been restored, and the resultant non-steady flow of gas toward the nucleus is likely responsible for both the new episode of infall-induced star formation and also the multiple epochs of radio activity., Comment: 15 pages, 7 figures. Accepted for publication in ApJ.

A number of experiments are set to measure the 21-cm signal of neutral hydrogen from the Epoch of Reionization (EoR). The common denominator of these experiments are the large data sets produced, contaminated by various instrumental effects, ionospheric distortions, RFI and strong Galactic and extragalactic foregrounds. In this paper, the first in a series, we present the Data Model that will be the basis of the signal analysis for the LOFAR (Low Frequency Array) EoR Key Science Project (LOFAR EoR KSP). Using this data model we simulate realistic visibility data sets over a wide frequency band, taking properly into account all currently known instrumental corruptions (e.g. direction-dependent gains, complex gains, polarization effects, noise, etc). We then apply primary calibration errors to the data in a statistical sense, assuming that the calibration errors are random Gaussian variates at a level consistent with our current knowledge based on observations with the LOFAR Core Station 1. Our aim is to demonstrate how the systematics of an interferometric measurement affect the quality of the calibrated data, how errors correlate and propagate, and in the long run how this can lead to new calibration strategies. We present results of these simulations and the inversion process and extraction procedure. We also discuss some general properties of the coherency matrix and Jones formalism that might prove useful in solving the calibration problem of aperture synthesis arrays. We conclude that even in the presence of realistic noise and instrumental errors, the statistical signature of the EoR signal can be detected by LOFAR with relatively small errors. A detailed study of the statistical properties of our data model and more complex instrumental models will be considered in the future., Comment: 20 pages, 9 figures

Radio Interferometry is an essential method for astronomical observations. Self-calibration techniques have increased the quality of the radio astronomical observations (and hence the science) by orders of magnitude. Recently, there is a drive towards sensor arrays built using inexpensive hardware and distributed over a wide area acting as radio interferometers. Calibration of such arrays poses new problems in terms of computational cost as well as in performance of existing calibration algorithms. We consider the application of the Space Alternating Generalized Expectation Maximization (SAGE) \cite{Fess94} algorithm for calibration of radio interferometric arrays. Application to real data shows that this is an improvement over existing calibration algorithms that are based on direct, deterministic non linear optimization. As presented in this paper, we can improve the computational cost as well as the quality of the calibration using this algorithm., Comment: 6 pages, 3 figures, Appearing in 13th IEEE DSP workshop (IEEE Signal Processing Society)

A small number of quasars exhibit interstellar scintillation on time-scales less than an hour; their scintillation patterns are all known to be anisotropic. Here we consider a totally anisotropic model in which the scintillation pattern is effectively one-dimensional. For the persistent rapid scintillators J1819+3845 and PKS1257-326 we show that this model offers a good description of the two-station time-delay measurements and the annual cycle in the scintillation time-scale. Generalising the model to finite anisotropy yields a better match to the data but the improvement is not significant and the two additional parameters which are required to describe this model are not justified by the existing data. The extreme anisotropy we infer for the scintillation patterns must be attributed to the scattering medium rather than a highly elongated source. For J1819+3845 the totally anisotropic model predicts that the particular radio flux variations seen between mid July and late August should repeat between late August and mid November, and then again between mid November and late December as the Earth twice changes its direction of motion across the scintillation pattern. If this effect can be observed then the minor-axis velocity component of the screen and the orientation of that axis can both be precisely determined. In reality the axis ratio is finite, albeit large, and spatial decorrelation of the flux pattern along the major axis may be observable via differences in the pairwise fluxes within this overlap region; in this case we can also constrain both the major-axis velocity component of the screen and the magnitude of the anisotropy., Comment: 5 pages, 4 figures, MNRAS submitted

Future high redshift 21-cm experiments will suffer from a high degree of contamination, due both to astrophysical foregrounds and to non-astrophysical and instrumental effects. In order to reliably extract the cosmological signal from the observed data, it is essential to understand very well all data components and their influence on the extracted signal. Here we present simulated astrophysical foregrounds datacubes and discuss their possible statistical effects on the data. The foreground maps are produced assuming 5 deg x 5 deg windows that match those expected to be observed by the LOFAR Epoch-of-Reionization (EoR) key science project. We show that with the expected LOFAR-EoR sky and receiver noise levels, which amount to ~52 mK at 150 MHz after 300 hours of total observing time, a simple polynomial fit allows a statistical reconstruction of the signal. We also show that the polynomial fitting will work for maps with realistic yet idealised instrument response, i.e., a response that includes only a uniform uv coverage as a function of frequency and ignores many other uncertainties. Polarized galactic synchrotron maps that include internal polarization and a number of Faraday screens along the line of sight are also simulated. The importance of these stems from the fact that the LOFAR instrument, in common with all current interferometric EoR experiments has an instrumentally polarized response., Comment: 18 figures, 3 tables, accepted to be published in MNRAS

The 4.8 GHz lightcurves of the scintillating intra-day variable quasar J1819+3845 during 2004-5 exhibit sharp structure, down to a time scale of 15 minutes, that was absent from lightcurves taken prior to this period and from the 2006 lightcurves. Analysis of the lightcurve power spectra show that the variations must be due to the emergence of new structure in the source. The power spectra yield a scattering screen distance of 3.8 +/- 0.3 pc for a best-fit v_ISS=59 +/- 0.5 km/s or 2.0 +/- 0.3 pc for the scintillation velocity reported by Dennett-Thorpe & de Bruyn (2003). The turbulence is required to be exceptionally turbulent, with C_N^2 > 0.7 Delta L_pc^{-1} m^{-20/3} for scattering material of thickness Delta L_{pc} pc along the ray path. The 2004 power spectrum can be explained in terms of a double source with a component separation 240 +/- 15 microas in 2004., Comment: MNRAS Lett (accepted), version with high-resolution figures at http://www.astro.caltech.edu/~jpm/MdB1819.pdf

auto-ignore This paper has been withdrawn by the authors due to dublicate submission. To download the paper please go to astro-ph/0611081, Comment: This paper has been withdrawn

We report the discovery of fast, frequency-dependent intensity variations from the scintillating intra-day variable quasar J1819+3845 at a wavelength of 21cm which resemble diffractive interstellar scintillations observed in pulsars. The timescale (down to 20 min) and the bandwidth (frequency decorrelation bandwidth of 160 MHz) of the observed variations jointly imply that the component of the source exhibiting this scintillation must possess a brightness temperature well in excess of the inverse Compton limit. A specific model in which both the source and scintillation pattern are isotropic implies a brightness temperature 0.5 x 10^13 z_{pc} K, where previous estimates place the distance to the scattering medium in the range z_{pc}=4-12pc, yielding a minimum brightness temperature >20 times the inverse Compton limit. An independent estimate of the screen distance using the 21cm scintillation properties alone indicates a minimum screen distance of z approx 40pc and a brightness temperature above 2 x 10^14 K. There is no evidence for anisotropy in the scattering medium or source from the scintillation characteristics, but these estimates may be reduced by a factor comparable to the axial ratio if the source is indeed elongated., Comment: A&A in press, 18 pages, 9 figs

We study the impact of service-time distributions on the distribution of the maximum queue length during a busy period for the M^X/G/1 queue. The maximum queue length is an important random variable to understand when designing the buffer size for finite buffer (M/G/1/n) systems. We show the somewhat surprising result that for three variations of the preemptive LCFS discipline, the maximum queue length during a busy period is smaller when service times are more variable (in the convex sense)., Comment: 12 pages

With the Westerbork Synthesis Radio Telescope (WSRT), multi-frequency polarimetric images were taken of the diffuse radio synchrotron background in a region centered on (l,b) = (161,16). The observations were done simultaneously in 5 frequency bands from 341 MHz to 375 MHz, with 5 arcmin resolution. Ubiquitous structure on arcminute and degree scales in the polarized intensity and polarization angle, combined with no observed structure in total intensity, indicates that the structure in the polarized radiation must be due to Faraday rotation and depolarization mostly in the warm nearby Galactic interstellar medium (ISM). Beam depolarization most likely creates "depolarization canals" of one beam wide, while depth depolarization is responsible for creating most of the structure on scales larger than a beam width. Rotation measures RM are in the range -17 < RM < 10 rad/m2 with a non-zero average of about -3.4 rad/m2. The gradient and average RM are consistent with a regular magnetic field of about 1 uG which has a pitch angle of p = -14 degrees. 13 Extragalactic sources in the field have |RM| < 13 rad/m2, with an estimated intrinsic source contribution of 3.6 rad/m2. The RMs of the extragalactic sources show a gradient (with a sign reversal) that is about 3 times larger than the gradient in the RMs of the diffuse emission, and that is approximately in Galactic latitude. This difference is ascribed to a vastly different effective length of the line of sight. The observations are interpreted in terms of a single-cell-size model of the warm ISM which contains gas and magnetic fields, with a polarized background., Comment: 15 pages, 14 figures, to be published in A&A

This paper describes an investigation of the early evolution of extragalactic radio sources using samples of faint and bright Gigahertz Peaked Spectrum (GPS) and Compact Steep Spectrum (CSS) radio galaxies. Correlations found between their peak frequency, peak flux density and angular size provide strong evidence that synchrotron self absorption is the cause of the spectral turnovers, and indicate that young radio sources evolve in a self-similar way. In addition, the data seem to suggest that the sources are in equipartition while they evolve. If GPS sources evolve to large size radio sources, their redshift dependent birth-functions should be the same. Therefore, since the lifetimes of radio sources are thought to be short compared to the Hubble time, the observed difference in redshift distribution between GPS and large size sources must be due to a difference in slope of their luminosity functions. We argue that this slope is strongly affected by the luminosity evolution of the individual sources. A scenario for the luminosity evolution is proposed in which GPS sources increase in luminosity and large scale radio sources decrease in luminosity with time. This evolution scenario is expected for a ram-pressure confined radio source in a surrounding medium with a King profile density. In the inner parts of the King profile, the density of the medium is constant and the radio source builds up its luminosity, but after it grows large enough the density of th e surrounding medium declines and the luminosity of the radio source decreases. A comparison of the local luminosity function (LLF) of GPS galaxies with that of extended sources is a good test for this evolution scenario [abridged]., Comment: LaTeX, 11 pages, 8 figures; Accepted by MNRAS. Related papers may be found at http://www.ast.cam.ac.uk/~snellen . Valuable comments of referee incorporated. More discussion on simulations

We report on a first measurement of tensor analyzing powers in quasi-elastic electron-deuteron scattering at an average three-momentum transfer of 1.7 fm$^{-1}$. Data sensitive to the spin-dependent nucleon density in the deuteron were obtained for missing momenta up to 150 MeV/$c$ with a tensor polarized $^2$H target internal to an electron storage ring. The data are well described by a calculation that includes the effects of final-state interaction, meson-exchange and isobar currents, and leading-order relativistic contributions., Comment: 4 pages, 3 figures

Considers the paradox of a liberal, pluralist society supporting (subsidizing) religious schools whose beliefs are more restrictive and judgmental. Argues that recognition of group rights is sanctioned in liberal thought as long as it does not impinge on individual rights. Discusses liberal responses to conflicts between communitarian concepts and autonomy. (MJP)