bluuebunny/crossref_metadata_2025 huggingface dataset:
Morphometric Change Detection of Lake Hawassa in the Ethiopian Rift Valley
Authors: Abebe Yonas , Bitew Menberu , Ayenew Tenalem , Alo Clement , Cherinet Assegid , Dadi Mulugeta
Published: May 2018

The Ethiopian Rift Valley lakes have been subjected to environmental and ecological changes due to recent development endeavors and natural phenomena, which are visible in the alterations to the quality and quantity of the water resources. Monitoring lakes for temporal and spatial alterations has become a valuable indicator of environmental change. In this regard, hydrographic information has a paramount importance. The first extensive hydrographic survey of Lake Hawassa was conducted in 1999. In this study, a bathymetric map was prepared using advances in global positioning systems, portable sonar sounder technology, geostatistics, remote sensing and geographic information system (GIS) software analysis tools with the aim of detecting morphometric changes. Results showed that the surface area of Lake Hawassa increased by 7.5% in 1999 and 3.2% in 2011 from that of 1985. Water volume decreased by 17% between 1999 and 2011. Silt accumulated over more than 50% of the bed surface has caused a 4% loss of the lake’s storage capacity. The sedimentation patterns identified may have been strongly impacted by anthropogenic activities including urbanization and farming practices located on the northern, eastern and western sides of the lake watershed. The study demonstrated this geostatistical modeling approach to be a rapid and cost-effective method for bathymetric mapping.
Bioremediation of Aluminium from the Waste Water of a Conventional Water Treatment Plant Using the Freshwater Macroalga Oedogonium
Authors: Roberts David A. , Shiels Laura , Tickle Julian , De Nys Rocky , Paul Nicholas A.
Published: May 2018

Conventional water treatment processes use aluminium sulphate (alum) as a coagulant in the production of potable water. While alum is an inexpensive and reliable means of treating water, the process generates waste water containing dissolved Al. This waste water is primarily dealt with via on-site retention. In this study we investigate the cultivation of the freshwater macroalga Oedogonium as a means to sequester dissolved Al from waste water from a conventional water treatment plant. Furthermore, we examine the use of CO2 to manipulate the pH of cultivation as a means of enhancing the sequestration of Al by either increasing the productivity of Oedogonium or increasing the bioavailability of Al in the waste water. The relative bioavailability of Al under conditions of CO2 and no-CO2 provision was contrasted by comparing Al uptake by Diffusive Gradients in Thin Films (DGTs). Oedogonium was able to grow rapidly in the waste water (12 g dry weight m−2 day−1) while consistently sequestering Al. The Oedogonium-treated waste water had a sufficiently low Al concentration that it could be used in unrestricted irrigation in the surrounding region. When CO2 was added to the waste water containing concentrations of Al up to 8 mg L−1, there was a slight increase (~10%) in the rate of sequestration of Al by Oedogonium relative to waste water not receiving CO2. This was due to two concurrent processes. The provision of CO2 increased the productivity of Oedogonium by 15% and the bioavailability of Al by up to 200%, as measured by the DGTs. Despite this strong effect of CO2 on Al bioavailability, the increase in Al sequestration by Oedogonium when CO2 was provided was modest (~10%). Al was sequestered by Oedogonium to concentrations below permissible limits for discharge without the need for the addition CO2. The cultivation of Oedogonium in waste water from conventional treatments plants can simultaneously treat waste water for re-use and provide a biomass source for value-added applications.
Data Pre-Analysis and Ensemble of Various Artificial Neural Networks for Monthly Streamflow Forecasting
Authors: Zhou Jianzhong , Peng Tian , Zhang Chu , Sun Na
Published: May 2018

This paper introduces three artificial neural network (ANN) architectures for monthly streamflow forecasting: a radial basis function network, an extreme learning machine, and the Elman network. Three ensemble techniques, a simple average ensemble, a weighted average ensemble, and an ANN-based ensemble, were used to combine the outputs of the individual ANN models. The objective was to highlight the performance of the general regression neural network-based ensemble technique (GNE) through an improvement of monthly streamflow forecasting accuracy. Before the construction of an ANN model, data preanalysis techniques, such as empirical wavelet transform (EWT), were exploited to eliminate the oscillations of the streamflow series. Additionally, a theory of chaos phase space reconstruction was used to select the most relevant and important input variables for forecasting. The proposed GNE ensemble model has been applied for the mean monthly streamflow observation data from the Wudongde hydrological station in the Jinsha River Basin, China. Comparisons and analysis of this study have demonstrated that the denoised streamflow time series was less disordered and unsystematic than was suggested by the original time series according to chaos theory. Thus, EWT can be adopted as an effective data preanalysis technique for the prediction of monthly streamflow. Concurrently, the GNE performed better when compared with other ensemble techniques.
A New Sensorless Drive Control System for Transmissionless EVs Using a Permanent-Magnet Synchronous Motor
Authors: Shinnaka Shinji , Takeuchi Shigeru
Published: May 2018

One of the most important technologies for electric vehicles (EVs) will be drive control technology for main traction motors. It is desired for the drive control system to have the following characteristics: 1) it is based on vector control methods that allow quick, efficient and/or precise torque production; 2) it can produce 150-250% rated torque at standstill and can have wide driving-range, consequently can allow development of EVs with no variable-transmission; 3) it does not require a position/speed sensor for controlling motor drive, which has been mounted on a rotor shaft. This paper proposes a new sensorless drive control system for such EVs using a permanent-magnet synchronous motor as a main traction motor. Potential usefulness of the proposed drive control system is examined through the development of a prototype EV capable of driving on public road.
Non-linear Optimal Controller Design of Vehicle With Low Speed Operation Based On Data Mining Algorithm
Authors: Kim YoungWoo , Matsuzaki Shinya , Narikiyo Tatsuo , Kim Jong-Hae
Published: May 2018

In this paper, we realize parallel parking task based on two-stage modeling method, where parking task model and vehicle dynamical model are developed respectively and incorporated into a entire model in a seamless manner. The vehicle dynamics is highly constrained by non-holonomic constraint with nonlinear tire characteristics. In order to describe vehicle dynamics, we use a new data mining based affine system modeling method. The entire parking task model is combined with several sub-parking task models, which consist of some conditions in state-input space of the system and their transitions to another. The incorporation of the both parking task model and vehicle dynamical model is realized using finite state machine. The proposed model is very general that regardless of the initial position of the vehicle, it is successfully controlled to move into the parking space. In the later part of this paper, we present a mathematical programming based optimal control scheme where the optimal inputs are selected among the permissible set of the input variable, considering all the limitations specified by linear inequalities. In order to confirm the usefulness of the proposed method, some simulation results are shown.
Symbolism and the Adoption of Fuel-Cell Vehicles
Authors: Heffner Reid , Kurani Kenneth , S.Turrentine Thomas
Published: May 2018

Since car buyers have limited practical experience with FCVs, direct study of FCV adoption is not feasible. However, consumer behavior toward other types of advanced-technology vehicles may offer clues about how the market for FCVs will develop. Research of hybrid-electric vehicles (HEVs) indicates that consumers adopt these vehicles partly because of the vehicles' symbolism. Any vehicle can serve as a symbol; it can represent larger ideas, meanings that frequently relate to the identity of the vehicle’s owner. This qualitative research study examines early buyers of HEVs to understand the symbolic meanings they perceived in their vehicles and the role symbolism played in their vehicle purchases. Findings from these buyers are then prospectively applied to the future market for FCVs. The study includes four specific recommendations to increase the possibility that FCV buyers can access and communicate relevant symbolic meanings with their vehicles.
Advanced Redundancy Technology for a Drive System Using In-Wheel Motors
Authors: Kawakami Kiyomoto , Tanabe Hidetoshi , Shimizu Hiroshi , Yoshida Hiroichi
Published: May 2018

In electric vehicles that use in-wheel motors, the right and left traction forces become unbalanced if a motor malfunctions by motor lock or loss of traction, generating yaw moment. Control methods were designed to reduce this effect by stopping the motor output on the opposite side of the same axle. By using a prototype “Eliica” car, the maximum yaw rate and lateral acceleration were compared for a breakdown of one motor with the results from the “Sensitivity to lateral wind” indicated in Z108-76 of the Japanese Automobile Standards Organization. Under redundancy control, the test results were confirmed to be below the tolerance limits
Normal Force Stabilizing Control Using Small EV Powered only by Electric Double Layer Capacitor
Authors: Kawashima Kiyotaka , Uchida Toshiyuki , Hori Yoichi
Published: May 2018

This paper has two topics. The first one is development of novel electric vehicle (EV) powered only by "Electrical Double Layer Capacitor (EDLC)". The second one is normal force stabilizing (NFS) vehicle motion control using this experimental vehicle. The vehicle provides us useful experimental environment of EV′s motion control, since EDLC power system can shorten charging time. Only 30 seconds-charging enables us 20 minutes driving experiments. The development of small EV and the vehicle control system are shown. Novel vehicle stabilizing control in rolling motion using differential torque is proposed. Normal force has strong connectivity with driving force and its sudden decrease causes tire slip, which makes the whole vehicle motion unstable. The simulation and experimental results are shown and the effectiveness of proposed method is discussed.
Measuring Range Anxiety: the Substitution-Emergency-Detour (SED) Method
Authors: Lin Zhenhong
Published: May 2018

Range anxiety has been widely recognized as a critical barrier for battery electric vehicles (BEV), but its measurement method is lacking. Such a knowledge gap makes it difficult to analyse the competiveness of and the demand for BEVs. This study develops the Substitution-Emergency-Detour (SED) method to measure the range anxiety cost, and conducts sensitivity analysis of range anxiety cost with respect to nine factors. It is found that the most effective ways to reduce range anxiety are reducing driving intensity, increasing the vehicle range, extending the vehicle range with better charging infrastructure. Better household vehicle flexibility and less range uncertainty can also significantly reduce range anxiety. The SED method and the numerical results are expected to contribute to better understanding of the range anxiety barrier and the BEV demand.
Realization and Control of the Lupo EL Electric Vehicle
Authors: Van Oorschot P.F. , Besselink I.J.M. , Meinders E. , Nijmeijer H.
Published: May 2018

During fall 2009, the Eindhoven University of Technology started the development of the Lupo EL (Electric Lightweight) research vehicle. The vehicle is fully operational now, allowed to drive on the public road and used in several research projects. This paper will focus more in-depth on the vehicle development and the research performed. The following subjects will be addressed: vehicle realization, specification and performance, data acquisition systems and control systems.
Imide arylation with aryl(TMP)iodonium tosylates
Authors: Basu Souradeep , Sandtorv Alexander H , Stuart David R
Published: May 2018

Herein, we describe the synthesis of N-aryl phthalimides by metal-free coupling of potassium phthalimide with unsymmetrical aryl(TMP)iodonium tosylate salts. The aryl transfer from the iodonium moiety occurs under electronic control with the electron-rich trimethoxyphenyl group acting as a competent dummy ligand. The yields of N-aryl phthalimides are moderate to high and the coupling reaction is compatible with electron-deficient and sterically encumbered aryl groups.
Smooth H i Low Column Density Outskirts in Nearby Galaxies
Authors: Ianjamasimanana R. , Walter Fabian , de Blok W. J. G. , Heald George H. , Brinks Elias
Published: May 2018

The low column density gas at the outskirts of galaxies as traced by the 21 cm hydrogen line emission (H i) represents the interface between galaxies and the intergalactic medium, i.e., where galaxies are believed to get their supply of gas to fuel future episodes of star formation. Photoionization models predict a break in the radial profiles of H i at a column density of ∼5 × 1019 cm−2 due to the lack of self-shielding against extragalactic ionizing photons. To investigate the prevalence of such breaks in galactic disks and to characterize what determines the potential edge of the H i disks, we study the azimuthally averaged H i column density profiles of 17 nearby galaxies from the H i Nearby Galaxy Survey and supplemented in two cases with published Hydrogen Accretion in LOcal GAlaxieS data. To detect potential faint H i emission that would otherwise be undetected using conventional moment map analysis, we line up individual profiles to the same reference velocity and average them azimuthally to derive stacked radial profiles. To do so, we use model velocity fields created from a simple extrapolation of the rotation curves to align the profiles in velocity at radii beyond the extent probed with the sensitivity of traditional integrated H i maps. With this method, we improve our sensitivity to outer-disk H i emission by up to an order of magnitude. Except for a few disturbed galaxies, none show evidence of a sudden change in the slope of the H i radial profiles: the alleged signature of ionization by the extragalactic background.
The Black Hole in the Most Massive Ultracompact Dwarf Galaxy M59-UCD3
Authors: Ahn Christopher P. , Seth Anil C. , Cappellari Michele , Krajnović Davor , Strader Jay , Voggel Karina T. , Walsh Jonelle L. , Bahramian Arash , Baumgardt Holger , Brodie Jean , Chilingarian Igor , Chomiuk Laura , den Brok Mark , Frank Matthias , Hilker Michael , McDermid Richard M. , Mieske Steffen , Neumayer Nadine , Nguyen Dieu D. , Pechetti Renuka , Romanowsky Aaron J. , Spitler Lee
Published: May 2018

We examine the internal properties of the most massive ultracompact dwarf galaxy (UCD), M59-UCD3, by combining adaptive-optics-assisted near-IR integral field spectroscopy from Gemini/NIFS and Hubble Space Telescope (HST) imaging. We use the multiband HST imaging to create a mass model that suggests and accounts for the presence of multiple stellar populations and structural components. We combine these mass models with kinematics measurements from Gemini/NIFS to find a best-fit stellar mass-to-light ratio (M/L) and black hole (BH) mass using Jeans anisotropic models (JAMs), axisymmetric Schwarzschild models, and triaxial Schwarzschild models. The best-fit parameters in the JAM and axisymmetric Schwarzschild models have BHs between 2.5 and 5.9 million solar masses. The triaxial Schwarzschild models point toward a similar BH mass but show a minimum χ
2 at a BH mass of ∼0. Models with a BH in all three techniques provide better fits to the central V
rms profiles, and thus we estimate the BH mass to be

4.2

−
1.7

+
2.1

×

10

6

M
⊙ (estimated 1σ uncertainties). We also present deep radio imaging of M59-UCD3 and two other UCDs in Virgo with dynamical BH mass measurements, and we compare these to X-ray measurements to check for consistency with the fundamental plane of BH accretion. We detect faint radio emission in M59cO but find only upper limits for M60-UCD1 and M59-UCD3 despite X-ray detections in both these sources. The BH mass and nuclear light profile of M59-UCD3 suggest that it is the tidally stripped remnant of a ∼109–1010
M
⊙ galaxy.
Chromospheric Response during the Precursor and the Main Phase of a B6.4 Flare on 2005 August 20
Authors: Awasthi Arun Kumar , Rudawy Pawel , Falewicz Robert , Berlicki Arkadiusz , Liu Rui
Published: May 2018

Solar flare precursors depict a constrained rate of energy release, in contrast to the imminent rapid energy release, which calls for a different regime of plasma processes to be at play. Due to the subtle emission during the precursor phase, its diagnostics remain delusive, revealing either nonthermal electrons (NTEs) or thermal conduction to be the driver. In this regard, we investigate the chromospheric response during various phases of a B6.4 flare on 2005 August 20. Spatiotemporal investigation of flare ribbon enhancement during the precursor phase, carried out using spectra images recorded in several wavelength positions on the Hα line profile, revealed its delayed response (180 s) compared to the X-ray emission, as well as a sequential increment in the width of the line profile, which are indicative of a slow heating process. However, the energy contained in the Hα emission during the precursor phase can reach as high as 80% of that estimated during the main phase. Additionally, the plasma hydrodynamics during the precursor phase, resulting from the application of a single-loop one-dimensional model, revealed the presence of a power-law extension in the model-generated X-ray spectra, with a flux lower than the RHESSI background. Therefore, our multiwavelength diagnostics and hydrodynamical modeling of the precursor emission indicates the role of a two-stage process. First, reconnection-triggered NTEs, although too small in flux to overcome the observational constraints, thermalize in the upper chromosphere. This leads to the generation of a slow conduction front, which causes plasma heating during the precursor phase.
MOSFiT: Modular Open Source Fitter for Transients
Authors: Guillochon James , Nicholl Matt , Villar V. Ashley , Mockler Brenna , Narayan Gautham , Mandel Kaisey S. , Berger Edo , Williams Peter K. G.
Published: May 2018

Much of the progress made in time-domain astronomy is accomplished by relating observational multiwavelength time-series data to models derived from our understanding of physical laws. This goal is typically accomplished by dividing the task in two: collecting data (observing), and constructing models to represent that data (theorizing). Owing to the natural tendency for specialization, a disconnect can develop between the best available theories and the best available data, potentially delaying advances in our understanding new classes of transients. We introduceMOSFiT: the Modular Open Source Fitter for Transients, aPython-based package that downloads transient data sets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light-curve fits to those data sets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community.MOSFiTis designed to help bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible,MOSFiTyields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result. As large-scale surveys such as that conducted with the Large Synoptic Survey Telescope (LSST), discover entirely new classes of transients, tools such asMOSFiTwill be critical for enabling rapid comparison of models against data in statistically consistent, reproducible, and scientifically beneficial ways.
Reducing and Analyzing the PHAT Survey with the Cloud
Authors: Williams Benjamin F. , Olsen Knut , Khan Rubab , Pirone Daniel , Rosema Keith
Published: May 2018

We discuss the technical challenges we faced and the techniques we used to overcome them when reducing the Panchromatic Hubble Andromeda Treasury (PHAT) photometric data set on the Amazon Elastic Compute Cloud (EC2). We first describe the architecture of our photometry pipeline, which we found particularly efficient for reducing the data in multiple ways for different purposes. We then describe the features of EC2 that make this architecture both efficient to use and challenging to implement. We describe the techniques we adopted to process our data, and suggest ways these techniques may be improved for those interested in trying such reductions in the future. Finally, we summarize the output photometry data products, which are now hosted publicly in two places in two formats. They are in simple fits tables in the high-level science products on MAST, and on a queryable database available through the NOAO Data Lab.
Schroedinger’s Code: A Preliminary Study on Research Source Code Availability and Link Persistence in Astrophysics
Authors: Allen Alice , Teuben Peter J. , Ryan P. Wesley
Published: May 2018

We examined software usage in a sample set of astrophysics research articles published in 2015 and searched for the source codes for the software mentioned in these research papers. We categorized the software to indicate whether the source code is available for download and whether there are restrictions to accessing it, and if the source code is not available, whether some other form of the software, such as a binary, is. We also extracted hyperlinks from one journal’s 2015 research articles, as links in articles can serve as an acknowledgment of software use and lead to the data used in the research, and tested them to determine which of these URLs are still accessible. For our sample of 715 software instances in the 166 articles we examined, we were able to categorize 418 records as according to whether source code was available and found that 285 unique codes were used, 58% of which offered the source code for download. Of the 2558 hyperlinks extracted from 1669 research articles, at best, 90% of them were available over our testing period.
A Model for Data Citation in Astronomical Research Using Digital Object Identifiers (DOIs)
Authors: Novacescu Jenny , Peek Joshua E. G. , Weissman Sarah , Fleming Scott W. , Levay Karen , Fraser Elizabeth
Published: May 2018

Standardizing and incentivizing the use of digital object identifiers (DOIs) to aggregate and identify both data analyzed and data generated by a research project will advance the field of astronomy to match best practices in other research fields like geoscience and medicine. An increase in the use of DOIs will prepare the discipline for changing expectations among funding agencies and publishers, who increasingly expect accurate and thorough data citation to accompany scientific outputs. The use of DOIs ensures a robust, sustainable, and interoperable approach to data citation in which due credit is given to the researchers and institutions who produce and maintain the primary data. We describe in this work the advantages of DOIs for data citation and best practices for integrating a DOI service in an astronomical archive. We report on a pilot project carried out in collaboration with AAS journals. During the course of the 1.5-year long pilot, over 75% of submitting authors opted to use the integrated DOI service to clearly identify data analyzed during their research project when prompted at the time of paper submission.
Coronal Mass Ejection Data Clustering and Visualization of Decision Trees
Authors: Ma Ruizhe , Angryk Rafal A. , Riley Pete , Boubrahimi Soukaina Filali
Published: May 2018

Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.
Astrolabe: Curating, Linking, and Computing Astronomy’s Dark Data
Authors: Heidorn P. Bryan , Stahlman Gretchen R. , Steffen Julie
Published: May 2018

Where appropriate repositories are not available to support all relevant astronomical data products, data can fall into darkness: unseen and unavailable for future reference and reuse. Some data in this category are legacy or old data, but newer data sets are also often uncurated and could remain dark. This paper provides a description of the design motivation and development of Astrolabe, a cyberinfrastructure project that addresses a set of community recommendations for locating and ensuring the long-term curation of dark or otherwise at-risk data and integrated computing. This paper also describes the outcomes of the series of community workshops that informed creation of Astrolabe. According to participants in these workshops, much astronomical dark data currently exist that are not curated elsewhere, as well as software that can only be executed by a few individuals and therefore becomes unusable because of changes in computing platforms. Astronomical research questions and challenges would be better addressed with integrated data and computational resources that fall outside the scope of existing observatory and space mission projects. As a solution, the design of the Astrolabe system is aimed at developing new resources for management of astronomical data. The project is based in CyVerse cyberinfrastructure technology and is a collaboration between the University of Arizona and the American Astronomical Society. Overall, the project aims to support open access to research data by leveraging existing cyberinfrastructure resources and promoting scientific discovery by making potentially useful data available to the astronomical community, in a computable format.
Prediction of Solar Eruptions Using Filament Metadata
Authors: Aggarwal Ashna , Schanche Nicole , Reeves Katharine K. , Kempton Dustin , Angryk Rafal
Published: May 2018

We perform a statistical analysis of erupting and non-erupting solar filaments to determine the properties related to the eruption potential. In order to perform this study, we correlate filament eruptions documented in the Heliophysics Event Knowledgebase (HEK) with HEK filaments that have been grouped together using a spatiotemporal tracking algorithm. The HEK provides metadata about each filament instance, including values for length, area, tilt, and chirality. We add additional metadata properties such as the distance from the nearest active region and the magnetic field decay index. We compare trends in the metadata from erupting and non-erupting filament tracks to discover which properties present signs of an eruption. We find that a change in filament length over time is the most important factor in discriminating between erupting and non-erupting filament tracks, with erupting tracks being more likely to have decreasing length. We attempt to find an ensemble of predictive filament metadata using a Random Forest Classifier approach, but find the probability of correctly predicting an eruption with the current metadata is only slightly better than chance.
The Significance of an Excess in a Counting Experiment: Assessing the Impact of Systematic Uncertainties and the Case with a Gaussian Background
Authors: Vianello Giacomo
Published: May 2018

Several experiments in high-energy physics and astrophysics can be treated as on/off measurements, where an observation potentially containing a new source or effect (“on” measurement) is contrasted with a background-only observation free of the effect (“off” measurement). In counting experiments, the significance of the new source or effect can be estimated with a widely used formula from Li & Ma, which assumes that both measurements are Poisson random variables. In this paper we study three other cases: (i) the ideal case where the background measurement has no uncertainty, which can be used to study the maximum sensitivity that an instrument can achieve, (ii) the case where the background estimate b in the off measurement has an additional systematic uncertainty, and (iii) the case where b is a Gaussian random variable instead of a Poisson random variable. The latter case applies when b comes from a model fitted on archival or ancillary data, or from the interpolation of a function fitted on data surrounding the candidate new source/effect. Practitioners typically use a formula that is only valid when b is large and when its uncertainty is very small, while we derive a general formula that can be applied in all regimes. We also develop simple methods that can be used to assess how much an estimate of significance is sensitive to systematic uncertainties on the efficiency or on the background. Examples of applications include the detection of short gamma-ray bursts and of new X-ray or γ-ray sources. All the techniques presented in this paper are made available in a Python code that is ready to use.
Machine-learning-based Brokers for Real-time Classification of the LSST Alert Stream
Authors: Narayan Gautham , Zaidi Tayeb , Soraisam Monika D. , Wang Zhe , Lochner Michelle , Matheson Thomas , Saha Abhijit , Yang Shuo , Zhao Zhenge , Kececioglu John , Scheidegger Carlos , Snodgrass Richard T. , Axelrod Tim , Jenness Tim , Maier Robert S. , Ridgway Stephen T. , Seaman Robert L. , Evans Eric Michael , Singh Navdeep , Taylor Clark , Toeniskoetter Jackson , Welch Eric , Zhu Songzhe ,   (The ANTARES Collaboration)
Published: May 2018

The unprecedented volume and rate of transient events that will be discovered by the Large Synoptic Survey Telescope (LSST) demand that the astronomical community update its follow-up paradigm. Alert-brokers—automated software system to sift through, characterize, annotate, and prioritize events for follow-up—will be critical tools for managing alert streams in the LSST era. The Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES) is one such broker. In this work, we develop a machine learning pipeline to characterize and classify variable and transient sources only using the available multiband optical photometry. We describe three illustrative stages of the pipeline, serving the three goals of early, intermediate, and retrospective classification of alerts. The first takes the form of variable versus transient categorization, the second a multiclass typing of the combined variable and transient data set, and the third a purity-driven subtyping of a transient class. Although several similar algorithms have proven themselves in simulations, we validate their performance on real observations for the first time. We quantitatively evaluate our pipeline on sparse, unevenly sampled, heteroskedastic data from various existing observational campaigns, and demonstrate very competitive classification performance. We describe our progress toward adapting the pipeline developed in this work into a real-time broker working on live alert streams from time-domain surveys.
Substructures and Tidal Distortions in the Magellanic Stellar Periphery
Authors: Mackey Dougal , Koposov Sergey , Costa Gary Da , Belokurov Vasily , Erkal Denis , Kuzma Pete
Published: May 2018

We use a new panoramic imaging survey conducted with the Dark Energy Camera to map the stellar fringes of the Large and Small Magellanic Clouds (LMC/SMC) to extremely low surface brightness V ≈ 32 mag arcsec−2. Our results starkly illustrate the closely interacting nature of the LMC–SMC pair. We show that the outer LMC disk is strongly distorted, exhibiting an irregular shape, evidence for warping, and significant truncation on the side facing the SMC. Large diffuse stellar substructures are present both to the north and south of the LMC, and in the inter-Cloud region. At least one of these features appears as co-spatial with the bridge of RR Lyrae stars that connects the Clouds. The SMC is highly disturbed; we confirm the presence of tidal tails, as well as a large line-of-sight depth on the side closest to the LMC. Young, intermediate-age, and ancient stellar populations in the SMC exhibit strikingly different spatial distributions. In particular, those with ages ∼1.5–4 Gyr exhibit a spheroidal distribution with a centroid offset from that of the oldest stars by several degrees toward the LMC. We speculate that the gravitational influence of the LMC may already have been perturbing the gaseous component of the SMC several Gyr ago. With careful modeling, the variety of substructures and tidal distortions evident in the Magellanic periphery should tightly constrain the interaction history of the Clouds.
A rare and unusual new bittiine genus with two new species from the South Pacific (Cerithiidae, Gastropoda)
Authors: Strong Ellen E. , Bouchet Philippe
Published: May 2018

A new genus, Limatium gen. n., and two new species, L.pagodula sp. n. and L.aureum sp. n. are described, found on outer slopes of barrier reefs and fringing reefs in the South Pacific. They are rare for cerithiids, which typically occur in large populations. The two new species are represented by 108 specimens sampled over a period of 30 years, only 16 of which were collected alive. Three subadults from the Philippines and Vanuatu likely represent a third species. In addition to their rarity, Limatium species are atypical for cerithiids in their smooth, polished, honey to golden brown shells with distinctive white fascioles extending suture to suture. The radula presents a unique morphology that does not readily suggest an affinity to any of the cerithiid subfamilies. Two live-collected specimens, one of each species and designated as holotypes, were preserved in 95% ethanol and sequenced. Bayesian analysis of partial COI and 16S rDNA sequences demonstrates a placement in the Bittiinae, further extending our morphological concept of the subfamily.
Grounded Theory Analysis of Successful Implementation of E-Government Projects
Authors: Al-Emadi Ameena , Anouze Abdel Latef
Published: May 2018

This article explores the perceptions of senior managers about the successful implementations of e-government projects in their agencies, identifying what problems they have encountered and how they have addressed these problems better. 17 e-government projects were interviewed to reveal their underlying perceptions on the successful implementation of e-government projects in their agencies. After analyzing their interview transcripts, forty-nine constructs were revealed, refined, and categorized. The findings indicate that there is a lack of consensus among project managers about what constitutes e-Government project success, there was agreement across all levels of management that project success needs to be measured through a set of quantitative measures such as the number of transactions submitted through the e-government system, number of users using the system, and total time required to complete a process. Drawing from the empirical findings, this article presents a conceptual framework for change management in e-government projects together with a set of recommendations.
An Empirical Study of Cloud-Based E-Governance Services Adoption in India
Authors: Sivathanu Brijesh
Published: May 2018

This article studies the factors affecting the adoption of the DigiLocker cloud-based E-governance service in India. This study integrates the e-GAM and UTAUT model to develop a hypothesized framework to investigate the DigiLocker E-governance service adoption in India from a citizen's perspective. The survey was conducted among citizens in Pune city and its suburbs using a structured questionnaire. The confirmatory factor analysis was done using the PLS-SEM technique. The results of this cross-sectional research explain that performance expectancy, effort expectancy, facilitating conditions, social influence, perceived awareness, computer self-efficacy, multilingual option, perceived quality of information, perceived response and perceived trust influence the behavioral intention and actual usage of DigiLocker cloud-based E-governance service. The outcome of this article is valuable to policymakers for providing better E-governance services. This research presents vital insights and highlights the factors that influence the cloud-based E-governance service adoption in developing countries like India.
Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm
Authors: Rajak Sonu , Parthiban P. , Dhanalakshmi R.
Published: May 2018

This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.
Anomaly Detection Using RFID-Based Information Management in an IoT Context
Authors: Parada Raúl , Melià-Seguí Joan , Pous Rafael
Published: May 2018

IoT-based environments may infer anomalies based on the data processed from their heterogeneous sensors. Within the technologies evolving the IoT concept, nowadays the Radio Frequency Identification (RFID) technology is a de facto standard in areas like retail or logistics. For instance, most retailers attach RFID-labels to their items to avoid stock-out in the inventory or speed up cash processes. Besides identification, RFID provides further RF data which can be used for information management like anomaly detection (i.e. a shoplifting in a RFID loss prevention system). This manuscript presents two IoT scenarios to detect anomalies using multivariate outlier detection methods, uniquely using RFID data. This research empirically evaluates the authors' proposed methods by reproducing a RFID-enabled store, and the two proposed scenarios. The evaluation achieved a False Positive Rate around 0.1% and a True Positive Rate around 87%.
Smart Vehicular System based on the Internet of Things
Authors: Reddy Midde Ranjit , Srinivasa K. G , Reddy B. Eswara
Published: May 2018

With the advent of smart city and its implications, different components of the smart city such as traffic, pollution monitoring, infotainment and others need to be considered as well for enabling the complete smartness. One of the major components of the smart city is regulation of traffic and its standards for smooth vehicular movement and it depends on the road conditions and environment. Road conditions provide valuable information for developing assistive systems for the vehicles and to be provided and trained with different road conditions for better accuracy and finally enabling the smartness around the system. With the increasing vehicular population around the globe and in developing countries like India, assistive systems based on Internet of Things (IoT) play a major role in developing smart systems for the vehicles. Once the population of the vehicles increases, assistive systems need a smart mechanism for parking as well. The proposed Internet of things (IoT) based system provides the user with different conditions of the road and a smart parking solution.
Impact of Information Technology on Information Search Channel Selection for Consumers
Authors: Khatwani Gaurav , Srivastava Praveen Ranjan
Published: May 2018

As information technology has evolved, digital media has become increasingly fragmented and has started to proliferate multiple information channels. In order to optimize on the various digital channels that are available, organizations are increasingly recognizing the importance of gaining solid insights into consumer behavior and preferences that can be translated into marketing strategies. Specifically, they are keen to identify which information channels they can use to effectively reach and communicate with their target market. In this regard, this paper describes how multi criteria decision making can be used to develop a new method of decision making that will enable an effective and systematic decision process of fuzzy AHP and TOPSIS. Further, these techniques can be used for the developing framework for identifying consumer preferences. This paper provides a demonstration of the underpinning working methodology of the proposed model by examining an real case that is based on the decision process Internet users employ during their online search for information.
Myeloid-Derived Suppressor Cells Impair B Cell Responses in Lung Cancer through IL-7 and STAT5
Authors: Wang Yong , Schafer Cara C. , Hough Kenneth P. , Tousif Sultan , Duncan Steven R. , Kearney John F. , Ponnazhagan Selvarangan , Hsu Hui-Chen , Deshane Jessy S.
Published: May 2018

Myeloid-derived suppressor cells (MDSCs) are known suppressors of antitumor immunity, affecting amino acid metabolism and T cell function in the tumor microenvironment. However, it is unknown whether MDSCs regulate B cell responses during tumor progression. Using a syngeneic mouse model of lung cancer, we show reduction in percentages and absolute numbers of B cell subsets including pro–, pre–, and mature B cells in the bone marrow (BM) of tumor-bearing mice. The kinetics of this impaired B cell response correlated with the progressive infiltration of MDSCs. We identified that IL-7 and downstream STAT5 signaling that play a critical role in B cell development and differentiation were also impaired during tumor progression. Global impairment of B cell function was indicated by reduced serum IgG levels. Importantly, we show that anti–Gr-1 Ab-mediated depletion of MDSCs not only rescued serum IgG and IL-7 levels but also reduced TGF-β1, a known regulator of stromal IL-7, suggesting MDSC-mediated regulation of B cell responses. Furthermore, blockade of IL-7 resulted in reduced phosphorylation of downstream STAT5 and B cell differentiation in tumor-bearing mice and administration of TGF-β–blocking Ab rescued these IL-7–dependent B cell responses. Adoptive transfer of BM-derived MDSCs from tumor-bearing mice into congenic recipients resulted in significant reductions of B cell subsets in the BM and in circulation. MDSCs also suppressed B cell proliferation in vitro in an arginase-dependent manner that required cell-to-cell contact. Our results indicate that tumor-infiltrating MDSCs may suppress humoral immune responses and promote tumor escape from immune surveillance.
The Nonparticipation Problem: Behavioral Economics and The Take-Up of Social Benefits
Authors: Alba Francesca
Published: May 2018

The nonparticipation of low-income households in social benefit programs remains a puzzle to many economists, especially when analyzed through a neoclassical lens. For some households, the decision to participate in a government benefit program could mean the difference between living above or below the poverty line. However, behavioral economics—a branch of economics that incorporates human psychology into economic models—may provide a useful framework through which to analyze the nonparticipation of low-income households in government benefit programs. Empirical research suggests that lack of knowledge, incomplete information, hassle costs, and procrastination each play an important role in this policy problem. This paper will begin with an overview of nonparticipation in social benefit programs in the United States, describe the neoclassical theory of how low-income households maximize their utility when deciding whether to participate in such a program, contrast this neoclassical approach with implications from theory and research from behavioral economics, and end with some broad implications—taken from the research—for future policy.
Conflict in the Middle East: The US and the Turkish-Kurdish Conflict
Authors: Dotzler Matthew
Published: May 2018

The conflict between Turkey and the Kurds is once again reaching a boiling point. Following the defeat of ISIL in northern Iraq and Syria, Turkey is now concerned that the returning Kurdish militias pose a threat to its national security. The United States, as an ally to both parties, finds itself in a unique position to push for diplomatic solutions and to mediate the conflict before it grows out of control once again. This paper will examine the history of the Turkish-Kurdish conflict, the actors involved, and how US foreign policy can be used to try and deter yet another war in the region.
A Case of Scarred Uterine Rupture at 11 Weeks of Gestation Having a Uterine Scar Places Induced by In Vitro Fertilization-Embryo Transfer
Authors: Takashima Akiko , Takeshita Naoki , Kinoshita Toshihiko
Published: May 2018

Having a uterine scar places a woman at increased risk of complications, such as Cesarean scar pregnancy (CSP), uterine rupture, placenta previa, and placenta accreta, in subsequent pregnancies. We report a case of uterine rupture at 11 weeks of gestation in a woman with a previous Cesarean section. A 43-year-old woman with a history of abdominal myomectomy and Cesarean section had her pregnancy induced by in vitro fertilization with donor eggs. The exact location of the gestational sac was identified on her first day of hospitalization, and her pregnancy was suspected to be a CSP. The following day, the patient complained of sudden lower abdominal pain. A uterine scar rupture was diagnosed, and an emergency surgery was required. It may be that first-trimester screening could allow the early recognition of patients at risk for these perinatal complications.