bluuebunny/crossref_metadata_2025_split huggingface dataset:
Desenvolvimento do Módulo de Pre-processamento da ferramenta SentimentALL
Authors: Brito Parcilene Fernandes , Gomes Luan 
Published: March 2019

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Os sistemas que utilizam em seu processo de análise a linguagem natural (por exemplo, sistemas que analisam comentários de sites, reviews de filmes, posts em redes sociais etc.) geralmente usam técnicas relacionadas ao Processamento de Linguagem Natural (PLN). Neste artigo, serão apresentadas as etapas de PLN utilizadas no desenvolvimento do Módulo de Pré-Processamento da Ferramenta SentimentALL, que tem como propósito realizar análises de textos que emitem opiniões sobre produtos. O módulo foi desenvolvido para ser usado em qualquer contexto, mas neste trabalho foi utilizado na análise dos comentários extraídos do site de turismo TripAdvisor. O módulo é composto das etapas de normalização, correção ortográfica, pos-tagging e identificação de expressões compostas. Para a sua implementação, foi utilizada a biblioteca NLTK, da linguagem de Programação Python.
Height Dependence of the Penumbral Fine-scale Structure in the Inner Solar Atmosphere
Authors: Murabito Mariarita , Ermolli I. , Giorgi F. , Stangalini M. , Guglielmino S. L. , Jafarzadeh S. , Socas-Navarro H. , Romano P. , Zuccarello F. 
Published: March 2019

Abstract
We studied the physical parameters of the penumbra in a large and fully developed sunspot, one of the largest over the last two solar cycles, by using full-Stokes measurements taken at the photospheric Fe i 617.3 nm and chromospheric Ca ii 854.2 nm lines with the Interferometric Bidimensional Spectrometer. Inverting measurements with the Non-LTE inversion COde (NICOLE) code, we obtained the three-dimensional structure of the magnetic field in the penumbra from the bottom of the photosphere up to the middle chromosphere. We analyzed the azimuthal and vertical gradient of the magnetic field strength and inclination. Our results provide new insights on the properties of the penumbral magnetic fields in the chromosphere at atmospheric heights unexplored in previous studies. We found signatures of the small-scale spine and intraspine structure of both the magnetic field strength and inclination at all investigated atmospheric heights. In particular, we report typical peak-to-peak variations of the field strength and inclination of ≈300 G and ≈20°, respectively, in the photosphere, and of ≈200 G and ≈10° in the chromosphere. In addition, we estimated the vertical gradient of the magnetic field strength in the studied penumbra: we find a value of ≈0.3 G km−1 between the photosphere and the middle chromosphere. Interestingly, the photospheric magnetic field gradient changes sign from negative in the inner to positive in the outer penumbra.
The Precious Set of Radio-optical Reference Frame Objects in the Light of Gaia DR2 Data
Authors: Makarov Valeri V. , Berghea Ciprian T. , Frouard Julien , Fey Alan , Schmitt Henrique R. 
Published: March 2019

Abstract
We investigate a sample of 3413 International Celestial Reference Frame (ICRF3) extragalactic radio-loud sources with accurate positions determined by very long baseline interferometry in the S/X band, mostly active galactic nuclei and quasars, which are cross-matched with optical sources in the second Gaia data release (Gaia DR2). The main goal of this study is to determine a core sample of astrometric objects that define the mutual orientation of the two fundamental reference frames, the Gaia (optical) and the ICRF3 (radio) frames. The distribution of normalized offsets between the VLBI sources and their optical counterparts is non-Rayleigh, with a deficit around the modal value and a tail extending beyond the 3σ confidence level. A few filters are applied to the sample in order to discard double cross-matches, confusion sources, and Gaia astrometric solutions of doubtful quality. Panoramic Survey Telescope and Rapid Response System and Dark Energy Survey stacked multicolor images are used to further deselect objects that are less suitable for precision astrometry, such as extended galaxies, double and multiple sources, and obvious misidentifications. After this cleaning, 2643 quasars remain, of which 20% still have normalized offset magnitudes exceeding 3, or a 99% confidence level. We publish a list of 2119 radio-loud quasars of prime astrometric quality. The observed dependence of binned median offset on redshift shows the expected decline at small redshifts, but also an unexpected rise at z ∼ 1.6, which may be attributed to the emergence of the C iv emission line in the Gaia’s G band. The Gaia DR2 parallax zero-point is found to be color-dependent, suggesting an uncorrected instrumental calibration effect.
Figuring Out Gas & Galaxies in Enzo (FOGGIE). I. Resolving Simulated Circumgalactic Absorption at 2 ≤ z ≤ 2.5
Authors: Peeples Molly S. , Corlies Lauren , Tumlinson Jason , O’Shea Brian W. , Lehner Nicolas , O’Meara John M. , Howk J. Christopher , Earl Nicholas , Smith Britton D. , Wise John H. , Hummels Cameron B. 
Published: March 2019

Abstract
We present simulations from the new “Figuring Out Gas & Galaxies in Enzo” (FOGGIE) project. In contrast to most extant simulations of galaxy formation, which concentrate computational resources on galactic disks and spheroids with fluid and particle elements of fixed mass, the FOGGIE simulations focus on extreme spatial and mass resolution in the circumgalactic medium (CGM) surrounding galaxies. Using the Enzo code and a new refinement scheme, FOGGIE reaches spatial resolutions of 381 comoving h
−1 pc and resolves extremely low masses (≲1–100

) out to 100 comoving h
−1 kpc from the central halo. At these resolutions, cloud and filament-like structures giving rise to simulated absorption are smaller, and better resolved, than the same structures simulated with standard density-dependent refinement. Most of the simulated absorption arises in identifiable and well-resolved structures with masses ≲104

, well below the mass resolution of typical zoom simulations. However, integrated quantities such as mass surface density and ionic covering fractions change at only the ≲30% level as resolution is varied. These relatively small changes in projected quantities—even when the sizes and distribution of absorbing clouds change dramatically—indicate that commonly used observables provide only weak constraints on the physical structure of the underlying gas. Comparing the simulated absorption features to the KODIAQ (Keck Observatory Database of Ionized Absorption toward Quasars) survey of z ∼ 2–3.5 Lyman limit systems, we show that high-resolution FOGGIE runs better resolve the internal kinematic structure of detected absorption and better match the observed distribution of absorber properties. These results indicate that circumgalactic medium resolution is key in properly testing simulations of galaxy evolution with circumgalactic observations.
The Present Special Solar Cycle 24: Casting a Shadow over Periodicity of the North–South Hemispherical Asymmetry
Authors: Li F. Y. , Xiang N. B. , Xie J. L. , Xu J. C. 
Published: March 2019

Abstract
The N–S asymmetry (the north–south hemispheric asymmetry) of sunspot areas for each of the cycles 7–24 have been investigated, and a trend of a long-term characteristic timescale of about eight cycles is inferred, which is confirmed again by studying the fitted lines of the yearly values of the N–S asymmetry of sunspot numbers and sunspot group numbers at solar cycle 24. Then, a periodic behavior of about 12 solar cycles is found in the cumulative counts of yearly sunspot areas for each of the cycles 7–24. Nevertheless, the cumulative counts of sunspot numbers and sunspot group numbers for cycle 24 have different behaviors. Moreover, the dominant hemispheres for cycles 7–23 show a trend of a long-term characteristic timescale of about 12 cycles. However, we cannot determine the dominant hemisphere of cycle 24, as these three parameters give different results for the dominant hemisphere. Cycle 24 is a particular solar activity cycle, as sunspot areas suggest a long characteristic timescale of about 12-cycle length, while sunspot numbers and sunspot group numbers support an eight-cycle period of the N–S asymmetry.
Supernova 2017eaw: Molecule and Dust Formation from Infrared Observations
Authors: Tinyanont Samaporn , Kasliwal Mansi M , Krafton Kelsie , Lau Ryan , Rho Jeonghee , Leonard Douglas C , De Kishalay , Jencson Jacob , Mawet Dimitri , Millar-Blanchaer Maxwell , Nilsson Ricky , Yan Lin , Gehrz Robert D , Helou George , Van Dyk Schuyler D , Serabyn Eugene , Fox Ori D , Clayton Geoffrey 
Published: March 2019

Abstract
We present infrared (IR) photometry and spectroscopy of the Type II-P SN 2017eaw and its progenitor in the nearby galaxy NGC 6946. Progenitor observations in the Ks band in four epochs from 1 yr to 1 day before the explosion reveal no significant variability in the progenitor star greater than 6% that lasts longer than 200 days. SN 2017eaw is a typical SN II-P with near-IR and mid-IR photometric evolution similar to those of SNe 2002hh and 2004et, other normal SNe II-P in the same galaxy. Spectroscopic monitoring during the plateau phase reveals a possible high-velocity He i 1.083 μm absorption line, indicative of a shock interaction with the circumstellar medium. Spectra between 389 and 480 days postexplosion reveal a strong CO first overtone emission at 389 days, with a line profile matching that of SN 1987A from the same epoch, indicating ∼10−3
M
⊙ of CO at 1800 K. From the 389 days epoch until the most recent observation at 566 days, the first overtone feature fades while the 4.5 μm excess, likely from the CO fundamental band, remains. This behavior indicates that the CO has not been destroyed, but that the gas has cooled enough that the levels responsible for first overtone emissions are no longer populated. Finally, the evolution of Spitzer 3.6 μm photometry shows evidence for dust formation in SN 2017eaw, with a dust mass of 10−6 or 10−4
M
⊙ assuming carbonaceous or silicate grains, respectively.
Distribution of various histopathological types of ovarian tumors: A study of 212 cases from a tertiary care center of Eastern Uttar Pradesh
Authors: Gupta Neha , Yadav Mahima , Gupta Vikas , Chaudhary Deepshikha , Patne Shashikant C. U. 
Published: March 2019

Abstract
BACKGROUND: Ovarian tumors are one of the leading cancers in females with variable pathological types. This study describes the distribution, clinical and pathological details of various histopathological types of ovarian tumors in a tertiary care hospital in North India.
MATERIALS AND METHODS: A retrospective data of 3 years were collected for ovarian tumors submitted to the pathology department of a tertiary care hospital. Data were classified according to the latest World Health Organization (WHO) Classification into epithelial tumors, germ cell tumors, sex cord–stromal tumors, and others.
RESULTS: A total of 212 cases of ovarian tumors were studied, 186 were unilateral and 26 were bilateral. Resection specimen, part of specimen, and block review formed 80.2%, 15.1%, 4.7%, respectively. Epithelial tumors formed the majority in 71.7% of cases followed by germ cell tumors (22.2%), sex cord–stromal tumors (3.8%) and others (2.3%). Maximum number of cases in the respective groups occurred in the age groups 31–40, 21–30, 51–60, and 41–50 years, respectively. Overall, benign tumors were 63.7%, malignant tumors were 31.1%, and borderline were 5.2%. The most common histopathological type of benign and malignant tumor was benign serous cystadenoma (18.8%) and serous carcinoma (9.9%), respectively.
CONCLUSION: In the present study, ovarian tumors were classified according to the WHO classification, epithelial and germ cell tumors were the major types of ovarian tumors. Benign epithelial tumor formed the majority with 46.2% cases. Serous cystadenoma and mature cystic teratoma were the predominant type of epithelial and germ cell tumors, respectively.
Etiological agents of diarrhea in hospitalized pediatric patients with special emphasis on diarrheagenic Escherichia coli in North India
Authors: Verma Sheetal , Venkatesh Vimala , Kumar Rashmi , Kashyap Saurabh , Kumar Manoj , Maurya Anand Kumar , Dhole T. N. , Singh Mastan 
Published: March 2019

Abstract
INTRODUCTION: Infectious diarrhea is leading infectious cause of childhood morbidity, hospitalizations, and mortality particularly in children living in developing countries like India. The etiological agents differ depending on geographical area, and recent data suggest increase in drug resistance to various enteropathogens.
AIMS AND OBJECTIVES: The aim of the study was to investigate emerging diarrheal agents and antimicrobial resistance profile of bacterial pathogens from children (<12 years of age) hospitalized with acute diarrhea.
MATERIALS AND METHODS: A cross-sectional, hospital-based observational study was conducted over 1 year in which 100 children <12 years who were hospitalized due to diarrhea were recruited. Diarrhea was defined as the passage of three or more liquid stools in a 24-h period using the World Health Organization guidelines. Samples were processed for detection of various bacterial, viral, and parasitic agents by standard microbiological, serological, and molecular tests. Antimicrobial resistance testing was performed with the Kirby–Bauer disk diffusion method. ELISA was performed for Rotavirus and Escherichia coli O157. Multiplex polymerase chain reaction test was performed to detect diarrheagenic E. coli (DEC).
RESULTS: Pathogenic diarrheal agents were found in 63% patients. Rotavirus was identified in 52.5%, DEC in 29%, Vibrio cholerae in 4%, Shigella flexneri in 3%, Aeromonas sp. in 1%, Giardia lamblia in 4%, and Entamoeba histolytica in 1% cases. Enteropathogenic E. coli (EPEC) in 19 (65.5%) cases was the most common agent followed by Enteroaggregative E. coli (EAEC) in 5 (17.2%), Enterotoxigenic E. coli (ETEC) in 2 (6%), and Enteroinvasive E. coli (EIEC) in 3 (10.3%) cases. Resistance rates of DEC to first-line therapeutic drugs were high, 97.3% to ampicillin and 95.95% to co-trimoxazole. DEC was susceptible to chloramphenicol in 58.11%, gentamicin in 48.19%, and amikacin in 58.11% cases. Shigella sp. and V. cholerae isolates were 100% sensitive to gentamicin and ofloxacin.
CONCLUSION: EPEC is the most common DEC pathotype and EAEC, ETEC, and EIEC are also emerging as dominant diarrheal agents. Rotavirus was the most common causative agents of diarrhea especially in children <5 years. Most of the bacterial isolates showed high level of drug resistance to first-line empirical drugs and were multidrug resistant making them unsuitable for empiric treatment. Laboratory monitoring of drug susceptibility of stool isolates appears necessary to formulate antibiotic policy for treating diarrheal illness at the local level. There is an urgent need to strengthen diarrheal surveillance to monitor susceptibility to commonly prescribed antibiotics.
A multi-collocation method for coastal zone observations with applications to Sentinel-3A altimeter wave height data
Authors: Schulz-Stellenfleth Johannes , Staneva Joanna 
Published: March 2019

Abstract. In many coastal areas there is an increasing number and variety
of observation data available, which are often very heterogeneous in their temporal and
spatial sampling characteristics. With the advent of new systems, like the radar
altimeter on board the Sentinel-3A satellite, a lot of questions arise concerning the
accuracy and added value of different instruments and numerical models. Quantification of
errors is a key factor for applications, like data assimilation and forecast improvement.
In the past, the triple collocation method to estimate systematic and stochastic
errors of measurements and numerical models was successfully applied to different data
sets.
This method relies on the assumption that three independent data sets provide estimates of the same quantity.
In coastal areas with strong gradients even small distances between measurements can lead
to larger differences and this assumption can become critical. In this study the
triple collocation method is extended in different ways with the specific
problems of the coast in mind. In addition to nearest-neighbour approximations considered
so far, the presented method allows for use of a large variety of interpolation
approaches to take spatial variations in the observed area into account. Observation and
numerical model errors can therefore be estimated, even if the distance between the
different data sources is too large to assume that they measure the same quantity. If the
number of observations is sufficient, the method can also be used to estimate error
correlations between certain data source components. As a second novelty, an estimator
for the uncertainty in the derived observation errors is derived as a function of the
covariance matrices of the input data and the number of available samples. In the first step, the method is assessed using synthetic observations and Monte Carlo
simulations. The technique is then applied to a data set of Sentinel-3A altimeter
measurements, in situ wave observations, and numerical wave model data with a focus on
the North Sea. Stochastic observation errors for the significant wave height, as well as
bias and calibration errors, are derived for the model and the altimeter. The analysis
indicates a slight overestimation of altimeter wave heights, which become more pronounced
at higher sea
states. The smallest stochastic errors are found for the in situ measurements. Different observation geometries of in situ data and altimeter tracks are furthermore
analysed, considering 1-D and 2-D interpolation approaches. For example, the geometry of
an altimeter track passing between two in situ wave instruments is considered with model
data being available at the in situ locations. It is shown that for a sufficiently large
sample, the errors of all data sources, as well as the error correlations of the model,
can be estimated with the new method.
Synergy between in situ and altimetry data to observe and study Northern Current variations (NW Mediterranean Sea)
Authors: Carret Alice , Birol Florence , Estournel Claude , Zakardjian Bruno , Testor Pierre 
Published: March 2019

Abstract. During the last 15 years, substantial progress has been achieved
in altimetry data processing, now providing data with enough accuracy to
illustrate the potential of these observations for coastal applications. In
parallel, new altimetry techniques improve data quality by reducing
land contamination and enhancing the signal-to-noise ratio. Satellite
altimetry provides more robust and accurate measurements ever closer to the
coast and resolve shorter ocean signals. An important issue is now to learn
how to use altimetry data in conjunction with other coastal observing
techniques. Here, we cross-compare and combine the coastal currents provided by large
datasets of ship-mounted acoustic Doppler current profilers (ADCPs), gliders,
high-frequency (HF) radars and altimetry. We analyze how the different
available observing techniques, with a particular focus on altimetry, capture
the Northern Current variability at different timescales. We also study the
coherence, divergence and complementarity of the information derived from the
different instruments considered. Two generations of altimetry missions and
both 1 Hz and high-rate measurements are used: Jason-2 (nadir Ku-band radar)
and SARAL/AltiKa (nadir Ka-band altimetry); their performances are compared. In terms of mean speed of the Northern Current, a very good spatial
continuity and coherence is observed at regional scale, showing the
complementarity among the types of current measurements. In terms of
current variability, there is still a good spatial coherence but the Northern
Current amplitudes derived from altimetry, glider, ADCP and HF radar data
differ, mainly because of differences in their respective spatial and
temporal resolutions. If we consider seasonal variations, 1 Hz altimetry
captures ∼60 % and ∼55 % of the continental slope current
amplitude observed by the gliders and by the ADCPs, respectively. For
individual dates this number varies a lot as a function of the
characteristics of the Northern Current on the corresponding date, with no
clear seasonal tendency observed. Compared to Jason-2, the SARAL altimeter
data tend to give estimations of the NC characteristics that are closer to in
situ data in a number of cases. The much noisier high-rate altimetry data
appear to be more difficult to analyze but they provide current estimates
that are generally closer to the other types of current measurements. Thus,
satellite altimetry provides a synoptic view of the Northern Current
circulation system and variability, which helps to interpret the other
observations. Its regular sampling allows for the observation of many features
that may be missed by irregular in situ data.
Robotic-Assisted Laparoscopic Prostatectomy for a Patient with Clinically Localized Prostate Cancer
Authors: Wang Dominic , Riggs Jamie 
Published: March 2019

A case of clinically localized prostate cancer is resected using robotic-assisted laparoscopic prostatectomy. Routine prostate screening guidelines using PSA and alternative treatment options (including traditional surgical approaches) as well as additional considerations of robotic-assisted procedures including cost and conflicts with current medical education are discussed.
Big Data Analytics
Authors: Bourne Shawna , Rihal Tarun 
Published: March 2019

Utilizing big data to guide decision-making for environmental health outcomes can provide the next level of health outcome improvements on a population basis.
Historical shifts in overall health and longevity came with environmental health interventions such as safe food and water supplies, the treatment of waste and the establishment of standards that have reduced acute illnesses in the population.
Big data analysis approaches have the potential to have a similar impact on quality and length of life by analyzing the factors leading to chronic illness in the population, and improving outcomes. Through the use of big data and machine learning, we can learn more about the environmental factors affecting population health. This article presents an opportunity to utilize pre-existing data to explore a novel way of assessing the impact of known health hazards. This is demonstrated by using drinking water test results as a case example. We demonstrate how big data analytics can be used in such a scenario to identify environmental public health risk. This approach is beginning to be used to collect new and better organized data with the intent of improving population health outcomes.