LLukas22/scidocs huggingface dataset:
Gender identity and lexical variation in social media

We present a study of the relationship between gender, linguistic style, and social networks, using a novel corpus of 14,000 Twitter users. Prior quantitative work on gender often treats this social variable as a female/male binary; we argue for a more nuanced approach. By clustering Twitter users, we find a natural decomposition of the dataset into various styles and topical interests. Many clusters have strong gender orientations, but their use of linguistic resources sometimes directly conflicts with the population-level language statistics. We view these clusters as a more accurate reflection of the multifaceted nature of gendered language styles. Previous corpus-based work has also had little to say about individuals whose linguistic styles defy population-level gender patterns. To identify such individuals, we train a statistical classifier, and measure the classifier confidence for each individual in the dataset. Examining individuals whose language does not match the classifier's model for their gender, we find that they have social networks that include significantly fewer same-gender social connections, and that in general, social network homophily is correlated with the use of same-gender language markers. Pairing computational methods and social theory thus offers a new perspective on how gender emerges as individuals position themselves relative to audiences, topics, and mainstream gender norms. [206 words]
Line Scratches Detection and Restoration via Light Diffraction

This paperpresents a unified model for the detection and removal of line scratches. It is based on modelling the scratch effect by allowing for the diffraction of light. The paper gives some evidence as to why light diffraction can give rise ro scrarches. The physical modelling of the defect along with its classification as region of partially missing data allows very good resulrs borh in detection and in restoration.
Image segmentation evaluation: A survey of unsupervised methods

Image segmentation is an important processing step in many image, video and computer vision applications. Extensive research has been done in creating many different approaches and algorithms for image segmentation, but it is still difficult to assess whether one algorithm produces more accurate segmentations than another, whether it be for a particular image or set of images, or more generally, for a whole class of images. To date, the most common method for evaluating the effectiveness of a segmentation method is subjective evaluation, in which a human visually compares the image segmentation results for separate segmentation algorithms, which is a tedious process and inherently limits the depth of evaluation to a relatively small number of segmentation comparisons over a predetermined set of images. Another common evaluation alternative is supervised evaluation, in which a segmented image is compared against a manuallysegmented or pre-processed reference image. Evaluation methods that require user assistance, such as subjective evaluation and supervised evaluation, are infeasible in many vision applications, so unsupervised methods are necessary. Unsupervised evaluation enables the objective comparison of both different segmentation methods and different parameterizations of a single method, without requiring human visual comparisons or comparison with a manually-segmented or pre-processed reference image. Additionally, unsupervised methods generate results for individual images and images whose characteristics may not be known until evaluation time. Unsupervised methods are crucial to real-time segmentation evaluation, and can furthermore enable self-tuning of algorithm parameters based on evaluation results. In this paper, we examine the unsupervised objective evaluation methods that have been proposed in the literature. An extensive evaluation of these methods are presented. The advantages and shortcomings of the underlying design mechanisms in these methods are discussed and analyzed through analytical evaluation and empirical evaluation. Finally, possible future directions for research in unsupervised evaluation are proposed. 2007 Elsevier Inc. All rights reserved.
Bayesian Analysis of Population PK/PD Models: General Concepts and Software

Markov chain Monte Carlo (MCMC) techniques have revolutionized the field of Bayesian statistics by enabling posterior inference for arbitrarily complex models. The now widely used WinBUGS software has, over the years, made the methodology accessible to a great many applied scientists, in all fields of research. Despite this, serious application of MCMC methods within the field of population PK/PD has been comparatively limited. We appreciate that for many applied pharmacokineticists the prospect of conducting a Bayesian analysis will require numerous alien concepts to be taken on board and it may be difficult to justify investing the time and effort required in order to understand them (especially since the approach is so computer-intensive). For this reason we provide here a thorough (but often informal) discussion of all aspects of Bayesian inference as they apply specifically to population PK/PD. We also acknowledge that while the WinBUGS software is general purpose, model specification for some types of problem, population PK/PD being a prime example, can be very difficult, to the extent that a specialized interface for describing the problem at hand is often a practical necessity. In the latter part of this paper we describe such an interface, namely PKBugs. A principal aim of the paper is to offer sufficient technical background, in an easy to follow format, that the reader may develop both the confidence and know-how to make appropriate use of the PKBugs/WinBUGS framework (or similar software) for their own data analysis needs, should they choose to adopt a Bayesian approach.
Growing pains for deep learning

Neural networks, which support online image search and speech recognition, eventually will drive more advanced services.
Oxygenation With a Single Portable Pulse-Dose Oxygen-Conserving Device and Combined Stationary and Portable Oxygen Delivery Devices in Subjects With COPD.

BACKGROUND
Portable oxygen devices simplify and facilitate patient therapy. This study was designed to compare S(pO2) and patient satisfaction with a portable oxygen concentrator or a combined system consisting of a fixed device with continuous-flow oxygen dispensation and a portable device with pulse dispensation for ambulation.


METHODS
This crossover trial assessed 25 subjects with COPD (92% men, mean age of 72.2 ± 7.4 y, mean FEV1 of 34.14 ± 12.51% of predicted) at 4 hospitals in Madrid. All subjects had previously used the combined system, consisting of a fixed oxygenation system and a portable system for ambulation, with 16 (64%) using stationary and portable concentrators and 9 (36%) using a stationary reservoir and portable liquid oxygen bag. Oxygenation settings at rest and while walking were determined at baseline. Subjects were maintained on the previous combined system for 1 week and then switched to the portable oxygen concentrator for 1 week. Mean S(pO2) over 24 h was calculated using the software in the oximeter, and compliance was monitored (Visionox).


RESULTS
Low S(pO2) (< 90%) was significantly more frequent during use of the portable concentrator alone than with the combined system (37.1% vs 18.4%, P < .05). The portable system alone was preferred by 43% of subjects, and the combined system was preferred by 36%, whereas 21% were not sure.


CONCLUSIONS
Subjects preferred using a single portable oxygenation system both at home and during ambulation. Portable systems alone, however, did not supply the same levels of oxygenation as the combination of fixed and portable systems. Before the widespread adoption of portable systems as a single device, additional studies are needed to determine best-practice protocols for adjustment of daytime and nighttime oxygenation settings. (ClinicalTrials.gov registration NCT02079753).
Cardiac arrest patients have an impaired immune response, which is not influenced by induced hypothermia

INTRODUCTION
Induced hypothermia is increasingly applied as a therapeutic intervention in ICUs. One of the underlying mechanisms of the beneficial effects of hypothermia is proposed to be reduction of the inflammatory response. However, a fear of reducing the inflammatory response is an increased infection risk. Therefore, we studied the effect of induced hypothermia on immune response after cardiac arrest.


METHODS
A prospective observational cohort study in a mixed surgical-medical ICU. Patients admitted at the ICU after surviving cardiac arrest were included and during 24 hours body temperature was strictly regulated at 33°C or 36°C. Blood was drawn at three time points: after reaching target temperature, at the end of the target temperature protocol and after rewarming to 37°C. Plasma cytokine levels and response of blood leucocytes to stimulation with toll-like receptor (TLR) ligands lipopolysaccharide (LPS) from Gram-negative bacteria and lipoteicoic acid (LTA) from Gram-positive bacteria were measured. Also, monocyte HLA-DR expression was determined.


RESULTS
In total, 20 patients were enrolled in the study. Compared to healthy controls, cardiac arrest patients kept at 36°C (n = 9) had increased plasma cytokines levels, which was not apparent in patients kept at 33°C (n = 11). Immune response to TLR ligands in patients after cardiac arrest was generally reduced and associated with lower HLA-DR expression. Patients kept at 33°C had preserved ability of immune cells to respond to LPS and LTA compared to patients kept at 36°C. These differences disappeared over time. HLA-DR expression did not differ between 33°C and 36°C.


CONCLUSIONS
Patients after cardiac arrest have a modest systemic inflammatory response compared to healthy controls, associated with lower HLA-DR expression and attenuated immune response to Gram-negative and Gram-positive antigens, the latter indicative of an impaired immune response to bacteria. Patients with a body temperature of 33°C did not differ from patients with a body temperature of 36°C, suggesting induced hypothermia does not affect immune response in patients with cardiac arrest.


TRIAL REGISTRATION
ClinicalTrials.gov NCT01020916, registered 25 November 2009.
Number of nexin links detectable at standard electron microscopy of normal human nasal cilia and at nexin link deficiency

Results In the control group the median number of nexin links was 4.5 per cilium, range 3.4 5.3. In the second group the mean number of nexin links per cilium was 1.1 1.4, in the third group 0.8 1.2, per patient. The median number of IDA was in the control group 4.2, range 3.3 5.2. In groups 2 and 3 the numbers were 3.0 3.5 and 0.2 1.0, respectively, per patient. Numbers of ODA were normal in all groups.
Mode of action of peppermint oil and (-)-menthol with respect to 5-HT3 receptor subtypes: binding studies, cation uptake by receptor channels and contraction of isolated rat ileum.

Peppermint oil (Mentha × piperita L. (Lamiaceae) has been shown to exert potent antiemetic properties, but its mode of action has not yet been elucidated. Among its active constituents (-)-menthol is the most important. Three different in vitro models were used to investigate the effects on 5-HT(3) receptors (serotonin receptor subtype): [(14)C]guanidinium influx into N1E-115 cells which express 5-HT(3) receptors, isotonic contractions of the isolated rat ileum and equilibrium competition binding studies using a radioactively labelled 5-HT(3) receptor antagonist ([(3)H]GR65630) (3-(5-methyl-1H-imidazol-4-yl)-1-(1-methyl-1H-indol-3-yl)-1-propanone). Both peppermint oil and (-)-menthol inhibited [(14)C]guanidinium influx through 5-HT(3) receptor channels as well as contractions of the ileum induced by serotonin. Neither the peppermint oil nor (-)-menthol, however, was able to displace [(3)H]GR65630 from 5-HT(3) binding sites. It may be concluded that peppermint oil and (-)-menthol exert their antiemetic effect at least partly by acting on the 5-HT(3) receptor ion-channel complex, probably by binding to a modulatory site distinct from the serotonin binding site.
Influences of Celestial Idea in Ancient China on Development of Science & Technology

Such meanings as sky, general natural existences and general human experiences on temporal things exist in the word celestial. The celestial idea had a great influence on development of ancient science and technology and functions as an enlightening to development of modern science and technology.
Theoretical and Practical Improvements on the RMQ-Problem, with Applications to LCA and LCE

The Range-Minimum-Query-Problem is to preprocess an array such that the position of the minimum element between two specified indices can be obtained efficiently. We present a direct algorithm for the general RMQ-problem with linear preprocessing time and constant query time, without making use of any dynamic data structure. It consumes less than half of the space that is needed by the method by Berkman and Vishkin. We use our new algorithm for RMQ to improve on LCA-computation for binary trees, and further give a constant-time LCE-algorithm solely based on arrays. Both LCA and LCE have important applications, e.g., in computational biology. Experimental studies show that our new method is almost twice as fast in practice as previous approaches, and asymptotically slower variants of the constant-time algorithms perform even better for today’s common problem sizes.
GPDTI: A Genetic Programming Decision Tree Induction method to find epistatic effects in common complex diseases

MOTIVATION
The identification of risk-associated genetic variants in common diseases remains a challenge to the biomedical research community. It has been suggested that common statistical approaches that exclusively measure main effects are often unable to detect interactions between some of these variants. Detecting and interpreting interactions is a challenging open problem from the statistical and computational perspectives. Methods in computing science may improve our understanding on the mechanisms of genetic disease by detecting interactions even in the presence of very low heritabilities.


RESULTS
We have implemented a method using Genetic Programming that is able to induce a Decision Tree to detect interactions in genetic variants. This method has a cross-validation strategy for estimating classification and prediction errors and tests for consistencies in the results. To have better estimates, a new consistency measure that takes into account interactions and can be used in a genetic programming environment is proposed. This method detected five different interaction models with heritabilities as low as 0.008 and with prediction errors similar to the generated errors.


AVAILABILITY
Information on the generated data sets and executable code is available upon request.
Preparing to Teach Mathematics with Technology: An Integrated Approach to Developing Technological Pedagogical Content Knowledge

Several organizations have highlighted the importance of preparing teachers to teach students mathematics using appropriate technology (e.g., Association of Mathematics Teacher Educators, 2006; International Society for Technology in Education, 2008). This article provides examples from teacher education materials that were developed using an approach that integrally develops teachers' understandings of content, technology, and pedagogy to prepare them to teach data analysis and probablity topics using specific technology tools. Technology in Mathematics Teacher Preparation In its most recent document, the National Council of Teachers of Mathematics (NCTM, 2000) stated, “Technology is essential in teaching and learning mathematics; it influences what is taught and enhances students’ learning” (p. 24). Whether technology will enhance or hinder students’ learning depends on teachers’ decisions when using technology tools, decisions that are often based on knowledge gained during a teacher preparation program. Recommendations by the Association of Mathematics Teacher Educators (AMTE, 2006) state that teacher education programs should “provide Contemporary Issues in Technology and Teacher Education, 8(4) 327 opportunities [for teachers] to acquire the knowledge and experiences needed to incorporate technology in the context of teaching and learning mathematics” (p. 1). The types of knowledge and skills prospective teachers need to support students’ uses of technology are further delineated in the International Society for Technology in Education National Educational Technology Standards for Teachers, which was originally released in 2000 and updated in 2008. There are strong recommendations for using technology to teach students who are learning mathematics and to prepare teachers who will teach mathematics. The purpose of this article is to share and discuss some examples from materials developed by the Preparing to Teach Mathematics with Technology (PTMT) project created to prepare teachers to use technology to teach mathematics in ways appropriate for students who live in a world that includes rapidly changing digital technology (see http://www.ncsu.edu/project/ptmt/mods.htm). The project has thus far developed materials focused only on the content areas of statistics and probability, and examples will focus on these contexts. We present our guiding framework and examples from the materials, as well as a discussion of field test results and implications.
Design Principles for a Spanish Treebank

Treebanks are widely recognised as a necessary source of information in NLP as well as in Linguistics studies. In this paper we present and justify methodological principles and syntactic criteria to build a Treebank for Spanish: annotating only explicit information, constituents and syntactic functions and being theory independent. Previous work is also presented in order to account for taken decisions. The annotation process will be done in different steps so that each one of them is the input of the next. We present the basic guidelines of syntactic annotation and the boundaries of the work to be done in a first step: annotation of low constituents and surface functions. Moreover, some semantic information (subject type) is likely to be included. 1 The need It is widely admitted that Treebanks constitute a crucial resource both to develop NLP applications and to acquire linguistic knowledge about how a language is used. So far, there is not a freely available Treebank for Spanish, in spite of some references to a 1,000sentence corpus ([25], [26], [27]). It is our aim to build up a 100,000-word Spanish Treebank which will be enriched in the future with semantic as well as pragmatic information, and which will be free for research purposes. Two groups are mainly involved in this project: CLiC, from the Universitat de Barcelona and TALP, from the Universitat Politècnica de Catalunya 1. This research has been partially funded by the Spanish Research Department: X-Tract PB98-1226; PETRA (TIC20001735-C02-02); PROFIT (FIT-150500-2002-244); MCT’s grant (AP98 39864555) and by the Catalan Research Department (CIRIT’s consolidated research group 1999SGR-150).
China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up.

BACKGROUND
Large blood-based prospective studies can provide reliable assessment of the complex interplay of lifestyle, environmental and genetic factors as determinants of chronic disease.


METHODS
The baseline survey of the China Kadoorie Biobank took place during 2004-08 in 10 geographically defined regions, with collection of questionnaire data, physical measurements and blood samples. Subsequently, a re-survey of 25,000 randomly selected participants was done (80% responded) using the same methods as in the baseline. All participants are being followed for cause-specific mortality and morbidity, and for any hospital admission through linkages with registries and health insurance (HI) databases.


RESULTS
Overall, 512,891 adults aged 30-79 years were recruited, including 41% men, 56% from rural areas and mean age was 52 years. The prevalence of ever-regular smoking was 74% in men and 3% in women. The mean blood pressure was 132/79 mmHg in men and 130/77 mmHg in women. The mean body mass index (BMI) was 23.4 kg/m(2) in men and 23.8 kg/m(2) in women, with only 4% being obese (>30 kg/m(2)), and 3.2% being diabetic. Blood collection was successful in 99.98% and the mean delay from sample collection to processing was 10.6 h. For each of the main baseline variables, there is good reproducibility but large heterogeneity by age, sex and study area. By 1 January 2011, over 10,000 deaths had been recorded, with 91% of surviving participants already linked to HI databases.


CONCLUSION
This established large biobank will be a rich and powerful resource for investigating genetic and non-genetic causes of many common chronic diseases in the Chinese population.
A More Reliable Step Counter using Built-in Accelerometer in Smartphone

Received Apr 9, 2018 Revised May 20, 2018 Accepted Jul 11, 2018 Step counter, being an active area of human daily physical activity, is an essential role in human activity determination research. As the current smartphones come with many different sensors and powerful processing capabilities, the step counting using built-in sensors in a smartphone is increasingly becoming a vital factor among many researchers. However, the step counting with a smartphone has still challenging due to many different walking behaviors and mobile phone positions. In this study, we introduce a more reliable step counter‟s technique using Accelerometer sensor in a smart phone. The objective of this study is to get the accurate steps of three different walking activities in four different mobile positions. In order to achieve this, a new reliable technique based on peak is attracting considerable in our work using average acceleration. The experimental result shows 99.02% as an overall step counting performance that the proposed method reliably detects the steps under varying walking speed in different devices modes. This result is encouraging to facilitate among of the complex walking activities using built-in sensors in smartphone.
Very Compact Printed Triple Band-Notched UWB Antenna With Quarter-Wavelength Slots

A very compact coplanar waveguide (CPW)-fed ultrawideband (UWB) printed monopole antenna (PMA) with triple band-notched characteristics is presented. The antenna uses three open-ended quarter-wavelength slots to create triple band-notched characteristics in 3.3-3.7 GHz for WiMAX, 5.15-5.825 GHz for WLAN, and 7.25-7.75 GHz for downlink of X-band satellite communication systems, respectively. The open-ended quarter-wavelength slot is analyzed in detail. Surface current distributions are used to show the effect of these slots. The antenna shows broad bandwidth and good omnidirectional radiation patterns in the passband, with a very compact size of 19 × 24 mm2.
Refining success and dropout in massive open online courses based on the intention–behavior gap

In this paper we present an alternative typology for determining success and dropout in massive open online courses (MOOCs). This typology takes the perspectives of MOOC-takers into account and is based on the their intentions and subsequent behaviour. An explorative study using two MOOCs was carried out to test the applicability of the typology. Following the traditional approach based on course completion to identify educational success, success rates were 6.5 and 5.6%. The success rates from the perspectives of the MOOC-taker were 59 and 70%. These findings demonstrate that merely looking at course completion as a measure for success does not suffice in the context of MOOCs. This change in addressing MOOC success and dropout provides an alternative view and demonstrates the importance of MOOC-takers’ perspectives.