nils-herrmann/clean_scirepeval huggingface dataset:
Past changes in the vegetation density of the Chinese Loess Plateau revealed by variations in the size of Artemisia pollen grains

We reconstructed paleovegetation changes on the Chinese Loess Plateau by applying concepts in palynology and pollination biology to the statistical analysis of the size of Artemisia pollen grains from 26 surface samples, four loess paleosoil profiles, and extant Artemisia species. We found that the size of Artemisia pollen grains varied in different plant communities, and was positively correlated with local habitat quality and population density of local Artemisia communities. The Mean Artemisia Pollen Size (MAPS) which has changed significantly since Marine Isotope Stage 3 (MIS3) reflects integrated ecological changes, including compositional changes and shifts in population density. During MIS3, the high MAPS values indicate that high population densities of Artemisia grassland covered the northern and southern Loess Plateau. During the Last Glacial Maximum (LGM) with much less favorable growing conditions, a low MAPS value indicates that lower density short grass steppe covered the Loess Plateau at that time. Overall, the results demonstrate that a statistical analysis of the size of fossil pollen grains at genus level can provide useful ecological information, e.g. on changes in the composition and population density of local communities, and thus can lead to a better understanding of the evolution of terrestrial ecosystems.
Light Rail Vehicle Noise: Evaluation of Rail Roughness and Noise from Wheel Rail Interface

Transit opened its first light rail line, the Central Link, in Seattle, Washington, in 2009. There were many community noise issues immediately after the line went into revenue service that were generally attributed to poor quality rail grinding when the initial mill scale grinding was performed. As a result of that experience, Sound Transit has been cautious when predicting noise and designing noise mitigation for new alignments. Future alignments include the University, Northgate, and Lynnwood Links to the north; the Federal Way and South 200th Links to the south; and the East Link to the east. Over the next 15 years, the system will be expanded from 16 mi to more than 50 mi. The detailed noise data collected as part of the final design of East Link suggest that measures could be taken to reduce the need for substantial noise mitigation on future Sound Transit extensions. This paper summarizes the measurements and key observations from that noise study. One key observation suggests that through implementing acoustic rail grinding and maintaining the current wheel truing program, there is potential for minimizing the amount of sound walls required to achieve community noise goals. The results also suggest that through a detailed, information based investigation, reference noise levels used to determine the need for noise mitigation could be reduced by approximately 4 dB. However, the results of this study, combined with experience from rail roughness studies in general, suggest that achieving a true acoustic rail grinding that leaves no artifacts is not straightforward, because it requires careful monitoring by the rail grinder operator as well as quality control measurements by the grinding company or the transit system.
Contextual Combinatorial Cascading Bandits
Venue: ICML

We propose the contextual combinatorial cascading bandits, a combinatorial online learning game, where at each time step a learning agent is given a set of contextual information, then selects a list of items, and observes stochastic outcomes of a prefix in the selected items by some stopping criterion. In online recommendation, the stopping criterion might be the first item a user selects; in network routing, the stopping criterion might be the first edge blocked in a path. We consider position discounts in the list order, so that the agent's reward is discounted depending on the position where the stopping criterion is met. We design a UCB type algorithm, C3 UCB, for this problem, prove an n step regret bound O(n) in the general setting, and give finer analysis for two special cases. Our work generalizes existing studies in several directions, including contextual information, position discounts, and a more general cascading bandit model. Experiments on synthetic and real datasets demonstrate the advantage of involving contextual information and position discounts.
Erythema Multiforme Associated With Misoprostol: A Case Report.
Venue: American journal of therapeutics

A 33 year old healthy woman at 6 weeks of gestation without any underlying disease developed erythema multiforme (EM) after misoprostol. She had no history of herpes simplex virus infection and drug allergy to nonsteroidal anti inflammatory drugs and antibiotic agents. Medical abortion was performed at 6 weeks' gestation. Later day, the patient developed oral lesions as several white bullae lesions in her buccal mucosa and hyperkeratotic lip plaques with mild pain. Then, lesions resolved within approximately 3 weeks. Microscopic finding of oral biopsy from beneath the tongue and lesions was performed. The result was consistent with erosive mucosa with granulation tissue formation and acute inflammation in favor of EM. This is the case report of probable misoprostol induced EM. Because EM may produce in skin as a Stevens Johnson syndrome in subsequent attack, monitoring of this adverse drug reaction should be considered for proper management and follow up.
Real time virtual view synthesis using light field
Venue: EURASIP J. Image Video Process.

Virtual view synthesis technique renders a virtual view image from several pre collected viewpoint images. The hotspot on virtual view synthesis area is depth image based rendering (DIBR) which has low one time imaging quality. To achieve high imaging quality artifacts, the holes must be inpainted after image warping which means high computational complexity. This paper proposed a real time virtual view synthesis method from light field. Then the light field is transformed into frequency domain. The light field is parameterized and reconstructed from image array. The virtual view is rendered by resampling the light field in frequency domain. After resampling the image by performing Fourier slice, the virtual view image is obtained by inverse Fourier transform. Experiments show that our method can get high one time imaging quality in real time.
YARN versus MapReduce A comparative study
Venue: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom)

The amount of digital data has exploded in recent years. One of the most popular tools for storage and processing of such huge digital data is Apache Hadoop[8] The initial version of Hadoop i.e Hadoop 1.x supports distributed processing of large scale data using core MapReduce processing engine. ) allows processing of big amount of data(i.e BigData) in parallel on large clusters of computers. Even though Hadoop can be considered as a fast, scalable, cost effective and fault tolerant solution to big data problem, certain limitations exists in the Hadoop 1.x. However, things changed with the introduction of Hadoop 2.x. Hadoop 2.0 uses YARN(Yet Another Resource Negotiator) which separates the resource management and job scheduling task. This paper discusses the advantages YARN offered over the previous version of processing framework in Hadoop and also compares MapReduce and YARN based on some selected parameters.
Trajectory tracking control of a flapping wing micro aerial vehicle via neural networks
Venue: 2016 International Conference on Advanced Robotics and Mechatronics (ICARM)

This conference paper figures out the tracking control issue of a flapping wing micro aerial vehicle (FWMAV) subject to uncertain system parameters based on the model in Lagrangian form. As we know, there are many uncertainties in the complex nonlinear system. To deal with this problem, radial basis function neural networks (RBFNNs) are considered to substitute uncertainties of FWMAV model. Through Lyapunov stability analysis, all the control performances of the FWMAV system are guaranteed via selecting the appropriate control variables. The boundedness of system states is achieved. Finally, a series of simulations are realized with MATLAB and show good tracking results via our control methods.
How Does Risk Flow in the Credit Default Swap Market?

We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow of risk and provide sufficient conditions for a bow tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS) ii) Dealers (indirectly connected to each other) iii) Ultimate Risk Buyers (URB) We show that the probability of widespread distress due to counterparty risk is higher in a bow tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 2014. We find the presence of a bow tie network architecture consistently across both reference entities and time, and that the flow of risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non banks (in particular asset managers) Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
Sentiment Analysis of Twitter Data A Survey of Techniques
Venue: ArXiv

the advancement of web technology and its growth, there is a huge volume of data present in the web for internet users and a lot of data is generated too. Internet has become a platform for online learning, exchanging ideas and sharing opinions. Social networking sites like Twitter, Facebook, Google+ are rapidly gaining popularity as they allow people to share and express their views about topics, have discussion with different communities, or post messages across the world. There has been lot of work in the field of sentiment analysis of twitter data. This survey focuses mainly on sentiment analysis of twitter data which is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous and are either positive or negative, or neutral in some cases. In this paper, we provide a survey and a comparative analyses of existing techniques for opinion mining like machine learning and lexicon based approaches, together with evaluation metrics. Using various machine learning algorithms like Naive Bayes, Max Entropy, and Support Vector Machine, we provide research on twitter data streams.We have also discussed general challenges and applications of Sentiment Analysis on Twitter.
Sentiment analysis of Twitter data for predicting stock market movements
Venue: 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)

Predicting stock market movements is a well known problem of interest. Now a days social media is perfectly representing the public sentiment and opinion about current events. Especially, Twitter has attracted a lot of attention from researchers for studying the public sentiments. Stock market prediction on the basis of public sentiments expressed on Twitter has been an intriguing field of research. Previous studies have concluded that the aggregate public mood collected from Twitter may well be correlated with Dow Jones Industrial Average Index (DJIA) The thesis of this work is to observe how well the changes in stock prices of a company, the rises and falls, are correlated with the public opinions being expressed in tweets about that company. Understanding author's opinion from a piece of text is the objective of sentiment analysis. The present paper have employed two different textual representations, Word2vec and N gram, for analyzing the public sentiments in tweets. In this paper, we have applied sentiment analysis and supervised machine learning principles to the tweets extracted from Twitter and analyze the correlation between stock market movements of a company and sentiments in tweets. In an elaborate way, positive news and tweets in social media about a company would definitely encourage people to invest in the stocks of that company and as a result the stock price of that company would increase. At the end of the paper, it is shown that a strong correlation exists between the rise and falls in stock prices with the public sentiments in tweets.
Colorism as a Salient Space for Understanding in Teacher Preparation

In this article, we posit the salience of colorism as an important aspect of race in the knowledge construction and preparation of teachers. Although many more teacher education programs across the United States have begun to infuse aspects of race into their curricula, there is sparse literature about the role of colorism in teacher preparation and its potential impact. This article explicitly focuses on darker skinned students, who experience trauma differently from lighter skinned students. This research chronicles the particular experiences of African American female students who endure deep seated biases and attitudes regarding their skin color, both outside of and within school environments. We argue that teacher education programs should include learning opportunities on construction of race as a phenotype (the physical construction of skin tone, hair texture, facial features, and body physique) as an influence on the thinking, beliefs, and consequent practices of teachers in P 12 classrooms. The article concludes with an explicit recommendation for teacher education programs to prioritize colorism in the preparation of teachers.
Nurse handover: patient and staff experiences.
Venue: British journal of nursing

to understand the purpose, impact and experience of nurse handover from patient and staff perspectives. BACKGROUND poor communication is increasingly recognised as a major factor in healthcare errors. Handover is a key risk point. Little consensus exists regarding the practice in nursing but the trend is towards bedside handover. Research on patient and staff experiences of handover is limited. DESIGN a qualitative and observational study on two acute wards in a large urban hospital in the UK. METHODS interviews conducted with patients and staff and observation of handovers, ward rounds and patient staff interactions. RESULTS diverse forms of nurse handover were found, used in combination: office based (whole nursing team) nurse in charge (NIC) to NIC, and bedside. Patients' and nurses' views concurred on the purpose of bedside handover transference of information about the patient between two nurses and about the medical ward round, which was seen as a discussion with the patient. Views diverged regarding the purpose and value of office handover. Bedside handover differed in style, content, and place of delivery, often driven by concerns regarding confidentiality and talking over patients, and there were varied views on the benefits of patient involvement in bedside handover. Nurses worked beyond their shift end to complete handover. Communication problems within the clinical team were identified by staff and patients. CONCLUSIONS while it is important to agree the purpose of handover and develop appropriate structure, content and style, it need not be a uniform process in all clinical areas. Nurse training to deliver bedside handover and patient information on the purpose of handover and the patient's role would be beneficial.
9 Norbornyl 6 chloropurine (NCP) induces cell death through GSH depletion associated ER stress and mitochondrial dysfunction.
Venue: Free radical biology medicine

UNLABELLED 9 Norbornyl 6 chloropurine (NCP) is a representative of a series of antienteroviral bicycle derivatives with selective cytotoxicity towards leukemia cell lines. In this work we explored the mechanism of the antileukemic activity of NCP in T cell lymphoblast cells (CCRF CEM) Specifically, we searched for a potential link between its ability to induce cell death on the one hand and to modulate intracellular glutathione (GSH) that is necessary to its metabolic transformation via glutathione S transferase on the other hand. We have observed that GSH levels decreased rapidly in NCP treated cells. Despite a complete regeneration following 24h of incubation with NCP, this profound drop in cellular GSH content triggered ER stress, ROS production and lipid peroxidation leading to the loss of mitochondrial membrane potential (MMP) These events induced concentration dependent cell cycle arrest in G2/M phase and apoptosis. Both MMP loss and apoptosis were reversed by sulfhydryl containing compounds (GSH, N acetyl l cysteine) Furthermore, we have also shown that NCP induced GSH decrease activated the Nrf2 pathway and its downstream targets NAD(P)H quinone oxidoreductase (NQO 1) and glutamate cysteine ligase modifier subunit (GCLm) thus explaining the fast restoration of GSH pool and ROS decrease. Importantly, we confirmed that the cell death inducing properties of the compounds were co dependent on their ability to diminish cellular GSH level by analyzing the relationships between the GSH depleting potency and cytotoxicity in a series of other norbornylpurine analogs. Altogether, the results demonstrated that in CCRF CEM cells NCP triggered apoptosis through GSH depletion associated oxidative and ER stress and mitochondrial depolarization.
Radio Sources in the NCP Region Observed with the 21 Centimeter Array

We present a catalog of 624 radio sources detected around the North Celestial Pole (NCP) with the 21 Centimeter Array (21CMA) a radio interferometer dedicated to the statistical measurement of the epoch of reionization (EoR) The data are taken from a 12 h observation made on 2013 April 13, with a frequency coverage from 75 to 175 MHz and an angular resolution of 4 arcmin. The catalog includes flux densities at eight sub bands across the 21CMA bandwidth and provides the in band spectral indices for the detected sources. To reduce the complexity of interferometric imaging from the so called "w" term and ionospheric effects, the present analysis are restricted to the east west baselines within 1500 m only. The 624 radio sources are found within 5 degrees around the NCP down to 0.1 Jy. Our source counts are compared, and also exhibit a good agreement, with deep low frequency observations made recently with the GMRT and MWA. In particular, for fainter radio sources below 1 Jy, we find a flattening trend of source counts towards lower frequencies. While the thermal noise ~0.4 mJy) is well controlled to below the confusion limit, the dynamical range ~10^4) and sensitivity of current 21CMA imaging is largely limited by calibration and deconvolution errors, especially the grating lobes of very bright sources, such as 3C061.1, in the NCP field which result from the regular spacings of the 21CMA. We note that particular attention should be paid to the extended sources, and their modeling and removals may constitute a large technical challenge for current EoR experiments. Our analysis may serve as a useful guide to design of next generation low frequency interferometers like the Square Kilometre Array.
What is the generalization of natural residual function for NCP

It is well known that the generalized Fischer Burmeister is a natural extension of the popular Fischer Burmeister function NCP function, in which the 2 norm is replaced by general p norm. As for another popular natural residual NCP function, its generalization was unknown during the past three decades. In this short communication, we answer this long standing open question. In particular, we propose the generalization of natural residual function for NCP, which possesses twice differentiability. This feature enables that many methods like Newton method can be employed directly for solving NCP. This is a new discovery to the literature and we believe that such generalized function can also be employed in many other contexts. Corresponding author. The author's work is supported by Ministry of Science and Technology, Taiwan.  chko@isu.edu.tw E mail: cantor0968@gmail.com
Refactoring the Genia Event Extraction Shared Task Toward a General Framework for IE Driven KB Development
Venue: BioNLP

For its fourth organization, the Genia event extraction (GE) shared task is refactored toward a general platform for shared information extraction (IE) tasks, and for an IEdriven knowledge base (KB) system. On the newly implemented shared task platform, the GE task is run as an experimental task. The task and the platform has been tested by two teams who cooperated with the organizers. The paper presents the new shared task system and discusses on the experimental submissions.
Effects of online presence on learning performance in a blog based online course
Venue: Internet High. Educ.

This study investigated how learners' perceived online presence contributed to their learning performance while participating in a blog based university course. Although the literature evidently highlights that there is a necessity for online presence in online courses, concrete design approaches and empirical evaluation of the impact of online presence on learning performance in blog based courses are lacking. An empirical study was therefore conducted to understand the relationship between individuals' perceptions of online presence, in terms of teaching, social and cognitive presences, and their learning performance, in terms of subjective and objective learning outcomes. Research questions were tested and data were analyzed using regression analysis. The results indicate that online presence has a significant influence on learning performance. A subsequent analysis found that cognitive presence played the most important role in blog based online learning performance. This study also identified a significant relationship in learning performance between students' subjective and objective learning outcomes.
The Effects of Instructor Control of Online Learning Environments on Satisfaction and Perceived Learning.

Instructional design is important as it helps set the discourse, context, and content of learning in an online environment. Specific instructional design decisions do not only play a part in the discourse of the learners, but they can affect the learners' levels of satisfaction and perceived learning as well. Numerous studies have shown the value that both student satisfaction and learning have on learner achievement. For this reason, the question of whether instructors can impact satisfaction and perceived learning through various instructional design decisions is important. This study looked at broad based instructor decisions to see if online environments with higher levels of instructor control lead to higher levels of student satisfaction and/or perceived learning. Three different online environments were used, with each one containing progressively more instructor control. The results show that there were no significant differences in regards to mean levels of satisfaction between the three environments. However, there were significant differences among mean levels of perceived learning based on the differing instructor controlled environments. This study shows that increasing the levels of instructor control within online environments leads to an increase in perceived learning.