nils-herrmann/clean_scirepeval huggingface dataset:
History of endonasal skull base surgery.
Venue: Journal of neurosurgical sciences

While the endonasal approach to the skull base continues to advance, this paper invokes its long history. The centuries of medieval neuroanatomy and early neurosurgery enabled the conception of the first transfacial approaches in the late 1800s; Henry Schloffer performed the first transsphenoidal surgery in 1907. Although the procedure was initially met with much interest, Harvey Cushing eventually led the field of neurosurgery to abandon the transsphenoidal approach in the 1920s. The following three generations of neurosurgeons contained several key figures including Norman Dott, Gerard Guiot, and Jules Hardy who were steadfast in preserving the technique as well as in addressing its shortcomings. The endoscopic approach developed simultaneously, and advances in magnifying and fiberoptics further resolved limitations previously inherent to the transsphenoidal approach. At last, in the 1960s, the transsphenoidal approach entered its renaissance. Today, the momentum of its development persists in the endoscopic endonasal approach, which has recently expanded the indications for transsphenoidal surgery across the skull base, far beyond its original jurisdiction of the sella. Continued progress must not take for granted the rich history of the transsphenoidal approach, which was developed over centuries by surgeons around the world. The authors present the evolution of modern endonasal surgery as a dynamic interplay between technology, medicine, and surgery over the past 100 years. Progress can be attributed to courageous surgeons who affirmed their contemporary practices despite gaps in technology or medicine, and to visionary individuals who produced and incorporated new elements into transsphenoidal surgery. And so while the new endoscopic technique brings forth new challenges, its development reaffirms the principles laid down by the pioneers of transsphenoidal surgery.
Trump, Brexit, and the Rise of Populism: Economic Have Nots and Cultural Backlash

Rising support for populist parties has disrupted the politics of many Western societies. What explains this phenomenon? Two theories are examined here. Perhaps the most widely held view of mass support for populism the economic insecurity perspective emphasizes the consequences of profound changes transforming the workforce and society in post industrial economies. Alternatively, the cultural backlash thesis suggests that support can be explained as a reaction against cultural changes that threaten the worldview of once predominant sectors of the population. To consider these arguments, Part I develops the conceptual and theoretical framework. Part II of the study uses the 2014 Chapel Hill Expert Survey (CHES) to identify the ideological location of 268 political parties in 31 European countries. Part III compares the pattern of European party competition at national level. Part IV uses the pooled European Social Survey 1 6 (2002 2014) to examine the cross national evidence at individual level for the impact of the economic insecurity and cultural values as predictors of voting for populist parties. Part V summarizes the key findings and considers their implications. Overall, we find consistent evidence supporting the cultural backlash thesis.
Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts
Venue: Lang. Resour. Evaluation

We present the development and evaluation of a semantic analysis task that lies at the intersection of two very trendy lines of research in contemporary computational linguistics: (1) sentiment analysis, and (2) natural language processing of social media text. The task was part of SemEval, the International Workshop on Semantic Evaluation, a semantic evaluation forum previously known as SensEval. The task ran in 2013 and 2014, attracting the highest number of participating teams at SemEval in both years, and there is an ongoing edition in 2015. The task included the creation of a large contextual and message level polarity corpus consisting of tweets, SMS messages, LiveJournal messages, and a special test set of sarcastic tweets. The evaluation attracted 44 teams in 2013 and 46 in 2014, who used a variety of approaches. The best teams were able to outperform several baselines by sizable margins with improvement across the 2 years the task has been run. We hope that the long lasting role of this task and the accompanying datasets will be to serve as a test bed for comparing different approaches, thus facilitating research.
Broad Twitter Corpus: A Diverse Named Entity Recognition Resource
Venue: COLING

One of the main obstacles, hampering method development and comparative evaluation of named entity recognition in social media, is the lack of a sizeable, diverse, high quality annotated corpus, analogous to the CoNLL'2003 news dataset. For instance, the biggest Ritter tweet corpus is only 45,000 tokens a mere 15% the size of CoNLL'2003. Another major shortcoming is the lack of temporal, geographic, and author diversity. This paper introduces the Broad Twitter Corpus (BTC) which is not only significantly bigger, but sampled across different regions, temporal periods, and types of Twitter users. The gold standard named entity annotations are made by a combination of NLP experts and crowd workers, which enables us to harness crowd recall while maintaining high quality. We also measure the entity drift observed in our dataset (i.e. how entity representation varies over time) and compare to newswire. The corpus is released openly, including source text and intermediate annotations.
Domain Adaptation for Named Entity Recognition Using CRFs
Venue: LREC

In this paper we explain how we created a labelled corpus in English for a Named Entity Recognition (NER) task from multi source and multi domain data, for an industrial partner. We explain the specificities of this corpus with examples and describe some baseline experiments. We present some results of domain adaptation on this corpus using a labelled Twitter corpus (Ritter et al. 2011) We tested a semi supervised method from (Garcia Fernandez et al. 2014) combined with a supervised domain adaptation approach proposed in (Raymond and Fayolle, 2010) for machine learning experiments with CRFs (Conditional Random Fields) We use the same technique to improve the NER results on the Twitter corpus (Ritter et al. 2011) Our contributions thus consist in an industrial corpus creation and NER performance improvements.
Stochastic blockmodels for exchangeable collections of networks

We construct a novel class of stochastic blockmodels using Bayesian nonparametric mixtures. These model allows us to jointly estimate the structure of multiple networks and explicitly compare the community structures underlying them, while allowing us to capture realistic properties of the underlying networks. Inference is carried out using MCMC algorithms that incorporates sequentially allocated split merge steps to improve mixing. The models are illustrated using a simulation study and a variety of real life examples.
Deep Learning Powered In Session Contextual Ranking using Clickthrough Data

User interactions with search engines provide many cues that can be leveraged to improve the relevance of search results through personalization. The context information (history of queries, clicked documents, etc. provides strong signals about users' search intent, which can be used to personalize the search experience and improve a web search engine. We demonstrate how to generate the semantic features from in session contextual information with deep learning models, and incorporate these semantic features into the current ranking model to re rank the results. We evaluate our approach using a large, real world search log data from a major commercial web search engine, and the experimental results show our approach can significantly improve the performance of the search engine. Furthermore, we also find that the domain specific, click based features can effectively decrease the unsatisfied clicks for the current ranking model to improve the search experience.
Anaerobic oxidation of methane associated with sulfate reduction in a natural freshwater gas source
Venue: The ISME Journal

The occurrence of anaerobic oxidation of methane (AOM) and trace methane oxidation (TMO) was investigated in a freshwater natural gas source. Sediment samples were taken and analyzed for potential electron acceptors coupled to AOM. Long term incubations with 13C labeled CH4 (13CH4) and different electron acceptors showed that both AOM and TMO occurred. In most conditions, 13C labeled CO2 (13CO2) simultaneously increased with methane formation, which is typical for TMO. In the presence of nitrate, neither methane formation nor methane oxidation occurred.  AOM was measured only with sulfate as electron acceptor. Here, sulfide production occurred simultaneously with 13CO2 production and no methanogenesis occurred, excluding TMO as a possible source for 13CO2 production from 13CH4. Archaeal 16S rRNA gene analysis showed the highest presence of ANME 2a/b (ANaerobic MEthane oxidizing archaea) and AAA (AOM Associated Archaea) sequences in the incubations with methane and sulfate as compared with only methane addition. Higher abundance of ANME 2a/b in incubations with methane and sulfate as compared with only sulfate addition was shown by qPCR analysis. Bacterial 16S rRNA gene analysis showed the presence of sulfate reducing bacteria belonging to SEEP SRB1. This is the first report that explicitly shows that AOM is associated with sulfate reduction in an enrichment culture of ANME 2a/b and AAA methanotrophs and SEEP SRB1 sulfate reducers from a low saline environment.
Exploiting plume structure to decode gas source distance using metal oxide gas sensors

Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that can be exploited for distance estimation in a turbulent environment lies in the relationship between source proximity and the temporal variance of the local gas concentration the farther the source, the more intermittent are gas encounters. However, exploiting this feature requires measurement of changes in gas concentration on a comparably fast time scale, that have up to now only been achieved using photo ionisation detectors. Here, we demonstrate that by appropriate signal processing, off the shelf metal oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance. We show that with a straightforward analysis method it is possible to decode events of large, consistent changes in the measured signal, so called 'bouts' The frequency of these bouts predicts the distance of a gas source in wind tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross wind offset to the centreline of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off the shelf metal oxide sensors. The analysis method we employ demands very few computational resources and is suitable for low power microcontrollers.
Young Children's Understanding of Social Norms and Social Institutions

Children are born into a world abundant with social norms that prescribe how one should and should not behave. Social norms also form the basis of more complex social institutions such as ownership that create obligations, rights and duties. As adults we typically navigate our social world effortlessly and mostly unaware of the intricate web of social norms and institutions shaping our behaviour. But when and how do young children first become aware of the norms and institutions of their socio cultural group? In this chapter, we will first provide a definition of social norms and institutions and explain their most important characteristics. We will then present empirical evidence that children as young as 3 years of age already understand some crucial aspects of social norms. We will further use the example of ownership to argue that it is one of the first social institutions that young children understand.
Investigating the Perceptions of Pakistani English Language Learners on Language Learning Anxiety in EFL Classroom

This quantitative study aims to investigate the perceptions of English Language Learners on Language learning Anxiety in EFL classroom. Participants of the study were 145 Intermediate level students of different public colleges of Hyderabad, Sindh who are learning English as a foreign language. The data was collected through the modified form of Foreign Language Classroom Anxiety Scale (FLCAS) by Horwitz et al. (1986) Findings of this study reveal the causes of foreign language anxiety from the learners' perceptions such as communication apprehension was identified as the main cause of anxiety followed by the learners' self perceived proficiency, fear of being negatively evaluated and nervousness as other sources of anxiety. However, their motivational intensity is higher to learn English. Based on the findings of the study, many of the suggestions are recommended for language teacher however it is also considered that language anxiety is a multi faceted and complicated in nature which needs further exploration.  Perceptions, Pakistani language learners, EFL classroom
Learning Strategies in Alleviating English Writing Anxiety for English Language Learners (ELLs) with Limited English Proficiency (LEP)

This study utilized the Oxford Strategy Inventory for Language Learning (SILL) and an English writing anxiety scale to examine the relationship between learning strategies and English writing anxiety in 102 university level English language learners (ELLs) with Limited English Proficiency (LEP) in a university in Taiwan. Kruskal Wallis Test results revealed no significant association between learning strategies and English writing anxiety. The common learning strategies utilized by participants were compensation, social, memory and mixed strategies. The interview data indicated that ELLs suffered considerably from writing anxiety. Coping strategies of highly anxious ELL of each learning strategy group is also reported. However, further studies of larger populations and comparison of different ethnic groups as well as quantitative statistics analyses are needed.
NARRATIVE STRATEGY AND IMPERIALISM IN CONRAD'S "LORD JIM"

"Indeed this affair, I may notice in passing, had an extraordinary power of defying the shortness of memories and the length of time: it seemed to live, with a sort of uncanny vitality, in the minds of men, on the tips of their tongues."1 So says Marlow, the main narrator in Lord Jim, of the abandonment of 800 Muslim pilgrims on the frigate, the Patna, by a white crew. The Patna affair provides the initial occasion of Marlow's interest in Jim, first mate on the frigate. The episode reflects the tension between white and non white in a world already carved out between various European nations. Yet, rather surprisingly, Marlow seems not to understand the hold of this event on the minds of people who are not seamen. Marlow's apparent incomprehension here is curious because the tale Marlow tells his listeners in Lord Jim is at least peripherally concerned with the relationship between colonizer and colonized. At various times, in fact, Jim's story provides the impetus for addressing the role of the white man in a colonial milieu. Yet rather than addressing the issues of race that underlie the Patna fiasco, Marlow's tale draws into question the relationship between duty and character. The event on the Patna leads to an analysis of the disjunction between an individual's heroic sense of himself and his private capacity.2 Although the origin of Marlow's interest in Jim is the racially charged episode aboard the Patna, his narrative quickly becomes concerned with "larger" issues of epistemological and metaphysical doubt. The shift of interest I describe here is representative of Marlow's narrative throughout Lord Jim: his chief concern is with "the state of a man's soul" (p. 43) rather than with the material conditions created by imperialism that determine the contours of Jim's life. For Marlow, the contradictions of the colonial situation only provide the backdrop for the narrative's interest in the modernist condition of fragmentation and isolation. By analysing three key moments of the narrative structure?first, the entry of Marlow into the narrative; second, the moment when his spoken narrative yields to his written one; and third, the shift to romance and adventure in the Patusan section?I argue that the narrative of Lord Jim relies on the discursive field of imperialism to explore the figure of Jim.3
Understanding the Acceptance of Augmented Reality at an Organisational Level: The Case of Geevor Tin Mine Museum
Venue: ENTER

Augmented Reality (AR) has recently emerged as a popular tool for tourism organisations to enhance visitors' experiences through its ability to overlay information into the real world environment. Cultural heritage attractions such as museums have begun exploring the potentials and benefits of AR, but it remains a largely new field of research. The importance of user acceptance and adoption studies are well established; however, research into the implementation of AR from an organisational perspective is scarce. This study therefore aims to understand the perception towards AR implementation at an organisational level using semi structured interviews with nine internal stakeholders at Geevor museum. Interviews were analysed using content analysis and findings demonstrate positive support for AR implementation, identifying a variety of potential ways it could enhance the experience of both visitors and staff.
Tackling Climate Change Through the Elimination of Trade Barriers for Low Carbon Goods: Multilateral, Plurilateral and Regional Approaches

While the trade and environment debate has long focused on the adverse impact of environmental measures on free trade and vice versa and on securing policy space to regulate in the environmental interest, the focus has only recently started to shift to the potentially reinforcing relationship between trade and sustainable development. The present contribution explores this notion by discussing the liberalization of trade in low carbon goods as a contribution to the fight against climate change. It provides an overview over the existing trade barriers and the efforts to eliminate these barriers for renewable energy goods and energy efficient technologies. The contribution furthermore identifies the liberalization potentials and main challenges in the multilateral, plurilateral and regional contexts. Perhaps surprisingly, mega regional trade agreements are identified as the most promising venue to pursue ambitious liberalization efforts for low carbon goods, if trade negotiators were willing to make this a central part of the agreements.
Malignant Brenner Tumour of the Ovary: A Rare Entity

Malignant Brenner tumors (MBTs) of the ovary are very rare, and their definition, biology and treatment modality have not been established. Most Brenner tumors are benign, with only 1% being malignant. In this study we present a case of 30 years old women with a rare malignant Brenner tumour. She presented at a peripheral referral hospital with a complaint of abdominal pain and mass. Ultrasonography revealed left sided ovarian tumours. She is referred for evaluation of a complex pelvic mass and elevated serum CA 125 level. She underwent left salpingo oophorectomy and the specimen was sent for histopathological study. Histopathology revealed malignant Brenner tumour. Immunohistochemistry tumour cells are positive for pancytokeratin and negative for CK7/CK8/WT1/Pax8/CA125/calretinin/inhibin.
Efficient implementation of scatter gather operations for large scale graph analytics
Venue: 2016 IEEE High Performance Extreme Computing Conference (HPEC)

We developed a methodology to improve the cache behavior and overall performance of sparse linear algebra kernels used in graph analytics. Large scale graph processing typically has low performance because it cannot effectively use processor caches, resulting in high latency for memory accesses. This is particularly true in a sparse linear algebra formulations of graph algorithms, which use well known kernels such as sparse matrix vector multiply and sparse matrix transposition. The proposed methodology partitions the inner loops of linear algebra kernels, and executes the iterations over these partitions in an independently ordered manner. This produces more cache friendly access patterns, which reduce cache misses and improve performance. We first illustrate the technique through an example and then generalize it to multiple scenarios. Our evaluation shows that execution time of key computational kernels is reduced by 2 to 5 fold, when large graphs are considered. Most of the improvement in execution time comes from a significant reduction in cycles per instruction (CPI) even as the path length of the executed code increases.
Scatter Gather I O No Longer Considered Harmful

Unified extensible modalities have led to many key advances, including the location identity split and von Neumann machines. Even though this result at first glance seems counterintuitive, it is derived from known results. After years of important research into cache coherence, we disprove the synthesis of the partition table. We demonstrate that while vacuum tubes can be made eventdriven, omniscient, and cacheable, extreme programming and hierarchical databases can cooperate to realize this objective.
A New Simple CO2 Minimum Miscibility Pressure Correlation

The minimum miscibility pressure (MMP) is one of the most important parameter to be determined in miscible gas injection projects to ensure and maximize the displacement sweep efficiency inside the reservoir. Usually the most effective way of determining the MMP is to run slim tube experiments. However, in the early screening stage, we often relay on the published empirical correlations to estimate the MMP and identify the candidate fields for EOR gas injection projects. The main objective of this paper was to examine different published empirical CO2 MMP correlations using measured data mainly obtained from Libya and other published resources, and also to develop a new simple reliable correlation to be applied in the oil industry. The data collected covered a wide range of CO2 MMP (1544 6244 psia) and oil API gravity (28 50oAPI) Minitab regression tool was extensively used in our study and a wide range of new constructed correlations ranging from simple to complex ones were developed and statistically evaluated. The proposed simple CO2 MMP correlation is mainly function of the measured Pb, API, T and Rsi and has very reliable degree of accuracy (SD=6.7% ARE=0.44% AARE=5.74% R2=95.22% for the examined data and has shown better performance when compared with the industry popular correlations. The new correlation was validated against 100 measured PVT variables (Pb, Rsi, T and API) obtained from Libya, and the predicted CO2 MMP results have demonstrated very reliable trend (within the measured CO2 MMP trend) with no anomalies.