nils-herrmann/clean_scirepeval huggingface dataset:
Clinical implementation of an emergency department coronary computed tomographic angiography protocol for triage of patients with suspected acute coronary syndrome
Venue: European Radiology

ObjectivesTo evaluate the efficiency and safety of emergency department (ED) coronary computed tomography angiography (CTA) during a 3 year clinical experience.MethodsSingle center registry of coronary CTA in consecutive ED patients with suspicion of acute coronary syndrome (ACS) The primary outcome was efficiency of coronary CTA defined as the length of hospitalization. Secondary endpoints of safety were defined as the rate of downstream testing, normalcy rates of invasive coronary angiography (ICA) absence of missed ACS, and major adverse cardiac events (MACE) during follow up, and index radiation exposure.ResultsOne thousand twenty two consecutive patients were referred for clinical coronary CTA with suspicion of ACS. Overall, median time to discharge home was 10.5 (5.7 24.1) hours. Patient disposition was 42.7 direct discharge from the ED, 43.2 discharge from emergency unit, and 14.1 hospital admission. ACS rate during index hospitalization was 9.1 One hundred ninety two patients underwent additional diagnostic imaging and 77 underwent ICA. The positive predictive value of CTA compared to ICA was 78.9 (95 CI 68.1 87.5 Median CT radiation exposure was 4.0 (2.5 5.8) mSv. No ACS was missed; MACE at follow up after negative CTA was 0.2 .ConclusionsCoronary CTA in an experienced tertiary care setting allows for efficient and safe management of patients with suspicion for ACS.Key points* ED Coronary CTA using advanced systems is associated with low radiation exposure. Negative coronary CTA is associated with low rates of MACE. CTA in ED patients enables short median time to discharge home. CTA strategy is characterized by few downstream tests including unnecessary ICA.
Nests of the brown booby (Sula leucogaster) as a potential indicator of tropical ocean pollution by marine debris

Seabirds collect debris primarily nearby breeding sites, and thus they may be used to monitor these pollutants in the ocean. This study aimed to investigate the prevalence of marine debris used as nesting materials by the brown booby (Sula leucogaster) and to test the species selectivity to debris type and color in two coastal islands of Brazil. We found marine debris in 61% of the brown booby nests on both islands. Fishing gear and hard plastic were the most frequent types of debris. Higher prevalence of fishing gear was found on the island with greater fishery activity. Similarly, hard plastic was the most frequent type of debris in nests and adjacent beach environment. The frequency of debris in brown booby nests can be a potential indicator of the abundance of specific items in surrounding marine waters. Monitoring debris in brown booby nests in a long term may provide a better understanding of the species selectivity for specific debris. Furthermore, the impacts of debris in seabird nests at population level remain an overlooked threat that may reduce the quality of nesting habitats. We showed that brown booby nests are widely impacted by marine debris and that these organisms are exposed to this form of pollution from the beginning of their life.
PotTS at SemEval 2016 Task 4: Sentiment Analysis of Twitter Using Character level Convolutional Neural Networks.
Venue: *SEMEVAL

This paper presents an alternative approach to polarity and intensity classification of sentiments in microblogs. In contrast to previous works, which either relied on carefully designed hand crafted feature sets or automatically derived neural embeddings for words, our method harnesses character embeddings as its main input units. We obtain task specific vector representations of characters by training a deep multi layer convolutional neural network on the labeled dataset provided to the participants of the SemEval 2016 Shared Task 4 (Sentiment Analysis in Twitter; Nakov et al. 2016b) and subsequently evaluate our classifiers on subtasks B (two way polarity classification) and C (joint five way prediction of polarity and intensity) of this competition. Our first system, which uses three manifold convolution sets followed by four non linear layers, ranks 16 in the former track; while our second network, which consists of a single convolutional filter set followed by a highway layer and three non linearities with linear mappings in between, attains the 10 th place on subtask C.1
A REVIEW OF RAIN STREAKS DETECTION AND REMOVAL TECHNIQUES FOR OUTDOOR SINGLE IMAGE Samer

The impact of rain weather in the images will make it complicated to distinguish in the environment surroundings using an outdoor camera. Moreover, single image plays important role in numerous areas such as in object recognition and detection, enhancement, noise removal and weather condition removal. Rainy weather of outdoor images and videos reduces the visibility, performance of computer vision algorithms and other outdoor activities, which use for extracting features and information from images. Most of the previous review papers focus on the video techniques and raindrops which adherent on the surface and in the images. This paper presents a review of restoration rain streaks detection and removal from single image which has different techniques used in video and includes the result of the implemented experiments using three images.
DehazeNet: An End to End System for Single Image Haze Removal
Venue: IEEE Transactions on Image Processing

Single image haze removal is a challenging ill posed problem. Existing methods use various constraints/priors to get plausible dehazing solutions. The key to achieve haze removal is to estimate a medium transmission map for an input hazy image. In this paper, we propose a trainable end to end system called DehazeNet, for medium transmission estimation. DehazeNet takes a hazy image as input, and outputs its medium transmission map that is subsequently used to recover a haze free image via atmospheric scattering model. DehazeNet adopts convolutional neural network based deep architecture, whose layers are specially designed to embody the established assumptions/priors in image dehazing. Specifically, the layers of Maxout units are used for feature extraction, which can generate almost all haze relevant features. We also propose a novel nonlinear activation function in DehazeNet, called bilateral rectified linear unit, which is able to improve the quality of recovered haze free image. We establish connections between the components of the proposed DehazeNet and those used in existing methods. Experiments on benchmark images show that DehazeNet achieves superior performance over existing methods, yet keeps efficient and easy to use.
Data Quality Challenges and Future Research Directions in Threat Intelligence Sharing Practice
Venue: WISCS@CCS

In the last couple of years, organizations have demonstrated an increased willingness to participate in threat intelligence sharing platforms. The open exchange of information and knowledge regarding threats, vulnerabilities, incidents and mitigation strategies results from the organizations' growing need to protect against today's sophisticated cyber attacks. To investigate data quality challenges that might arise in threat intelligence sharing, we conducted focus group discussions with ten expert stakeholders from security operations centers of various globally operating organizations. The study addresses several factors affecting shared threat intelligence data quality at multiple levels, including collecting, processing, sharing and storing data. As expected, the study finds that the main factors that affect shared threat intelligence data stem from the limitations and complexities associated with integrating and consolidating shared threat intelligence from different sources while ensuring the data's usefulness for an inhomogeneous group of participants.Data quality is extremely important for shared threat intelligence. As our study has shown, there are no fundamentally new data quality issues in threat intelligence sharing. However, as threat intelligence sharing is an emerging domain and a large number of threat intelligence sharing tools are currently being rushed to market, several data quality issues particularly related to scalability and data source integration deserve particular attention.
Optimal Power Flow Using an Improved Electromagnetism like Mechanism Method

In this article, an improved version of the electromagnetism like mechanism is developed and proposed to find the optimal solution for the optimal power flow problem in a power system. To show the effectiveness of the developed method, it has been demonstrated on standard IEEE 30 bus and IEEE 57 bus test systems for seven different objectives that reflect fuel cost minimization with generators that may have either convex or non convex fuel cost characteristics, voltage profile improvement, voltage stability enhancement, and active and reactive power transmission losses minimization. The results obtained using the improved version of the electromagnetism like mechanism method are compared with those obtained using different methods reported in the literature. Considering the quality of these results, the proposed method is a quite promising alternative approach for solving optimal power flow problems.
Level Set Methods And Fast Marching Methods

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Clinical relevance of the tumor microenvironment and immune escape of oral squamous cell carcinoma
Venue: Journal of Translational Medicine

BackgroundChanges in the tumor microenvironment and immune surveillance represent crucial hallmarks of various kinds of cancer, including oral squamous cell carcinoma (OSCC) and a close crosstalk of hypoxia regulating genes, an activation of chemokines and immune cells has been described.MethodsA review about the pivotal role of HIF 1, its crosstalk to various cornerstones in OSCC tumorigenesis is presented.ResultsHypoxia is a frequent event in OSCC and leads to a reprogramming of the cellular metabolism in order to prevent cell death. Hypoxic OSCC cells induce different adaptive changes such as anaerobic glycolysis, pH stabilisation and alterations of the gene and protein expression profile. This complex metabolic program is orchestrated by the hypoxia inducible factor (HIF) 1, the master regulator of early tumor progression. Hypoxia dependent and independent alterations in immune surveillance lead to different immune evasion strategies, which are partially mediated by alterations of the tumor cells, changes in the frequency, activity and repertoire of immune cell infiltrates and of soluble and environmental factors of the tumor micromilieu with consecutive generation of an immune escape phenotype, progression of disease and poor clinical outcome of OSCC patients.ConclusionsThis review focusses on the importance of HIF 1 in the adaption and reprogramming of the metabolic system to reduced oxygen values as well as on the role of the tumor microenvironment for evasion of OSCC from immune recognition and destruction.
Rule Extraction Algorithm for Deep Neural Networks: A Review
Venue: ArXiv

Despite the highest classification accuracy in wide varieties of application areas, artificial neural network has one disadvantage. The way this Network comes to a decision is not easily comprehensible. The lack of explanation ability reduces the acceptability of neural network in data mining and decision system. This drawback is the reason why researchers have proposed many rule extraction algorithms to solve the problem. Recently, Deep Neural Network (DNN) is achieving a profound result over the standard neural network for classification and recognition problems. It is a hot machine learning area proven both useful and innovative. This paper has thoroughly reviewed various rule extraction algorithms, considering the classification scheme: decompositional, pedagogical, and eclectics. It also presents the evaluation of these algorithms based on the neural network structure with which the algorithm is intended to work. The main contribution of this review is to show that there is a limited study of rule extraction algorithm from DNN.
PSI/TM Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases
Venue: Nucleic Acids Res.

The PSI/TM Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE(tm) The web server is available at http:/tcoffee.crg.cat/tmcoffee.
Caring Masculinities

A space has emerged for theorizing "caring masculinities," as the concept has increasingly become a focus of European critical studies on men and masculinities (CSMM) In this article, I present a practice based framework of the concept. I propose that caring masculinities are masculine identities that reject domination and its associated traits and embrace values of care such as positive emotion, interdependence, and relationality. I suggest that these caring masculinities constitute a critical form of men's engagement and involvement in gender equality and offer the potential of sustained social change for men and gender relations. I draw on CSMM and feminist care theory to construct the framework proposed here. In doing so, I offer a feminist exploration of how masculinities might be reworked into identities of care rather than domination.
Men And Masculinities

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A Review and Future Perspectives of Arabic Question Answering Systems
Venue: IEEE Transactions on Knowledge and Data Engineering

Question Answering Systems (QASs) have emerged as a good alternative for information seekers to retrieve precise information over the Internet. A good amount of research has been done to improve the performance of QASs across several languages, including European and Asian languages. However, Arabic, a morphologically rich Semitic language spoken by over 422 million people, has not seen similar development in the field of question answering. This article reviews the developments taking place in Arabic QASs as well as the challenges faced by researchers in developing Arabic QASs. After conducting an extensive literature survey of a number of English and Arabic QASs, this article classifies them according to several criteria. The most commonly used architecture for the development of an Arabic QAS, known as pipeline architecture, has been presented. In order to encourage and support the new researchers and scholars in conducting research in Arabic QASs, a list of techniques, tools, and computational linguistic resources, required to implement the components of the presented pipelined architecture, are described in this article in a simple and persuasive manner. Finally, the gap analysis between the research in Arabic and English QASs has been performed and accordingly, some future directions for research in Arabic QASs have been proposed.
Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems
Venue: 2016 IEEE 16th International Conference on Data Mining (ICDM)

Product review websites provide an incredible lens into the wide variety of opinions and experiences of different people, and play a critical role in helping users discover products that match their personal needs and preferences. To help address questions that can't easily be answered by reading others' reviews, some review websites also allow users to pose questions to the community via a question answering (QA) system. As one would expect, just as opinions diverge among different reviewers, answers to such questions may also be subjective, opinionated, and divergent. This means that answering such questions automatically is quite different from traditional QA tasks, where it is assumed that a single 'correct' answer is available. While recent work introduced the idea of question answering using product reviews, it did not account for two aspects that we consider in this paper: (1) Questions have multiple, often divergent, answers, and this full spectrum of answers should somehow be used to train the system, and (2) What makes a 'good' answer depends on the asker and the answerer, and these factors should be incorporated in order for the system to be more personalized. Here we build a new QA dataset with 800 thousand questions and over 3.1 million answers and show that explicitly accounting for personalization and ambiguity leads both to quantitatively better answers, but also a more nuanced view of the range of supporting, but subjective, opinions.
Modular Health Kiosk for health self assessment
Venue: 2016 IEEE Symposium on Computers and Communication (ISCC)

We describe the architecture, problems and lessons learned from building a Health Kiosk from commercial, off the shelf Personal Health Devices and a computer with a touch screen interface. The kiosk is used autonomously by patients to measure vital data prior to a consultation, in the scope of a population screening, or for routinely monitoring. The prototype was tested in multiple events with different user groups, aided by observer reporting and user questionnaires to assess problems and difficulties with the interface and device usage.
Stock markets and economic growth: a comparative analysis between Islamic and conventional markets in Malaysia

This paper aims at examining the impact of Islamic and conventional stock markets upon the macroeconomic performance in Malaysia. Real GDP is used to represent economic growth; while Islamic market capitalisation ratio and conventional market capitalisation ratio are used to indicate the Islamic and conventional stock market development, respectively. Investment ratio and GDP deflator are added as controlled variables for both models. The results shows there is a bidirectional relationship between Islamic stock markets and economic growth in Malaysia, and the contribution towards the economic growth is seemed to be indirectly through its impact on investment. On the other hand, there is a unidirectional relationship between conventional stock markets and economic performance in Malaysia, in which the development of conventional stock market causes the growth. Interestingly, the impact of the development on conventional stock market upon economic growth is more than the impact of the Islamic one. The exogeneity test shows that both the Islamic and conventional stock markets development is found to be super exogenous.
AN AUTOMATED SUPERELEVATION MEASUREMENT METHOD FOR HORIZONTAL CURVE SAFETY ASSESSMENT USING A LOW COST MOBILE DEVICE

1 The horizontal curve is one of the focal points of roadway safety because it plays a critical role 2 in smoothly transitioning vehicles among tangent roadway sections; more importantly, vehicle 3 crashes frequently concentrate on horizontal curves despite their disproportional length in the road 4 network. As one of the most critical safety properties of horizontal curves, adequate supereleva5 tion is crucial to vehicle safety because it counteracts the lateral acceleration produced in vehicles 6 when they travel the curve. Despite several sensing based methods having emerged in recent 7 years, labor intensive and time consuming manual superelevation evaluation is often carried out 8 by transportation agencies because emerging methods usually demand expensive equipment (e.g. 9 high resolution cameras, mobile light detection and ranging (LiDAR) sensors etc. and compli10 cated operations. Therefore, transportation agencies are still urgently searching for low cost, re11 liable alternatives to improve their data collection practices. This paper proposes an automated 12 superelevation measurement method using inexpensive mobile devices (e.g. smartphone, tablet) 13 The proposed method integrates and processes sensing data from a mobile device (including a 14 global positioning system (GPS) an accelerometer, and a gyroscope) and derives superelevation 15 values by employing the fundamental vehicle kinematics at a horizontal curve. Kalman Filtering16 based noise reduction, regression based radius computation, and complementary filtering based 17 rolling angle computation methods are introduced to achieve accurate and robust results in spite of 18 low frequency, noisy signals from the inexpensive devices. An experimental test on State Route 19 2 in Georgia demonstrates that the proposed method delivers results with accuracy comparable to 20 the LiDAR based method. A case study of applying the proposed method in high friction surface 21 treatment (HFST) site selection using ball bank indicator (BBI) shows that the proposed method 22 provides a promising alternative for transportation agencies to achieve low cost, yet reliable data 23 collection for safety analysis and improvement. 24 25
Escherichia coli and Salmonella :cellular and molecular biology

Preface The Enteric Bacterial Cell and the Age of Bacteria Variations on a Theme by Escherichia Part I: Molecular Architecture and Assembly of Cell Parts (11 chapters) Part II: Metabolism and General Physiology (58 chapters) Part III: Utilization of Energy for Cell Activities (7 chapters) Part IV: Regulation of Gene Expression (19 chapters) Part V: Growth of Cells and Cultures (12 chapters) Part VI: Genome, Genetics and Evolution (40 chapters) Part VII: Molecular Pathogenesis (7 chapters)