nils-herrmann/clean_scirepeval huggingface dataset:
A Comparison of Emotion Annotation Approaches for Text

While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of a more nuanced affect has received less attention: there are few publicly available annotated resources and there are a number of competing emotion representation schemes with as yet no clear approach to choose between them. To address this lack, we present a series of emotion annotation studies on tweets, providing methods for comparisons between annotation methods (relative vs. absolute) and between different representation schemes. We find improved annotator agreement with a relative annotation scheme (comparisons) on a dimensional emotion model over a categorical annotation scheme on Ekman’s six basic emotions; however, when we compare inter-annotator agreement for comparisons with agreement for a rating scale annotation scheme (both with the same dimensional emotion model), we find improved inter-annotator agreement with rating scales, challenging a common belief that relative judgements are more reliable. To support these studies and as a contribution in itself, we further present a publicly available collection of 2019 tweets annotated with scores on each of four emotion dimensions: valence, arousal, dominance and surprise, following the emotion representation model identified by Fontaine et al. in 2007.
Multimedia learning object to build cognitive understanding in learning introductory programming

Programming is taught as foundation module at the beginning of undergraduate studies and/or during foundation year. Learning introductory programming languages such as Pascal, Basic / C (procedural) and C++ / Java (object oriented) requires learners to understand the underlying programming paradigm, syntax, logic and the structure. Learning to program is considered hard for novice learners and it is important to understand what makes learning program so difficult and how students learn.
 The prevailing focus on multimedia learning objects provides promising approach to create better knowledge transfer. This project aims to investigate: (a) students' perception in learning to program and the difficulties. (b) effectiveness of multimedia learning objects in learning introductory programming language in a face-to-face learning environment.
Exploring generational cohort work satisfaction in hospital nurses.

Although extensive research exists regarding job satisfaction, many previous studies used a more restrictive, quantitative methodology. The purpose of this qualitative study is to capture the perceptions of hospital nurses within generational cohorts regarding their work satisfaction.  A preliminary qualitative, phenomenological study design explored hospital nurses' work satisfaction within generational cohorts - Baby Boomers (1946-1964), Generation X (1965-1980) and Millennials (1981-2000). A South Florida hospital provided the venue for the research. In all, 15 full-time staff nurses, segmented into generational cohorts, participated in personal interviews to determine themes related to seven established factors of work satisfaction: pay, autonomy, task requirements, administration, doctor-nurse relationship, interaction and professional status.  An analysis of the transcribed interviews confirmed the importance of the seven factors of job satisfaction. Similarities and differences between the generational cohorts related to a combination of stages of life and generational attributes.  The results of any qualitative research relate only to the specific venue studied and are not generalizable. However, the information gleaned from this study is transferable and other organizations are encouraged to conduct their own research and compare the results.  This study is unique, as the seven factors from an extensively used and highly respected quantitative research instrument were applied as the basis for this qualitative inquiry into generational cohort job satisfaction in a hospital setting.
Tightly-coupled Monocular Visual-odometric SLAM using Wheels and a MEMS Gyroscope

In this paper, we present a novel tightly-coupled probabilistic monocular visual-odometric Simultaneous Localization and Mapping algorithm using wheels and a MEMS gyroscope, which can provide accurate, robust and long-term localization for the ground robot moving on a plane. Firstly, we present an odometer preintegration theory that integrates the wheel encoder measurements and gyroscope measurements to a local frame. The preintegration theory properly addresses the manifold structure of the rotation group SO(3) and carefully deals with uncertainty propagation and bias correction. Then the novel odometer error term is formulated using the odometer preintegration model and it is tightly integrated into the visual optimization framework. Furthermore, we introduce a complete tracking framework to provide different strategies for motion tracking when (1) both measurements are available, (2) visual measurements are not available, and (3) wheel encoder experiences slippage, which leads the system to be accurate and robust. Finally, the proposed algorithm is evaluated by performing extensive experiments, the experimental results demonstrate the superiority of the proposed system.
Domain Specific Web Crawler : A Survey

The ―Domain Specific web crawler‖ is a system or a program which we will design to search information from web. A crawler is an automation tool that traverses the web page for the purpose of extracting information. In domain specific Web crawler, the crawler crawls the pages, which are relevant to our domain. To find the domain related web page we need to visit a Web page and calculate the relevance value. Based on relevance value the selection of page is decided.For a crawler it is not an easy task to download the domain specific Web pages. It focus will be to identify Web pages for a particular domain in web. The usage of internet is immense on a large scale for the past many years. In this survey we are going to discuss about types of crawler ,crawling algorithm , relevancy check and machine learning.  Crawler, Ant, Spider, bot, agent, Automation, Search Engine, Focused, web mining, text analysis
3D HD versus 2D HD: surgical task efficiency in standardised phantom tasks

Common video systems for laparoscopy provide the surgeon a two-dimensional image (2D), where information on spatial depth can be derived only from secondary spatial depth cues and experience. Although the advantage of stereoscopy for surgical task efficiency has been clearly shown, several attempts to introduce three-dimensional (3D) video systems into clinical routine have failed. The aim of this study is to evaluate users’ performances in standardised surgical phantom model tasks using 3D HD visualisation compared with 2D HD regarding precision and working speed. This comparative study uses a 3D HD video system consisting of a dual-channel laparoscope, a stereoscopic camera, a camera controller with two separate outputs and a wavelength multiplex stereoscopic monitor. Each of 20 medical students and 10 laparoscopically experienced surgeons (more than 100 laparoscopic cholecystectomies each) pre-selected in a stereo vision test were asked to perform one task to familiarise themselves with the system and subsequently a set of five standardised tasks encountered in typical surgical procedures. The tasks were performed under either 3D or 2D conditions at random choice and subsequently repeated under the other vision condition. Predefined errors were counted, and time needed was measured. In four of the five tasks the study participants made fewer mistakes in 3D than in 2D vision. In four of the tasks they needed significantly more time in the 2D mode. Both the student group and the surgeon group showed similarly improved performance, while the surgeon group additionally saved more time on difficult tasks. This study shows that 3D HD using a state-of-the-art 3D monitor permits superior task efficiency, even as compared with the latest 2D HD video systems.
StreamCloud: An Elastic and Scalable Data Streaming System

Many applications in several domains such as telecommunications, network security, large-scale sensor networks, require online processing of continuous data flows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static configurations that lead to either under or overprovisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation, and a thorough evaluation of the scalability and elasticity of the fully implemented system.
A review of cardiorespiratory fitness-related neuroplasticity in the aging brain

The literature examining the relationship between cardiorespiratory fitness and the brain in older adults has increased rapidly, with 30 of 34 studies published since 2008. Here we review cross-sectional and exercise intervention studies in older adults examining the relationship between cardiorespiratory fitness and brain structure and function, typically assessed using Magnetic Resonance Imaging (MRI). Studies of patients with Alzheimer's disease are discussed when available. The structural MRI studies revealed a consistent positive relationship between cardiorespiratory fitness and brain volume in cortical regions including anterior cingulate, lateral prefrontal, and lateral parietal cortex. Support for a positive relationship between cardiorespiratory fitness and medial temporal lobe volume was less consistent, although evident when a region-of-interest approach was implemented. In fMRI studies, cardiorespiratory fitness in older adults was associated with activation in similar regions as those identified in the structural studies, including anterior cingulate, lateral prefrontal, and lateral parietal cortex, despite heterogeneity among the functional tasks implemented. This comprehensive review highlights the overlap in brain regions showing a positive relationship with cardiorespiratory fitness in both structural and functional imaging modalities. The findings suggest that aerobic exercise and cardiorespiratory fitness contribute to healthy brain aging, although additional studies in Alzheimer's disease are needed.
New islanding detection technique for DG using Discrete Wavelet Transform

Islanding phenomenon is a problem for Distributed Generator (DG) based networks leading to troubles in voltage and frequency control and other power quality issues. This paper describes the development of a method based on Discrete Wavelet Transform (DWT), in order to detect islanding for DGs. This method detects the islanding state only by evaluating the terminal current of DGs. Hence, different types of current signal in the case of fault occurrence, load and capacitor switching and motor starting have been investigated. In order to increase the accuracy of the wavelet analysis, the proposed algorithm is executed for each type of current signals using different types of mother wavelets, decomposition levels, length of data window and moving size of window to decide on the best assumption of each parameter. The results of the study show that the proposed method can detect the islanding state within a time less than one third of a cycle with a good accuracy.
Agile Project Management: A Case Study of a Virtual Research Environment Development Project

In this paper we use a case study of a project to create a Web 2.0-based, Virtual Research Environment (VRE) for researchers to share digital resources in order to reflect on the principles and practices for embedding eResearch applications within user communities. In particular, we focus on the software development methodologies and project management techniques adopted by the project team in order to ensure that the project remained responsive to changing user requirements without compromising their capacity to keep the project ‘on track’, i.e. meeting the goals declared in the project proposal within budget and on time. Drawing on ethnographic fieldwork, we describe how the project team, whose members are distributed across multiple sites (and often mobile), exploit a repertoire of coordination mechanisms, communication modes and tools, artefacts and structuring devices as they seek to establish the orderly running of the project while following an agile, user-centred development approach.
Android based heart rate monitoring and automatic notification system

In this paper, the design of an integrated portable device that can monitor heart rate (HR) continuously and send notifications through short message service (SMS) over the cellular network using Android application is presented. The primary goal of our device is to ensure medical attention within the first few critical hours of an ailment of the patient with poor heart condition, hence boost chances of his or her survival. In situations where there is an absence of doctor or clinic nearby (e.g., rural area) and where the patient cannot realize their actual poor heart condition, is where our implemented system is of paramount importance. The designed system shows the real time HR on the mobile screen through Android application continuously and if any abnormal HR of the patient is detected, the system will immediately send a message to the concerned doctors and relatives whose numbers were previously saved in the Android application. This device ensures nonstop monitoring for cardiac events along with notifying immediately when an emergency strikes.
Near duplicate detection in an academic digital library

The detection and potential removal of duplicates is desirable for a number of reasons, such as to reduce the need for unnecessary storage and computation, and to provide users with uncluttered search results. This paper describes an investigation into the application of scalable simhash and shingle state of the art duplicate detection algorithms for detecting near duplicate documents in the CiteSeerX digital library. We empirically explored the duplicate detection methods and evaluated their performance and application to academic documents and identified good parameters for the algorithms. We also analyzed the types of near duplicates identified by each algorithm. The highest F-scores achieved were 0.91 and 0.99 for the simhash and shingle-based methods respectively. The shingle-based method also identified a larger variety of duplicate types than the simhash-based method.
[Rare benign breast tumors including Abrikossoff tumor (granular cell tumor), erosive adenomatosis of the nipple, cytosteatonecrosis, fibromatosis (desmoid tumor), galactocele, hamartoma, hemangioma, lipoma, juvenile papillomatosis, pseudoangiomatous hyperplasia, and syringomatous adenoma: Guideline

To provide guidelines for clinical practice from the French College of Gynaecologists and Obstetricians (CNGOF), based on the best evidence available, concerning rare benign breast tumors: Abrikossoff (granular cell tumor), erosive adenomatosis of the nipple, cytosteatonecrosis, fibromatosis (desmoid tumor), galactocele, hamartoma, hemangioma, lipoma, juvenile papillomatosis, pseudoangiomatous hyperplasia, and syringomatous adenoma.



Bibliographical search in French and English languages by consultation of Pubmed, Cochrane and international databases.



For erosive adenomatosis of the nipple, surgical excision is recommended to exclude Paget's disease or cancer (grade C). When surgery is performed for breast desmoid tumor or syringomatous adenoma, free margins are recommended (grade C). Without clinico-radio-histologic discordance, surgical abstention may be proposed for Abrikossoff tumor (granular cell tumor), cytosteatonecrosis, galactocele, hamartoma, hemangioma, lipoma, juvenile papillomatosis, pseudoangiomatous hyperplasia, and syringomatous adenoma (grade C).
Coordination of Pharyngeal and Laryngeal Swallowing Events During Single Liquid Swallows After Oral Endotracheal Intubation for Patients with Acute Respiratory Distress Syndrome

To evaluate timing and duration differences in airway protection and esophageal opening after oral intubation and mechanical ventilation for acute respiratory distress syndrome (ARDS) survivors versus age-matched healthy volunteers. Orally intubated adult (≥ 18 years old) patients receiving mechanical ventilation for ARDS were evaluated for swallowing impairments via a videofluoroscopic swallow study (VFSS) during usual care. Exclusion criteria were tracheostomy, neurological impairment, and head and neck cancer. Previously recruited healthy volunteers (n = 56) served as age-matched controls. All subjects were evaluated using 5-ml thin liquid barium boluses. VFSS recordings were reviewed frame-by-frame for the onsets of 9 pharyngeal and laryngeal events during swallowing. Eleven patients met inclusion criteria, with a median (interquartile range [IQR]) intubation duration of 14 (9, 16) days, and VFSSs completed a median of 5 (4, 13) days post-extubation. After arrival of the bolus in the pharynx, ARDS patients achieved maximum laryngeal closure a median (IQR) of 184 (158, 351) ms later than age-matched, healthy volunteers (p < 0.001) and it took longer to achieve laryngeal closure with a median (IQR) difference of 151 (103, 217) ms (p < 0.001), although there was no significant difference in duration of laryngeal closure. Pharyngoesophageal segment opening was a median (IQR) of − 116 (− 183, 1) ms (p = 0.004) shorter than in age-matched, healthy controls. Evaluation of swallowing physiology after oral endotracheal intubation in ARDS patients demonstrates slowed pharyngeal and laryngeal swallowing timing, suggesting swallow-related muscle weakness. These findings may highlight specific areas for further evaluation and potential therapeutic intervention to reduce post-extubation aspiration.
Defining Big Data

As Big Data becomes better understood, there is a need for a comprehensive definition of Big Data to support work in fields such as data quality for Big Data. Existing definitions of Big Data define Big Data by comparison with existing, usually relational, definitions, or define Big Data in terms of data characteristics or use an approach which combines data characteristics with the Big Data environment. In this paper we examine existing definitions of Big Data and discuss the strengths and limitations of the different approaches, with particular reference to issues related to data quality in Big Data. We identify the issues presented by incomplete or inconsistent definitions. We propose an alternative definition and relate this definition to our work on quality in Big Data.
Fault injection attack on deep neural network

Deep neural network (DNN), being able to effectively learn from a training set and provide highly accurate classification results, has become the de-facto technique used in many mission-critical systems. The security of DNN itself is therefore of great concern. In this paper, we investigate the impact of fault injection attacks on DNN, wherein attackers try to misclassify a specified input pattern into an adversarial class by modifying the parameters used in DNN via fault injection. We propose two kinds of fault injection attacks to achieve this objective. Without considering stealthiness of the attack, single bias attack (SBA) only requires to modify one parameter in DNN for misclassification, based on the observation that the outputs of DNN may linearly depend on some parameters. Gradient descent attack (GDA) takes stealthiness into consideration. By controlling the amount of modification to DNN parameters, GDA is able to minimize the fault injection impact on input patterns other than the specified one. Experimental results demonstrate the effectiveness and efficiency of the proposed attacks.
Dropout Sampling for Robust Object Detection in Open-Set Conditions

Learning and evaluated for image classification and regression tasks. This paper investigates the utility of Dropout Sampling for object detection for the first time. We demonstrate how label uncertainty can be extracted from a state-of-the-art object detection system via Dropout Sampling. We evaluate this approach on a large synthetic dataset of 30,000 images, and a real-world dataset captured by a mobile robot in a versatile campus environment. We show that this uncertainty can be utilized to increase object detection performance under the open-set conditions that are typically encountered in robotic vision. A Dropout Sampling network is shown to achieve a 12.3 % increase in recall (for the same precision score as a standard network) and a 15.1 % increase in precision (for the same recall score as the standard network).
THE SELFIE PHENOMENON : THE IDEA OF SELF-PRESENTATION AND ITS IMPLICATIONS AMONG YOUNG WOMEN A

The purpose of this study is to explore how female users identify the act of uploading selfies as an expression of external affirmation or as an act of empowerment in terms of redefining beauty standards that are reinforced in society. In addition, this study attempts to provide a foundation for understanding the selfie phenomenon and its relationship to perceived sense of self-worth in young women from the usage of Instagram. As the literature review indicates, there is a lack of research presented on the user’s emotional state in relation to using Instagram. Thus, the most appropriate research design for this subject was a qualitative study. The interview questions were open-ended and structured to acquire knowledge about participant’s ability to believe in themselves, assumptions taught about what it means to be a woman, and motivations for personal aspirations and happiness. The sample consisted of eleven participants. The findings in this study provide valuable information that build on the current literature of social networking sites and it’s implications on the users’ emotional state. Results from the findings include handling rejection and criticism, conflict between external expectations and personal aspirations, comparison to others and independence. This study provides a framework for future explorations of identity construction through self-presentation and social media use in a rapidly changing, communication environment. It is important to continue research in the area of selfies as a category on its own due to the endless ways it is incorporated in our lives.  THE IDEA OF SELF-PRESENTATION AND ITS IMPLICATIONS AMONG YOUNG WOMEN A project based upon an independent investigation, submitted in partial fulfillment of the requirements for the degree of Master of Social Work.
Bioprinting Technology : A Current State-ofthe-Art Review

Bioprinting is an emerging technology for constructing and fabricating artificial tissue and organ constructs. This technology surpasses the traditional scaffold fabrication approach in tissue engineering (TE). Currently, there is a plethora of research being done on bioprinting technology and its potential as a future source for implants and full organ transplantation. This review paper overviews the current state of the art in bioprinting technology, describing the broad range of bioprinters and bioink used in preclinical studies. Distinctions between laser-, extrusion-, and inkjet-based bioprinting technologies along with appropriate and recommended bioinks are discussed. In addition, the current state of the art in bioprinter technology is reviewed with a focus on the commercial point of view. Current challenges and limitations are highlighted, and future directions for next-generation bioprinting technology are also presented.