nils-herrmann/clean_scirepeval huggingface dataset:
TimeLineCurator: Interactive Authoring of Visual Timelines from Unstructured Text

We present TimeLineCurator, a browser-based authoring tool that automatically extracts event data from temporal references in unstructured text documents using natural language processing and encodes them along a visual timeline. Our goal is to facilitate the timeline creation process for journalists and others who tell temporal stories online. Current solutions involve manually extracting and formatting event data from source documents, a process that tends to be tedious and error prone. With TimeLineCurator, a prospective timeline author can quickly identify the extent of time encompassed by a document, as well as the distribution of events occurring along this timeline. Authors can speculatively browse possible documents to quickly determine whether they are appropriate sources of timeline material. TimeLineCurator provides controls for curating and editing events on a timeline, the ability to combine timelines from multiple source documents, and export curated timelines for online deployment. We evaluate TimeLineCurator through a benchmark comparison of entity extraction error against a manual timeline curation process, a preliminary evaluation of the user experience of timeline authoring, a brief qualitative analysis of its visual output, and a discussion of prospective use cases suggested by members of the target author communities following its deployment.
Service Based Brand Equity , Measure of Purchase Intention , Mediating Role of Brand Performance

This research tends to explore relationship between brand equity as a whole construct comprising (brand association & brand awareness, perceived service quality and service loyalty) with purchase intention. Questionnaire has been designed from previous research settings and modified according to Pakistani context in order to ensure validity and reliability of the developed instrument. Convenience sampling comprising a sample size of 150 (non-student) has been taken in this research. Research type is causal correlational and cross sectional in nature. In order to accept or reject hypothesis correlation and regression techniques were applied. Results indicated significant and positive relationship between brand equity and purchase intention, while partial mediation has been proved for brand performance. Only three dimensions of brand equity (perceived service quality, brand association & awareness and service loyalty) have been measured. Other dimensions as brand personality have been ignored. English not being the primary language may have hampered the response rate. As far as the practical implications are concerned practitioners can get benefits from this research as the contribution of brand equity has more than 50% towards purchase intention.
Stereoscopic Neural Style Transfer

This paper presents the first attempt at stereoscopic neural style transfer, which responds to the emerging demand for 3D movies or AR/VR. We start with a careful examination of applying existing monocular style transfer methods to left and right views of stereoscopic images separately. This reveals that the original disparity consistency cannot be well preserved in the final stylization results, which causes 3D fatigue to the viewers. To address this issue, we incorporate a new disparity loss into the widely adopted style loss function by enforcing the bidirectional disparity constraint in non-occluded regions. For a practical realtime solution, we propose the first feed-forward network by jointly training a stylization sub-network and a disparity sub-network, and integrate them in a feature level middle domain. Our disparity sub-network is also the first end-to-end network for simultaneous bidirectional disparity and occlusion mask estimation. Finally, our network is effectively extended to stereoscopic videos, by considering both temporal coherence and disparity consistency. We will show that the proposed method clearly outperforms the baseline algorithms both quantitatively and qualitatively.
Evaluating aggregated search pages

Aggregating search results from a variety of heterogeneous sources or verticals such as news, image and video into a single interface is a popular paradigm in web search. Although various approaches exist for selecting relevant verticals or optimising the aggregated search result page, evaluating the quality of an aggregated page is an open question.
 This paper proposes a general framework for evaluating the quality of aggregated search pages. We evaluate our approach by collecting annotated user preferences over a set of aggregated search pages for 56 topics and 12 verticals. We empirically demonstrate the fidelity of metrics instantiated from our proposed framework by showing that they strongly agree with the annotated user preferences of pairs of simulated aggregated pages.
 Furthermore, we show that our metrics agree with the majority preference more often than current diversity-based information retrieval metrics. Finally, we demonstrate the flexibility of our framework by showing that personalised historical preference data can be used to improve the performance of our proposed metrics.
Fuzzy c-means clustering with spatial information for image segmentation

A conventional FCM algorithm does not fully utilize the spatial information in the image. In this paper, we present a fuzzy c-means (FCM) algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership function in the neighborhood of each pixel under consideration. The advantages of the new method are the following: (1) it yields regions more homogeneous than those of other methods, (2) it reduces the spurious blobs, (3) it removes noisy spots, and (4) it is less sensitive to noise than other techniques. This technique is a powerful method for noisy image segmentation and works for both single and multiple-feature data with spatial information.
Deep learning algorithm for arrhythmia detection

Most of cardiovascular disorders or diseases can be prevented, but death continues to rise due to improper treatment because of misdiagnose. One of cardiovascular diseases is Arrhythmia. It is sometimes difficult to observe electrocardiogram (ECG) recording for Arrhythmia detection. Therefore, it needs a good learning method to be applied in the computer as a way to help the detection of Arrhythmia. There is a powerful approach in Machine Learning, named Deep Learning. It starts to be widely used for Speech Recognition, Bioinformatics, Computer Vision, and many others. This research used the Deep Learning to classify the Arrhythmia data. We compared the result to other popular machine learning algorithm, such as Naive Bayes, K-Nearest Neighbor, Artificial Neural Network, and Support Vector Machine. Our experiment showed that Deep Learning algorithm achieved the best accuracy, which was 76,51%.
Got Many Labels?: Deriving Topic Labels from Multiple Sources for Social Media Posts using Crowdsourcing and Ensemble Learning

Online search and item recommendation systems are often based on being able to correctly label items with topical keywords. Typically, topical labelers analyze the main text associated with the item, but social media posts are often multimedia in nature and contain contents beyond the main text. Topic labeling for social media posts is therefore an important open problem for supporting effective social media search and recommendation. In this work, we present a novel solution to this problem for Google+ posts, in which we integrated a number of different entity extractors and annotators, each responsible for a part of the post (e.g. text body, embedded picture, video, or web link). To account for the varying quality of different annotator outputs, we first utilized crowdsourcing to measure the accuracy of individual entity annotators, and then used supervised machine learning to combine different entity annotators based on their relative accuracy. Evaluating using a ground truth data set, we found that our approach substantially outperforms topic labels obtained from the main text, as well as naive combinations of the individual annotators. By accurately applying topic labels according to their relevance to social media posts, the results enables better search and item recommendation.
Psychometric evaluation of a new questionnaire measuring treatment satisfaction in hypothyroidism: the ThyTSQ.

There is a clinical impression of dissatisfaction with treatment for hypothyroidism among some patients. Psychometric properties of the new ThyTSQ questionnaire are evaluated. The questionnaire, measuring patients' satisfaction with their treatment for hypothyroidism, has two parts: the seven-item ThyTSQ-Present and four-item ThyTSQ-Past, measuring satisfaction with present and past treatment, respectively, on scales from 6 (very satisfied) to 0 (very dissatisfied).



The questionnaire was completed once by 103 adults with hypothyroidism, age (mean [SD]) 55.2 [14.4], range 23-84 years (all treated with thyroxine).



Completion rates were very high. Internal consistency reliability was excellent for both ThyTSQ-Present and ThyTSQ-Past (Cronbach's alpha = 0.91 and 0.90, respectively [N = 102 and 103]). Principal components analyses indicated that the seven items of the ThyTSQ-Present and the four items of the ThyTSQ-Past could be summed into separate Present Satisfaction and Past Satisfaction total scores. Mean Present Satisfaction was 32.5 (7.8), maximum range 0-42, and mean Past Satisfaction was 17.5 (6.1), maximum range 0-24, indicating considerable room for improvement. Patients were least satisfied with their present understanding of their condition, mean 4.2 (1.7) (maximum range 0-6), and with information provided about hypothyroidism around the time of diagnosis, mean 3.9 (1.8) (maximum range 0-6).



The ThyTSQ is highly acceptable to patients with hypothyroidism (excellent completion rates), and has established internal consistency reliability. It will assist health professionals in considering psychological outcomes when treating people with hypothyroidism, and is suitable for clinical trials and routine clinical monitoring.
Surfing the money tides: understanding the foreign exchange market through metaphors.

This study describes metaphorical conceptualizations of the foreign exchange market held by market participants and examines how these metaphors socially construct the financial market. Findings are based on 55 semi-structured interviews with senior foreign exchange experts at banks and at financial news providers in Europe. We analysed interview transcripts by metaphor analysis, a method based on cognitive linguistics. Results indicate that market participants' understanding of financial markets revolves around seven metaphors, namely the market as a bazaar, as a machine, as gambling, as sports, as war, as a living being and as an ocean. Each of these metaphors highlights and conceals certain aspects of the foreign exchange market and entails a different set of implications on crucial market dimensions, such as the role of other market participants and market predictability. A correspondence analysis supports our assumption that metaphorical thinking corresponds with implicit assumptions about market predictability. A comparison of deliberately generated and implicitly used metaphors reveals notable differences. In particular, implicit metaphors are predominantly organic rather than mechanical. In contrast to academic models, interactive and organic metaphors, and not the machine metaphor, dominate the market accounts of participants.
PIC a Different Word: A Simple Model for Lexical Substitution in Context

The Lexical Substitution task involves selecting and ranking lexical paraphrases for a target word in a given sentential context. We present PIC, a simple measure for estimating the appropriateness of substitutes in a given context. PIC outperforms another simple, comparable model proposed in recent work, especially when selecting substitutes from the entire vocabulary. Analysis shows that PIC improves over baselines by incorporating frequency biases into predictions.
Extracting PICO Sentences from Clinical Trial Reports using Supervised Distant Supervision

Systematic reviews underpin Evidence Based Medicine (EBM) by addressing precise clinical questions via comprehensive synthesis of all relevant published evidence. Authors of systematic reviews typically define a Population/Problem, Intervention, Comparator, and Outcome (a PICO criteria) of interest, and then retrieve, appraise and synthesize results from all reports of clinical trials that meet these criteria. Identifying PICO elements in the full-texts of trial reports is thus a critical yet time-consuming step in the systematic review process. We seek to expedite evidence synthesis by developing machine learning models to automatically extract sentences from articles relevant to PICO elements. Collecting a large corpus of training data for this task would be prohibitively expensive. Therefore, we derive distant supervision (DS) with which to train models using previously conducted reviews. DS entails heuristically deriving 'soft' labels from an available structured resource. However, we have access only to unstructured, free-text summaries of PICO elements for corresponding articles; we must derive from these the desired sentence-level annotations. To this end, we propose a novel method - supervised distant supervision (SDS) - that uses a small amount of direct supervision to better exploit a large corpus of distantly labeled instances by learning to pseudo-annotate articles using the available DS. We show that this approach tends to outperform existing methods with respect to automated PICO extraction.
Critical phenomena in complex networks

The combination of the compactness of networks, featuring small diameters, and their complex architectures results in a variety of critical effects dramatically different from those in cooperative systems on lattices. In the last few years, researchers have made important steps toward understanding the qualitatively new critical phenomena in complex networks. We review the results, concepts, and methods of this rapidly developing field. Here we mostly consider two closely related classes of these critical phenomena, namely structural phase transitions in the network architectures and transitions in cooperative models on networks as substrates. We also discuss systems where a network and interacting agents on it influence each other. We overview a wide range of critical phenomena in equilibrium and growing networks including the birth of the giant connected component, percolation, k-core percolation, phenomena near epidemic thresholds, condensation transitions, critical phenomena in spin models placed on networks, synchronization, and self-organized criticality effects in interacting systems on networks. We also discuss strong finite size effects in these systems and highlight open problems and perspectives.
The specificity and accuracy of (111)In-hexavalent lactoside in estimating liver reserve and its threshold value for mortality in mice.

The asialoglycoprotein receptor on hepatocyte membranes recognizes the galactose residues of glycoproteins. We investigated the specificity, accuracy and threshold value of asialoglycoprotein receptor imaging for estimating liver reserve via scintigraphy using (111)In-hexavalent lactoside in mouse models.



(111)In-hexavalent lactoside scintigraphy for asialoglycoprotein receptor imaging was performed on groups of normal mice, orthotopic SK-HEP-1-bearing mice, subcutaneous HepG2-bearing mice, mice with 20-80% partial hepatectomy and mice with acute hepatitis induced by acetaminophen. Liver reserve was measured by relative liver uptake and compared with normal mice. Asialoglycoprotein receptor blockade was performed via an in vivo asialofetuin competitive binding assay.



A total of 73.64±7.11% of the injection dose accumulated in the normal liver tissue region, and radioactivity was barely detected in the hepatoma region. When asialoglycoprotein receptor was blocked using asialofetuin, less than 0.41±0.04% of the injection dose was detected as background in the liver. Asialoglycoprotein receptor imaging data revealed a linear correlation between (111)In-hexavalent lactoside binding and residual liver mass (R(2)=0.8548) in 20-80% of partially hepatectomized mice, demonstrating the accuracy of (111)In-hexavalent lactoside imaging for measuring the functional liver mass. Asialoglycoprotein receptor imaging data in mice with liver failure induced using 600mg/kg acetaminophen revealed 19-45% liver reserve relative to normal mice and a fatal threshold value of 25% liver reserve.



The (111)In-hexavalent lactoside imaging method appears to be a good, specific, visual and quantitative predictor of functional liver reserve. The diagnostic threshold for survival was at 25% liver reserve in mice.
Visualization of vessel movements

We propose a geographical visualization to support operators of coastal surveillance systems and decision making analysts to get insights in vessel movements. For a possibly unknown area, they want to know where significant maritime areas, like highways and anchoring zones, are located. We show these features as an overlay on a map. As source data we use AIS data: Many vessels are currently equipped with advanced GPS devices that frequently sample the state of the vessels and broadcast them. Our visualization is based on density fields that are derived from convolution of the dynamic vessel positions with a kernel. The density fields are shown as illuminated height maps. Combination of two fields, with a large and small kernel provides overview and detail. A large kernel provides an overview of area usage revealing vessel highways. Details of speed variations of individual vessels are shown with a small kernel, highlighting anchoring zones where multiple vessels stop. Besides for maritime applications we expect that this approach is useful for the visualization of moving object data in general.
Genital Beautification: A Concept That Offers More Than Reduction of the Labia Minora

The interest and demand for female genital rejuvenation surgery are steadily increasing. This report presents a concept of genital beautification consisting of labia minora reduction, labia majora augmentation by autologous fat transplantation, labial brightening by laser, mons pubis reduction by liposuction, and vaginal tightening if desired. Genital beautification was performed for 124 patients between May 2009 and January 2012 and followed up for 1 year to obtain data about satisfaction with the surgery. Of the 124 female patients included in the study, 118 (95.2 %) were happy and 4 (3.2 %) were very happy with their postoperative appearance. In terms of postoperative functionality, 84 patients (67.7 %) were happy and 40 (32.3 %) were very happy. Only 2 patients (1.6 %) were not satisfied with the aesthetic result of their genital beautification procedures, and 10 patients (8.1 %) experienced wound dehiscence. The described technique of genital beautification combines different aesthetic female genital surgery techniques. Like other aesthetic surgeries, these procedures are designed for the subjective improvement of the appearance and feelings of the patients. The effects of the operation are functional and psychological. They offer the opportunity for sexual stimulation and satisfaction. The complication rate is low. Superior aesthetic results and patient satisfaction can be achieved by applying this technique. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
Prevalence of Depression Among Students of Urmia University of Medical Sciences (Iran)

A depressive disorder is an illness that involves the body, mood, thoughts and behaviors. This study was performed to identify the presence of depression among medical students of Urmia University of Medical Sciences.



A descriptive cross-sectional study was conducted on 700 undergraduate medical and basic sciences students. Beck depression inventory (BDI) used for data gathering.



Mean score of BDI was 10.4 ± 0.8 and 52.6% of students scored under the depression threshold. Four of them had severe depression. RESULTS showed no significant relationship between depression and age, education, sex, rank of birth or duration of education.



Prevalence of depression that can affect the students' quality of education and social behavior was high in Urmia University of Medical Sciences.
Anywhere surface touch: utilizing any surface as an input area

The current trend towards smaller and smaller mobile devices may cause considerable difficulties in using them. In this paper, we propose an interface called Anywhere Surface Touch, which allows any flat or curved surface in a real environment to be used as an input area. The interface uses only a single small camera and a contact microphone to recognize several kinds of interaction between the fingers of the user and the surface. The system recognizes which fingers are interacting and in which direction the fingers are moving. Additionally, the fusion of vision and sound allows the system to distinguish the contact conditions between the fingers and the surface. Evaluation experiments showed that users became accustomed to our system quickly, soon being able to perform input operations on various surfaces.
Brief report: an evaluation of the AQ-10 as a brief screening instrument for ASD in adults.

There is a need for brief screening instruments for autistic spectrum disorders (ASD) that can be used by frontline healthcare professionals to aid in the decision as to whether an individual should be referred for a full diagnostic assessment. In this study we evaluated the ability of a short form of the autism spectrum quotient (AQ) questionnaire, the 10 item AQ-10, to correctly classify individuals as having or not having ASD. In a sample of 149 individuals with ASD and 134 controls without an ASD diagnosis, we found that the full AQ (AQ-50) abridged AQ (AQ-S) and AQ-10 all performed well as a screen for ASD. ROC analysis indicated that sensitivity, specificity and area under the curve were very similar at suggested cut-off's for ASD across measures, with little difference in performance between the AQ-10 and full AQ-50. Results indicate the potential usefulness of the AQ-10 as a brief screen for ASD.
Development of flowering plant gametophytes.

Plant reproduction occurs through the production of gametes by a haploid generation, the gametophyte. Flowering plants have highly reduced male and female gametophytes, called pollen grains and embryo sacs, respectively, consisting of only a few cells. Gametophytes are critical for sexual reproduction, but detailed understanding of their development remains poor as compared to the diploid sporophyte. This article reviews recent progress in understanding the mechanisms underlying gametophytic development and function in flowering plants. The focus is on genes and molecules involved in the processes of initiation, growth, cell specification, and fertilization of the male and female gametophytes derived primarily from studies in model systems.