Paragraphs Of Text Research Articles

Smart abnormal emotion analysis from English sentences

Smart abnormal emotion analysis refers to identifying abnormal sentiments, opinions, or attitudes from massive patterns automatically. The abnormal emotion may be hidden in a paragraph of text to reflect the sentiment suddenly changes. The suddenly changed emotion should be identified in time to avoid severe consequence. For instance, a customer would not buy a product any more if he or she has a negative emotion to this product. With the popularization of social media, more and more information is available. For example, feedbacks, comments, or opinions widely exist on Twitter. Identifying abnormal emotion by analyzing texts in social media becomes a hot topic, which enables companies or government organizations to take prevention strategies in time if needing. In this paper, we propose a multivariate Gaussian model based abnormal emotion detection method. In multivariate Gaussian model, whether a user has abnormal emotion is determined by the joint probability density. The distribution test shows that the negative, positive, and neutral emotions of a user follow a normal distribution, while the surprise and anger emotions do not follow. The emotions of texts from social media posted by a group follow a “power law distribution”, while the individual users do not. The abnormal emotion can be detected by multivariate Gaussian about 84.60%.

VQA Model Based on Image Descriptive Paragraph and Deep Integration of BERT

Visual Question Answering (VQA) is a fast developing field involving multiple disciplines, and it is constantly challenging more complex tasks. The classic combination of CNN+LSTM can effectively extract images and language representation to complete the VQA task, but there are still many problems, such as excessively long sequence processing, etc. In recent years, BERT model has expanded rapidly from the field of natural language processing to a broader multi-modal field with its strong learning ability. In this paper, we propose a novel way to apply BERT model in the VQA field. We use the descriptive paragraph generation technology to transform the picture into a text paragraph description, and integrate question information and image information on BERT model. Our model achieves an excellent performance on the VQA2.0 dataset with an overall accuracy 5% higher than previous models.

Two-stage three-way enhanced technique for ensemble learning in inclusive policy text classification

With the development of the social economy, small and medium-sized enterprises (SMEs) play a vital role in promoting economic development. Multiple local governments in China are developing policy recommended platforms in order to help SMEs better understand the inclusive policy. However, these online platforms manually extract the key information from the inclusive policy texts, which takes a lot of time and causes low efficiency. The policy text is composed of some paragraphs and each paragraph corresponds to a topic. When we classify the paragraphs into different topics, there exists a decision risk of text misclassification. Therefore, we design two-stage based three-way enhanced technique to automatically classify these text paragraphs into the predefined categories. At the first stage, by using ensemble learning algorithms, we construct an ensemble convolution neural network (CNN) model in order to ensure the generalization ability and stability of text classification results. Meanwhile, we develop a new weight determination method to integrate the prediction results of all base classifiers according to the accuracy and classification confidence. With the help of three-way decisions (3WD), we assign the samples with poor resolution to the boundary area for secondary classification, which can reduce the decision risk. At the second stage, in order to classify the boundary region samples and improve the overall classification results, we further utilize traditional machine learning method as the secondary classifier. Finally, we develop some comparison experiments to verify our proposed method. The experimental results show that the two-stage three-way enhanced classification framework is valid and obtains a better performance. Our proposed method can effectively support the designment of policy recommended platforms and serve SMEs.

Comparing Reading Speeds for Reading Standardized Single Sentences and Paragraphs in Patients with Maculopathy

Introduction: The purpose of this study was to compare reading speeds (RS) of either paragraphs of text or single sentences in patients with maculopathy by investigating the repeatability of RS to decide which text type to use in studies on patients with maculopathy. Methods: RS was measured for standardized texts in 25 participants with a central scotoma due to maculopathy (mean age 77.8 years ± 9.9 SD, mean binocular visual acuity 0.65 logMAR (±0.85 SD), median magnification requirement 3-fold). Reading 3 single sentences taken from the Radner reading charts (sample #1, #2, and #3) of 14 words and reading 3 paragraphs of International Reading Speed Texts (IReST, sample # 3, #6, and #10) with a mean of 132 (±3.2 SD) words, each in German, were compared. The 6 texts were read aloud in random order from a closed-circuit TV system, with size adjusted according to the individual magnification requirement. Reading time was measured by stopwatch, and speed was calculated in correctly read words per minute (wpm). Differences in RS depending on text length (single sentence vs. paragraph) and text sample were calculated by the Bland-Altman analysis. Results: The mean RS showed no significant difference between 2 charts of the same kind (sentences: 93 wpm ± 37 SD; paragraphs: 95 wpm ± 38 SD). RS differences between 2 charts were lower in paragraphs than in single sentences. Highest correlations of RS between all 6 texts existed between the 3 IReST text samples (r = 0.98, 0.98, and 0.98) compared with the 3 Radner sentences (r = 0.89, 0.81, and 0.90). The inter-chart reliability (coefficient of repeatability) was smaller for the paragraphs (12.9 wpm) than for the single sentences (36.4 wpm). Conclusion: In patients with maculopathy, single sentences are well suited for single measurement of RS. For repeated measurements (e.g., monitoring the course of a reading disorder or assessing effects of interventions), paragraphs are preferable because of their lower variability of RS between the paragraphs.

Emile Durkheim Rides Again: The Death of the Western Hero and the Rise of the Moral Individualist

Emile Durkheim Rides Again: The Death of the Western Hero and the Rise of the Moral Individualist Scott Pearce Corrigendum: (updated 10.05.20) Page 79: The last paragraph of text has been updated to read: "At the beginning of the film, Munny is living a law-abiding life as a farmer while raising two children, but it is only an illusion of social integration. At the end of the film, after his rampage, Munny has demonstrated the magnitude of the threat he poses to society. When the epilogue then notes that Munny “prospered in dry goods," signaling his return to an illusion of integration (magnified, in fact, by prosperity), the film holds the myth of a nation’s moral identity in a final contempt." This article examines the function, transition, and ultimate removal of the hero from the Western film genre in the late 1960s. Most examinations of the genre, especially of its mid-twentieth-century heyday, have assumed that the Western requires a “hero.” Even “antihero” Westerns of the late 1960s depend on this assumption, for although the hero is often absent from antihero narratives, the hero and antihero exist on the same spectrum. The result has been a remarkably binary approach to the genre, with heroic figures played by the likes of Errol Flynn, Randolph Scott, Alan Ladd, and John Wayne used as lenses for understanding large-scale cultural movements.1 This article argues instead that revisionist Westerns, which arose as early as The Ox-Bow Incident (Wellman 1943) but flourished in the 1970s onwards, present neither hero nor antihero but, rather, the “moral individualist”—a complex and problematic figure best understood through the work of sociologist Emile Durkheim. Origins of the Western The Western film genre has its roots in “Manifest Destiny,” the nineteenth-century form of exceptionalism in America that conflated westward expansion with Christian hegemony. The concept sprang, in part, from European settlers, who themselves could trace exceptionalism not just to nation-state expansions and retreats over the previous thousand years but to religious crusades and to key theological constructs that required both [End Page 67] domination and sacrifice. But the United States adapted and consolidated that exceptionalism into a new sense of personal and political destiny. Spreading the American republic over the vast North American continent required a relatively modern vision of conquest, in which the land would be dominated not by hierarchy or caste but by the egalitarianism and individualism—even if these values required deception, dispossession, and extermination to effectuate. It was the creed of the exceptional individual, the hero, taken from classical myth but deployed not in service to any single collective but in service to the assorted masses of individuals. The killer was simultaneously the personal liberator. There were clear and deliberate attempts to establish the legitimacy of this national myth towards the end of the nineteenth century. Stephen McVeigh names the four-volume collection The Winning of the West (1889–1896) by Theodore Roosevelt, along with Roosevelt’s presidency itself (1901–1909), as vital to the promotion of the mythology of the West. For McVeigh, at the core of Roosevelt’s work are two directives: the “negation of the Native-American” and “the formation of the American character,” the latter defined by self-reliance, and “the priority of the individual” (21). Roosevelt’s position early on as both a former frontiersman in South Dakota and a former member of the lower house of the New York State Legislature bridged the gap between the east and the west, between the cultivated and the wild. Roosevelt embodied both forms of life in America, winning him broad acceptance among the populace. His presidency, along with his expeditions to Africa and South America, only fortified his position as an authoritative voice on how and why America had flourished. He offered in his own life an example of the exceptional American individual. Roosevelt, however, was supported by other like-minded people, most familiar of whom was Frederick Jackson Turner, whose essay “The Significance of the Frontier in American History,” presented in 1893 at a meeting of the American Historical Association, formulated for academics a new direction and perspective on the foundations of...

Interpretation bias and contamination-based obsessive-compulsive symptoms influence emotional intensity related to disgust and fear.

Biased processing of disgust-related stimuli is increasingly discussed in addition to fear-related processing as a maintenance factor for contamination-based obsessive-compulsive disorder (C-OCD). However, the differential impact of fear and disgust on biased processing in C-OCD is not yet completely understood. Because it is difficult to distinguish the two emotions in self-report assessment by directly addressing the specific emotions, a text paragraph-based interpretation bias paradigm was applied to more implicitly assess emotions. For the text-based interpretation bias paradigm, disgust-related, fear-related, disgust-fear-ambiguous and neutral text paragraphs describing everyday life situations were developed and validated in a pre-study (N = 205). Fifty-nine healthy participants watched either disgust- or fear-inducing movies and afterwards rated their experienced emotional response to the text paragraphs. The results show that fear and disgust components of an emotional response to mixed-emotional situations are strongly influenced by the situational context, and across the levels of trait contamination fear people did not differ in their fear experiences to everyday situations (which was overall strong), but in their disgust experiences. These findings highlight the strength of situational context on interpretation bias for mixed-emotional disorders and the important role of disgust for C-OCD.

ATA2020 Session Summaries (Abstracts)

ATA2020 Session Summaries (Abstracts)

Automatic Question Generation u sing Sequence to Sequence RNN Model

Automatic Question Generation (AQG) has recently received growing focus in the processing of natural language (NLP). This attempts to create questions from a text paragraph, where certain sub-spans of the passage in question will answer the questions produced.. Traditional methods predominantly use rigid heuristic rules to turn a sentence into related questions. In this research, we suggest using the neural encoder-decoder model to produce substantive and complex questions from the sentences of natural language. We apply a attention-based sequence to sequence learning paradigm for the task and analyze the impact of encoding sentence vs. knowledge at paragraph level. Information retrieval and NLP are the core components of AQG. It incorporates the application of production rules; recurrent neural network (RNN) based encoder-decoder sequence to sequence (seq2seq) models, and other intelligent techniques. RNN is used because of its long short term memory power (LSTM).The proposed system focus on generating factual WH type questions.

Sentiment Analysis Using Gated Recurrent Neural Networks

Text sentiment analysis is an important and challenging task. Sentiment analysis of customer reviews is a common problem faced by companies. It is a machine learning problem made demanding due to the varying nature of sentences, different lengths of the paragraphs of text, contextual understanding, sentiment ambiguity and the use of sarcasm and comparatives. Traditional approaches to sentiment analysis use the tally or recurrence of words in a text which are allotted sentiment values by some expert. These strategies overlook the order of words and the complex different meanings they can communicate. Hence, RNNs were introduced that are effective yet challenging to train. Bi-GRUs and Bi-LSTM architectures are a recent form of RNNs which can store information about long-term dependencies in sequential data. In this work, we attempted a survey of different deep learning techniques that have been applied to sentiment classification and analysis. We have implemented the baseline models for LSTM, GRU and Bi-LSTM and Bi-GRU on an Amazon review dataset.

STUDENTS PERCEPTION OF REFERENCES IN DESCRIPTIVE TEXT

This research focuses on student perception about how to prepare to understand the use of types of references (anaphoric, cataphoric, and exophoric reference) in the Descriptive text. The objectives of this research are to find out what the types of references that many used in Descriptive text and how many types of references for all paragraph in Descriptive text. The method used in this research is a descriptive qualitative method. The researcher got the data from document analysis namely in the Descriptive text about Artikel. The result from this research are the result from the tenth paragraph of the Descriptive text that has already done to analysis, there are 6 anaphoric reference, 6 cataphoric and in this article contains an understanding of a text and a concept so students can understand about the material.

Prehistory and Archaeology of Northeast India: Multidisciplinary Investigation in an Archaeological Terra Incognita by Manjil Hazarika

Reviewed by: Prehistory and Archaeology of Northeast India: Multidisciplinary Investigation in an Archaeological Terra Incognita by Manjil Hazarika Kathleen D. Morrison Prehistory and Archaeology of Northeast India: Multidisciplinary Investigation in an Archaeological Terra Incognita. Manjil Hazarika. Delhi: Oxford University Press, 2017. 378 pp., 2 maps, 17 figures. Hardcover US $35, ISBN 9780199474660. The subtitle of Prehistory and Archaeology of Northeast India refers to northeast India as an archaeological terra incognita; this is certainly no exaggeration. This volume is thus an important contribution to the history and archaeology of this fascinating yet understudied region. The northeast is here defined as including the Indian states of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura, a vast area bordered by Bangladesh, Bhutan, China, Nepal, and Myanmar. Almost completely overlooked by archaeologists, this region is a critical border zone between what is traditionally defined as South Asia and Southeast Asia. Its complex history reflects this interstitial location; one hopes that this volume is just the first of many archaeological studies of this key region. The book covers a lot of ground in its effort to compile existing information about the archaeology and historical linguistics of the northeast and present new archaeological survey data from the Garbhanga Reserve Forest in the state of Assam, along with ethnographic observations of the Karbi, local swidden agriculturalists. In its wide range of topics, the volume reminds one of gazetteers, regionally-specific summaries covering topics from history to household composition. Produced throughout the colonial period and even beyond, gazetteers provided authoritative summaries of official knowledge for general use. Hazarika’s work, a revision of his Bern University PhD thesis, has something of this feel—a wide-ranging guide to the ethnography, historical linguistics, and archaeology of the northeast. Of necessity, the goal of the work is primarily descriptive, asking questions about prehistoric cultural identity, territories, and change through time. Hazarika adopts a multifaceted approach, combining evidence from linguistics, archaeology, and ethnography to try and fill out a picture of local prehistory. Natural conditions have made archaeological fieldwork difficult in this area, with frequent floods, alluvial deposition by the Brahmaputra river, rain, and heavy vegetation cover posing logistical challenges. Chapters 1 and 2 introduce the work and present general background. Chapter 3 is entirely devoted to a reviewof the linguistic groups of the region and their probable patterns of change through time. While linguistic patterns doubtless hold much historical information, the author is not in a position to draw firm connections between this material and the archaeological data, leaving this chapter hanging somewhat awkwardly. Chapter 4 is a very useful synthesis of previous archaeological research in the northeast. There is, as noted, not a great deal of prior work, but this chapter does a good job of bringing what does exist together. In this chapter, the tables with lists of sites, their time periods, and basic artifact inventories are especially helpful, though it would have been even better if locational information had also been included. In many ways, this chapter is the heart of the volume. Not only does it provide a summary of existing work, but the tables also highlight similarities and differences between sites in terms of their recovered botanical material and artifact inventories. Chapter 5 presents new data from Hazarika’s archaeological reconnaissance of the Garbhanga Reserve Forest in the state of Assam. He describes four sites, although only the site of Bargaon gets more than a paragraph of text. Bargaon contains redware ceramics, chipped and groundstone tools (including celts), iron artifacts, and megaliths. Although the surface was cleared, the site does not seem to have been excavated and so does not have a secure date. Many of the recovered remains, including a large number of bovine teeth, were collected by the local Karbi villagers, who the author views as an important analogue for past residents. Indeed, most of [End Page 489] chapter 5 is devoted to a description of Karbi farming and life ways. This material, also gathered by the author, is in many ways the primary novel contribution of the work. In chapter 6, Hazarika makes a case for the in situ domestication of rice and other plant and animal domesticates in northeast India...

A Novel Document-Level Relation Extraction Method Based on BERT and Entity Information

Document-level relation extraction aims to extract the relationship among the entities in a paragraph of text. Compared with sentence-level, the text in document-level relation extraction is much longer and contains many more entities. It makes the document-level relation extraction a harder task. The number and complexity of entities make it necessary to provide enough information about the entities for the models in document-level relation extraction. To solve this problem, we put forward a document-level entity mask method with type information (DEMMT), which masks each mention of the entities by special tokens. By using this entity mask method, the model can accurately obtain every mention and type of the entities. Based on DEMMT, we propose a BERT-based one-pass model, through which we can predict the relationships among the entities by processing the text once. We test the proposed model on the DocRED dataset, which is a large scale open-domain document-level relation extraction dataset. The results on the manually annotated part of DocRED show that our approach obtains 6% F1 improvement compared with the state-of-the-art models that do not use pre-trained models and has 2% F1 improvement than BERT which does not use the DEMMT. On the distant supervision generated part of DocRED, the improvement of F1 is 2% compared with no pre-trained models, and 5% compared with pure BERT.

Karcı summarization: A simple and effective approach for automatic text summarization using Karcı entropy

Increases in the amount of text resources available via the Internet has amplified the need for automated document summarizing tools. However, further efforts are needed in order to improve the quality of the existing summarization tools currently available. The current study proposes Karcı Summarization, a novel methodology for extractive, generic summarization of text documents. Karcı Entropy was used for the first time in a document summarization method within a unique approach. An important feature of the proposed system is that it does not require any kind of information source or training data. At the stage of presenting the input text, a tool for text processing was introduced; known as KUSH (named after its authors; Karcı, Uçkan, Seyyarer, and Hark), and is used to protect semantic consistency between sentences. The Karcı Entropy-based solution chooses the most effective, generic and most informational sentences within a paragraph or unit of text. Experimentation with the Karcı Summarization approach was tested using open-access document text (Document Understanding Conference; DUC-2002, DUC-2004) datasets. Performance achievement of the Karcı Summarization approach was calculated using metrics known as Recall-Oriented Understudy for Gisting Evaluation (ROUGE). The experimental results showed that the proposed summarizer outperformed all current state-of-the-art methods in terms of 200-word summaries in the metrics of ROUGE-1, ROUGE-2, ROUGE-L, and ROUGE-W-1.2. In addition, the proposed summarizer outperformed the nearest competitive summarizers by a factor of 6.4% for ROUGE-1 Recall on the DUC-2002 dataset. These results demonstrate that Karcı Summarization is a promising technique and it is therefore expected to attract interest from researchers in the field. Our approach was shown to have a high potential for adoptability. Moreover, the method was assessed as quite insensitive to disorderly and missing texts due to its KUSH text processing module.

Students Ability in Constructing Paragraph of Recount Text

Writing skills is one type of language skills which should be controlled by the student. The students must be familiar with English especially to writing skill which write about their experience at the past time or to write recount text. For this reason, the researcher intended to investigate the students’ ability in constructing paragraph of recount text. The objective of this research is to measure students’ ability in constructing paragraphs and find out the causes of error made by the students. The design of this research is quantitative decriptive to measure students ability in constructing paragraphs at recount text. The population was students Madrasah Aliyah Negeri Model Sorong Grade XII. The technique of collecting data, the students were assigned to write the paragraphs in personal recount text based on their experiences in 60 minutes so the students decided the theme by themselves. The result of this research shows that 10 students score 43,4 % in good, then the students category of average was 9 students (39,1 %), and the students category of excellent was 4 students (17,1 %). The writer concluded that the students ability in constructing paragraph was average.

The development of the “Bawi Kuwu” learning model in the text writing material of the observation report

The application of the learning model is an operational step to achieving maximum learning goals. Based on the results of the author's observation on Indonesian Language subjects, especially in the field of writing skills, the Report on Observation Results (LHO) is often found to be a problem, students find it difficult to make sentences and paragraphs of LHO text. This is because the teacher often implements an inappropriate learning model, so students have not been able to fully understand the concept of the LHO text. The selection of creative and innovative learning methods and models can influence the ability of students to construct their knowledge well. The application of creative and innovative learning models can also be developed from a local wisdom in each region, for example the local wisdom of Bawi Kuwu folklore in Central Kalimantan. Folklore Bawi Kuwu can be modified into a learning model by paying attention to the cultural value of the story. The Bawi Kuwu (BK) learning model is a group learning model based on the cultural value of folklore in Central Kalimantan and the collaboration between the concept of cooperative jigsaw learning models and peer teaching. The application of the Bawi Kuwu learning pattern in writing the Observation Results Text is very suitable to be applied because in its application the students in the group try to construct their knowledge and convey it to a student in his group with the guidance of the teacher.

STUDENTS’ ABILITY IN WRITING DESCRIPTIVE TEXT BASED ON ITS GENERIC STRUCTURE AT THE TENTH GRADE STUDENT OF VOCATIONAL HIGH SCHOOL

Study of language skills in English is pretty important to increase students’ skill in study English. One of the most important skills is writing. It can make students share the ideas into written form in the text or paragraph with the right order of generic structure. The purposes of this study are to find out the students ability in writing descriptive text and to find out whether students writing descriptive are already well organized or not. The research method used qualitative research method. The researchers took 33 students as respondents. The data analysis took from the students’ descriptive text results. Based on the data analysis, the researchers found 15 or 45 % students created the descriptive text and 18 or 55 % students created the report text. It showed 10 or 30 % students created the paragraphs of descriptive text properly based on its generic structure and 5 or 15 % students could not apply it properly. It can be concluded that most of the students’ paragraphs are well organized. Meanwhile, the other students could not make it properly, because they still confused and could not distinguish the differences between descriptive text and report text.

Erratum for Riccio et al., "Characterization of Sex Differences in Ocular Herpes Simplex Virus 1 Infection and Herpes Stromal Keratitis Pathogenesis of Wild-Type and Herpesvirus Entry Mediator Knockout Mice".

Volume 4, issue 2, e00073-19, 2019, [https://doi.org/10.1128/mSphere.00073-19][1]. In the 2nd sentence of the importance section (PDF page 1, second paragraph) and the 1st sentence of the 2nd paragraph of the main text (PDF page 2, first full paragraph), herpesvirus stromal keratitis should be

INTEGRATING ONE OF INTERNAL STRUCTURE OF DISCOURSE CALLED ‘PROCESS’ IN WRITING PROCEDURE TEXT FOR INTERMEDIATE LEVEL

<p><em>In this article the researcher applies one of internal structure of discourse called ‘Process’ in writing ‘Procedures text’. </em><em>Procedure text is a piece of writing that tells us information of making/doing something through several steps/directions. There are two important parts that students have to consider in procedure text; the generic structure and the language features. In the language features, the internal structure of “Process” of discourse integrated. The aim of internal structure of “Process” are offers the procedure/process for how something is done/created. The problem occurs when students ignore the internal structure of discourse, therefore they will face difficulties in writing process.</em></p><p><em>The first step of the researcher did in this research was making a lesson plan and student’ assessment. After finish it the researcher discussed with the expert to get the feedback. Based on the feedback the researcher revised it. Once again researcher discussed with the expert to get the final result of lesson plan and student’ assessment. The next step was conducting try out. It was held on 28<sup>th</sup> December 2017. The subjects are 3 students of UNY. The subjects are chosen randomly. </em></p><p><em>Based on the research finding, internal structure is applicable in writing. The generic structure and language features are also really helpful for students in writing English especially procedures text. Thus, all of the subjects of the research be able to produce discourse part with the same structure and successfully produce a paragraph of procedure text.</em></p><p> </p>

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis)

HomeJournal of the American Heart AssociationVol. 8, No. 9Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis) Open AccessCorrectionPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citations ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toOpen AccessCorrectionPDF/EPUBDetection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis) Originally published4 May 2019https://doi.org/10.1161/JAHA.118.002294Journal of the American Heart Association. 2019;8:e002294This article corrects the followingDetection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis)In the article by Sparapani et al, “Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis),” which published online March 2, 2019, and appeared in the March 5, 2019 issue of the journal (J Am Heart Assoc. 2019;8:e009959. DOI: 10.1161/JAHA.118.009959), the article title was incorrectly written as, “Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.” It has now been corrected to read, “Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis).”In the supplemental material, page 2, the last paragraph of text was missing. The following text has now been added, “At the following Uniform Resource Locator (URL), we provide a technical report showing how to make predictions with Bayesian Additive Regression Trees (BART) for Normalized Left Ventricular Mass (LVM), LVM and Left Ventricular Hypertrophy (LVH). https://www.mcw.edu/-/media/MCW/Departments/Biostatistics/tr067.pdf.”The publisher regrets the error.The online version of the article has been updated and is available at https://www.ahajournals.org/doi/10.1161/JAHA.118.009959Footnotes Previous Back to top Next FiguresReferencesRelatedDetailsRelated articlesDetection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA (Multi‐Ethnic Study of Atherosclerosis)Rodney Sparapani, et al. Journal of the American Heart Association. 2019;8 May 7, 2019Vol 8, Issue 9Article InformationMetrics Copyright © 2019 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley BlackwellThis is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.https://doi.org/10.1161/JAHA.118.002294PMID: 31057031 Originally publishedMay 4, 2019 PDF download

Decision-makers’ underestimation of user innovation

In the past few decades, much research has documented the importance of users as sources of innovations. Over the last 10 years, Research Policy alone has published 56 research articles investigating this phenomenon. We ask to what degree the findings of users as innovators have been absorbed by decision-makers responsible for new product development (managers) and by those who shape the contextual conditions for innovation (policy makers and public administration). A realistic perception of the sources of innovation is important as it constitutes the basis for a rational allocation of resources and thus indirectly impacts the innovation performance of companies and societies at large.In a large-scale survey of n = 1500 decision-makers, we found support for a substantial underestimation of users as a source of innovation: While the true proportion of user innovation among the most valuable 1678 innovations in nine industries is 54.4% (as established in existing research articles), decision-makers estimate it to be 21.7%. A content analysis of transfer media (450 academic textbooks, popular innovation books, and business articles) underscores this theory-practice gap: Of 3469 text paragraphs dealing with the sources of innovation, only 2.7% mention users as innovators. We develop six propositions on the reasons for and consequences of this underestimation that may serve as a starting point for future research and practical consequences.