Non-invasive physical plasma improves conventional wound management of cut and bite wounds in wild European hedgehogs by Jürgen Eichler, Björn Rulik, Alexander Abazid, Matthias B. Stope

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The Experience of Emotional Distancing in the Management of Compulsive Hoarding: A Visual Methods Approach Using the “Hoard” Acronym Tool by Colin Jones, Satwant Singh

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Application of Medical-Nursing Integration Multidisciplinary-Assisted Surgical Wound Nursing Mode in Improving the Quality of Wound Treatment by Jinyan Wang, Ting Yuan, Jun Shi

“…Surgical treatment is a common clinical intervention for trauma, but postoperative pain and poor nursing lead to slow wound recovery and wound infection. Therefore, it is extremely important to select effective nursing intervention methods to improve the quality of wound treatment. …”
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Dynamic reconfiguration of default and frontoparietal network supports creative incubation by Ziyi Li, Ze Zhang, Tengteng Tan, Jing Luo

Subjects: “…KeyWord…”
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The role of the hippocampus in working memory and word reading: Novel neural correlates of reading among youth living in the context of economic disadvantage by ET. Marcelle, H. Yang, JW. Cohen, B. Ramphal, D. Pagliaccio, V. Rauh, BS. Peterson, F. Perera, H. Andrews, AG. Rundle, J. Herbstman, AE. Margolis

Subjects: “…Working memory…”
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Linguistic methods of personality identification in the fiction text (using S.D. Dovlatov's works) by A.V. Bastrikov, E.M. Bastrikova

Subjects: “…author’s linguistic world image…”
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The influence of positive and negative electronic word of mouth review on hotel customer e-repurchase by Endang Tjahjaningsih, Dian Suprapti, Euis Soliha, Tristiana Rijanti

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THE LEXICAL EQUIVALENCE VARIETY OF F-WORDS TRANSLATION INTO INDONESIAN : CORPUS-BASED TRANSLATION RESEARCH by Isra F. Sianipar, Sajarwa Sajarwa

Subjects: “…F-Words Translation…”
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Biterm topic model of social network users’ sentiment by integrating word co-occurrence by Qiuyang GU, Bao WU, Chunhua JU

“…With the increasing number of social network users in recent years,text-based user sentiment analysis technology has been widely concerned and applied.However,data sparsity and low accuracy often reduce the accuracy and speed of emotion recognition methods.The user emotion Biterm topic model (US-BTM) was proposed which could find user preference and emotional tendency from the text of specific places,so as to effectively use Biterm for topic modeling.The strategy of user aggregation to form pseudo-documents was used,and word pairs were created for the whole corpus to solve the problems of data sparsity and short text.Then the topic was studied through the lexical co-occurrence model,so as to infer the topic with abundant corps-level information,and the purpose of accurately predicting the user’s interest,preference and emotion to the specific scene was achieved by analyzing the lexical matching set in the comment corpus under the specific scene and the emotion of the corresponding topic.The experimental results show that the method proposed can accurately capture users’ emotional tendency and correctly reveal users’ preference,which can be widely used in social network content description,recommendation,social network user interest description,semantic analysis and other fields.…”
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Text steganography method based on automatic selection coding and dynamic word selection strategy by Hui LI, Jiali JIN, Shuyu JIN, Weijiao MA

“…A text steganography method based on automatic selection coding and dynamic word selection strategy was proposed for the inflexible text coding method and candidate word increasing number leading to the low quality of generated steganographic text.Steganographic translations was generated based on Transformer’s neural machine translation model.In generating steganographic translations, fixed-length coding and Huffman coding were used to establish the mapping relationship between candidate words and codewords, and dynamic word selection based on the probability difference threshold was achieved by calculating the probability difference percentage between steganographic words and normal words.Finally, the size of the two generated steganographic translations Sacrebleu was compared to realize the automatic selection of coding mode.The experimental results show that the proposed method can generate steganographic translations with high fluency and readability.When the embedding rate is 11.19%, the Sacrebleu of the steganographic translation reaches 10.53.…”
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The Power of Words: A Study of How Search Contents Can Affect Financial Decisions by Du Ni, Xingzhi Li, Zhi Xiao, Ke Gong

“…Therefore, this study was carried out to analyze the emotional meanings of 13,915 English words obtained from Google Trends and the profits gained from the US house market by automatic transactions and discovered that the emotional meanings of the search contents could modulate the financial decision with unsupervised machine learning methods.…”
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Structure and usage do not explain each other: an analysis of German word-initial clusters by Wiese Richard, Orzechowska Paula

“…The present study focuses on German word-initial consonant clusters and asks whether feature-based phonotactic preferences correlate with patterns of type and token frequencies in present-day usage. …”
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Corrigendum to “High on Cannabis and Calcineurin Inhibitors: A Word of Warning in an Era of Legalized Marijuana” by Naomi Hauser, Tanmay Sahai, Rocco Richards, Todd Roberts

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The effect of social media marketing, electronic word-of-mouth, brand image on purchase intention by Aldan Mutia Ramadhan, Heppy Millanyani

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Forming of pseudo-international words translation skills in the process of learning a foreign language by Amaliya L. Kyuregyan, Ekaterina A. Milyutina

Subjects: “…international words…”
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Pengaruh Kepercayaan Merek, Brand Ambassador dan Word of Mouth Terhadap Keputusan Pembelian by Vianandra Intan Puspanada, Suzy Widyasari

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Affective polarization in a word: Open-ended and self-coded evaluations of partisan affect by Spencer Kiesel, Sharif Amlani

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Introducing an Unknown-Familiar one and a âNew Design for Word-Formation in Persian by وحید سبزیان‌پور

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A Quantitative Study on Dream of the Red Chamber: Word-Length Distribution and Authorship Attribution by Yue Yu, Wei Liu, Ying Feng

“…This paper investigates the distribution characteristics of word lengths in the Dream of the Red Chamber (DRC), measured in terms of the number of syllables or characters. …”
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Drug-target binding affinity prediction based on power graph and word2vec by Jing Hu, Shuo Hu, Minghao Xia, Kangxing Zheng, Xiaolong Zhang

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