Analysis of patient safety messages delivered and received during clinical rounds by Diane Levine, Jaya Gadivemula, Raya Kutaimy, Srinivasa Kamatam, Nagaratna Sarvadevabatla, Prateek Lohia

“…Residents recalled 56.4% of safety messages delivered; students recalled 76.7% of safety messages.Conclusion Patient safety is a focus of teaching during clinical rounds and provides meaningful opportunities to train students and residents to practice safe patient care.…”
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Adolescent Emoji Use in Text-Based Messaging: Focus Group Study by Matt Minich, Bradley Kerr, Megan Moreno

“… Abstract BackgroundAdolescents increasingly communicate through text-based messaging platforms such as SMS and social media messaging. …”
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Agitational Work for Providing Domestic Political Stability in North Caucasus Region: History, Practice, Experience by Gennady Viktorovich Marchenko

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Staged left ventricular recruitment facilitated by Sano conduit upsizingCentral Message by Neel K. Prabhu, BSE, Douglas M. Overbey, MD, Arya M. Iranmanesh, MD, Michael J. Campbell, MD, Nicholas D. Andersen, MD, Joseph W. Turek, MD, PhD, MBA

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Enhancing wellbeing in cancer care: Engagement in smart-messaging programmes for symptom management by Clement Boutry, Chloe Mays, Anika Kochar, Nima Moghaddam, Priya Patel, Emily Watson, Matthew Dicks, Felicity Gibbons, Sam Malins, James Rathbone

“…The workshop emphasised the need for improved promotional materials and staff training. Conclusion A tailored text messaging intervention shows promise in alleviating cancer-related symptoms, yet enrolment and active engagement remain obstacles. …”
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Impact of level crossing sign messages on temporary stop ratio of automobile drivers by Mayuko UEDA, Kazushige WADA, Shinnosuke USUI

“…The experiment revealed that a sign of “gratitude” showing the message “Thank you for stopping” had a significantly higher temporary stop ratio in comparison to the other signs or to no sign during the condition in which a train is not passing along the tracks. …”
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TRAINING OF THE FUTURE INTERPRETERS’ WORKING MEMORY by Antonina V. Prokopenko, Valeriia M. Rava

“…The article is devoted to the issues of functioning and training of short-term and long-term memory of future interpreters. …”
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Reservoir Computing Based on Two Parallel Reservoirs Under Identical Electrical Message Injection by Dian-Zuo Yue, Zheng-Mao Wu, Yu-Shuang Hou, Chun-Xia Hu, Zai-Fu Jiang, Guang-Qiong Xia

“…RC can be accomplished by three ways, namely RC₁/RC₂ (the virtual node states originating from SL₁/SL₂ are used for training and testing) and RC_M (the merged virtual node states originating from two SLs are used for training and testing). …”
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Pediatric resident use, perceptions, and desires for improvement of a clinical secure messaging application by Andrew W Halterman, Anneli R Cochrane, Andrew D Miller, Joy L Lee, William E Bennett, Jr, Emily L Mueller

“…Background: Hospitals are transitioning away from traditional pagers to secure text messaging (STM) applications. STM is perceived to improve efficiency and accessibility. …”
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Toward Representing Identical Privacy-Preserving Graph Neural Network via Split Learning by Yiming Fang, Huiyun Jiao, Risheng Huang

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FastClothGNN: Optimizing message passing in Graph Neural Networks for accelerating real-time cloth simulation by Yang Zhang, Kailuo Yu, Xinyu Zhang

“…We present an efficient message aggregation algorithm FastClothGNN for Graph Neural Networks (GNNs) specifically designed for real-time cloth simulation in virtual try-on systems. …”
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Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection by Tanjim Mahmud, Md. Alif Hossen Prince, Md. Hasan Ali, Mohammad Shahadat Hossain, Karl Andersson

“…The SMS Phishing Collection dataset was used, with a preparatory procedure involving the transformation of unstructured text data into numerical representations and the training of Word2Vec on preprocessed text. Experimental results demonstrate that the proposed CNN-Bi-GRU model outperforms existing approaches, achieving an overall highest accuracy of 99.82% in detecting SMS phishing messages. …”
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Surgical resection of severely calcified ascending arch in a pediatric congenital patientCentral Message by Cathlyn K. Medina, BA, Berk Aykut, MD, Lauren E. Parker, BS, Lindsey Reynolds, BS, Stephen Miller, MD, Joseph Y. Cao, MD, Joseph W. Turek, MD, PhD, MBA, Douglas M. Overbey, MD, MPH, Ziv Beckerman, MD

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Recontextualising theology: A challenge for theological training by Jaco Beyers

“…This is exacerbated by the challenge to train students to be able to pass the Christian message responsibly on into a new context. …”
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Commentary: Minimally invasive pulmonary valve replacement and the adoption curve for novel techniquesCentral Message by Joseph R. Nellis, MD, MBA, Joseph W. Turek, MD, PhD, Nicholas D. Andersen, MD

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A minimally invasive approach for atrial and ventricular sew-on epicardial lead placementCentral Message by Joseph R. Nellis, MD, MBA, Mohammed K. Alsarraj, BS, Jude S. Sauer, MD, Jacob A. Klapper, MD, Salim F. Idriss, MD, PhD, Joseph W. Turek, MD, MBA, PhD

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Interpretable Ordinal-Aware With Contrastive-Enhanced Anomaly Severity Detection on UAV Flight Log Messages by Swardiantara Silalahi, Tohari Ahmad, Hudan Studiawan, Eirini Anthi, Lowri Williams

“…We found that the model perceived the log messages’ semantics differently and were not aligned with how a human expert would. …”
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A novel system applying artificial intelligence in the identification of air leak sitesCentral MessagePerspective by Yuka Kadomatsu, MD, PhD, Megumi Nakao, PhD, Harushi Ueno, MD, Shota Nakamura, MD, PhD, Toyofumi Fengshi Chen-Yoshikawa, MD, PhD

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Predicting pressure gradient using artificial intelligence for transcatheter aortic valve replacementCentral MessagePerspective by Anoushka Dasi, BS, Beom Lee, MS, Venkateshwar Polsani, MD, FACC, FASE, Pradeep Yadav, MD, FACC, Lakshmi Prasad Dasi, PhD, FACC, FAIMBE, Vinod H. Thourani, MD, FACS, FACC

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Underwater Acoustic Communication Using Multi-Layer Vector Approximate Message Passing Evaluated on the Watermark Benchmark by Julian Winkler, Sabah Badri-Hoeher

“…A pre-trained artificial neural network is used as prior for the channel estimation. …”
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