Is guideline-driven prophylaxis for venous thromboembolism common practice in the South African private hospital setting? by Melissa van der Merwe, Marlene Julyan, Jesslee M. du Plessis

“…This study evaluated prescribing patterns of VTE prophylaxis in one of the largest South African (SA) private hospital groups. …”
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Muscle Activity Onset Prior to Landing in Patients after Anterior Cruciate Ligament Injury: A Systematic Review and Meta-Analysis. by Daniel Theisen, Isabel Rada, Amélie Brau, Paul Gette, Romain Seil

“…Six studies meeting inclusion criteria underwent quality assessment, data extraction and re-computing procedures for the meta-analysis. The quality was rated "moderate" for 2 studies and "poor" for 4. …”
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Reading English-Language Haiku: Processes of Meaning Construction Revealed by Eye Movements by Hermann J Mueller, Thomas Geyer, Franziska Günther, Jim Kacian, Stella Pierides

“…To examine this process, we recorded readers’ eye movements, and we obtained measures of memory for the read poems as well as subjective ratings of comprehension difficulty and understanding achieved. …”
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Image Quality Assessment of Augmented Reality Glasses as Medical Display Devices (HoloLens 2) by Simon König, Simon Siebers, Claus Backhaus

“…HoloLens 2 was assessed for overall image quality, luminance, grayscale consistency, and color uniformity. Five participants rated the TG18-OIQ pattern under ambient lighting conditions of 2.4 and 138.7 lx. …”
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I-AIR: intention-aware travel itinerary recommendation via multi-signal fusion and spatiotemporal constraints by Xiao Cui, Zhihua Wang, Ping Li, Qiang Xu

“…Additionally, many approaches decouple POI selection from itinerary construction and depend heavily on limited behavioral signals, failing to capture richer feedback such as ratings, dwell times, or click histories. To address these limitations, we propose an intention-aware deep learning framework that integrates diverse user signals into a unified itinerary planning model. …”
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CRYPTOCURRENCY TIME SERIES FORECASTING MODEL USING GRU ALGORITHM BASED ON MACHINE LEARNING by Melina Melina, Sukono Sukono, Herlina Napitupulu, Norizan Mohamed, Yulison Herry Chrisnanto, Asep ID Hadiana, Valentina Adimurti Kusumaningtyas

“…This research aims to build a cryptocurrency forecasting model with a machine learning-based time series approach using the gated recurrent units (GRU) algorithm. The dataset used is historical Bitcoin closing price data from January 1, 2017, to July 31, 2024. …”
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Scalability analysis of heavy-duty gas turbines using data-driven machine learning by Shubhasmita Pati, Julian D. Osorio, Mayank Panwar, Rob Hovsapian

“…The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). …”
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Consensus-Driven Development of an Exercise Base Manual Programme for Prediabetic Patients: A Delphi Study by Hafeez S, Shakil-Ur-Rehman S, Riaz S, Hafeez S, Hafeez JS, Mumtaz H

“…Initial recommendations were rated by panalists through a 5-point Likert scale. …”
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Gut–Vaginal Microbiome Crosstalk in Ovarian Cancer: Implications for Early Diagnosis by Hao Lin, Zhen Zeng, Hong Zhang, Yongbin Jia, Jiangmei Pang, Jingjing Chen, Hu Zhang

“…Ovarian cancer remains a formidable global health burden, characterized by frequent late-stage diagnosis and elevated mortality rates attributable to its elusive pathogenesis and the critical lack of reliable early-detection biomarkers. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. …”
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MSA-GCN: Exploiting Multi-Scale Temporal Dynamics With Adaptive Graph Convolution for Skeleton-Based Action Recognition by Kowovi Comivi Alowonou, Ji-Hyeong Han

“…On the other hand, the TMST module integrates a Gated Multi-stage Temporal Convolution (GMSTC) with a Temporal Multi-Head Self-Attention (TMHSA) to capture global temporal features and accommodate both long-term and short-term dependencies within action sequences. …”
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GT-SRR: A Structured Method for Social Relation Recognition with GGNN-Based Transformer by Dejiao Huang, Menglei Xia, Ruyi Chang, Xiaohan Kong, Shuai Guo

“…In order to overcome these restrictions, this essay suggests a SRR model that integrates Gated Graph Neural Network (GGNN) and Transformer. …”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

“…These components are then modeled independently: long short-term memory (LSTM) and convolutional neural networks (CNN) handle trend and seasonal patterns, while gated recurrent units (GRU) and Transformer process residual fluctuations. …”
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Multiscale Convolutional Fusion Network for Efficient Monaural Speech Separation by Rui Yang, Shanliang Pan

“…MSCF first employs dynamic convolution-based downsampling to enhance the multiscale feature representation. Adaptive gating and multiscale convolutions are then utilized to capture complex acoustic patterns. …”
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Enhancing Stock Price Forecasting with CNN-BiGRU-Attention: A Case Study on INDY by Madilyn Louisa, Gumgum Darmawan, Bertho Tantular

“…The method applied a hybrid model combining a Convolutional Neural Network (CNN), Bidirectional Gated Recurrent Unit (BiGRU), and an Attention Mechanism (AM) to address the nonlinear, volatile, and noisy characteristics of stock data. …”
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Adherence to the Singapore Integrated 24 h Activity Guidelines for Pre-Primary School Children Before, During and After the COVID-19 Lockdown in Singapore by Seow Ting Low, Terence Buan Kiong Chua, Dan Li, Michael Chia

“…The COVID-19 pandemic has significantly disrupted the lives of pre-primary school children in Singapore where increased infection rates prompted lockdown measures that altered children’s daily routines. …”
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Optical and photoluminescence characteristics of Pr3+-doped P2O5 +BaO+La2O3 glasses by C.R. Kesavulu, Ch. Basavapoornima, Pikkili Ramprasad, C.J. Deviprasad, Shobha Rani Depuru, C.K. Jayasankar

“…A luminescence peak at 600 nm was used as a monitoring level, and a 445 nm excitation was used to assess the decay curves. The decay rates exhibit a bi-exponential pattern, meaning that as the concentration of Pr3+ ions increase, the lifetimes become shorter. …”
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Numerical Study on the Influence of Inlet Blockage Ratios and Flow Conditions on Scour Development in Circular Culverts by Salam Hussein Sulaiman, Kaywan Othman Ahmed, Mohsen Isari, Jamil Bahrami

“…Each hydrograph included seven different flow discharges, and steady flow tests were conducted at the maximum rates observed during the unsteady scenarios. This study examined circular culverts subjected to inlet blockages of 0%, 25%, and 50% and compared the numerical result from Flow-3D simulations utilizing the Renormalization Group (RNG) turbulence model with observed data. …”
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Use of complementary medicine and uptake of COVID-19 vaccination among US adults by Holger Cramer, Holger Cramer, Mirela Bilc, Mirela Bilc

“…However, vaccination uptake was lower for both COVID-19 and flu vaccines, respectively, in individuals who visited chiropractors (AOR = 0.78, 95% CI [0.69, 0.89], p < 0.001; AOR = 0.71, 95% CI [0.63, 0.81], p < 0.001) and naturopaths (AOR = 0.66, 95% CI [0.51, 0.86], p = 0.002; AOR = 0.72, 95% CI [0.55, 0.94], p = 0.017). Uptake rates for both COVID-19 and flu vaccines were higher among individuals who visited an acupuncturist (COVID-19: AOR = 1.46, 95% CI [1.15, 1.86], p = 0.002; flu: AOR = 1.32, 95% CI [1.08, 1.63], p = 0.008). …”
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The association between cognitive ability and body mass index: A sibling-comparison analysis in four longitudinal studies. by Liam Wright, Neil M Davies, David Bann

“…<h4>Background</h4>Body mass index (BMI) and obesity rates have increased sharply since the 1980s. While multiple epidemiologic studies have found that higher adolescent cognitive ability is associated with lower adult BMI, residual and unobserved confounding due to family background may explain these associations. …”
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