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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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection by Muhammad Shafiq, J. Kavitha, Dhruva R. Rinku, N. K. Senthil Kumar, Kamal Poon, Amar Y. Jaffar, V. Saravanan

“…Based on features, the sorted-out data gets evaluated through a GRU-LSTM (Gated Recurrent Unit - Long Short-Term Memory) network to identify the state of the infant as usual and suggestive of hypoglycemia—blood glucose below 70 mg/dL, pale complexion, profuse perspiration. …”
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Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks by Ahmad Almadhor, Shtwai Alsubai, Imen Bouazzi, Vincent Karovic, Monika Davidekova, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The study also provides a comparison with different DL models such as Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNN), Long Short-Term Memory-Recurrent Neural Networks (LSTM-RNN), and Gated Recurrent Unit (GRU). The CICEVSE2024 (EVSE-A and EVSE-B) datasets are used to assess the framework, where one dataset is used to train and store weights, and the second is used to evaluate the learned patterns using transfer learning. …”
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An Adaptive Convolutional Neural Network With Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP) for Robust EEG-Based Motor Imagery Classification by Aaqib Raza, Mohd Zuki Yusoff

“…The proposed model integrates a Dynamic Pathway Convolution Network (DPCN) for adaptive feature extraction, incorporating a Dynamic Gating Controller (DGC) and Dynamic Adaptive Spatio-Temporal (DAST) blocks to efficiently capture multi-scale spatial and temporal dependencies. …”
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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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Clinical features of post-COVID-19 period. Results of the international register “Dynamic analysis of comorbidities in SARS-CoV-2 survivors (AKTIV SARS-CoV-2)”. Data from 6-month f... by G. P. Arutyunov, E. I. Tarlovskaya, A. G. Arutyunov, Yu. N. Belenkov, A. O. Konradi, Yu. M. Lopatin, A. P. Rebrov, S. N. Tereshchenko, A. I. Chesnikova, H. G. Hayrapetyan, A. P. Babin, I. G. Bakulin, N. V. Bakulina, L. A. Balykova, A. S. Blagonravova, M. V. Boldina, A. R. Vaisberg, A. S. Galyavich, V. V. Gomonova, N. Yu. Grigorieva, I. V. Gubareva, I. V. Demko, A. V. Evzerikhina, A. V. Zharkov, U. K. Kamilova, Z. F. Kim, T. Yu. Kuznetsova, N. V. Lareva, E. V. Makarova, S. V. Malchikova, S. V. Nedogoda, M. M. Petrova, I. G. Pochinka, K. V. Protasov, D. N. Protsenko, D. Yu. Ruzanau, S. A. Sayganov, A. Sh. Sarybaev, N. M. Selezneva, A. B. Sugraliev, I. V. Fomin, O. V. Khlynova, O. Yu. Chizhova, I. I. Shaposhnik, D. A. Shchukarev, A. K. Abdrahmanova, S. A. Avetisian, H. G. Avoyan, K. K. Azarian, G. T. Aimakhanova, D. A. Ayipova, A. Ch. Akunov, M. K. Alieva, A. V. Aparkina, O. R. Aruslanova, E. Yu. Ashina, O. Yu. Badina, O. Yu. Barisheva, T. I. Batluk, A. S. Batchayeva, R. A. Bashkinov, A. M. Bitieva, I. U. Bikhteyev, N. A. Borodulina, M. V. Bragin, A. M. Budu, G. A. Bykova, K. R. Vagapova, D. D. Varlamova, N. N. Vezikova, E. A. Verbitskaya, O. E. Vilkova, E. A. Vinnikova, V. V. Vustina, E. A. Gаlova, V. V. Genkel, E. I. Gorshenina, E. V. Grigorieva, E. Yu. Gubareva, G. M. Dabylova, I. A. Demchenko, O. Yu. Dolgikh, M. Y. Duyshobayev, D. S. Evdokimov, K. E. Egorova, A. N. Ermilova, A. E. Zheldybayeva, N. V. Zarechnova, Yu. D. Zimina, S. Yu. Ivanova, E. Yu. Ivanchenko, M. V. Ilina, M. V. Kazakovtseva, E. V. Kazymova, Yu. S. Kalinina, N. A. Kamardina, A. M. Karachenova, I. A. Karetnikov, N. A. Karoli, M. K. Karsiev, D. S. Кaskaeva, K. F. Kasymova, Zh. B. Kerimbekova, A. Sh. Kerimova, E. S. Kim, N. V. Kiseleva, D. A. Klimenko, A. V. Klimova, O. V. Kovalishena, E. V. Kolmakova, T. P. Kolchinskaya, M. I. Kolyadich, O. V. Kondriakova, M. P. Konoval, D. Yu. Konstantinov, E. A. Konstantinova, V. A. Kordukova, E. V. Koroleva, A. Yu. Kraposhina, T. V. Kriukova, A. S. Kuznetsova, T. Yu. Kuzmina, K. V. Kuzmichev, Ch. K. Kulchoroeva, T. V. Kuprina, I. M. Kouranova, L. V. Kurenkova, N. Yu. Kurchugina, N. A. Kushubakova, V. I. Levankova, N. A. Lyubavina, N. A. Magdeyeva, K. V. Mazalov, V. I. Majseenko, A. S. Makarova, A. M. Maripov, A. A. Marusina, E. S. Melnikov, N. B. Moiseenko, F. N. Muradova, R. G. Muradyan, Sh. N. Musaelian, A. O. Myshak, E. S. Nekaeva, N. M. Nikitina, B. B. Ogurlieva, A. A. Odegova, Yu. M. Omarova, N. A. Omurzakova, Sh. O. Ospanova, E. V. Pahomova, L. D. Petrov, S. S. Plastinina, V. A. Pogrebetskaya, D. V. Polyakov, D. S. Polyakov, E. V. Ponomarenko, L. L. Popova, N. A. Prokofeva, I. A. Pudova, N. A. Rakov, A. N. Rakhimov, N. A. Rozanova, S. Serikbolkyzy, A. A. Simonov, V. V. Skachkova, D. V. Soloveva, I. A. Soloveva, I. M. Sukhomlinova, A. G. Sushilova, D. R. Tagayeva, Yu. V. Titojkina, E. P. Tikhonova, D. S. Tokmin, A. A. Tolmacheva, M. S. Torgunakova, K. V. Trenogina, N. A. Trostianetckaia, D. A. Trofimov, M. A. Trubnikova, A. A. Tulichev, A. T. Tursunova, N. D. Ulanova, O. V. Fatenkov, O. V. Fedorishina, T. S. Fil, I. Yu. Fomina, I. S. Fominova, I. A. Frolova, S. M. Tsvinger, V. V. Tsoma, M. B. Cholponbaeva, T. I. Chudinovskikh, O. A. Shevchenko, T. V. Sheshina, E. A. Shishkina, K. Yu. Shishkov, S. Yu. Sherbakov, E. A. Yausheva

“…The highest mortality rate was observed in the first 3 months in the group of patients with class II-IV heart failure, as well as in patients with cardiovascular diseases and cancer. …”
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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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Impact of LDL-C levels on severity and outcome of intracranial haemorrhage: a single-centre retrospective study by Kang-Po Lee, Li-Chi Hsu

“…Moreover, statin use is associated with better long-term outcome and may attenuate the effects of initial LDL-C in ICH patients.Conclusions In patients with ICH, particularly those with deep ICH, lower LDL-C levels are associated with more severe ICH and higher short-term and long-term mortality rates. Further randomised controlled trials are warranted to determine the optimal LDL-C levels in patients with ICH and dyslipidaemia.…”
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A Global Systematic Review and Meta‐Analysis of Methods Used to Evaluate Predation and Diet of Domestic Cats (Felis catus) by Hannah L. Lockwood, Maren Huck

“…Palatability and detectability of prey appear to influence the data reported, and these aspects should be considered when calculating total predation rates.…”
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The Use of Sound Recorders to Remotely Measure Grass Intake Behaviour in Horses by Daisy E. F. Taylor, Bryony E. Lancaster, Andrea D. Ellis

“…Grazing was identified audibly (SR_ear) and visually through soundwave pattern software (SR_wav). Chew rates (SR_ear: 47 ± 5 chews/min, VD: 43 ± 4 chews/min) were similar between methods. …”
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Perennial and Non‐Perennial Streamflow Regime Shifts Across California, USA by Jessica R. Ayers, Sarah M. Yarnell, Ethan Baruch, Robert A. Lusardi, Theodore E. Grantham

“…Streams impacted by human activities had greater drying rates, but regulation has caused some non‐perennial streams to become perennial. …”
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Integrated evaluation and optimization of acid fracturing effectiveness in carbonate reservoirs: Experimental insights and field validation. by Peng Lu, Songlei Li, Jinsong Liu, Nan Yuan, Heng Liu

“…Implementation of the proposed methodology has increased stimulation success rates from 55% to 82% in pilot fields, with sustained production gains exceeding 35%. …”
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