Symptom Trajectories and Clinical Subtypes in Post–COVID-19 Condition: Systematic Review and Clustering Analysis by Mingzhi Hu, Tian Song, Zhaoyuan Gong, Qianzi Che, Jing Guo, Lin Chen, Haili Zhang, Huizhen Li, Ning Liang, Guozhen Zhao, Yanping Wang, Nannan Shi, Bin Liu

“…Asia and Europe documented the most comprehensive symptom profiles, with Asia reporting lower early dyspnea rates (29%, 95% CI 18%‐40%) and Europe exhibiting more complex multisystem involvement during long-term follow-up. …”
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Multiple bursts of speciation in Madagascar’s endangered lemurs by Kathryn M. Everson, Luca Pozzi, Meredith A. Barrett, Mary E. Blair, Mariah E. Donohue, Peter M. Kappeler, Andrew C. Kitchener, Alan R. Lemmon, Emily Moriarty Lemmon, Carlos J. Pavón-Vázquez, Ute Radespiel, Blanchard Randrianambinina, Rodin M. Rasoloarison, Solofonirina Rasoloharijaona, Christian Roos, Jordi Salmona, Anne D. Yoder, Rosana Zenil-Ferguson, Dietmar Zinner, David W. Weisrock

“…Our analyses reveal multiple bursts of diversification (without subsequent declines) that explain much of today’s lemur diversity. We also find higher rates of speciation in Madagascar’s lemurs compared to lorisiforms, and we demonstrate that the lemur clades with high diversification rates also have high rates of genomic introgression. …”
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National trends in emergency conditions through the Omicron COVID‐19 wave in commercial and Medicare Advantage enrollees by Maria A. Stevens, Edward R. Melnick, Samuel T. Savitz, Molly Moore Jeffery, Bidisha Nath, Alexander T. Janke

“…Cardiac arrest/severe arrhythmia visit rates increased 4.0% (95% CI, 0.2%–8.0%) during Waves 2−3; myocardial infarction rates increased 4.9% (95% CI, 2.1%–7.8%) during Waves 2−3. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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Exposure-Sensitivity-Adaptability (ESA) framework based evaluation and characteristics analysis of urban disasters vulnerability in China by Rui Zhang, Anli Jiang, Linlin Jiang

“…Analysis reveals distinct spatial patterns: eastern cities show 35% lower vulnerability scores compared to central and western regions, forming a clear vulnerability gradient. …”
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A test of ecophysiological theories on tropical forest functional traits along a VPD gradient by Huanyuan Zhang-Zheng, Yadvinder Malhi, Kasia Ziemińska, Agne Gvozdevaite, Theresa Peprah, Mickey Boakye, Stephen Adu-Bredu, Jesús Aguirre-Gutiérrez, Sam Moore, David Sandoval, Minxue Tang, Iain Colin Prentice, Imma Oliveras Menor

“…These patterns were associated with greater deciduousness, increased respiration rates and enhanced water transport at drier sites. …”
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Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan by Francesco Poggi, Olga Nardini, Simone Fiaschi, Roberto Montalti, Emanuele Intrieri, Federico Raspini

“…The employment of these two techniques enables the acquisition of insights into the distinctive characteristics and dynamics of the landslide, including the displacement rates up to 246 mm/year in the horizontal component; the precise mapping of landslide boundaries and the identification of distinct sectors with varying deformation patterns; and an estimation of the volume involved within the landslide, which is approximately of 1 billion m³.…”
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Characterizing Holocene sediments for assessing coastal-deltaic subsidence: the role of cone penetration tests and geomechanics by Carla Buffardi, Philip S. J. Minderhoud, Philip S. J. Minderhoud, Philip S. J. Minderhoud, Alessandro Mandolini, Daniela Ruberti

“…These variable characteristics underlie, and in part explain, the spatial patterns in observed subsidence rates. The increased geomechanical insights advance our understanding of the spatio-temporal consolidation of the Holocene sedimentary sequence and its various depositional facies beyond standard lithological geotechnical characterization. …”
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Consensus guidelines for the management of intracranial ependymoma for low- and middle-income countries by Ahsan Ali Khan, Muhammad Usman Khalid, Mohammad Hamza Bajwa, Izza Tahir, Shahier Paracha, Muhammad Shakir, Bilal Mazhar Qureshi, Naureen Mushtaq, Ahmed Gilani, Pakistan Brain Tumour Consortium: (Authors list at the end of the supplement), Syed Ather Enam.

“…Acknowledging the distinctepidemiological patterns of ependymomas, notably theirhigher incidence in paediatric patients, and variablesurvival rates, these guidelines emphasize tailoredmanagement approaches for different age groups. …”
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Comorbidity health pathways in heart failure patients: A sequences-of-regressions analysis using cross-sectional data from 10,575 patients in the Swedish Heart Failure Registry. by Claire A Lawson, Ivonne Solis-Trapala, Ulf Dahlstrom, Mamas Mamas, Tiny Jaarsma, Umesh T Kadam, Anna Stromberg

“…The following hypotheses were tested: (i) comorbidities are associated with more severe symptoms and functional limitations and subsequently worse patient-rated health in HF, and (ii) these patterns of association differ among selected comorbidities.…”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…Concurrently, variational mode decomposition (VMD) provides frequency-domain decomposition capability, while the gated recurrent unit (GRU) captures long-term dependencies. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

“…This study evaluates multiple ML models, including logistic regression, random forest, and LightGBM, alongside DL architectures such as ALBERT and Gated Recurrent Units (GRUs), for both binary and multi-class classification of mental health conditions. …”
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Relationship of psychoalgological status and results of neurosurgical treatment of patients with discogenic radiculopathy by V. I. Leonov, I. O. Kritskaya, D. V. Svistov, E. V. Litvinenko, T. V. Sergeeva, V. V. Flud, M. N. Kravtsov, S. D. Mirzametov, N. P. Alexeyeva, A. Yu. Shcherbuk, Yu. A. Shcherbuk

“…According to the long-term results of neurosurgical treatment, patients were divided into three groups: 1 – with a good result; 2 – patients with a number of preserved complaints, who rated the result of the operation as satisfactory; 3 – unsatisfactory outcome. …”
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Maternal and Clinical Outcomes of Placenta Accreta Spectrum: Insights from a Retrospective Study in Bahrain by Kareeza Selby Chacko, Reem Satam AlSubeaei, Soumya Sunil Nair, Nusrat Khalil Kazi, Rafiea Jeddy

“…Placenta accreta spectrum (PAS) refers to a group of abnormal placental attachments in which the placenta adheres too deeply to the uterine wall, with varying degrees of invasion classified as accreta, increta, or percreta. Increased rates of uterine surgeries, advanced maternal age, and cesarean deliveries have all contributed to an increase in the incidence of PAS. …”
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Microbial responses to antibiotics cryptically shift the direction of disease outcomes by Isabela Velasquez, Kyra Ricci, Eve Milusich, Bryon F. Tuthill, Karin Sauer, Obed Hernández-Gómez, Jessica Hua

“…Abstract Diseases are emerging at unprecedented rates, prompting global efforts to understand factors shaping disease outcomes. …”
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Integration of FEM-based permeation analysis and AI-based predictive models for improved chemical grout permeation assessment in heterogeneous soils by Khin Nyein Chan Kyaw, Kuo Chieh Chao, Shinya Inazumi

“…Results showed that even with 5.5 % low-permeability content, average fill rates of 94.5 % (FEM) and 96 % (AI) were achieved, with worst-case scenarios dropping to approximately 81 % and 83 %, respectively. …”
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Oral cancer in Libya and development of regional oral cancer registries: A review by E. BenNasir, M. El Mistiri, R. McGowan, R.V. Katz

“…The aims of this paper are three-fold: (1) to summarize the current epidemiological data on oral cancer in Libya as reported in the published literature and as compared to other national oral cancer rates in the region; (2) to present both the history of the early development, and future goals, of population-based oral cancer tumor registries in Libya as they partner with the more established regional and international population-based cancer tumor registries; and, (3) to offer recommendations that will likely be required in the near future if these nascent, population-based Libyan oral cancer registries are to establish themselves as on-going registries for describing the oral cancer disease patterns and risk factors in Libya as well as for prevention and treatment. …”
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Data-driven nutritional assessment of urban food landscapes: insights from Boston, London, and Dubai by Michele Tufano, Fábio Duarte, Martina Mazzarello, Javad Eshtiyagh, Carlo Ratti, Guido Camps

“…The analysis revealed significant patterns between urban food landscapes, socioeconomic features, and obesity rates. …”
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Improved Performance for Dye-Sensitized Solar Cells Using a Compact TiO2 Layer Grown by Sputtering by Hung-Chih Chang, Ming-Jenq Twu, Chun-Yao Hsu, Ray-Quen Hsu, Chin-Guo Kuo

“…The results show that when the Ar/O2/N2 flow rates are 36 : 18 : 9, the photo-induced decomposition of methylene blue and photo-induced hydrophilicity are enhanced. …”
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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…Conventional methods – like clustering, statistical thresholds, and classical time series analysis – often fail to account for the spatial-temporal dependencies inherent in these systems, leading to high false positive rates or missed complex anomalies. In this paper, we propose a novel anomaly detection approach that combines Temporal Graph Neural Networks (TGNN) with Autoencoders. …”
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