Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

“…Artificial intelligence (AI) tools, such as machine learning algorithms, can optimize irrigation, increase yields, save water, and properly estimate sugarcane production. …”
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Proposing a New Classification for Managing Prostaglandin-Induced Enophthalmos in Glaucoma Patients by Ferraro V, Gaeta A, Barone G, Confalonieri F, Tredici C, Vinciguerra P, Di Maria A

“…The proposed therapeutic algorithm stratifies treatment: mild cases benefit from conservative management or fillers, moderate cases from calcium hydroxyapatite (CAHY) injections, and severe cases from combined CAHY and autologous fat grafting.Conclusion: A lack of a standardized grading system hinders consensus on management of PAPS. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…Also, the presented TATPat-based EFE model is a good model for explainable artificial intelligence (XAI) since TTPat-based EFE is cooperating by the DLob.…”
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Transceiver Design for Full-Duplex UAV Based Zero-Padded OFDM System With Physical Layer Security by Joarder Jafor Sadique, Shaikh Enayet Ullah, Md. Rabiul Islam, Raad Raad, Abbas Z. Kouzani, M. A. Parvez Mahmud

“…In this proposed system, intertwining logistic map (ILM)-cosine transform aided encryption algorithm combined with artificial noise enhancing physical layer security (PLS) is introduced. …”
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Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020 by Luis Gabriel Cuervo, Carmen Juliana Villamizar, Daniel Cuervo, Pablo Zapata, Maria B. Ospina, Sara Marcela Valencia, Alfredo Polo, Ángela Suárez, Maria O. Bula, J. Jaime Miranda, Gynna Millan, Diana Elizabeth Cuervo, Nancy J. Owens, Felipe Piquero, Janet Hatcher-Roberts, Gabriel Dario Paredes, María Fernanda Navarro, Ingrid Liliana Minotta, Carmen Palta, Eliana Martínez-Herrera, Ciro Jaramillo, on behalf of the AMORE Project Collaboration

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Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch... by Shaolin Chen, Ting Deng, Qing Yang, Jin Li, Juanyan Shen, Xu Luo, Juan Tang, Xulian Zhang, Jordan Tovera Salvador, Junliang Ma

“…Feature selection involved univariate analysis, collinearity analysis, nine ML algorithms, and expert consensus. Twelve independent ML models and 26 stacking ensemble models were developed. …”
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Validation of 12 years (2008–2019) of IASI-A CO with IAGOS aircraft observations by B. Barret, P. Loicq, E. Le Flochmoën, Y. Bennouna, J. Hadji-Lazaro, D. Hurtmans, B. Sauvage

“…<p>IASI-A, IASI-B and IASI-C (Infrared Atmospheric Sounding Interferometer) are nadir-looking thermal-infrared sensors which have monitored the atmospheric composition since 2008. Atmospheric carbon monoxide (CO) is retrieved from IASI radiances with two algorithms: the SOftware for a Fast Retrieval of IASI Data (SOFRID) and Fast Optimal Retrievals on Layers for IASI (FORLI). …”
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Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target by Hao Wu, Yuan Li, Yuxuan Jiang, Xinran Li, Shenglan Wang, Changle Zhao, Changle Zhao, Ximiao Yang, Baocheng Chang, Juhong Yang, Juhong Yang, Jianjun Qiao, Jianjun Qiao

“…Utilizing machine learning (ML) algorithms to predict obesity-associated gut microbiota and validating their efficacy with specific bacterial strains could significantly enhance obesity management strategies.MethodsWe leveraged gut microbiome data from 1,563 healthy individuals and 2,043 overweight patients sourced from the GMrepo database. …”
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An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Nan Yi, Shuangyang Mo, Yan Zhang, Qi Jiang, Yingwei Wang, Cheng Huang, Shanyu Qin, Haixing Jiang

“…A novel interpretable DL model and nomogram were developed and validated using EUS images, cooperating with machine learning algorithms. This approach demonstrates significant potential for enhancing the clinical applicability of EUS in predicting PNETs from pancreatic cancer, thereby offering valuable insights for future research and implementation.…”
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A multi-cohort validated OXPHOS signature predicts survival and immune profiles in grade II/III glioma patients by Jun Mou, Min Zhang, Fumin Qin, Yajie Cui, Keyou Xu, Baoye Pang, Xinyue Li, Wanyi Tan, Aiqi Yang, Yaxin Liu, Lingjun Shen, Yanting Liu, Kai Xu

“…Differentially expressed genes (DEGs) between subtypes were determined using the limma package. The immune cell composition and tumor microenvironment (TME) characteristics were assessed using ESTIMATE, MCPcounter, and CIBERSORT algorithms. …”
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Optimization of Gradient Catalyst Layers in PEMFCs Based on Neural Network Models by Guo-Rui Zhao, Wen-Zhen Fang, Zi-Hao Xuan, Wen-Quan Tao

“…The gradient structure can cooperate with the unevenly distributed reactants in CL to enhance the Pt utilization. …”
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Simulation of extreme flood events for risk assessment for flood control of a reservoir-lake-river system under spatially dependent uncertainties by Huili Wang, Bin Xu, Jianyun Zhang, Guoqing Wang, Ping-an Zhong, Xinman Qin, Xuesong Yang, Ran Mo, Jinshu Li, William W.-G. Yeh

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Stochastic <i>H</i>_∞ Filtering of the Attitude Quaternion by Daniel Choukroun, Lotan Cooper, Nadav Berman

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PRe-hospital Evaluation of Sensitive TrOponin (PRESTO) Study: multicentre prospective diagnostic accuracy study protocol by Richard Body, Aloysius Siriwardena, Abdulrhman Alghamdi, Edward Carlton, Kim Kirby, Mark Hann, Eloïse Cook, Alexander Thompson, Angela Foulkes, John Phillips, Jamie Cooper, Steve Bell, Andy Rosser

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Diagnostic accuracy of an app-guided, self-administered test for influenza among individuals presenting to general practice with influenza-like illness: study protocol by Nigel Stocks, Matthew Thompson, Barry Lutz, Mark Rieder, Monica Zigman Suchsland, Victoria Lyon, Monique Chilver, Philip Su, Shawna Cooper, Chunjong Park, Libby Rose Lavitt, Alex Mariakakis, Shwetak Patel, Chelsey Graham, Cynthia LeRouge

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Rethinking the Paradigm of Using Ps for Diagnosing Compartment Syndrome by Yasser Bouklouch, BSc, MPH, July Agel, MA, ATC, William T. Obremskey, MD, MPH, MMHC, Andrew H. Schmidt, MD, Kathy Liu, MB, ChB, Jerald R. Westberg, MPH, Matthew Zakariah, BSc, Eli Bunzel, MD, Greer Henry, MSc, Andres Fidel Diaz, MD, Thierry Bégué, MD, Mitchell Bernstein, MD, Edward J. Harvey, MDCM, MSc

“…The combinations were tested for predictive power using 2 machine learning algorithms. Results:. Pressure on palpation was the strongest clinical predictor of ACS while pain was the weakest. …”
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Exploration of ductility for refractory high entropy alloys via interpretive machine learning by Shaolong Zheng, Lingwei Yang, Liyang Fang, Chenran Xu, Guanglong Xu, Yifang Ouyang, Xiaoma Tao

“…While ductility can be engineered through alloying composition and processing condition optimization, this remains challenging due to the virtually infinite and vast unexplored compositional space. …”
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Anellovirus abundance as an indicator for viral metagenomic classifier utility in plasma samples by Gabriel Montenegro de Campos, Luan Gaspar Clemente, Alex Ranieri Jerônimo Lima, Eleonora Cella, Vagner Fonseca, João Paulo Bianchi Ximenez, Milton Yutaka Nishiyama, Enéas de Carvalho, Sandra Coccuzzo Sampaio, Marta Giovanetti, Maria Carolina Elias, Svetoslav Nanev Slavov

“…Interestingly, despite employing different algorithms and data types (protein-based vs. nucleotide-based), Kaiju and Kraken2 performed similarly. …”
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Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis by Qian Dai, Qian Dai, Hua Wang, Hua Wang, Fang Li, Fang Li, Runchun Huang, Runchun Huang, Chenjun Jiang, Chenjun Jiang, Liuya Yuan, Liuya Yuan, Yayun Wang, Yayun Wang, Xun Li, Xun Li

“…Notably, the deconvolution algorithm revealed different compositions of the tumor microenvironment, with a greater proportion of neutrophils observed in the high-risk group. ③ Finally, we conducted single-cell sequencing analysis and established a prostate cancer organoid model to confirm that TANs may exacerbate the TME in PCa via neutrophil trap formation, which is mediated by the PSMA1-NF-κB-HIF-1α signaling axis. …”
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Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned by Marketa Ciharova, Khadicha Amarti, Ward van Breda, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Xianhua Peng, Mieke Schulte, Mieke Schulte, Eirini Karyotaki, Eirini Karyotaki, Eirini Karyotaki, Pim Cuijpers, Pim Cuijpers, Pim Cuijpers, Heleen Riper, Heleen Riper

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