Extraction of Significant Wave Height from Spreading First-Order Bragg Peaks of Shipborne High-Frequency Surface Wave Radar with a Single Antenna by Xinbo Zhang, Junhao Xie, Guowei Yao, Chenghui Cao

“…Simulations and field experiments validate the feasibility and accuracy of the method across various scenarios, with a detection range of up to 120 km without auxiliary measurements. …”
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Hyperion Image Analysis Depicts a Preliminary Landscape of Tumor Immune Microenvironment in OSCC with Lymph Node Metastasis by Shang Xie, Xin-Yuan Zhang, Xiao-Feng Shan, Vicky Yau, Jian-Yun Zhang, Wei Wang, Yong-Pan Yan, Zhi-Gang Cai

“…This study is aimed at utilizing the Hyperion imaging system to depict a preliminary landscape of the tumor immune microenvironment in OSCC with lymph node metastasis. Methods. We collected neoplasm samples from OSCC patients. …”
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The impact of land use/land cover change on ecosystem services in Golestan province by Hamidreza Kamyab, Nasim Shabani

“…We also used sensitivity analysis to explore the robustness of results by 50% adjustment of value coefficients. Material and methods: Golestan Province is one of the 31 provinces of Iran, located in the south of the Caspian Sea. …”
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Application of deep learning in cloud cover prediction using geostationary satellite images by Yeonjin Lee, Seyun Min, Jihyun Yoon, Jongsung Ha, Seungtaek Jeong, Seonghyun Ryu, Myoung-Hwan Ahn

“…Traditional methods for cloud cover prediction encounter significant limitations in capturing complete spatial and temporal cloud dynamics. …”
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Research on Multiscale Atmospheric Chaos Based on Infrared Remote-Sensing and Reanalysis Data by Zhong Wang, Shengli Sun, Wenjun Xu, Rui Chen, Yijun Ma, Gaorui Liu

“…Among quantitative methods, the Wolf method is used to calculate the Largest Lyapunov Exponents, while the G–P method is used to calculate the correlation dimensions. …”
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The microbial landscape action on development destructive erysipelas forms by L. A. Vasilevskaya

“…Of our studies indicate that the microflora of the primary cells in destructive forms of the erysipelas changed both quantitatively and qualitatively. Detected microbial pathogens in bacteriological studies of soft tissue exudates allowed installing criteria for forecasting the development of purulent complications. …”
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An LJDRNN-based efficient energy intensity prediction in carbon fiber composite material manufacturing process by Rangaswamy Nikhil, Karthikeyan A G, Prabhu Loganathan, Tabrej Khan, Tamer A Sebaey

“…By enabling more precise energy intensity forecasting, the proposed method supports producers in optimizing their manufacturing processes, reducing energy costs, and aligning with sustainable production goals, ultimately driving greater operational efficiency and competitiveness in the CF industry.…”
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Bacterial Infections Transmitted by Ticks in Barnaul: Epidemiological and Epizootological Situation, Diagnostic Problems by T. A. Chekanova, A V. Rakov, K. Petremgvdlishvili, A. V. Timonin, N. V. Lukyanenko, T. V. Safyanova, S. V. Shirokostup, N. Ya. Lukyanenko, U. V. Kalinina, I. G. Pashchenko

“…The difficulty of diagnostic of tick-borne rickettsiosis without rash is aggravated by the shortage of reagent kits, primarily for the detection of specific antibodies. The landscape confinement of Dermacentor and Ixodes ticks should take into account when organizing long-term stationary observation sites for monitoring and forecasting the epidemiological and epizootological situation. …”
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Content of macro- and microelements in the plants of Artemisia annua L., A. ludoviciana Nutt. and A. austriaca L. by О. А. Корабльова, Д. Б. Рахметов, M. І. Шанайда, O. M. Вергун, Л. В. Свиденко, В. І. Войцехівський

“…., A. ludoviciana Nutt. and A. austriaca L. Methods. Determination of the elemental composition of plant material was carried out by the X-ray fluorescence method. …”
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BRCA1 promoter methylation predicts PARPi response in ovarian cancer: insights from the KOMET study by Léna Nougarede, Florence Hazane-Puch, Florence de Fraipont, Emmanuelle Jacquet, Marie Bidart

“…Our study aimed to determine the clinical relevance of BRCA1 promoter methylation for patients with ovarian carcinoma. Method The KOMET (Ovarian Cancer Methylation) study is a single-center retrospective study involving 88 ovarian cancer patients treated between January 2021 and July 2024. …”
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Trends and advances in Leptospira, a bibliometric analysis by Wei Wang, Wei Wang, Wei Wang, Yamin Gao, Yamin Gao, Yamin Gao, Jianyu Ji, Jianyu Ji, Jianyu Ji, Zhai Huang, Zhai Huang, Bin Xiong, Bin Xiong, Shulin Xiang, Shulin Xiang

“…This study applies bibliometric analysis to generate a visual knowledge map, identifying research hotspots and forecasting future trends in leptospirosis investigations.MethodsData were extracted from the Web of Science Core Collection (WOSCC), encompassing all publications up to May 1, 2024. …”
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Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“…This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. …”
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Early Fault Diagnosis and Prediction of Marine Large-Capacity Batteries Based on Real Data by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Qijia Song, Yuelin Chen, Lin Liu, Shoude Jiang

“…Furthermore, the fault prediction method based on the iTransformer model is introduced to forecast variations in battery cluster voltages. …”
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The Application of Artificial Digital Models in X-Ray Computed Tomography (CT) of the Core in Solving the Problem of Binarization of the Void Space of Reservoir Rocks by O. A. Melkishev, Y. V. Savitsky, S. V. Galkin

“…These phantoms were then converted into tomograms, allowing us to determine statistical characteristics of the values for X-ray densities of the samples at the reconstruction stage.Based on the statistical analysis of the X-ray density distribution in the sample, we determined the boundary values that are most suitable for reliable void space detection. Using regression and correlation methods, we developed a model to estimate the optimal boundary value for X-ray density in void space allocation.We proposed an algorithm for determining and applying this value in the analysis of core X-ray CT data.This model was tested on real samples that were not used in the development of the forecast model. …”
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Year-round infectome profiling of acute febrile respiratory illness unveiled complex epidemiological dynamics postlifting of COVID-19 restrictions by Shisong Fang, Lin Zhu, Shaohui Bai, Weijian Tian, Yuanfei Pan, Shumiao Zhang, Rongjun Bi, Minqi Liang, Gengyan Luo, Xiaojing Chen, Minwu Peng, Hanlin Liu, Lu Xie, Runzi Zhang, Wudi Zhou, Shengze Zhang, Ting Xie, Haolu Zha, Chuming Luo, Xin Wang, Ying Sun, Hui Liu, Min Jiang, Weihua Wu, Xuan Zou, Yaoqing Chen, Jianhui Yuan, Ying Jiang, Nan Wu, Mang Shi, Yuelong Shu, Huanle Luo

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Scenario-based validation and prediction of land use changes in Birjand watershed in 1404 by Elham Yusefiroobiat, Fatemeh Jahanishakib

“…Introduction: Nowadays, detection and modeling land use changes using satellite imagery is a useful tool for understanding future environmental changes associated with human activities. …”
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Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework by Shaik Khasim Saheb, B. Narayanan, T.V. Narayana Rao

“…The performance metrics like accuracy, precision, fscore and sensitivity are analyzing the proposed method performance. The proposed SC2SSP approach attains 3.101% and 7.12% higher accuracy; 24.13% and 13.04% higher precision compared with existing methods, like the Detection of COVID-19 from Chest X-ray Images Using Convolutional Neural Networks (Resnet50), Deep learning for automated recognition of covid-19 from chest X-ray images (VGGNet), respectively. …”
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The emerging role of circulating tumor DNA in brain tumor research by Amir Modarresi Chahardehi, Niki Faraji, Nikoo Emtiazi, Reza Nasiri, Maryam Daghagheleh, Helia Mohammadaein, Fatemeh Masoudi, Kimia Ghazi Vakili, Aylin Sefidmouy Azar, Hossein Fatemian, Hossein Motedayyen, Reza Arefnezhad, Fatemeh Rezaei-Tazangi, Zahra Niknam, Marziye Ranjbar Tavakoli

“…Hence, advancements in next-generation sequencing (NGS) and digital PCR have enhanced the sensitivity of ctDNA detection, rendering it a feasible method for monitoring tumor dynamics and evaluating therapy responses. …”
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Advancing pancreatic cancer management: the role of artificial intelligence in diagnosis and therapy by Dilber Uzun Ozsahin, Natacha Usanase, Ilker Ozsahin

“…Main body Artificial intelligence (AI) technology enables rapid detection of high-risk groups for pancreatic cancer using various techniques such as medical imaging, pathological examination, biomarkers, and other methods, facilitating early detection of pancreatic cancer. …”
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A high-resolution divergence and vorticity dataset in Beijing derived from radar wind profiler mesonet measurements by X. Guo, J. Guo, D. Meng, Y. Sun, Z. Zhang, Z. Zhang, H. Xu, L. Zeng, J. Chen, N. Li, T. Chen

“…This paper aims to produce a temporally continuous horizontal divergence and vertical vorticity dataset at the vertical resolution of 120 m, which is derived from horizontal winds measured by the RWP mesonet in Beijing using the triangle method. This dataset is generated at intervals of 6 min for the whole year of 2023, covering the altitude range of 0.51–4.11 km. …”
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