Predator occupancy rates in a thinned ponderosa pine forest, Arizona: A pilot study by Kevin J. Barrett, Elizabeth L. Kalies, Carol L. Chambers

“…We sampled 33 sites for 2 weeks each in order to detect presence of predators, and estimated occupancy using occupancy models and multimodel inference. …”
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Occurrence and Diversity of Fungi and Their Mycotoxin Production in Common Edible and Medicinal Substances from China by Ling Chen, Junhui Wu, Shuhong Zhang, Xinqi Liu, Meiping Zhao, Weipeng Guo, Jumei Zhang, Wei Chen, Zhenjie Liu, Meiqing Deng, Qingping Wu

“…One <i>Nelumbinis</i> semen sample contained 10.75 μg·kg⁻¹ AFB₁, and one <i>Raisin tree</i> semen sample contained 484.30 μg·kg⁻¹ ZEN, which exceeded regulatory limits in Europe and China. …”
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Assessing the effect of model specification and prior sensitivity on Bayesian tests of temporal signal. by John H Tay, Arthur Kocher, Sebastian Duchene

“…Using microbial molecular sequence data sets and simulation experiments, we assess the impact of the tree prior and its hyperparameters on the accuracy of temporal signal detection. …”
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Advancing Stem Volume Estimation Using Multi-Platform LiDAR and Taper Model Integration for Precision Forestry by Yongkyu Lee, Jungsoo Lee

“…At present, stem volume is commonly estimated indirectly by constructing a taper model that utilizes sampling, diameter at breast height (DBH), and tree height. …”
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Remote sensing for monitoring and assessment of invasive herbaceous plants: the case of Oenothera drummondii in coastal ecosystems by Pablo J. Hidalgo, Nuria Montiel, Mónica Ortega-Moreno, Rubén Fernández de Villarán, Cristina Pérez-Carral

“…The subsequent application of the classification tree obtained across the entire study area resulted in the detection of O. drummondii with an accuracy rate of 83%, demonstrating that this UAV-based technique enables the identification of exotic invasive herbaceous species. …”
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Identification of Regional Lymph Node Involvement of Colorectal Cancer by Serum SELDI Proteomic Patterns by Nai-Jun Fan, Chun-Fang Gao, Xiu-Li Wang

“…Proteomic spectra of serum samples from 70 node-positive CRC patients and 75 age- and gender-matched node-negative CRC patients were employed as a training set, and a classification tree was generated by using Biomarker Pattern Software package. …”
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Position Normalization of Propellant Grain Point Clouds by Junchao Wang, Fengnian Tian, Renfu Li, Zhihui Li, Bin Zhang, Xuelong Si

“…In the coarse normalization stage, a layer-by-layer feature points detection scheme based on k-dimensional trees (KD-tree) and k-means clustering (k-means) is designed to extract feature points from the propellant grain point cloud. …”
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<p><strong>Molecular identification of <em>Haemaphysalis</em> <em>sulcata</em> (Acari: Ixodidae) larval stages collected using the Berlese funnel in Northern Iran</strong></p> by Milad Davari, Masoud Hakimitabar, Asadollah Hosseini Chegeni

“… Molecular detection techniques based on conventional PCR and sequencing of the partial genome of living organisms are considered an important tool for identification. …”
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Study on Class Imbalance in Land Use Classification for Soil Erosion in Dry–Hot Valley Regions by Yuzhuang Deng, Guokun Chen, Bohui Tang, Xingwu Duan, Lijun Zuo, Haijuan Zhao

“…The inherent spatial heterogeneity of land types often leads to a class imbalance in remote sensing-based classification, reducing the accuracy of minority class detection. Consequently, current land use datasets are often inadequate for the specific needs of soil erosion studies. …”
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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

“…For the Chi-Square and ReliefF methods, the maximum classification accuracy obtained is 86.7% and 85.6% for the fine and medium trees. For bagged tree model, a maximum accuracy of 86.1% was obtained with Kruskal-Wallis method. …”
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The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses by Liu Jun, Hongguo Li, Yu Mao, Lan Hu, Dan Wu

“…IntroductionSpeech impediments (SIs) are increasingly prevalent among middle-aged and older adults, raising concerns within public health. Early detection of potential SI in this demographic is critical. …”
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Data Mining Approaches in Predicting Entrepreneurial Intentions Based on Internet Marketing Applications by Milan Krivokuća, Mihalj Bakator, Dragan Ćoćkalo, Marijana Vidas-Bubanja, Vesna Makitan, Luka Djordjević, Borivoj Novaković, Stefan Ugrinov

“…Afterward, classifier decision trees QUEST (quick, unbiased, efficient, statistical tree), and CHAID (chi-squared automatic interaction detection) were used. …”
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Multi-model machine learning framework for lung cancer risk prediction: A comparative analysis of nine classifiers with hybrid and ensemble approaches using behavioral and hematolo... by Vinod Kumar, Chander prabha, Deepali Gupta, Sapna Juneja, Swati Kumari, Ali Nauman

“…LC continues to be the most prevalent cause of cancer deaths worldwide, which calls for sophisticated detection strategies. The present study investigates 34 demographic, behavioral, and hematological risk factors based on a sample of 2,000 patient data records. …”
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Explaining the Earnings Management Prediction Model Using the Hybrid of Machine Learning Methods by Hassan Hassani, Esfandiar Malekian Kallehbasti, Yahya Kamyabi

“…In this context, this study attempts to present prediction tools that aid in detecting earnings management activities. For this purpose, six machine learning methods have been discussed to predict earnings management.Methods & MaterialA  sample of  180  companies listed on the  Tehran  Stock  Exchange during the period  2010-2021  was selected for testing hypotheses. …”
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ForestSemantic: a dataset for semantic learning of forest from close-range sensing by Xinlian Liang, Hanwen Qi, Xuejie Deng, Jianchang Chen, Shangshu Cai, Qingjun Zhang, Yunsheng Wang, Antero Kukko, Juha Hyyppä

“…Thus, the dataset supports both instance and semantic studies, such as objects detection and segmentation and classification at both tree- and plot-levels. …”
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Stroke Lesion Prediction by Bille-Viper-Segmentation with Tandem-MU-net Model by Beevi Fathima, N Santhi Dr, N Ramasamy Dr

“…This novel method effectively samples pixel data and analyzes fogging phases related to stroke lesions by utilizing a Deep Luxe Gauging Tree. …”
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An Ensemble Classification Method Based on a Stacking Strategy for Ship Type Classification with AIS Data by Lei Deng, Shichen Yang, Limin Jia, Danyang Geng

“…A stacking strategy is adopted for the classification, integrating multiple tree structure-based classifiers to improve classification performance. …”
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Isolation and molecular characterization of a Xylella fastidiosa subsp. multiplex strain from almond (Prunus dulcis) in Apulia, Southern Italy by Vito MONTILON, Oriana POTERE, Leonardo SUSCA, Francesco MANNERUCCI, Franco NIGRO, Stefania POLLASTRO, Giuliana LOCONSOLE, Francesco PALMISANO, Claudio ZAZA, Marco CANTATORE, Francesco FARETRA

“…Given the potential risk posed by this pathogen to cultivated and ornamental plants, mandatory annual surveys and laboratory testing are required in Member States to early detect outbreaks. In the course of surveys carried out during early spring 2024 in the Apulia region (Southern Italy), X. fastidiosa subsp. multiplex was identified using quantitative real-time Polymerase Chain Reaction (qPCR), in a non-symptomatic sample from an almond tree (Prunus dulcis) in an orchard located in Santeramo in Colle, in Bari province. …”
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A lightweight framework to secure IoT devices with limited resources in cloud environments by Vivek Kumar Pandey, Dinesh Sahu, Shiv Prakash, Rajkumar Singh Rathore, Pratibha Dixit, Iryna Hunko

“…This paper proposes a lightweight decision tree-based intrusion detection framework suitable for real-time anomaly detection in a resource-constrained IoT environment. …”
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The Defectiveness of Spruce Stands in the Northern Taiga Zone of the Arkhangelsk Region by Sergey V. Koptev, Sergey A. Vaskin

“…To determine the age of the trees in the sample plot, core samples have been taken from the root collar. …”
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