Automated Container Terminal Production Operation and Optimization via an AdaBoost-Based Digital Twin Framework by Yu Li, Daofang Chang, Yinping Gao, Ying Zou, Chunteng Bao

“…Second, we introduce a random forest and XGBoost to compare with AdaBoost to select the best algorithm to train and optimize the DT mechanism model. …”
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Presença ausente e ausência presente do Estado na produção do espaço para o turismo no Vale do Ribeira paulista by Carolina Todesco

“…Ribeira Valley Region, located in the southern State of Sao Paulo, has 20% of the remaining Atlantic Forest of Brazil and has the lowest human development indices of this State which has the highest density of technical-scientific-informational environment and capital. …”
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Computer analysis shows differences between mitochondrial miRNAs and other miRNAs by P. S. Vorozheykin, I. I. Titov

“…To identify the most pronounced characteristics of mitochondrial miRNAs that distinguish them from other miRNAs, we classified mitomiR sequences using the Random Forest algorithm. The analysis revealed, for the first time, a significant difference between mitomiRs and other microRNAs by the following criteria (in descending order of importance in the classification): mitomiRs are evolutionarily older (have a lower phylostratigraphic age index, PAI); have more targets and disease associations, including mitochondrial ones (twosided Fisher’s exact test, average p-values 1.82×10–89/1.13×10–96 for all mRNA/diseases and 6.01×10–22/1.09×10–9 for mitochondria, respectively); and are in the class of “circulating” miRNAs (average pvalue 1.20×10–56). …”
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HERPETOFAUNAL REMAINS (ANURA, CROCODYLIA, TESTUDINES, SQUAMATA) FROM THE LATE MIOCENE OF THE CREVILLENTE AREA (SE SPAIN): PALAEOBIOGEOGRAPHICAL AND PALAEOECOLOGICAL IMPLICATIONS by Rafael Marquina Blasco, DAVID MORALES-FLORES, ÁNGEL D. BARTOLOMÉ-BOMBÍN, PLINIO MONTOYA

“…At both localities, the surrounding landscape must have been dominated by open habitats with patches of forest/shrubland formations close to water bodies. …”
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Effect of mechanical debridement with and without adjunct antimicrobial photodynamic therapy for the treatment of peri-implant disease in obese patients: A systematic review and me... by Sultan Albeshri, Raed AlRowis

“…Various keywords were used in different combinations using Boolean operators. A forest plot was generated to visually present the results of the meta-analysis. …”
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Fault Diagnosis of Signal Equipment on the Lanzhou-Xinjiang High-Speed Railway Using Machine Learning for Natural Language Processing by Lei Shi, Yulin Zhu, Youpeng Zhang, Zhongji Su

“…This was compared and analyzed with the traditional Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbor (KNN) algorithms. …”
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Mudança no uso e cobertura da terra na bacia hidrográfica do rio Araguaia e seus reflexos nos recursos hídricos, o trecho médio do rio Araguaia em Goiás by Maximiliano Bayer, Pâmela Camila Assis, Tainá Medeiros Suizu, Matheus Cardoso Gomes

“…For the area of the Araguaia river basin in Goiás, the analysis of land use and occupation processes showed a decrease of 33,8% for forest formation, 48,9% for savanna formation and an increase of 51,50% of the areas pasture and 510,6% of the annual and perennial crop areas. …”
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Énoncés capacitifs et constructions à sujet locatif : quel alignement syntaxe-sémantique ? by Christelle Lacassain, Caroline Marty

“…The reign of Charles II saw the end of the great Forest courts) constructions – which are comparable in more than one way. …”
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Combining machine learning and single-cell sequencing to identify key immune genes in sepsis by Hao Wang, Linghan Len, Li Hu, Yingchun Hu

“…Next, a Biological association network was constructed, and five key hub genes (CD4, HLA-DOB, HLA-DRB1, HLA-DRA, AHNAK) were identified using a combination of three topological analysis algorithms (MCC, Closeness, and MNC) and four machine learning algorithms (Random Forest, LASSO regression, SVM, and XGBoost). immune cell distribution showed that the key genes correlated with multiple immune cell infiltrations. …”
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Evaluation of the Anthropogenic Impacts of Yusufeli Dam in terms of Landscape Planning by Belgin Yılmam, Hilal Turgut

“…After the completion of the Yusufeli Dam, 612ha forest and 62ha agricultural fields will be destroyed. …”
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Characterizing Stream Condition with Benthic Macroinvertebrates in Southeastern Minnesota, USA: Agriculture, Channelization, and Karst Geology Impact Lotic Habitats and Communities by Neal D. Mundahl

“…BIBI ratings improved from poor and very poor at headwater sites in channelized stream sections draining agricultural lands to fair to good to excellent in downstream sections flowing through natural channels in largely forested lands. Fifty percent of samples rated stream sites as poor or very poor. …”
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Extraction of Oil from Azadirachta indica and Moringa stenopetala Seeds and Evaluation of its Physicochemical Properties by Degnechew Genene

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Daily reference evapotranspiration prediction using empirical and data-driven approaches: A case study of Adana plain by Semin Topaloğlu Paksoy, Deniz Levent Koç

“…The objective of this research was to examine the effectiveness of five different data-driven techniques, including artificial neural networks "multilayer perceptron" (ANN), gene expression programming (GEP), random forest (RF), support vector machine "radial basis function" (SVM), and multiple linear regression (MLR) to model the daily ET0. …”
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Downscaling of ERA5 reanalysis land surface temperature based on attention mechanism and Google Earth Engine by Shiyu Li, Hong Wan, Qun Yu, Xinyuan Wang

“…Finally, the downscaling accuracy of the network was evaluated through simulated data experiments and real data experiments and compared with the Random Forest (RF) method. The results show that the network proposed in this study outperforms the RF method, with RMSE reduced by approximately 32–51%. …”
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Enlightening the black and white: species delimitation and UNITE species hypothesis testing in the Russula albonigra species complex by Ruben De Lange, Slavomír Adamčík, Katarína Adamčíkova, Pieter Asselman, Jan Borovička, Lynn Delgat, Felix Hampe, Annemieke Verbeken

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Evaluation of hygienic food handling practices and associated factors among food handlers in the Amhara region, Ethiopia: a systematic review and meta-analysis by Lamenew Fenta, Kebadu Tadesse

“…Eyeball testing using forest plots, Cochrane Q test statistics and I² had been used to identify and measure heterogeneity. …”
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Etude démographique du magot (Macaca sylvanus) dans le site touristique des cascades d’Ouzoud (Maroc) by Abderrazak El Alami, Abderrahman Chait

“…This species represents an excellent biological indicator of the forest quality and the Barbary macaque demography can monitor the decline of this species and the degradation of its natural habitats. …”
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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

“…Our novel framework integrates ensemble resampling methods with advanced feature selection techniques, addressing data imbalance and enhancing predictive accuracy. The balanced random forest classifier, optimized using the genetic algorithm for feature selection, achieved an area under the receiver operating characteristic curve (AUC) of 0.8708 and an accuracy of 82.67 % on the internal test set, with an accuracy of 86.36 % on the external validation set. …”
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Impactos atmosféricos das transformações territoriais e do crescimento do agronegócio na Amazônia matogrossense by Andrea Cavicchioli, Ericka Pardini Morrone, Rodrigo Marques, Adalgiza Fornaro

“…The State of Mato Grosso, in the west-central part of Brazil, has undergone over the last two decades a severe process of land transformation with the opening of large agricultural areas to the detriment of tropical forest and savannahs. This deforestation process is largely associated to the production of soybeans: in 2005, the soybean-cultivated area surpassed 6.1 mi hectares with an overall production of 17.76 mi tons. …”
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Implementasi Sensor Polar H10 dan Raspberry Pi dalam Pemantauan dan Klasifikasi Detak Jantung Beberapa Individu Secara Simultan dengan Pendekatan Machine Learning  by eko sakti pramukantoro, Kasyful Amron, Viera Wardhani, Putri Annisa Kamila

“…Data tersebut kemudian diprediksi menggunakan model machine learning berbasis random forest yang berjalan pada Raspberry Pi untuk prediksi 5 jenis detak jantung. …”
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