New evidence on the Late Bronze – Early Iron Age human nutrition in the Crimea (northern Pontic Region) based on the stable isotope analysis and radiocarbon dating by Kulkova Marianna A., Kashuba Maya N., Kulkov Aleksandr M., Kozhukhovskaya Yuliya V., Tikhomirov Vitaliy A., Streltsov Mihail A.

“…One of the controversial questions is the problem of transition from sedentary forms of agriculture and cattle-breeding to mobile cattle-breeding among ancient communities in the Eurasian steppe and forest-steppe. On the base of data obtained various groups of people were identified, which are characterized by different nutritional systems, primarily related to the specifics of their economic activities. …”
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Study of bats in the upper Neretva River valley (Bosnia and Herzegovina) by Maja Zagmajster, Vojo Milanović, Behare Rexhepi, Ester Premate, Špela Borko, Anton Vorauer

“… The upper Neretva River valley with river and tributaries, preserved forests, natural caves and buildings represents a very interesting area for bats. …”
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Rabies re-emergence after long-term disease freedom (Amur Oblast, Russia) by A. D. Botvinkin, I. D. Zarva, I. V. Meltsоv, S. A. Chupin, E. M. Poleshchuk, N. G. Zinyakov, S. V. Samokhvalov, I. V. Solovey, N. V. Yakovleva, G. N. Sidorov, I. A. Boyko, V. G. Yudin, E. I. Andaev, A. Ye. Metlin

“…After 2018, the epizootic spread within the forest-steppe landscapes of the Zeya-Bureya Plain, where human and animal rabies cases had been earlier reported (until 1972). …”
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New records of the golden jackal (Canis aureus L.) in the upper Soča valley, Slovenia by Miha Mihelič, Miha Krofel

“…We also reviewed the database of the reported jackal depredations on livestock at the Bovec Forest Service. In total, we conducted 31 interviews and gathered information on 100 records of jackal presence from 2009 to 2012. …”
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Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation by Xiaoming Zhang, Lean Yu, Hang Yin

“…The experimental results demonstrated that the proposed domain-adaptation-based multistage ensemble learning paradigm is superior to principal component analysis, joint distribution adaptation, random forest, and other ensemble and transfer learning methods. …”
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Molecular Signatures of Humic Acids from Different Sources as Revealed by Ultrahigh Resolution Mass Spectrometry by Shuai Qin, Chengbin Xu, Yingzi Xu, Yingchen Bai, Fei Guo

“…Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) has performed molecular-level analysis of two standard HAs from the Suwannee River (SRHA) and leonardite (LEHA) and HA from Jiufeng forest in Beijing (JFHA), which is impossible for other conventional instruments. …”
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Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders by Souhaila Khalfallah, William Puech, Mehdi Tlija, Kais Bouallegue

“…Hence, our findings show impressive accuracy, with the random forest model achieving 99.85% accuracy in classifying autism vs. healthy subjects and 100% accuracy in distinguishing healthy individuals from those with dementia using Support Vector Machines (SVM). …”
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The Developing Progress of Australian Cellular Agriculture in 2023—2024 by TAN Hong-zhuo, FANG Zhong-xiang, YI Cui-ping

“…In this paper,we have explained why developing cellular agriculture is important from 6 aspects: food safety, reduced forest area, preventing biodiversity loss, mitigating climate change, improving public health and promoting animal welfare. …”
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A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities by José Luis Uc Castillo, Ana Elizabeth Marín Celestino, Diego Armando Martínez Cruz, José Tuxpan Vargas, José Alfredo Ramos Leal, Janete Morán Ramírez

“…It observed that Artificial Neural Networks (ANN) models were preferred, probably due to their capability to learn and model non-linear and complex relationships in addition to other popular models such as Random Forest (RF) and Support Vector Machines (SVM). It identified that the selection and application of the algorithms rely on the study objective and the data patterns. …”
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Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries by Sadiqa Jafari, Jisoo Kim, Wonil Choi, Yung-Cheol Byun

“…In order to improve the accuracy of our predictions, we combined these models into a stacked ensemble using a Random Forest (RF) meta-model. This resulted in an <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> value of 0.987, MAE of 0.02559, MSE of 0.0013, and RMSE of 0.00624. …”
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Evaluation of the diagnostic efficiency of fluorescence in situ hybridization for pulmonary tuberculosis: a systematic review and meta-analysis by Yu-Qi Hu, Yu-Qi Hu, Kang Liu, Kang Liu, Le-Qing Lai, Le-Qing Lai, Yi-Ru He, Yi-Ru He, Li-Ping Hong, Li-Ping Hong, Chu-Qian Jiang, Chu-Qian Jiang, Si-Min Liu, Si-Min Liu, Ming-Zhu Cao

“…We used Meta-DiSc software to create forest plots.ResultsThe search yielded 7 studies, involving 1,224 sputum samples that could be included in our meta-analysis. …”
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Enhancing Sarcopenia Prediction Through an Ensemble Learning Approach: Addressing Class Imbalance for Improved Clinical Diagnosis by Dilmurod Turimov, Wooseong Kim

“…Several foundational models were employed, including support vector machine, random forest, neural network, logistic regression, and decision tree. …”
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Long Time Series Spatiotemporal Variations in NPP Based on the CASA Model in the Eco-Urban Agglomeration Around Poyang Lake, China by Tianmeng Du, Fei Yang, Jun Li, Chengye Zhang, Kuankuan Cui, Junxi Zheng

“…Scenic areas showed high forest cover and vigorous NPP changes, highlighting the need for targeted urban ecological management to enhance green development. …”
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Integration of local knowledge systems and decision on land use allocation among rural households in South Africa by Muhammad, Mubbin, Lobina G, Palamuleni, Tabukeli, Musigi Ruhiiga, Syed, Atif Bokhar

“…A more multifaceted model of land-use allocation occurs on stripping slopes, hills, and foot slopes, which are difficult to access and are covered by forests and scrubland. The study detected a strong linkage between land-use patterns and environmental knowledge. …”
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Analysis of Power Outages in Kabale Town: A Case Study of 33 KV Mbarara North-Kabale West Feeder. by Atibuni, Yofat

“…Environmental factors further exacerbated these problems, with tree cutting in Kyobugombe and Ndija, forested areas in Maziba, deteriorating poles in Katinda, and frequent lightning in Rubaya causing line faults and prolonged outages. …”
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Improved representation of laminar and turbulent sheet flow in subglacial drainage models by Tim Hill, Gwenn Elizabeth Flowers, Matthew James Hoffman, Derek Bingham, Mauro Angelo Werder

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Modeling Impact of Land Use Dynamics on Hydrology and Sedimentation of Megech Dam Watershed, Ethiopia by Abebe Tarko Assfaw

“…Whereas the grassland area has decreased from 11.42% to 5.33%, plantation forest from 1.84% to 0.9%, and bareland from 3.58% to 2.56%. …”
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Conspectus of the genus <i>Juniperus</i> L. growing in Kazakhstan by M. M. Yermagambetova, S. I. Abugalieva, Ye. K. Turuspekov, Sh. S. Almerekova

“…Besides, the continuation of comprehensive botanical and molecular genetic studies on junipers will help to examine and preserve the genetic diversity of the species and conserve forest bioresources.…”
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Molecular detection of piroplasms, Anaplasma, and Ehrlichia species in Kazakhstan by Weixin Zeng, Zhumanov Kairat, Madina Awulibieer, Sansyzbay Abylay, Khizat Serik, Meihua Yang, Yuanzhi Wang, Wurelihazi Hazihan

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Fisher Discriminant Analysis for Extracting Interpretable Phenological Information From Multivariate Time Series Data by Conor T. Doherty, Meagan S. Mauter

“…We also compare FDA (which is linear) to nonlinear planting date estimation models based on curve-fitting and random forest (RF) estimators. We find that multivariate FDA models significantly improve on univariate curve-fitting and have comparable performance when using the same univariate inputs despite the linearity of FDA. …”
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