Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset by Omid Kohandel Gargari, Mobina Fathi, Shahryar Rajai Firouzabadi, Ida Mohammadi, Mohammad Hossein Mahmoudi, Mehran Sarmadi, Arman Shafiee

“…After careful selection of variables related to asthma, various ML algorithms including Support Vector Machine (SVM), Random Forest (RF), AdaBoost (ADA), XGBoost (XGB), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Multi-Layer Perceptron (MLP) were evaluated. …”
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Machine Learning Algorithm for Estimating Surface PM2.5 in Thailand by Pawan Gupta, Shanshan Zhan, Vikalp Mishra, Aekkapol Aekakkararungroj, Amanda Markert, Sarawut Paibong, Farrukh Chishtie

“…The integrated data then used to train and validate a supervised MLA’ random forest’ to estimate hourly and daily PM2.5 concentrations. …”
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Characterization and molecular biological identification of tick species in Nanjing city by Luyao SUN, Xuemin CHEN, Bingdong SONG, Yan ZHANG, Yanqun SUN, Yue MIN, Shougang ZHANG

“…The highest number of free-living ticks in different habitats was collected in suburban parks (50), followed by those around rural natural villages (47) and barren grasslands (33), and then in forest areas (2). Parasitic ticks were collected from goats, dogs, and hedgehogs, which accounted for 55.79% (776 ticks), 9.35% (130), and 34.87% (485) of the 1 391 parasitic ticks collected, respectively. …”
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ANALYSIS OF AIR QUALITY IN TELEORMAN BY MEANS OF BIOMONITORS-LICHENS by Cernat POPA

“…In carrying out the study, I ordered the selection of the area, namely Teleorman county - in 5 urban points, the sampling of lichen samples from the Troianul Forest - Teleorman, their transplantation in 5 measurement points on the bark of some trees at a height of 1.50 m and their application with natural resin and the exposure period is 30 days between October 11, 2021 and November 11, 2021. …”
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Use of building wastes and red mud as CO2 sorbent and catalyst for the production of hydrogen by Despina Vamvuka, Stavroula Panagiotidou, Agapi Orfanoudaki

“…Selected materials were forest and agricultural wastes as feedstocks, as well as demolition wastes from construction activities and red mud (RM) waste from the aluminum industry as a novel CO2 sorbent and catalyst, respectively. …”
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Searching for the best post-land abandonment management to enhance long-term carbon storage in Mediterranean mountain areas by Melani Cortijos-López, Teodoro Lasanta, Erik Cammeraat, Estela Nadal-Romero

“…A study was conducted in La Rioja (Iberian System, Spain), comparing three post-abandonment management strategies: secondary succession, forest management, and shrub clearing and extensive grazing. …”
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Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…The results showed that random forest, extreme gradient boosting, adaptive boosting and k-nearest neighbor models performed best on the combined dataset (weighted score of 1), where the feature set consisted of 9 key features selected by the cuckoo search algorithm when the population size was 25; while on the Framingham dataset, the k-nearest neighbor model performed best (weighted score of 0.92), and its feature set was derived from 10 features selected by the whale optimization algorithm when the population size was 50. …”
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Assessing crown reduction as a strategy to mitigate drought stress during initial development of sessile oak and Norway spruce saplings by Arsić Janko, Stojanović Marko, Horáček Petr, Mikhailov Sergei, Krejza Jan

“…Droughts, amplified by climate change, pose a significant threat to the success of both artificially and naturally regenerated forests. Understanding how these changes affect the initial stages of saplings development is crucial for forest establishment, particularly for ecologically and economically important species like Norway spruce and sessile oak in Central Europe. …”
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Characterising the short- and long-term impacts of tropical cyclones on mangroves using the Landsat archive by Emma Asbridge, Claire Krause, Richard Lucas, Christopher J. Owers, Kerrylee Rogers, Leo Lymburner, Norman Mueller, Emma Ai, Sebastian Wong

“…Tropical cyclones can significantly impact mangrove forests, with some recovering rapidly, whilst others may change permanently. …”
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A SDGs-oriented evaluation of the ecological sustainability of international horticultural exposition sites in Chengdu, China by Biao Huang, Haolin Yang, Kankan Shang, Ruoyu Wang, Yufei Meng, Hongming Peng, Yonghong Hu, Zehui Jiang

“…The development of Integrated Service areas will lead to an increase in impervious surfaces. The anticipated forest loss, along with declines in vegetation coverage, three-dimensional green volume, and vegetation carbon stock will adversely affect the highest sustainability. …”
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Inter-agency collaboration in building urban fire resilience in Indonesia: how do metropolitan cities address it? by Ahmad Harakan, Yusuf Adam Hilman, A. Junaedi Karso, Awaluddin Awaluddin, Nurhalijah Nurhalijah, Indah Sidrawaty Muin, Aldy Nurdiansyah B, Arfan Fadillah, Rudi Hardi

“…In Indonesia, recurring fire incidents, ranging from forest fires to residential fires in densely populated areas, highlight the urgent need for effective fire disaster management. …”
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Land use transition and its driving mechanisms in China’s human-elephant conflict areas by WANG Yuan, WANG Yahui, YANG Aoxi, FAN Hui, XIE Fei

“…[Results] (1) Land use transition in regions inhabited by Asian elephants is significant, with forest areas experiencing a decrease followed by a slow recovery, accompanied by a decrease in orchard area. …”
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Estimation of minimum miscible pressure in carbon dioxide gas injection using machine learning methods by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Fatemeh Mohammadinia, Amirjavad Borhani

“…Furthermore, ML algorithms such as Artificial Neural Networks (ANN), Bayesian networks, Random Forest (RF), Support Vector Machine (SVM), LSBoost, and Linear Regression (LR) were employed to estimate MMP. …”
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A dataset from the Cryptogamia-Lichenes section of the Herbarium Universitatis Taurinensis (TO) by Rosanna Piervittori, Deborah Isocrono, Enrica Matteucci, Mariagrazia Morando, Luca Dessì, Laura Guglielmone, Heimo Rainer, Stefano Martellos, Andrea Moro, Pier Luigi Nimis, Matteo Conti, Sergio Enrico Favero-Longo

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Using selective NIR wavelengths in portable devices to evaluate the chemical composition of cattle feeds by Lorenzo Serva, Luisa Magrin, Giovanni Chillemi, Giorgio Marchesini, Daniele Pietrucci, Francesco Renzi, Riccardo Valentini, Igino Andrighetto, Marco Milanesi

“…This was achieved by evaluating various cattle rations and silages (including rations for cows and bulls and grass and corn silage), where we selected the most significant wavelengths for fibre characterisation using the Random Forest (Boruta) algorithm. The number of identified features varied based on the spectral pre-treatments applied or the use of a batch effect reduction algorithm (ComBat function). …”
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Development of a respiratory virus risk model with environmental data based on interpretable machine learning methods by Shuting Shi, Haowen Lin, Leiming Jiang, Zhiqi Zeng, ChuiXu Lin, Pei Li, Yinghua Li, Zifeng Yang

“…We utilized the CRFC algorithm, a random forest-based method for multi-label classification, to predict the presence of various respiratory viruses. …”
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Characterization of differences in volatile compounds and metabolites of six varieties of potato with different processing properties by Wenyuan Zhang, Liang Li, Yaqi Zhao, Haixia Yang, Xuejie Zhang, Zhanquan Zhang, Xue Wang, Zhenzhen Xu, Wanxing Wang, Jianjun Deng

“…Moreover, the different expressed metabolites were involved in the metabolism of amino acids, flavone and flavanol biosynthesis, and tryptophan metabolism. The Random forest showed that the fresh eating and processing type potatoes could be distinguished by the content of amino acids and phenols.…”
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Metabarcoding the night sky: Monitoring landscape-scale insect diversity through bat diet by Cynthia Tobisch, Svenja Dege, Bernd Panassiti, Julian Treffler, Christoph Moning

“…Species composition in the diet showed high variation in space and time, but was also associated with edge density and the proportion of grassland within 2 km radius of the roosts. Moreover, forest and grassland percentages within 2-km buffers around the roosts significantly increased species richness within the diet. …”
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An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…Later, five state-of-the-art ensemble models for healthcare diagnosis were implemented along with a proposed ensemble machine learning model, KNN-XGBoost-SVM-Random Forest (KNN-X-SVM-R). The proposed model achieved an accuracy of 97.03% which supersedes all the other state-of-the-art models. …”
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