Diagnostic Performance of Des-γ-carboxy Prothrombin for Hepatocellular Carcinoma: A Meta-Analysis by Rong Zhu, Jing Yang, Ling Xu, Weiqi Dai, Fan Wang, Miao Shen, Yan Zhang, Huawei Zhang, Kan Chen, Ping Cheng, Chengfen Wang, Yuanyuan Zheng, Jingjing Li, Jie Lu, Yingqun Zhou, Dong Wu, Chuanyong Guo

“…Data are presented as forest plots and summary receiver operating characteristic curve (SROC) analysis was used to summarize the overall test performance. …”
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Oncolytic alphavirus-induced extracellular vesicles counteract the immunosuppressive effect of melanoma-derived extracellular vesicles by Darshak K. Bhatt, Annemarie Boerma, Silvina Odete Bustos, Andréia Hanada Otake, Alexis Germán Murillo Carrasco, Patrícia Pintor Reis, Roger Chammas, Toos Daemen, Luciana Nogueira de Sousa Andrade

“…Here we show that upon oncolytic virotherapy with Semliki Forest virus-based replicon particles (rSFV), metastatic melanoma cells release EVs with a distinct biochemical profile and do not lead to suppression of immune cells. …”
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Environmental DNA (eDNA) as a tool to detect Arctic grayling and their habitat preferences in the Northwest Territories, Canada by Heather D. Veilleux, Melissa D. Misutka, Morag D. McPherson, Peter A. Cott, Greg G. Goss, Mark Poesch, Chris N. Glover

“…The presence of eDNA was related to habitat metrics via Random Forest and correlation analyses. Riffles and water temperature were identified as being predictive of Arctic grayling eDNA abundance; however, no significant relationship between eDNA abundance and biomass proxies (fish abundance and fork length metrics) could be established. …”
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Classifying Dementia Using Local Binary Patterns from Different Regions in Magnetic Resonance Images by Ketil Oppedal, Trygve Eftestøl, Kjersti Engan, Mona K. Beyer, Dag Aarsland

“…We explored the use of 2D local binary pattern (LBP) extracted from FLAIR and T1 MR images of the brain combined with a Random Forest classifier in an attempt to discern patients with Alzheimer's disease (AD), Lewy body dementia (LBD), and normal controls (NC). …”
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Nutritional contribution of Coula edulis B. and Tetracarpidium conophorum M. A. to the Cameroon food composition table by Talla Tagne Naccis, Kotue Taptue Charles, Fokou Elie

“…This study aimed to determine the nutritional properties of Coula edulis (CE) and Tetracarpidium conophorum (TC), two non-timber forest products from Cameroon. Samples were analyzed using standard methods. …”
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Comparing Supervised Machine Learning Models for Covid-19 patient detection using a Combination of Clinical and Laboratory Dataset by Narges Mohebbi, Mehdi Tutunchian, Meysam Alavi, Mehrdad Kargari, Amir Behnam Kharazmy

“…Considering the importance and role of using clinical and laboratory data in the diagnosis of people with covid-19, in this paper K-NN, SVM, decision tree, random forest, Naive Bayes, neural network and XGBoost models are the most common machine learning models, and a dataset containing 1354 records consisting of clinical and laboratory data of patients in Imam Hossein Hospital in Tehran has been used to diagnose patients with covid-19. …”
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A New Cooperative MIMO Scheme Based on SM for Energy-Efficiency Improvement in Wireless Sensor Network by Yuyang Peng, Jaeho Choi

“…Combining the proposed scheme with monitoring sensor node will provide a good performance in arbitrary deployed WSN such as forest fire detection system.…”
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Oxidative potential and persistent free radicals in dust storm particles and their associations with hospitalization by Linjun Qin, Lili Yang, Ling Liu, Shilu Tong, Qian Liu, Gang Li, Haiyan Zhang, WuYuxin Zhu, Guorui Liu, Minghui Zheng, Guibin Jiang

“…We mapped the OP and EPFRs concentrations at 1735 sites in China during SDS periods using experimental data for 2021–2023 and a random forest model. We examined 855,869 hospitalizations during SDS events for 2015–2022 in Beijing, China. …”
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Strategies to reduce reliance on soya bean meal and palm kernel meal in livestock nutrition by J.M. Wilkinson, R.H. Young

“…Greenhouse gas emissions and loss of wildlife habitats have stimulated growing global concern over the continued expansion of soya bean and palm oilseed production on land recently converted from forest and natural grasslands. This paper reviews the roles of soya bean meal and palm kernel meal in livestock nutrition, drawing on research data to explore the potential for their replacement in nutritionally balanced diets. …”
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Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints by Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan

“…Experimental results demonstrate that this approach significantly outperforms methods such as polynomial interpolation, random forest, and LSTM-AE in terms of anomaly detection accuracy on field datasets from oilfields, accompanied by a notably lower false alarm rate.…”
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EVALUATING THREATS OF ARMED BANDITRY ON HUMAN AND FOOD SECURITY IN SHIRORO LOCAL GOVERNMENT AREA OF NIGER STATE, NIGERIA by DR MUSA EMMANUEL UMARU, DR ALIYU MOHAMMED BELLO, DR CHARLES O. OKWUWA

“…This involves providing advanced detection equipment in the forested lands of the study area to effectively address the prevailing challenges. …”
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Particle-size fractions-dependent extracellular enzyme activity in sediments and implications for resource allocation in a subtropical mangrove ecosystem by L. Luo, J.-D. Gu

“…Among these fractions, the highest activities of phenol oxidase (PHO), β-D glucosidase (GLU), and N-acetyl-glucosiminidase (NAG) were found in sand, and greater than bulk sediments of both intertidal zone (IZ) and mangrove forest (MG). This result implied that sand fractions might protect selective enzymes through the adsorption without affecting their activities. …”
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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods by Minghui Lv, Liping Wang, Ranran Huang, Aijie Wang, Yunxin Li, Guowei Zhang

“…The support vector machine (SVM), random forest (RF) and logistic regression (LR) algorithms, were used to establish the classification model for NIHL. …”
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Improving the accuracy of soil texture determination using pH and electro conductivity values with ultrasound penetration-based digital soil texture analyzer by Emre Kilinc, Umut Orhan

“…Using the Ultrasound Penetration-based Digital Soil Texture Analyzer (USTA), this research combined ultrasound time series data with pH and EC measurements to predict sand, silt, and clay ratios through machine learning methods—support vector regression (SVR), Random Forest (RF), and multi-layer perceptron neural network (MLPNN). …”
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Township-Level Ecological Management for Enhanced Ecosystem Services in the Qinling Mountains by Yan Zhao, Yiping Chen, Wenqi Wu, Hanwen Tian, Huiwen Zhang

“…The Qinling Mountains, known for high forest cover and multiple ecosystem services (ES), present significant potential for advancing ecological management (EM) paradigms. …”
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Urban greenspaces reduce the community specialization of soil nematodes by Justin Louis Kafana Coulibaly, Xin Gong, Yuanhu Shao, Huayuan Shangguan, Alexis Kayiranga, Ismail Koné, Yanjiang Cai, Xin Sun

“…Here, we examined the responses of diversity and community composition of soil nematodes, the most abundant metazoans on Earth, to several urban land use types (i.e., forests, farmlands, green belts, hospitals, industrials, urban parks, and residential areas) related to urbanization. …”
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An Enhanced Deep Neural Network for Predicting Workplace Absenteeism by Syed Atif Ali Shah, Irfan Uddin, Furqan Aziz, Shafiq Ahmad, Mahmoud Ahmad Al-Khasawneh, Mohamed Sharaf

“…The efficacy of the proposed method is tested with traditional machine learning techniques, and the results indicate 90.6% performance in Deep Neural Network as compared to 73.3% performance in a single-layer Neural Network and 82% performance in Decision Tree, SVM, and Random Forest. The proposed model will provide a useful mechanism to organizations that are interested to know the behavior of employees at the time of hiring and can reduce the cost of paying to inefficient or habitually absent employees. …”
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Monitoring Coastal Water Turbidity Using Sentinel2—A Case Study in Los Angeles by Yuwei Kong, Karina Jimenez, Christine M. Lee, Sophia Winter, Jasmine Summers-Evans, Albert Cao, Massimiliano Menczer, Rachel Han, Cade Mills, Savannah McCarthy, Kierstin Blatzheim, Jennifer A. Jay

“…Machine learning models were assessed for predictive accuracy, with the random forest model achieving the highest performance (R² = 0.632), indicating its robustness in modeling complex turbidity patterns. …”
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Functional diversity of bacteria in various saline soil plant vegetations around Sialang Buah Coast, North Sumatra, Indonesia by Mariani Sembiring, Juli M. Hutahuruk, Dwi Ningsih Susilowati, Erny Yuniarti, T. Sabrina, Luthfi A. Mahmud Siregar

“…The method employed in this research was random composite sampling taken from three vegetation types: mangrove forests, grasslands, and oil palm plantations, with sample collection locations influenced by tidal fluctuations. …”
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Exploiting self-organization and fault tolerance in wireless sensor networks: A case study on wildfire detection application by Felipe Taliar Giuntini, Delano Medeiros Beder, Jó Ueyama

“…Wireless sensor networks have been shown to be a good alternative for environmental monitoring applications, as they can collect and send information in real time, such as humidity, wind, and temperature of various parts of the forest. Due to problems such as power limitation, communication failure, and loss of nodes, the network topology is constantly changing, requiring mechanisms to achieve self-organization and fault tolerance. …”
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