Venturing Into the Unknown: The Importance of Variable Selection When Modelling Alien Species Under Non‐Analogue Climatic Conditions by Tom Vorstenbosch, Franz Essl, Bernd Lenzner, Johannes Wessely, Stefan Dullinger

“…Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non‐analogue climates. …”
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Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features by Daniel Hilário da Silva, Caio Tonus Ribeiro, Leandro Rodrigues da Silva Souza, Adriano Alves Pereira

“…Seventeen ML algorithms were applied to a dataset of voice recordings from Healthy Control and PD individuals, sourced from a publicly available repository. We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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A New Modeling Method for Meteorological Information of Regional Distributed Photovoltaic Power Generation Based on Multi‐Source Information Fusion by Yuhang Wang, Dengxuan Li, Wenwen Ma, Xi Zhang, Honglu Zhu

“…Precise meteorological information is the foundation for achieving these functions. However, DPV sites are typically scattered with small installed capacities and generally lack dedicated weather stations. …”
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Complex I deficiency due to selective loss of Ndufs4 in the mouse heart results in severe hypertrophic cardiomyopathy. by Edward T Chouchani, Carmen Methner, Guido Buonincontri, Chou-Hui Hu, Angela Logan, Stephen J Sawiak, Michael P Murphy, Thomas Krieg

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Raw-Data Driven Functional Data Analysis with Multi-Adaptive Functional Neural Networks for Ergonomic Risk Classification Using Facial and Bio-Signal Time-Series Data by Suyeon Kim, Afrooz Shakeri, Seyed Shayan Darabi, Eunsik Kim, Kyongwon Kim

“…To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. …”
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AI Chatbots and Cognitive Control: Enhancing Executive Functions Through Chatbot Interactions: A Systematic Review by Pantelis Pergantis, Victoria Bamicha, Charalampos Skianis, Athanasios Drigas

“…The criteria aligned with the study objectives, ensuring a focus on AI chatbots and the impact of conversational agents on executive function. The initial collection totaled <i>n</i> = 115 articles; however, the eligibility requirements led to the final selection of <i>n</i> = 10 studies. …”
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Selected Problems of the Patient after the Peak-occipital Decompression Surgery Treatment in the Course of the Chiari type I Malformation by Beata Haor, Robert Ślusarz, Agnieszka Królikowska, Renata Jabłońska, Mariola Głowacka, Anita Królikowska

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Phage display of cDNA libraries: enrichment of cDNA expression using open reading frame selection by Peggy Ho Faix, Michael A. Burg, Michelle Gonzales, Edward P. Ravey, Andrew Baird, David Larocca

“…The high level of cDNA expression obtained by ORF selection suggests that ORF-enriched phage cDNA libraries prepared by these methods will be useful as functional genomics tools for identifying natural ligands from various source tissues.…”
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Dynamic Double-Networked Hydrogels by Hybridizing PVA and Herbal Polysaccharides: Improved Mechanical Properties and Selective Antibacterial Activity by Weidong Liu, Chuying Yao, Daohang Wang, Guangyan Du, Yutian Ji, Quan Li

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Walkability Evaluation of Historical and Cultural Districts Based on Multi-Source Data: A Case Study of the Former Russian Concession in Hankou by Haoran She, Jing Sun, Yuchen Zeng, Wenyu Tu, Guang Ao, Wei Shang

“…Key issues such as low spatial quality and functional disorder were identified, and targeted optimization strategies are proposed. …”
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Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection by Weichao Liu, Jiapeng Xiao, Rongyuan Liu, Yan Liu, Yunzhu Tao, Tian Zhang, Fuping Gan, Ping Zhou, Yuanbiao Dong, Qiang Zhou

“…We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

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An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

“…However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.To mitigate the high consumption of computational resources in real-time deployment of existing models, we integrate the Fasternet Block into the C2f of the backbone network and neck network, effectively reducing the parameter count and the computational load of the model. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems by Christian Goetz, Bernhard G. Humm

“…Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. …”
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An energy storage planning method for improving the security of receiving-end system considering the selection of power conversion systems by Haibo Zhang, Kai Wei, Yukang Hu, Quan Hu

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Application of metal nanoparticle-loaded nanocomposites for extraction, removal, and detection of mycotoxins in foods by Mehdi Maham, Reza Abedi-Firoozjah, Mohammad Hadi Moradiyan, Maryam Azizi Lalabadi, Elham Assadpour, Hamed Ahari, Seid Mahdi Jafari

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