π-π2max: Bridging molecular characteristics to crystal packing in nitro-containing two-dimensional energetic materials by Xiaokai He, Chao Chen, Zhixiang Zhang, Linyuan Wen, Yiding Ma, Yilin Cao, Yingzhe Liu

“…Furthermore, the proposed model shows superior classification predictive performance compared to typical machine learning methods, such as random forest, on the external validation samples. …”
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Lymph node metastasis in early invasive lung adenocarcinoma: Prediction model establishment and validation based on genomic profiling and clinicopathologic characteristics by Wei Guo, Tong Lu, Yang Song, Anqi Li, Xijia Feng, Dingpei Han, Yuqin Cao, Debin Sun, Xiaoli Gong, Chengqiang Li, Runsen Jin, Hailei Du, Kai Chen, Jie Xiang, Junbiao Hang, Gang Chen, Hecheng Li

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CPredictive performance of CT images-based 3D ResNet18 model for identifying lung tuberculosis drug resistance by LI Chunhua, LIU Xueyan, ZHENG Jiaofeng

“…Six radiologists independently evaluated DR-TB identification on the test set, and their performance was compared with the best-performing deep learning model. …”
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Research into performance optimization control strategy of a hydrostatic drive bulldozer based on the constant speed cruise by Hongbin Qiang, He Li, Shaopeng Kang, Kailei Liu, Jing Yang, Xingfei Luo

“…This method calculates the required engine power and the preset motor speed to determine the displacement settings of the pump and motor at maximum efficiency for each operating condition. The required engine power is derived by reversing the efficiency, while maintaining the motor speed (i.e., working point identification).Then, the engine and hydraulic system models are developed and co-simulated. …”
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Deep Learning for Traffic Scene Understanding: A Review by Parya Dolatyabi, Jacob Regan, Mahdi Khodayar

“…The significance of Hyperparameter Optimization (HPO) is also discussed, emphasizing its critical role in enhancing model performance and efficiency, particularly in adapting DL models for practical, real-world use. …”
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A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms by Mohammad Ghattas, Antonio M. Mora, Suhail Odeh

“…Similarly, Random Forest models showed a slight improvement, reaching 81% with feature selection versus 80% without. …”
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Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual‐branch structure by Xuebin Lv, Fuzheng Liu, Mingshun Jiang, Faye Zhang, Lei Jia

“…Firstly, multi‐characteristic dissolved gas ratio analysis is used to construct multi‐dimensional supplementary feature vectors, which enrich the characterisation features of transformers and facilitate efficient diagnosis of classification models. Secondly, a dual‐branch structure combining focal‐gradient harmonic loss and cross‐entropy loss is introduced to improve the attention and recognition ability of the model to a few categories in the dataset and alleviate the influence of data imbalance on the diagnostic results. …”
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Evaluating preventive measures for the zoonotic transmission of swine influenza A variant at agricultural fairs in the United States: a mathematical modeling study by Dana C. Pittman Ratterree, Sapna Chitlapilly Dass, Martial L. Ndeffo-Mbah, Martial L. Ndeffo-Mbah

“…As agricultural fairs present a substantial risk for zoonotic influenza outbreaks and potential pandemics, it is paramount to identify efficient preventive measures for mitigating the risk of variant influenza A transmission from pigs to humans at swine exhibitions.MethodsWe developed a mathematical model of swine influenza A variant transmission at agricultural fairs. …”
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Paddy Field Scale Evapotranspiration Estimation Based on Two-Source Energy Balance Model with Energy Flux Constraints and UAV Multimodal Data by Tian’ao Wu, Kaihua Liu, Minghan Cheng, Zhe Gu, Weihua Guo, Xiyun Jiao

“…These adaptations enabled the TSEB model to achieve a satisfactory accuracy in estimating energy flux compared to the single-source SEBAL model, with R² values of 0.8501 for <i>Rn</i> − <i>G</i> and 0.7503 for latent heat (<i>LE</i>), as well as reduced rRMSE values. …”
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Multi-Type Change Detection and Distinction of Cultivated Land Parcels in High-Resolution Remote Sensing Images Based on Segment Anything Model by Zhongxin Huang, Xiaomei Yang, Yueming Liu, Zhihua Wang, Yonggang Ma, Haitao Jing, Xiaoliang Liu

“…To address the issue of detecting diverse types of changes in cultivated land parcels, this study constructs an automated workflow framework for change detection, based on the unsupervised segmentation method of the SAM (Segment Anything Model). By performing spatial connection analysis on cultivated land parcel units extracted by the SAM for two phases and combining multiple features such as texture features (GLCM), multi-scale structural similarity (MS-SSIM), and normalized difference vegetation index (NDVI), precise identification of cultivation type and pattern change areas was achieved. …”
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Evaluation of deep learning models for RGB image-based detection of potato virus y strain symptoms (O, NO, and NTN) in potato plants by Charanpreet Singh, Gurjit S. Randhawa, Aitazaz A. Farooque, Yuvraj S. Gill, Lokesh Kumar KM, Mathuresh Singh, Khalil Al-Mughrabi

“…These models may assist roguers in the real-time identification of PVY-infected plants that may help in controlling the disease spread and improving the crop yield.…”
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Spatial Localization of Broadleaf Species in Mixed Forests in Northern Japan Using UAV Multi-Spectral Imagery and Mask R-CNN Model by Nyo Me Htun, Toshiaki Owari, Satoshi N. Suzuki, Kenji Fukushi, Yuuta Ishizaki, Manato Fushimi, Yamato Unno, Ryota Konda, Satoshi Kita

“…Precise spatial localization of broadleaf species is crucial for efficient forest management and ecological studies. …”
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Instance Segmentation of Sugar Apple (<i>Annona squamosa</i>) in Natural Orchard Scenes Using an Improved YOLOv9-seg Model by Guanquan Zhu, Zihang Luo, Minyi Ye, Zewen Xie, Xiaolin Luo, Hanhong Hu, Yinglin Wang, Zhenyu Ke, Jiaguo Jiang, Wenlong Wang

“…The model incorporates Gamma Correction (GC) to enhance image brightness and contrast, improving target region identification and feature extraction in orchard settings. …”
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Development of Construction Safety Dashboard Based on Four-Dimensional Building Information Modeling for Fall Prevention: Case Study of Stadium Roof Works by Rossy Armyn Machfudiyanto, Titi Sari Nurul Rachmawati, Naufal Budi Laksono, Mehrtash Soltani, Chansik Park

“…The proposed approach includes four modules: (1) identification and assessment of risk from identified work activities, (2) development of 4D BIM model, (3) creation of a dashboard to share safety knowledge, and (4) validation of the dashboard through interviews with safety managers and site workers. …”
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Evolution of strain field and crack prediction in cemented paste backfill specimens based on digital image correlation and computer vision recognition model by Huanbao Zhang, Tao Gao, Fulin Wang, Qibin Lin, Shenchen Zhang, Changhui Zou, Shijiao Yang, Haiyang He

“…By applying the first derivative of these proportions, the model enables early crack prediction. This approach overcomes the limitations and subjectivity of traditional artificial vision methods for crack identification, providing precise quantification of CPB strain evolution. …”
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Identifying Forest Burned Area Using a Deep Learning Model Based on Post-Fire Optical and SAR Remote Sensing Images by Xiaofei Xi, Man Kang, Long Dai, Yan Jing, Peng Han, Congqiang Hou

“…Besides, it is found that, the CSAR module is helpful to promote both the precision and the training efficiency of the proposed model.…”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…Particle Swarm Optimization (PSO) is then employed to optimize the selected ML model (XGBoost), leading to the identification of optimal input parameters for biodiesel production. …”
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Identifying Inefficient Urban Residential Land within Shenzhen City: An Approach Using Gaussian Mixture Model and Multi-Source Big Data by Y. Liu, S. Liang, R. Guo, W. Wang, D. Ma, Y. Zheng, L. Zhang, Q. Liu, X. Li

“…To address these issues, this paper employs the Gaussian Mixture Model (GMM) clustering method and integrates multi-source geographical big data to quantitatively characterize land use efficiency. …”
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Dual RNA-seq study of the dynamics of coding and non-coding RNA expression during Clostridioides difficile infection in a mouse model by Victor Kreis, Claire Toffano-Nioche, Cécile Denève-Larrazet, Jean-Christophe Marvaud, Julian R. Garneau, Florent Dumont, Erwin L. van Dijk, Yan Jaszczyszyn, Anaïs Boutserin, Francesca D'Angelo, Daniel Gautheret, Imad Kansau, Claire Janoir, Olga Soutourina

“…To better understand the dynamics of ncRNA expression contributing to C. difficile infectious cycle and host response, we used a dual RNA-seq approach in a conventional murine model. From the pathogen side, this transcriptomic analysis revealed the upregulation of virulence factors, metabolism, and sporulation genes, as well as the identification of 61 ncRNAs differentially expressed during infection that correlated with the analysis of available raw RNA-seq data sets from two independent studies. …”
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Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch... by Shaolin Chen, Ting Deng, Qing Yang, Jin Li, Juanyan Shen, Xu Luo, Juan Tang, Xulian Zhang, Jordan Tovera Salvador, Junliang Ma

“…Twelve independent ML models and 26 stacking ensemble models were developed. …”
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