YOLOv8-SAMURAI: A Hybrid Tracking Framework for Ladder Worker Safety Monitoring in Occlusion Scenarios by Sangyoon Yun, Hyunsoo Kim

“…Monitoring worker safety during ladder operations at construction sites is challenging due to occlusion, where workers are partially or fully obscured by objects or other workers, and overlapping, which makes individual tracking difficult. …”
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Predictive Archaeological Risk Assessment at Reservoirs with Multitemporal LiDAR and Machine Learning (XGBoost): The Case of Valdecañas Reservoir (Spain) by Enrique Cerrillo-Cuenca, Primitiva Bueno-Ramírez

“…This study assesses the potential of using multitemporal LiDAR data and Machine Learning (ML)—specifically the XGBoost algorithm—to predict erosional and sedimentary processes affecting archaeological sites in the Valdecañas Reservoir (Spain). …”
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A Novel Behavioral Strategy for RoboCode Platform Based on Deep Q-Learning by Hakan Kayakoku, Mehmet Serdar Guzel, Erkan Bostanci, Ihsan Tolga Medeni, Deepti Mishra

“…It should also be noted that this new model facilitates simulation performance in adaptive and partially cluttered environments.…”
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Orchard: Building large cancer phylogenies using stochastic combinatorial search. by Ethan Kulman, Rui Kuang, Quaid Morris

“…Here, we introduce Orchard, a cancer phylogeny reconstruction algorithm that is fast and accurate using up to 1000 mutations. …”
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Chest Wall Perforator Flaps in Breast Conservation: Versatile, Affordable, and Scalable: Insights from the Largest Single-Surgeon Audit from India by C. B. Koppiker, Rupa Mishra, Vaibhav Jain, Priya Sivadasan, Chetan Deshmukh, Beenu Varghese, Upendra Dhar, Anushree Vartak, Namrata Athavale, Neerja Gupta, Laleh Busheri, Vishesha Lulla, Sneha Bhandari, Sneha Joshi

“…Chest wall perforator flaps (CWPFs) are a promising option for partial breast reconstruction but are underutilized, particularly in resource-limited settings. …”
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Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model by Bowen Zhang, Liang Chen, Tao Li

“…An interpretable machine learning (ML) model was developed to predict CKD using data from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2007 to 2016. Four ML algorithms—random forest classifier (RF), XGBoost (XGB), k-nearest neighbors (KNN), and support vector machine (SVM)—were used alongside traditional logistic regression to predict CKD. …”
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Segmentation of CAD models using hybrid representation by Claude Uwimana, Shengdi Zhou, Limei Yang, Zhuqing Li, Norbelt Mutagisha, Edouard Niyongabo, Bin Zhou

“…The first component of our hybrid system involves advanced mesh-labeling algorithms that harness the digitization of CAD properties to mesh models. …”
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Associations between organophosphorus pesticides exposure and age-related macular degeneration risk in U.S. adults: analysis from interpretable machine learning approaches by Yu-Xin Jiang, Si-Yu Gui, Xiao-Dong Sun

“…CONCLUSION: Urinary DAP metabolites of OPPs exposure are associated with AMD risk and ML algorithms show the excellent generalizability and differentiability in the course of AMD risk prediction.…”
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Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan by Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid, Amira Khattak

“…Third, XGBoost and Random Forest machine learning algorithms were employed to examine and validate the importance of the spatial lag component. …”
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Identifying emphysema risk using brominated flame retardants exposure: a machine learning predictive model based on the SHAP methodology by Qihang Xie, Haoran Qu, Jianfeng Li, Rui Zeng, Wenhao Li, Rui Ouyang, Chengxiang Zhang, Siyu Xie, Siyu Xie, Ming Du

“…Eight machine learning algorithms, including lightGBM, MLP, DT, KNN, RF, SVM, Enet, and XGBoost, were applied to build and evaluate the model. …”
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Validating laboratory predictions of soil rewetting respiration pulses using field data by X. Li, X. Li, M. Pallandt, M. Pallandt, D. Naidu, D. Naidu, J. Rousk, G. Hugelius, G. Hugelius, S. Manzoni, S. Manzoni

“…LR and FR were explained by six predictors using random forest algorithms and partial dependence plots. Results indicated that the most important drivers of LR and FR were SOC and temperature, respectively. …”
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Cadmium accumulation in wheat grain: Accumulation models and soil thresholds for safe production by Lu Lin, Xiaopeng Zhao, Yumeng Li, Jingbo Ling, Jinghua Ren, Qilin Liao, Dongmei Zhou, Xueyuan Gu

“…Correlation analyses and Partial Least Squares Path Model indicated that soil Cd, soil pH, and CEC together controlled the transfer of Cd from soil to wheat. …”
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A Stackelberg Trust-Based Human–Robot Collaboration Framework for Warehouse Picking by Yang Liu, Fuqiang Guo, Yan Ma

“…In this framework, HRC with trust for warehouse picking is defined as the Partially Observable Stochastic Game (POSG) model. …”
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Lane and Traffic Sign Detection for Autonomous Vehicles: Addressing Challenges on Indian Road Conditions by H. S. Gowri Yaamini, Swathi K J, Manohar N, Ajay Kumar G

“…To address these issues, the models need to be trained with a wide variety of Indian data samples for the autonomous vehicles to perform better in India. YOLOv8 algorithm has its challenges but gives better precision results and YOLOv8 nano variant is widely used as it is computationally less complex comparatively. …”
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MFFCI–YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…There is a growing need for lightweight algorithms in certain remote sensing devices. Moreover, remote sensing images (RSIs) often contain numerous small, densely distributed targets, which pose significant detection challenges. …”
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Double‐row suture‐bridge technique does not yield better clinical and radiological results than single‐row technique in patients older than 55 years at 2 years minimum follow‐up: A... by Vito Gaetano Rinaldi, Sassoli Iacopo, Federico Coliva, Antongiulio Favero, Alberto Bazzocchi, Marco Miceli, Stefano Di Paolo, Stefano Zaffagnini, Giulio Maria Marcheggiani Muccioli

“…Further research, including randomized controlled trials with long‐term follow‐up, is needed to refine treatment algorithms and improve patient outcomes in rotator cuff surgery. …”
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Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases by Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba

“…Employing Random Forest and Boruta algorithms, we identified significant features for responder-non-responder differentiation. …”
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A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration by Xuanran Zhao, Yan Wu, Xin Hu, Zhikang Li, Ming Li

“…However, the inherent differences between the two modalities pose a challenge to the existing deep-learning algorithms that only depend on local features. To address this problem, we propose a global and local feature extraction network (GLFE-Net) for SAR and optical image registration. …”
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Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera by Guo Chen, Li Li, Weiqi Jin, Su Qiu, Hui Guo

“…This paper proposes an image multi-scale decomposition method based on gradient domain guided filter (GDGF), which can better extract image details. The fusion algorithm adopts different fusion strategies for different scales. …”
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Accelerometers can correctly count orthopaedic patients' early post‐operative steps while using walking aids by Spiros Tsamassiotis, Michael Schwarze, Philipp Gehring, Roman F. Karkosch, Lars‐René Tücking, Ann‐Kathrin Einfeldt, Eike Jakubowitz

“…However, it remains unclear if commercially available wearables or accelerometers using simple algorithms can accurately count steps in early post‐operative conditions. …”
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