QUANTIFYING THE IMPACT OF SOCIAL AND POLITICAL INSTABILITY ON SUPPLY CHAIN OPERATIONS: A RISK ASSESSMENT FRAMEWORK by Bing Wang, Lokhman Hakim Osman, Mohd Rizal Palil, Nurul Atasha Binti Jamaludin

“…To mitigate the effects of external uncertainties on disruptions in the supply chain, proactive risk management has grown in significance. …”
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How do entrepreneurial traits affect green entrepreneurial performance? A Fuzzy set qualitative comparative analysis (fsQCA) by Ying Ding, Hong Yang, Can Peng, Chaolin Lyu

“…Second, social capital, prior engineering experience, and green innovativeness emerge as pivotal factors; social capital is present in five performance configurations, playing a central role in high-performance outcomes, while prior experience and green innovativeness feature in four configurations. Third, startups can attain strong green performance by leveraging substantial social capital, rich prior experience, and proactive green innovativeness, even with relatively moderate psychological traits. …”
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Hybrid machine learning applications in pavement engineering: predicting spalling with PSO-GBM by Ali Alnaqbi, Ghazi G. Al-Khateeb, Waleed Zeiada

“…This study contributes to pavement engineering by introducing an optimized hybrid machine learning approach that enhances spalling prediction accuracy, offering a data-driven decision-making tool for proactive CRCP maintenance and management.…”
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Zibellino: tipi, funzioni e simbolismo by Anna Savchenkova

“…Portraits of the XV and XVI centuries sometimes feature unusual accessories - zibellini. They repeat the shape of wild animals from the Mustelidae: ermines, martens, sables. …”
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Analysis and Prediction of Wear in Interchangeable Milling Insert Tools Using Artificial Intelligence Techniques by Sonia Val, María Pilar Lambán, Javier Lucia, Jesús Royo

“…This proactive approach enhances operational efficiency and reduces overall production costs. …”
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Hybrid sequence learning with interpretability for multi-class quality prediction in injection molding by Varathorn Punyangarm, Supatchaya Chotayakul

“…The Transformer module captures long-range temporal dependencies, while TabNet provides feature-level interpretability through sparse attention masks. …”
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A scalable machine learning strategy for resource allocation in database by Fady Nashat Manhary, Marghny H. Mohamed, Mamdouh Farouk

“…This approach enables proactive, decentralized, and scalable resource management through three innovations: high-accuracy forecasting using BiLSTM with feature-wise attention, variance-regularized credit assignment for stable multi-agent coordination, and faster convergence via adaptive prioritized replay. …”
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PlantHealthNet: Transformer-Enhanced Hybrid Models for Disease Diagnosis and Severity Estimation in Agriculture by Abid Iqbal

“…With a hierarchical attention mechanism for efficient feature extraction, the Swin Transformer achieves a top 1 accuracy of 85.6%, and a top 5 accuracy of 96.2%. …”
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High-accuracy PM2.5 prediction via mutual information filtering and Bayesian-Optimized Spatio-Temporal Convolutional Networks by Wanyu Wang

“…Abstract Air pollution, particularly fine particulate matter (PM2.5), poses severe threats to human health and ecological sustainability, rendering accurate prediction of PM2.5 concentrations imperative for proactive public health interventions and evidence-based policy-making. …”
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Exploring the effect of climate change on food supply chains in Africa: a systematic review with a focus on South Africa by Merishca Naicker, Denver Naidoo, Rob Slotow, Mjabuliseni Simon C. Ngidi

“…Thereafter the coding feature was used to tag the duplicates. A manual verification was then conducted, as NVivo does not allow for the automatic deletion of duplicates. …”
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Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection by Nwamaka Georgenia Ezeji, Kingsley Ifeanyi Chibueze, Nnenna Harmony Nwobodo-Nzeribe

“…Methodology used are data collection, data analysis, feature selection with Chi-Square, feature transformation with Principal Component Analysis (PCA), Support Vector Machine (SVM) and model for electricity theft detection.   …”
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Edge–Cloud Intelligence for Sustainable Wind Turbine Blade Transportation: Machine-Vision-Driven Safety Monitoring in Renewable Energy Systems by Yajun Wang, Xiaodan Wang, Yihai Wang, Shibiao Fang

“…It is enhanced with convolutional block attention modules (CBAMs) for feature refinement, CARAFE upsampling for better contextual detail, and bidirectional feature pyramid networks (BiFPNs) for multi-scale object detection. …”
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Assessing preference heterogeneity for nature-based flood control measures: An econometric analysis using a choice experiment by Takahiro Tsuge, Ayumi Onuma, Jun Nishihiro, Yuki Shibata, Taro Shoji, Yasutaka Satake, Takehito Yoshida

“…In recent years, green infrastructure has gained attention due to the increasing risk of disasters caused by extreme weather and growing concern for environmental conservation. A key feature of green infrastructure is its multifunctionality. …”
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Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism by Hanieh Mohammadi, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…Our proposed model leverages a hybrid architecture of convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) layers, and an attention mechanism, enabling refined spatial and temporal feature extraction to enhance BP estimation accuracy. …”
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Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model by Can Chen, Yumin Cao, Keshuang Tang, Keping Li

“…The dynamic path flows estimated by the trained model can be applied to travel information provision, proactive route guidance, and signal control with high real-time requirements.…”
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Predicting Forest Evapotranspiration using Remote Sensing and Machine Learning by B. Yadav, L. K. Sharma, B. Bijarniya

“…Using ML algorithms to estimate ET rates can be useful for proactive resource management, particularly in water-stressed areas.…”
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Research status of roof water and sand bursting disaster in thick bedrock stope of coal seam by Zhaoxing Liu, Shuning Dong, Xiaoming Guo, Xiaolong Li, Dongliang Chen

“…Three principal research components essential for elucidating the disaster mechanism have been systematically established: the feedback characteristics and response relationships of water-induced deterioration in weakly cemented strata to influencing factors; The variation patterns of stress conditions in overlying hard rock strata and basic roof with the deterioration of weakly cemented formations; The dynamic mechanisms of inrush from deteriorated weakly cemented strata and channel evolution under incremental loading. An integrated proactive prevention strategy has been proposed, featuring advanced hard rock pre-splitting and grouting modification of weakly cemented formations, which fundamentally alters the objective conditions for disaster initiation. …”
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Trend prediction and influencing factors of the production comparative advantage of China's main apple-producing provinces. by Wenping Ning, Fuhong Zhang, Meiling Zhang

“…Besides, the change of APCA had significant spatial spillover effect, and highly advantage provinces featured more prominent proactive spillovers. 3) There is significant heterogeneity among the influencing factors.…”
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AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management by Joseph Finkelstein, Aref Smiley, Christina Echeverria, Kathi Mooney

“…The findings demonstrate that both CNN’s temporospatial feature extraction and LSTM’s temporal modeling effectively capture escalation patterns in symptom progression. …”
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Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey by Yizhe Wang, Ruifa Luo, Xiaoguang Yang

“…Meanwhile, ETC data-based urban traffic management is transitioning from passive responses to proactive prediction, from single functions to comprehensive services, and from isolated systems to integrated platforms. …”
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