Sustainability through lignin valorization: recent innovations and applications driving industrial transformation by Poulose Sarojam Jiju, Anil Kumar Patel, Nalinakshan Sreevidya Shruthy, Saseendran Shalu, Cheng-Di Dong, Reeta Rani Singhania

“…Despite its significant potential, lignin valorization is constrained by challenges including structural complexity, inefficient processing, and scalability limitations. …”
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A New Multi-granular 2-Tuple WASPAS-H Approach for Evaluating Water Resources for Olive Tree Irrigation under Group Decision-Making by Wiem Daoud-BenAmor, Hela Moalla Frikha

“…However, existing ranking approaches rarely offer efficient tools to handle hierarchical criteria structures. …”
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Characterization and Modelling of Potential Seaborne Disasters, in the ANA Region by Ashraf Labib, Dylan Jones, Natalia Andreassen, Rune Elvegård, Mikel Dominguez Cainzos

“…We demonstrate how such tools can be used by applying some of them to a selective case study and drawing lessons learned from the application of root cause analysis, which can help emergency response organisations with preparedness work and hence more efficient response. …”
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Predicting Wheat Potential Yield in China Based on Eco-Evolutionary Optimality Principles by Shen Tan, Shengchao Qiao, Han Wang, Sheng Chang

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FPG-AI RNN: A Technology-Agnostic Framework for the Automatic Acceleration of LSTM/GRU-Based Models on FPGAs by Tommaso Pacini, Pietro Nannipieri, Silvia Moranti, Luca Fanucci

“…FPGAs have emerged as an efficient technology for accelerating these algorithms, especially in resource- and power-constrained platforms such as edge devices. …”
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A comprehensive review of performance, innovation, challenges and future directions of desulfurization technologies by Karim Maghfour Sarkarabad, Ahad Ghaemi

“…Using cutting-edge materials like metal-organic frameworks (MOFs) and activated carbons, adsorptive desulfurization (ADS) provides reduced operating complexity and cost for lighter fuels. Although extractive desulfurization (EDS) and biomass desulfurization (BDS) demonstrate the ability to remove sulfur selectively, they are constrained by slower reaction rates and chemical or biological limitations. …”
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Designing Supplementary Controller With Thyristor-Controlled Series Capacitor for Enhancing Inertia-Sharing Capability by Thongchart Kerdphol

“…Unlike conventional strategies that rely on deploying additional energy storage systems or distributed virtual inertia units, the proposed method utilizes existing transmission infrastructure, thereby reducing implementation complexity and cost. The efficacy of the proposed control strategy is assessed using a benchmark interconnected model configured to reflect practical multi-area dynamics and intertie constraints. …”
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Deep learning-based prediction of multi-level just noticeable distortion by Haifeng XU, Hongkui WANG, Haibing YIN, Chuqiao CHEN

“…Visual just noticeable distortion (JND) directly reflects the sensitivity of the human visual system to visual signal noise, and is widely used in image and video processing.Aiming at the multilevel prediction problem of video JND threshold, it was transformed into the prediction problem of satisfied user ratio (SUR) curve, and a feature fusion-based SUR curve prediction model was proposed.The model was mainly divided into key frame extraction module, feature extraction and fusion module, and SUR score regression module.In the key frame extraction module, according to the visual perception mechanism, the spatial-temporal domain perception complexity was proposed and used as the video key frame judgment index.In the feature extraction and fusion module, a multi-scale dense residual network was proposed based on dense residual block (RDB) to realize image feature extraction and multi-scale fusion.The experimental results show that the proposed SUR curve prediction model is overall better than the existing models in terms of JND prediction accuracy and reduces the time cost by 8.1% on average in terms of operational efficiency.Meanwhile, the model can also be used to predict other layers of JND thresholds, which can be directly applied to video multilevel perceptual coding optimization.…”
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Constitutive model of metal rubber material considering plastic accumulation behavior by FENG Zhipeng, YANG Fang, FU Hailong, AI Shigang, WANG Yue, YUAN Liangyang

“…This distinctive structural configuration enables efficient mechanical energy dissipation under dynamic loading conditions through multiple synergistic mechanisms, including inter-coil dry friction, elastic bending deformation, and plastic deformation.…”
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Multi-objective vessel routing problems with safety considerations: A review by Nazanin Sharif, Mikael Rönnqvist, Jean-François Cordeau, Jean-François Audy, Gurjeet Warya, Trung Ngo

“…This complexity arises from the difficulty of finding an appropriate balance between several objectives and safety concerns, often conflicting, that adequately reflects the preferences of the decision makers. …”
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Concept of integrated analysis of financial health of global corporations by Čavlin Miroslav, Jovanović Zoran, Đurović Milan

“…This research focuses on the financial health analysis of multinational corporations within the complexity of the global business environment. An integrated analytical model was developed, encompassing six evaluation dimensions: competitive positioning, benchmarking, variance analysis, time dynamics, structural efficiency, and causal interdependencies among indicators. …”
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The Equal-Time Waypoint Method: A Multi-AUV Path Planning Approach That Is Based on Velocity Variation by Chenxin Yin, Kai Shi, Hailong Wang

“…In collaborative operations of multiple autonomous underwater vehicles (AUVs), the complexity of underwater environments and limited onboard energy make environmental adaptation and energy efficiency critical metrics for evaluating path quality. …”
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Intelligent transportation systems: A survey on modern hardware devices for the era of machine learning by Issam Damaj, Salwa K. Al Khatib, Tarek Naous, Wafic Lawand, Zainab Z. Abdelrazzak, Hussein T. Mouftah

“…To alleviate the difficulties faced in the non-trivial task of selecting suitable ML techniques and MHDs for an ITS with a specific complexity level, a performance evaluation framework is proposed. …”
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SegTrackDetect: A window-based framework for tiny object detection via semantic segmentation and tracking by Aleksandra Kos, Karol Majek, Dominik Belter

“…SegTrackDetect is optimized with inference speed in mind, offering a highly efficient pipeline while providing users with the flexibility to customize models. …”
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An Integrated Neural Network-Based Traffic Congestion Prediction for Material Handling Systems of Semiconductor Manufacturing by Donghun Lee, Suhee Kim, Hoonseok Park, Haejoong Kim, Ri Choe, Younkook Kang, Jae-Yoon Jung, Kwanho Kim

“…In semiconductor manufacturing, the most important logistics management is the efficient operation of overhead hoist transports (OHTs). …”
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Thermodynamic Characteristics of the Ion-Exchange Process Involving REMs of the Light Group by Olga V. Cheremisina, Maria A. Ponomareva, Yulia A. Mashukova, Nina A. Nasonova, Maria D. Burtseva

“…The study considers the use of anion- and cation-exchange resins with different functional groups for efficient and environmentally safe REM separation. …”
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Seeing Beyond Noise: Improving Cryptocurrency Forecasting with Linear Bias Correction by Sibtain Syed, Syed Muhammad Talha, Arshad Iqbal, Naveed Ahmad, Mohammed Ali Alshara

“…The proposed methodology includes collecting cryptocurrency data and precious metal data from Coindesk and BullionVault, respectively, and then finding the optimal model input combination for each cryptocurrency by lag adjustment and correlating feature selection. Hyperparameter tuning was performed by trial-and-error technique, and an early stopping function was applied to minimize time and space complexity. …”
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Understanding adaptations in a community-vetted COVID-19 testing program by Breanna J. Reyes, Stephenie Tinoco Calvillo, Angel Lomeli, Angel Lomeli, Arleth A. Escoto, Maria Linda Burola, Kelli L. Cain, Linda Salgin, Linda Salgin, Maria Balbuena-Bojorquez, Anne-Marie Engler, Marva Seifert, Louise C. Laurent, Nicole A. Stadnick, Nicole A. Stadnick, Nicole A. Stadnick, Borsika A. Rabin, Borsika A. Rabin

“…BackgroundAdaptations are expected when complex public health interventions are implemented in dynamically and rapidly changing real-world settings, as seen for many programs during the COVID-19 pandemic. …”
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Research on key technologies of safety monitoring data sharing for railway engineering construction based on blockchain by Yuhong LIU, Liang YANG, Chunhui PIAO, Zhiguo ZHANG

“…In order to solve the problems that the monitoring data was easy to be tampered with in the process of railway engineering construction safety monitoring, and the authenticity of the data might be questioned during the accountability of accidents, a blockchain-based railway engineering construction safety monitoring data sharing model was proposed.The characteristics of automatic execution of smart contracts ensured the transparency of the process of monitoring data on the chain.In the PBFT algorithm, there was a problem that the Byzantine nodes and the normal nodes were selected as the master node with the same probability, a reputation-based practical Byzantine fault tolerance algorithm was proposed.Streaming data on the chain might cause network congestion, which simplified the consensus protocol and reduced the time complexity from O(n²) to O(n).A comparative experiment was conducted using Hyperledger Caliper to prove that the delay of the improved algorithm is lower than PBFT algorithm, and the throughput is higher than PBFT algorithm.A quantitative analysis of the possibility of attack and the probability of successful attack was carried out, and it was determined that the smart contract provides tamper-proof modification for the monitoring data on the chain.Comparative analysis proves that the proposed blockchain-based railway engineering construction safety monitoring data sharing model is good than other models in terms of consensus efficiency, TPS and block generation speed.…”
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Research on key technologies of safety monitoring data sharing for railway engineering construction based on blockchain by Yuhong LIU, Liang YANG, Chunhui PIAO, Zhiguo ZHANG

“…In order to solve the problems that the monitoring data was easy to be tampered with in the process of railway engineering construction safety monitoring, and the authenticity of the data might be questioned during the accountability of accidents, a blockchain-based railway engineering construction safety monitoring data sharing model was proposed.The characteristics of automatic execution of smart contracts ensured the transparency of the process of monitoring data on the chain.In the PBFT algorithm, there was a problem that the Byzantine nodes and the normal nodes were selected as the master node with the same probability, a reputation-based practical Byzantine fault tolerance algorithm was proposed.Streaming data on the chain might cause network congestion, which simplified the consensus protocol and reduced the time complexity from O(n²) to O(n).A comparative experiment was conducted using Hyperledger Caliper to prove that the delay of the improved algorithm is lower than PBFT algorithm, and the throughput is higher than PBFT algorithm.A quantitative analysis of the possibility of attack and the probability of successful attack was carried out, and it was determined that the smart contract provides tamper-proof modification for the monitoring data on the chain.Comparative analysis proves that the proposed blockchain-based railway engineering construction safety monitoring data sharing model is good than other models in terms of consensus efficiency, TPS and block generation speed.…”
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