Advances in value-added depolymerization by catalytic fast pyrolysis of lignin by SHEN Weiwei, CAO Bin, HE Sirong, JIANG Ding, MU Mao, WANG Shuang*

“…However, there are challenges such as low product selectivity and poor product stability in the direct pyrolysis process, which limit the efficient conversion and economic viability of lignin-based conversion. …”
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GAPO: A Graph Attention-Based Reinforcement Learning Algorithm for Congestion-Aware Task Offloading in Multi-Hop Vehicular Edge Computing by Hongwei Zhao, Xuyan Li, Chengrui Li, Lu Yao

“…Efficient task offloading for delay-sensitive applications, such as autonomous driving, presents a significant challenge in multi-hop Vehicular Edge Computing (VEC) networks, primarily due to high vehicle mobility, dynamic network topologies, and complex end-to-end congestion problems. …”
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A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement by Yongho Jeong, Taeuk Noh, Yonghak Lee, Seonjae Lee, Kwangil Choi, Sujin Jeong, Sunghwan Kim

“…Although some models showed error rates of 7.8% and 7.4% in hip circumference measurements, this was attributed to the complexity of 3D structures and the challenges in selecting keypoint locations. …”
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Five-Level MLI-Based Grid-Connected Photovoltaic Systems: A Review on Control Methodologies, Modulation Strategies and Recent Developments by Anurag Tiwari, Vinayak Kumar, Ruchi Agarwal, Mohammad Amir, Mohammed A. Alharbi, S. M. Muyeen

“…Examples of these techniques include pulse width modulation (PWM) and selective harmonic elimination (SHE). Further analysis of the structural features of five-level MLI-based systems is done, which helps to clarify the trade-offs between complexity, dependability, and cost. …”
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High-Switching-Frequency SiC Power Conversion Systems with Improved Finite Control Set Method Prediction Control by Yibiao Fan, Lixia Tong, Yingjie Lu, Xiaowei Cai, Zhihe Fu, Xingkui Mao

“…This simple improved strategy can reduce the computational complexity of traditional MPC for rolling optimization, resulting in a reduction in the vectors from 27 to 8. …”
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ANTIFUNGAL POTENTIAL OF BIOACTIVE COMPOUNDS OF BIOWASTE FRUIT PEEL OF PUNICA GRANATUM AGAINST PATHOGENIC FUNGI by RICHA SAXENA, RICHA SHARMA, GAJANAND SHARMA, PANKAJ SAXENA

“…Therefore, the current study aims to account the PG II fraction of biowaste fruit peel of P. granatum is a major source of polyphenolic complexes. Although, the present study recommended the pomegranate biowaste fruit peel that can place as a relatively more precious plant source of herbal secondary metabolites for rising novel efficient food-pharma constituents with encouraging human being fitness.…”
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The Function of TiO2 with Respect to Sensitizer Stability in Nanocrystalline Dye Solar Cells by A. Barkschat, T. Moehl, B. Macht, H. Tributsch

“…In presence of TiO2, it is enhanced by formation of a stabilizing charge-transfer complex between oxidized Ru dye and back-bonding interfacial Ti3+ states. …”
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A Review on New Frontiers in Drug-Drug Interaction Predictions and Safety Evaluations with In Vitro Cellular Models by Lara Marques, Nuno Vale

“…While indispensable, these approaches have inherent limitations in scalability, cost, and ability to predict complex interactions. Recent advancements in analytical technologies, particularly the development of more sophisticated cellular models and computational modeling, have paved the way for more accurate and efficient DDI assessments. …”
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Evaluating a Hybrid LLM Q-Learning/DQN Framework for Adaptive Obstacle Avoidance in Embedded Robotics by Rihem Farkh, Ghislain Oudinet, Thibaut Deleruyelle

“…The LLM addresses traditional Q-learning limitations, such as slow convergence and poor adaptability, by analyzing action histories and optimizing decision-making policies in complex, dynamic environments. A selective triggering mechanism ensures efficient LLM intervention, minimizing computational overhead. …”
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Dynamic Ionic Environment Modulation for Precise Electrosynthesis of Heterostructured Bimetallic Nanoparticles by Heekwon Lee, Xun Zhan, Jamie H. Warner, Hang Ren

“…The high spatial resolution and on‐demand control over the composition and structure make this method well‐suitable for creating arrays of complex, multi‐metallic heterostructures, which is expected to accelerate the discovery of advanced electrocatalytic materials, offering a platform for efficient and scalable electrocatalyst screening.…”
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Space Trajectory Planning with a General Reinforcement-Learning Algorithm by Andrea Forestieri, Lorenzo Casalino

“…Space trajectory planning is a complex combinatorial problem that requires selecting discrete sequences of celestial bodies while simultaneously optimizing continuous transfer parameters. …”
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Thermostabilization of the Human Serotonin Transporter in an Antidepressant-Bound Conformation. by Evan M Green, Jonathan A Coleman, Eric Gouaux

“…To identify a human SERT (hSERT) construct suitable for detailed biochemical and structural studies, we developed an efficient thermostability screening protocol and rapidly screened 219 mutations for thermostabilization of hSERT in complex with the SSRI paroxetine. …”
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Dual-Resource Scheduling with Improved Forensic-Based Investigation Algorithm in Smart Manufacturing by Yuhang Zeng, Ping Lou, Jianmin Hu, Chuannian Fan, Quan Liu, Jiwei Hu

“…In the first stage, an improved multi-objective FBI algorithm is used to obtain the Pareto front solutions of this model, in which a hybrid real and integer encoding–decoding method is used for exploring the solution space and a fast non-dominated sorting method for improving efficiency. In the second stage, a multi-criteria decision analysis method based on an analytic hierarchy process (AHP) is used to select the optimal solution from the Pareto front solutions. …”
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Detection of Mycotoxins in Cereal Grains and Nuts Using Machine Learning Integrated Hyperspectral Imaging: A Review by Md. Ahasan Kabir, Ivan Lee, Chandra B. Singh, Gayatri Mishra, Brajesh Kumar Panda, Sang-Heon Lee

“…Mycotoxins exhibit heightened sensitivity to specific spectral bands within HSI, facilitating accurate detection. Additionally, selecting only relevant spectral features reduces ML model complexity and enhances reliability in the detection process. …”
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Manipulating photodissociation dynamics via an embedding UV pulse by Yan Rong Liu, Xin Bai, Quan Wei Nan, Victor Kimberg, Maomao Gong, Yu Kun Yang, Yongjun Cheng, Jing Chen, Oriol Vendrell, Kiyoshi Ueda, Jan-Michael Rost, Song Bin Zhang

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Assessment of pollution and risk of soil pollution in Bor using different indices by Nikolić Violeta, Staletović Novica, Presburger-Ulniković Vladanka, Jovanović Ivan

“…Pearson's correlation coefficients indicated a strong correlation between Cu and Pb (0.887), Cu and As (0.953), Pb and As (0.960) and Cr and Ni (0.889). …”
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Streamlined Bearing Fault Detection Using Artificial Intelligence in Permanent Magnet Synchronous Motors by Javier de las Morenas, Lidia M. Belmonte, Rafael Morales

“…Permanent magnet synchronous motors (PMSMs) are widely used in industrial applications due to their high efficiency and reliability. However, bearing faults remain a critical issue, necessitating robust fault detection strategies. …”
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A hybrid blockchain-based solution for secure sharing of electronic medical record data by Gang Han, Yan Ma, Zhongliang Zhang, Yuxin Wang

“…To address the inherent complexity of managing multiple blockchains, a unique cross-chain signature algorithm is introduced, based on the Boneh-Lynn-Shacham (BLS) signature aggregation technique. …”
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BER performance analysis of polar-coded FBMC/OQAM in the presence of AWGN and Nakagami-m fading channel by Tadele A. Abose, Fanuel O. Ayana, Thomas O. Olwal, Yihenew W. Marye

“…It offers several advantages over traditional orthogonal frequency-division multiplexing (OFDM) modulation, including higher spectral efficiency, lower out-of-band emission, and improved robustness to time-frequency selective channels. …”
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An Interpretable Hybrid Deep Learning Model for Molten Iron Temperature Prediction at the Iron-Steel Interface Based on Bi-LSTM and Transformer by Zhenzhong Shen, Weigang Han, Yanzhuo Hu, Ye Zhu, Jingjing Han

“…This paper proposes an interpretable hybrid deep learning model combining Bi-LSTM and Transformer to solve the complexity of temperature drop prediction. By leveraging Catboost-RFECV, the most influential variables are selected, and the model captures both local features with Bi-LSTM and global dependencies with Transformer. …”
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