Waste Biomass Pretreatments for Biogas Yield Optimization and for the Extraction of Valuable High-Added-Value Products: Possible Combinations of the Two Processes toward a Biorefin... by Jessica Di Mario, Nicolò Montegiove, Alberto Maria Gambelli, Monica Brienza, Claudia Zadra, Giovanni Gigliotti

“…To address these challenges, various pretreatments are employed to enhance digestion efficiency and mitigate issues associated with biomass complexity. …”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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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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Monitoring the Occurrence of <i>Aspergillus</i> in the Air of Intensive Care Units by Anna Inglot, Agnieszka Gniadek, Zuzanna Tokarz, Wirginia Krzyściak, Monika Papież, Paweł Krzyściak

“…The highest concentration of <i>Aspergillus</i> species complexes was detected during autumn, while the lowest was in spring. …”
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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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Adaptive Neuro-Fuzzy System for Detection of Wind Turbine Blade Defects by Lesia Dubchak, Anatoliy Sachenko, Yevgeniy Bodyanskiy, Carsten Wolff, Nadiia Vasylkiv, Ruslan Brukhanskyi, Volodymyr Kochan

“…The proposed adaptive neuro-fuzzy inference system processes the data vectors with lower complexity and higher accuracy. For this purpose, the authors explored grid partitioning and subtractive clustering methods and selected the last one because it uses three rules only for fault detection, ensuring low computational costs and enabling the discovery of wind turbine defects quickly and efficiently. …”
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Apply Ridge Regression Model to Predict the Lateral Velocity Difference of Tight Reservoirs by HAN Longfei, ZHANG Yongfei, WANG Miaomiao, LI Yu

“…The random forest algorithm is used to rank the influence factors, and the vertical wave time lag, bulk density, and compensated neutron logging curves are selected as the input parameters of the lateral wave time lag prediction model to reduce the complexity of the model. …”
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Hydraulic-thermal decoupling simulation model for transient operation of natural gas pipeline networks by Chunyu YU, Chunhao YU, Gang LIU, Rui LIU, Fang YANG, Yang QIN, Lili ZUO, Qian CHEN

“…Currently, the primary challenge in transient operation simulation technology for natural gas pipeline networks is the complexity of the nonlinear coupling of spatial and temporal variables, making it urgent to enhance the calculation efficiency of the simulation process. …”
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IMix: a user-friendly application for source partitioning using stable isotopes by Wenchen Song, Fei Li, Chuyang Luo

“…Results IMix is an accurate and easy-to-use tool that simplifies the calculation of source partitioning using stable isotopes and eliminates the associated complexity and uncertainty. It can also automatically analyse the advantages and disadvantages of isotope mixing models and automatically select the optimal mixing model based on user data. …”
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Simultaneous multi-objective framework of natural gas pipeline network operations by Mohamed Mostafa Hassanein Hussein

“…The method generates a diverse set of Pareto optimal solutions, empowering decision-makers to select the most suitable solution for gas transportation networks. …”
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Evaluation of Sustainable Performance of Industry 4.0 Technologies Using a Novel Fuzzy OPLO-POCOD Method by Reza Sheikh, Soheila Senfi

“…In the rapidly evolving landscape of decision-making, particularly amid the complexities of managing extensive data, it is crucial to develop methodologies that facilitate informed choices. …”
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Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area by M. Sofiya, M. Arulmozhi

“…Abstract In recent years, smart agricultural environments have gained attention for enhancing farming efficiency and productivity. These systems use smart sensors integrated with Internet of Things (IoT) devices to collect data such as temperature, soil moisture, and humidity, helping to improve yield and optimize water usage. …”
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Hemoglobin-Derived Antioxidant Peptides from Beef Cattle in Ningxia: Identification Based on Computerized Screening and Molecular Docking by XU Feiran, WANG Yu, WANG Xiaojing, CUI Wei, WANG Yongkun, ZHOU Hui, WANG Zhaoming, CAI Kezhou, ZHANG Bao, XU Baocai

“…The potential antioxidant peptides were selected by computerized analysis and their activities were verified. …”
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Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…This decreases the complexity of the model without losing essential information. …”
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Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…A comprehensive comparative study demonstrates that our approach outperforms state-of-the-art models in both prediction accuracy and computational efficiency.…”
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An analysis of unconventional grid sizes for wind farm layout optimization using a genetic algorithm by Mohandes Mohamed, Khan Salman A., Rehman Shafiqur, Al-Shaikhi Ali, Iqbal Kashif

“…Results indicate that the maximum average conversion efficiency of 0.992 was obtained with a grid size of 19×19, while a grid size of 10×10 produced the minimum average conversion efficiency of 0.813. …”
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Advancing Monoclonal Antibody Manufacturing: Process Optimization, Cost Reduction Strategies, and Emerging Technologies by Ranbhor R

“…Integration of machine learning and advanced analytics has significantly enhanced process control and optimization capabilities.Conclusion: The evolution of mAb manufacturing technologies offers promising pathways for improving production efficiency and reducing costs. Scale-dependent considerations remain crucial in selecting optimal manufacturing strategies, while emerging technologies present new opportunities for process optimization. …”
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Molecular Fractionation Induced by Viscosity-Driven Segregative Phase Separation Behavior of Gum Arabic/Hydroxypropyl Methylcellulose by Lingyu Han, Cunzhi Zhang, Nuo Dong, Jixin Yang, Qiuyue Zheng, Xiaobo Zhang, Ronggang Liu, Jijuan Cao, Bing Hu

“…By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. …”
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