Synergistic co-metabolism enhancing the crude oil degradation by Acinetobacter oleivorans DR1 and its metabolic potential by Lairenjam Paikhomba Singha, Renuka Kumari, Keisam Malabika Singha, Piyush Pandey, Pratyoosh Shukla

“…ABSTRACT Bacterial degradation of hydrocarbons during co-metabolism with glucose often resulted in variable degradation efficiency. This study explored the mechanistic understanding of the metabolic response during co-metabolism in Acinetobacter oleivorans DR1 using a metabolomics approach. …”
Get full text

Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

Get full text

Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions by Binrui Liu, Xinguang He, Wenkai Lyu, Lizhi Tao

“…A Physics-Data Learning (PDL) model is first formed by adding a complementary physical variable generated by Penman–Monteith (PM) equation to a deep learning (DL) model along with driving variables to regress latent heat flux. …”
Get full text

Ammonia Gas Adsorption in Fixed Bed and Fluidized Bed Using Bentonite Particles by Gabriela Muntianu, Ana-Maria Georgescu, Ana-Maria Rosu, Nicoleta Platon, Vasilica Alisa Arus, Cosmin Valeriu Jinescu, Ileana Denisa Nistor

“…Fluidized bed adsorption can be an efficient technique to accelerate mass transfer between ammonia from air and adsorbent particles.…”
Get full text

Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…During the optimization process, these controlling parameters are used as a design variable whereas the objective function required to me be a maximum is the summation of turbidity removal and salinity removal. …”
Get full text

Application of marine bacterial alginate lyases in wastewater treatment, biofilm removal and green technology by M.U.K. Anjung, H. Nursyam, A.A. Prihanto, E. Chasanah

“…Despite notable progress, challenges remain in achieving efficient large-scale production, enhancing enzyme robustness, and fine-tuning catalytic properties. …”
Get full text

Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The input solar PV power data are broken down into intrinsic mode functions (IMFs) using EMD technique is fed into the PSO-ANFIS, along with important meteorological variables. …”
Get full text

Engineering safe anti-CD19-CD28ζ CAR T cells with CD8a hinge domain in serum-free media for adoptive immunotherapy by Muthuganesh Muthuvel, Muthuganesh Muthuvel, Thamizhselvi Ganapathy, Trent Spencer, Sunil S. Raikar, Saravanabhavan Thangavel, Alok Srivastava, Alok Srivastava, Alok Srivastava, Sunil Martin

“…CARs are modular synthetic antigen receptors integrating the single-chain variable fragment (scFv) of an immunoglobulin molecule to the TCR signaling. …”
Get full text

A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

“…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
Get full text

Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
Get full text

Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
Get full text

COVID-19 recovery: benefits of multidisciplinary respiratory rehabilitation by Wim Janssens, Greet Hermans, Rik Gosselink, Daniel Langer, Thierry Troosters, Hilde Beyens, Stephanie Everaerts, Arne Heyns, Natalie Lorent

“…Impressive results on physical recovery were determined after 6 weeks and 3 months, with significant improvement of lung function, muscle force and exercise capacity variables. …”
Get full text

Signatures of Rapidly Rotating Stars with Chemically Homogeneous Evolution in the First Galaxies by Boyuan Liu, Yves Sibony, Georges Meynet, Volker Bromm

“…We find that the rest-frame UV luminosity of star-forming galaxies can be significantly enhanced by a factor of  ∼3−6 when CHE stars above a minimum initial mass of ${m}_{\star ,\min }^{\mathrm{CHE}}\sim 2-10\,{M}_{\odot }$ account for more than half of the total stellar mass following a Salpeter initial mass function. As a result, the UV luminosity functions observed at z  ∼ 12−16 can be reproduced with less extreme values of star formation efficiency and UV luminosity stochastic variability. …”
Get full text

Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong, Chaohai Li

“…Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. …”
Get full text

Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
Get full text

Robust Optimization Research of Cyber–Physical Power System Considering Wind Power Uncertainty and Coupled Relationship by Jiuling Dong, Zilong Song, Yuanshuo Zheng, Jingtang Luo, Min Zhang, Xiaolong Yang, Hongbing Ma

“…Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology–function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. …”
Get full text

Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks by Ehsan Kharati

“…For this purpose, we need to calculate the derivative of the Lagrangian function relative to its variables, in order to determine the condition as a multi-excited multi-equation device. …”
Get full text

Retrieval of carbon and inorganic phosphorus during hydrothermal carbonization: ANN and RSM modeling by Abolfazl Shokri, Mohammad Amin Larki, Ahad Ghaemi

“…Next, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were used to compare the results and improve the model fit. …”
Get full text

Support vector regression model for the prediction of buildings’ maximum seismic response based on real monitoring data by Dongwang Tao, Shizhe Fang, Haixu Liu, Jianqi Lu, Jiang Wang, Qiang Ma

“…Our results demonstrate that SVR-MDR model outperform other machine learning models such as kernel ridge regression and decision tree models, and SVR-MDR and RSVR-MDR models outperform conventional loglinear regression and multinomial models, because SVR can map the complex nonlinear function of multiple variables and consider the available information of buildings especially the fundamental frequency. …”
Get full text

Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

“…However, significant variability within high‐frequency data sets can result in poor explanation of temporal dynamics using the simple C‐Q equation. …”
Get full text