Identifying missing sources and reducing NO_<i>x</i> emissions uncertainty over China using daily satellite data and a mass-conserving method by L. Lu, L. Lu, J. B. Cohen, J. B. Cohen, K. Qin, K. Qin, X. Li, X. Li, Q. He, Q. He

“…<span class="inline-formula">±</span> 68.9 Kt yr<span class="inline-formula">⁻¹</span> (163 % higher than the a priori), consistent with missing light and medium industries located along the river, contradicting previous studies attributing water as the source of NO<span class="inline-formula">_<i>x</i></span> emissions. …”
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Structural and ion transport characteristics of transparent proton conducting biopolymer electrolytes based on chitosan and cold water fish skin gelatin by Peshawa O. Hama, Shujahadeen B. Aziz, Omed Gh. Abdullah

“…Abstract In the current study transparent solid ion conducting biopolymer blend electrolytes consisting of chitosan/cold water fish skin gelatin were prepared utilizing casting methodology. …”
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Research on energy storage planning methods for distributed renewable energy integrated rural power distribution networks by Haoshuai Jia, Renqing Feng, Hai Jiang, Chao Gao, Yue Zhao, Rui Zhang, Ziyi Xuan

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Regression Analysis in Development of Method for Isolation and Quantitative Determination of Water-soluble Polysaccharides from Sunflower Roots of One-year-old by N. A. Dyakova

“…The aim of this study is to select optimal parameters of ultrasonic extraction of water-soluble polysaccharides from sunflower roots of oneyear old based on regression analysis.Materials and methods. …”
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Modelling of acid brown 14 and acid yellow 36 dyes adsorption from water by self-nitrogen-doped activated carbon by Mohamed A. El-Nemr, Mohamed A. Hassaan, Murat Yılmaz, Ahmed El Nemr

“…This study aims to manufacture self-nitrogen-doped porous activated carbon (AC7-800) and investigate its effectiveness in removing the AB14 and AY36 dyes from water solutions. The AC7-800 was created by combining fish waste (with a protein composition of 60% as a nitrogen source), which served as a self-nitrogen dopant. …”
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Evaluation and estimation of changes in water quality using zoning map and researchers-developed software (case study: Pir-Bazar river) by Majid Homami, Seyed Ahmad Mirbagheri, Seyed Mehdi Borghei, Madjid Abbaspour

“…Considering the positive and high values of the coefficient of performance for TP and TN between 0.87 and 0.918 (mean 0.894), it can be argued that phosphorus and nitrogen in this water basin are likely to share the same source; meanwhile the coefficient of performance varied between 0.187 and 0.721, showing the best performance for nitrate and phosphate, respectively.  …”
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Comprehensive evaluation and scenario simulation for determining the optimal conservation priority of ecological services in Danjiangkou Reservoir Area, China by Pengcheng Zhao, Lihui Wang, Yuhong Huang, Yifan Zhao, Qichi Yang, Jinliang Huang, Yun Du, Feng Ling

“…This study offers new insights into the quantification and visualization of the identification of optimal conservation priority. The outcomes serve as a reference for informing the protection and management strategies of water source areas and regions with a high supply of ESs.…”
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Kajian Potensi Energi Terbarukan Dan Wisata Sungai Cidurian Depan Universitas Widyatama by Raden Herdian Bayu Ash Shiddiq, Fuad Hasan, Sandy Radhitya Akbar, Roeshartono Roespinoedji

“…From the results of the analysis it is also known that river water still meets Class II water quality standards.   …”
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An Annual Peak Regulation Auxiliary Service Demand Assessment Model Based on Multi-time Scale Stochastic Optimization by Huorang LIU, Wei YAN, Zugui LIN, Hong TAN, Guoqiang LI, Xu WEN

“…For the short-term stage, the hourly power balance of source-load and its fluctuation is considered to optimize the units output on a ten-day basis according to the mid-and-long term plan. …”
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Simulation of the Power Generation Process of a Solid Oxide Fuel Cell Powered by Green Hydrogen from an Alkaline Water Electrolysis by Pedro C. Dias, Alexander Polasek, Jose G. M. Furtado, Alexandre V. Grillo, Roberto B. de Carvalho, Brunno F. dos Santos

“…To address this challenge, there is a growing interest in sustainable energy sources with lower environmental impact, such as green hydrogen. …”
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Use of Chitosan and Chitosan–Magnetite Spheres for Arsenic Groundwater Removal: Factorial Designs as Tools to Optimize the Efficiency of Removal by Mayra Hernández Trespalacios, María Florencia Mangiameli, Lina Gribaudo, María Inés Frascaroli, Juan Carlos González

“…In Santa Fe, Argentina, the population uses groundwater as a source of drinking water. Unfortunately, it has high concentrations of As(V), which makes it unsuitable for consumption. …”
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Statistical optimization of process variables for improved poly(ethylene terephthalate) plastic degradation by a rhizospheric bacterial consortium by Vaishali Dhaka, Simranjeet Singh, Raman Rao, Shashank Garg, Jastin Samuel, Nadeem A. Khan, Praveen C. Ramamurthy, Joginder Singh

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Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter by J. Lee, M.-I. Lee, S. Tak, E. Seo, E. Seo, Y.-K. Lee

“…This approach constitutes an objective method that optimally combines two previously unattempted incomplete data sources: the satellite SWE retrieval from the Advanced Microwave Scanning Radiometer 2 (AMSR2) and dynamically balanced SWE from the JULES land surface model. …”
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Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

“…Total nitrogen (TN) is one of the important indicators to reflect the degree of water pollution and measure the eutrophication status of lakes and reservoirs.To improve the accuracy of TN prediction,based on the empirical wavelet transform (EWT) and wavelet packet transform (WPT) decomposition technology,this paper proposes a Gaussian process regression (GPR) prediction model optimized by osprey optimization algorithm (OOA),rime optimization algorithm (ROA),bald eagle search (BES) and black widow optimization algorithm (BWOA) respectively.Firstly,the TN time series is decomposed into several more regular subsequence components by EWT and WPT respectively.Then,the paper briefly introduces the principles of OOA,ROA,BES,and BWOA algorithms and applies OOA,ROA,BES,and BWOA to optimize GPR hyperparameters.Finally,EWT-OOA-GPR,EWT-ROA-GPR,EWT-BES-GPR,EWT-BWOA-GPR,WPT-OOA-GPR,WPT-ROA-GPR,WPT-BES-GPR,WPT-BWOA-GPR models (EWT-OOA-GPR and other eight models for short) are established to predict the components of TN by the optimized super-parameters.The final prediction results are obtained after reconstruction,and WT-OOA-GPR,WT-ROA-GPR,WT-BES-GPR and WT-BWOA-GPR models based on wavelet transform (WT) are built.Eight models,including EWT-OOA-SVM based on support vector machine (SVM),the paper compares the unoptimized EWT-GPR,WPT-GPR models,and the uncomposed OOA-GPR,ROA-GPR,BES-GPR,and BWOA-GPR models.The models were verified by the monitoring TN concentration time series data of Mudihe Reservoir,an important drinking water source in China,from 2008 to 2022.The results are as follows.① The average absolute percentage error of eight models such as EWT-OOA-GPR for TN prediction is between 0.161% and 0.219%,and the coefficient of determination is 0.999 9,which is superior to other comparison models,with higher prediction accuracy and better generalization ability.② EWT takes into account the advantages of WT and EMD.WPT can decompose low-frequency and high-frequency signals at the same time.Both of them can decompose TN time series data into more regular modal components,significantly improving the accuracy of model prediction,and the decomposition effect is better than that of the WT method.③ OOA,ROA,BES,and BWOA can effectively optimize GPR hyperparameters and improve GPR prediction performance.…”
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Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency by Anup Kumar, Bhupendra K. Sharma, Bandar Almohsen, Laura M. Pérez, Kamil Urbanowicz

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Agricultural production structure adjustment based on a multi-objective control in the Tiaoxi watershed by YE Zhennan, WANG Fei’er, JI Lingye, YU Jie

“…The optimization of agricultural production structure is an important way to control the agricultural non-point source (NPS) pollution. …”
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Integrated thermal and battery management for electric vehicles: Experimental validation and simulation-based optimization of lithium-ion batteries by Pujari Harish Kumar, Gayathri Raju, Mohit Bajaj, Nallolla Chinna Alluraiah, Pasala Gopi, Sunil Kumar Pulumithi, Reshma Gopi Remabhai, Rashmi Gangadhar, Ievgen Zaitsev

“…However, lithium-ion batteries (LIBs), the primary energy source for EVs, face critical thermal management, safety, and long-term efficiency challenges. …”
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A Refined Terrace Extraction Method Based on a Local Optimization Model Using GF-2 Images by Guobin Kan, Jie Gong, Bao Wang, Xia Li, Jing Shi, Yutao Ma, Wei Wei, Jun Zhang

“…Finally, we utilized multi-source RS data along with terrain elements for correction and optimization to generate a 1 m resolution terrace distribution map in the Zuli River Basin (TDZRB). …”
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Thermal performance analysis of quaternary hybrid nanofluids with radiative and Joule heating effects in magnetohydrodynamic flow over a stretched surface by Faisal Mumtaz, A. Al-Zubaidi, Tasawar Abbas, S. Saleem

“…In this study, the thermal behavior of hybrid nanofluids (HNFs) composed of aluminum (Al2O3), titanium (TiO2), copper (Cu), and silver (Ag) nanoparticles dispersed in water. Hybrid nanofluids are considered for two-dimensional unsteady flow over porous stretched sheets under the influence of an inclined magnetic field and a non-uniform heat source/sink. …”
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Integrating geospatial technologies and AHP for optimal urban green space development: a case study of Gondar, Ethiopia by Bewketu Kiberet, Assayew Nebere, Bantayehu Ayalew Workineh, Muralitharan Jothimani

“…Applying the Analytic Hierarchy Process (AHP), the study assesses seven key factors: land use, road access, soil quality, proximity to water sources, population density, historical landmarks, and slope suitability. …”
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