Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

“…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
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“Why would I bother?” Understanding prosumer motivations and engagement in renewable energy communities: a qualitative study of polish photovoltaic installation owners by Maksymilian Bielecki, Ewa Neska, Anna Kowalska-Pyzalska

“…The development and efficient functioning of RECs depend not only on technical or economic factors but also on numerous socio-psychological variables deeply rooted in local historical, political, economic, and cultural contexts. …”
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Research on the Planning and Design of Med–Small-Sized Hospitals in China Based on Patient Perceived Value in the Context of Healthcare Model Transformation by Yunhui Zhu, Ying Zhou

“…There are 24 observed variables in six dimensions, including cost value, functional value, social value, cognitive value, patient satisfaction, and patient loyalty. …”
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Development of a Data‐Driven Lightning Scheme for Implementation in Global Climate Models by Vincent Verjans, Christian L. E. Franzke

“…Abstract This study proposes a new lightning scheme applicable at the global scale, predicting lightning rates from climatic variables. Using satellite lightning records spanning a period of 29 years, we apply machine learning methods to derive a functional relationship between lightning and climate reanalysis data. …”
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Multi-Objective Routing and Categorization of Urban Network Segments for Cyclists by Konstantinos Theodoreskos, Konstantinos Gkiotsalitis

“…Data collection methods include GPS tracking, field measurements, and qualitative approaches to understand cyclists’ behavior and preferences. Nine objective functions are constructed based on criteria related to safety and comfort, incorporating decision variables related to cyclists riding on sidewalks, capturing the complexity of urban cycling infrastructure. …”
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Removal of <i>para</i>-Phenylenediamine (PPD) Dye from Its Aqueous Solution by Adsorption Using the Activated Carbon Nanoparticles by Shabaa Fayyad Bdewi, Hanaa Hassan Hussein, Shireen Abdulmohsin Azeez

“…This study focused on the development of an efficient preparation method of activated carbon for the removal of para-phenylenediamine (PPD) dye in an aqueous solution. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…A novel application of RL for dynamic feature refinement and adjustment based on reward functions was employed to optimize the detection capabilities of the model. …”
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Vibration Analysis of Rotating Tapered Timoshenko Beams by a New Finite Element Model by Bulent Yardimoglu

“…A new finite element model is developed and subsequently used for transverse vibrations of tapered Timoshenko beams with rectangular cross-section. The displacement functions of the finite element are derived from the coupled displacement field (the polynomial coefficients of transverse displacement and cross-sectional rotation are coupled through consideration of the differential equations of equilibrium) approach by considering the tapering functions of breadth and depth of the beam. …”
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RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. …”
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Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849 by L. Zhu, L. Zhu, L. Zhu, L. Zhu, P. Ciais, Y. Yao, D. Goll, S. Luyssaert, I. Martínez Cano, A. Fendrich, A. Fendrich, L. Li, H. Yang, S. Saatchi, W. Li, W. Li

“…Current dynamic global vegetation models (DGVMs), which use one or two plant functional types for tropical rainforests, fail to capture observed biomass and mortality gradients in this region, raising concerns about their ability to predict forest responses to global change drivers. …”
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The Relationship Between Supply Environment, Supply Chain Integration and Performance Considering Opportunistic Behaviors by Abbas َAsadi, safanaz Heidari

“…Then, inferential statistics are employed to explain the relationships between variables and generalize the results to the society. …”
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Impact of Wall Material Composition (Maltodextrin vs. Inulin vs. Nutriose) and Emulsion Preparation System (Nano- vs. Microemulsion) on Properties of Spray-Dried Linseed Oil by Dorota Ogrodowska, Iwona Zofia Konopka, Grzegorz Dąbrowski, Beata Piłat, Józef Warechowski, Fabian Dajnowiec, Małgorzata Tańska

“…For these independent variables, the properties of the prepared emulsions (flow curves and viscosity) and the resulting powders (encapsulation efficiency, particle size distribution, water activity, bulk and tapped density, Carr’s index, color parameters, and thermal stability) were determined. …”
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Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB by Francesco Paciolla, Giovanni Popeo, Alessia Farella, Simone Pascuzzi

“…Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. …”
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Bioactive compounds from tropical fruit by-products: Extraction, characterization and therapeutic potential by Niza Otero-Guzman, Ricardo Andrade-Pizarro

“…However, there are several challenges associted with the efficient extraction and accurate characterization of these compounds, including the complexity of plant matrices, variability in compound polarity, and the need for scalable, eco-friendly methods that preserve their bioactivity. …”
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Transcriptome profiling of Hyacinthus orientalis L. cultivars in floral pigmentation by Kwan-Ho Wong, Hoi-Yan Wu, Cheryl Wood-Yee Shum, Jerome Ho-Lam Hui, Pang-Chui Shaw, David Tai-Wai Lau

“…In addition, the usability of the dataset was demonstrated by the identification of differentially expressed genes, functional annotation and functional enrichment analysis. …”
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Enhancing access to specialist appointments in tertiary healthcare in Shanghai, China: a structured reservation pathway using digital health technologies by Li Li, Tao Zheng, Enhong Dong, Minjie Chen, Xiaojing Zhao, Binyuan Zhang, Xuji Zhao, Weijun Shao, Yiling Fan

“…Objective The aim of this study is to develop, implement the precise reservation path (PRP) and investigate its prediction function for scheduling shunting patients for specialist appointment registration in Shanghai, China.Design The PRP system was built on the hospital’s existing information system, integrated with WeChat (WeCom) for user convenience. …”
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