Wei Yang¹, Weicong Tan¹, Zhijian Zeng¹, Ren Li¹, Jie Qin¹, Yuting Xie¹, Yongjun Zhang², Runting Cheng², Dongliang Xiao^2,*

Energy Engineering, Vol.122, No.5, pp. 1697-1713, 2025, DOI:10.32604/ee.2025.060571 - 25 April 2025

Abstract The rapid development of electricity retail market has prompted an increasing number of electricity consumers to sign green electricity contracts with retail electricity companies, which poses greater challenges for the market service for green energy consumers. This study proposed a two-stage feature extraction approach for green energy consumers leveraging clustering and term frequency-inverse document frequency (TF–IDF) algorithms within a knowledge graph framework to provide an information basis that supports the green development of the retail electricity market. First, the multi-source heterogeneous data of green energy consumers under an actual market environment is systematically introduced and… More >

Perry Yang Tchie Hunn¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, Vol.122, No.5, pp. 1789-1804, 2025, DOI:10.32604/ee.2025.060124 - 25 April 2025

Abstract With growing interest in its potential applications across both stationary and transportation sectors, hydrogen has emerged as a promising alternative for environmentally responsible power generation. By replacing traditional fuels, hydrogen can significantly reduce greenhouse gas emissions in the transportation sector. This study focuses on the design and downsizing of a green hydrogen fuel cell car, aiming to scale the concept for larger vehicles. Key components, including fuel cells, electrolysers, and solar panels, were evaluated through extensive laboratory testing. The findings reveal that variations in sunlight impact the solar panel’s hydrogen production rate, with differences of… More > Graphic Abstract

Amelia Hariry¹, Efri Mardawati^1,2,*, Apri Heri Iswanto³, Tati Karliati⁴, Lukmanul Hakim Zaini^5,6,*, Muhammad Adly Rahandi Lubis^2,7

Journal of Renewable Materials, Vol.13, No.4, pp. 773-798, 2025, DOI:10.32604/jrm.2025.058359 - 21 April 2025

Abstract Nanocellulose-based adhesives are gaining attention as a viable alternative to conventional adhesives, offering benefits such as cost-effectiveness and scalability, which make them suitable for various sectors, including cosmetics, pharmaceuticals, biodegradable products, and as reinforcing agents in natural adhesives. This review delves into the current advancements in nanocellulose-based adhesive solutions for sustainable and eco-friendly wood composites, using systematic review methods and bibliometric analysis. Data were collected from the Scopus database, spanning from 2007 to 2024, and visualized using VOSviewer to highlight emerging trends in the field. The analysis revealed that nanocellulose shows great potential as a More >

Prans Brazdausks^*, Maris Puke, Guntis Sosins

Journal of Renewable Materials, Vol.13, No.4, pp. 719-730, 2025, DOI:10.32604/jrm.2025.057944 - 21 April 2025

Abstract Oat husks, a byproduct of oat milling operations with limited economic value, present a promising feedstock for biorefinery processes due to their chemical composition. This study investigates the conversion of C5 carbohydrates in oat husks into furfural through hydrothermal pretreatment using various phosphate-based catalysts, including H₃PO₄, NH₄H₂PO₄, NaH₂PO₄, KH₂PO₄, K₂HPO₄ and K₃PO₄ as catalyst. The catalysts’ effectiveness in promoting furfural production was evaluated under identical hydrothermal conditions (treatment time for 60 min at a constant temperature of 170°C and a catalyst amount). Continuous water steam was used to strip furfural from the reaction zone and minimize its degradation.… More > Graphic Abstract

YONGFENG CHENG¹, YIPING SHEN², YUNFEI ZHANG¹, HAILIQIGULI NURIDING¹, XUEMEI WANG¹, CHUNYAN FAN¹, GULIBAHA MAIMAITI¹, YU LIU¹, YINGBIN YUE¹, DANLU LI¹, MEI YAN^1,*

Oncology Research, Vol.33, No.5, pp. 1173-1187, 2025, DOI:10.32604/or.2025.057842 - 18 April 2025

Abstract Background: The growth of the B-cell lymphoma subtype, Hodgkin lymphoma (HL), is associated with increased autophagy. A mycobacterial antigen, Ag85, has been reported to inhibit cell autophagy under a variety of conditions. Whether Ag85 could inhibit autophagy in HL is unknown. Methods: Lymph node samples from patients with HL and healthy controls were collected to assess proliferation and autophagy. The human HL cell line, L-428, was cultured and subjected to Ag85B treatment. Autophagy in L-428 cells was evaluated through western blotting analysis, immunohistochemistry, and transmission electron microscopy. Apoptosis in these cells was measured using flow… More >

Oncology Research Editorial Office

Oncology Research, Vol.33, No.5, pp. 1253-1253, 2025, DOI:10.32604/or.2024.056916 - 18 April 2025

Abstract This article has no abstract. More >

XI ZHU^1,2,#, KAI HUANG^3,#, XIAOMING KAO², ZHAOHUI TANG³, WENJIE GUO³, TIANCONG WU^4,*, QIURONG LI^1,2,*

Oncology Research, Vol.33, No.5, pp. 1149-1159, 2025, DOI:10.32604/or.2024.054930 - 18 April 2025

Abstract Background: Colorectal cancer (CRC) holds the third position in global cancer prevalence mortality. Although chemotherapy is a conventional treatment, recent investigations have shed light on the therapeutic potential of the cGAS cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway in CRC management. Despite the primary role of the death domain-associated protein (Daxx) in cellular apoptosis, its influence on the regulation of cGAS-STING activation remains elusive. Methods: The Daxx degradation and speck formation were conducted using immunofluorescence and Western blotting. The Daxx knock-down and over-expression in CRC cells were performed to detect in vivo and in vitro… More >

Tareq Hamadneh¹, Belal Batiha², Omar Alsayyed³, Widi Aribowo⁴, Zeinab Montazeri⁵, Mohammad Dehghani^5,*, Frank Werner^6,*, Haider Ali⁷, Riyadh Kareem Jawad⁸, Ibraheem Kasim Ibraheem⁹, Kei Eguchi¹⁰

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2677-2718, 2025, DOI:10.32604/cmc.2025.064087 - 16 April 2025

Abstract In this study, a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm (BaOA). Inspired by the human interactions between barbers and customers, BaOA captures two key processes: the customer’s selection of a hairstyle and the detailed refinement during the haircut. These processes are translated into a mathematical framework that forms the foundation of BaOA, consisting of two critical phases: exploration, representing the creative selection process, and exploitation, which focuses on refining details for optimization. The performance of BaOA is evaluated using 52 standard… More >

Yaping Qi^1,*, Weijie Yang^2,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1555-1559, 2025, DOI:10.32604/cmc.2025.064061 - 16 April 2025

Abstract AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization. Platforms such as Digital Catalysis Platform (DigCat) and Dynamic Database of Solid-State Electrolyte (DDSE) demonstrate how machine learning and predictive modeling can improve catalyst and solid-state electrolyte development. These databases facilitate data standardization, high-throughput screening, and cross-disciplinary collaboration, addressing key challenges in materials informatics. As AI techniques advance, materials databases are expected to play an increasingly vital role in accelerating research and innovation. More >

Sheik Mohideen Shah¹, Meganathan Selvamani¹, Mahesh Thyluru Ramakrishna^2,*, Surbhi Bhatia Khan^3,4,5, Shakila Basheer⁶, Wajdan Al Malwi⁷, Mohammad Tabrez Quasim⁸

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2907-2926, 2025, DOI:10.32604/cmc.2025.063809 - 16 April 2025

Abstract Efficient energy management is a cornerstone of advancing cognitive cities, where AI, IoT, and cloud computing seamlessly integrate to meet escalating global energy demands. Within this context, the ability to forecast electricity consumption with precision is vital, particularly in residential settings where usage patterns are highly variable and complex. This study presents an innovative approach to energy consumption forecasting using a bidirectional Long Short-Term Memory (LSTM) network. Leveraging a dataset containing over two million multivariate, time-series observations collected from a single household over nearly four years, our model addresses the limitations of traditional time-series forecasting… More >