Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.03.031
Yanli Liu , Xin Chen , Jianyun Zhang , Xing Yuan , Tiesheng Guan , Junliang Jin , Guoqing Wang
Soil could represent a potentially notable source of carbon for achieving global carbon neutrality. However, how the land surface soil organic carbon (SOC) stock, which is more sensitive to climate change than other carbon stocks, will change naturally under the influence of global warming remains unknown. In this work, the global land surface SOC trends from 1981 to 2019 were explored, and the driving factors were identified. A random forest model (a type of machine learning method) was proposed to predict future global surface SOC trends integrated with climate scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The results revealed that the global surface SOC content will increase, while the temperature and precipitation are the main climate drivers at the global scale, and vegetation cover is a crucial local factor influencing the increase in SOC. However, under the 1.5 °C global warming scenario, the land SOC sink will increase by 13.0 petagram carbon (PgC) at most compared with that under the SSP2-4.5 scenario, which accounts for only 19% of the total carbon emission capacity at the current 1.1 to 1.5 °C global warming level. Moreover, this value is far from the Paris Agreement target of four out of one thousand for the annual increase in the soil carbon stock 40 cm below the surface over the next 20 years (2.72 PgC·a−1). This illustrates that overreliance on natural carbon sinks is a high-risk strategy. These findings highlight the urgency of implementing mitigation and removal strategies to reduce greenhouse gas emissions.
{"title":"Nature-Based Global Land Surface Soil Organic Carbon Indicates Increasing Driven by Climate Change","authors":"Yanli Liu , Xin Chen , Jianyun Zhang , Xing Yuan , Tiesheng Guan , Junliang Jin , Guoqing Wang","doi":"10.1016/j.eng.2025.03.031","DOIUrl":"10.1016/j.eng.2025.03.031","url":null,"abstract":"<div><div>Soil could represent a potentially notable source of carbon for achieving global carbon neutrality. However, how the land surface soil organic carbon (SOC) stock, which is more sensitive to climate change than other carbon stocks, will change naturally under the influence of global warming remains unknown. In this work, the global land surface SOC trends from 1981 to 2019 were explored, and the driving factors were identified. A random forest model (a type of machine learning method) was proposed to predict future global surface SOC trends integrated with climate scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The results revealed that the global surface SOC content will increase, while the temperature and precipitation are the main climate drivers at the global scale, and vegetation cover is a crucial local factor influencing the increase in SOC. However, under the 1.5 °C global warming scenario, the land SOC sink will increase by 13.0 petagram carbon (PgC) at most compared with that under the SSP2-4.5 scenario, which accounts for only 19% of the total carbon emission capacity at the current 1.1 to 1.5 °C global warming level. Moreover, this value is far from the Paris Agreement target of four out of one thousand for the annual increase in the soil carbon stock 40 cm below the surface over the next 20 years (2.72 PgC·a<sup>−1</sup>). This illustrates that overreliance on natural carbon sinks is a high-risk strategy. These findings highlight the urgency of implementing mitigation and removal strategies to reduce greenhouse gas emissions.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 306-316"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.08.039
Fengyu Wang , Yuan Zheng , Wenjun Xu , Junxiao Liang , Ping Zhang , Zhu Han
Increasing demands for massive data transmission pose significant challenges to communication systems. Compared with traditional communication systems that focus on the accurate reconstruction of bit sequences, semantic communications (SemComs), which aim to deliver information connotation, are regarded as a key technology for sixth-generation (6G) mobile networks. Most current SemComs utilize an end-to-end (E2E) trained neural network (NN) for semantic extraction and interpretation, which lacks interpretability for further optimization. Moreover, NN-based SemComs assume that the application and physical layers of the protocol stack can be jointly trained, which is incompatible with current digital communication systems. To overcome those drawbacks, we propose a SemCom system that employs explicit semantic bases (Sebs) as the basic units to represent semantic connotations. First, a mathematical model of Sebs is proposed to build an explicit knowledge base (KB). Then, the Seb-based SemCom architecture is proposed, including both a communication mode and a KB update mode to enable the evolution of communication systems. Sem-codec and channel codec modules are designed specifically, with the assistance of an explicit KB for the efficient and robust transmission of semantics. Moreover, unequal error protection (UEP) is strategically implemented, considering communication intent and the importance of Sebs, thereby ensuring the reliability of critical semantics. In addition, a Seb-based SemCom protocol stack that is compatible with the fifth-generation (5G) protocol stack is proposed. To assess the effectiveness and compatibility of the proposed Seb-based SemComs, a case study focusing on an image-transmission task is conducted. The simulations show that our Seb-based SemComs outperform state-of-the-art works in learned perceptual image patch similarity (LPIPS) by over 20% under varying communication intents and exhibit robustness under fluctuating channel conditions, highlighting the advantages of the interpretability and flexibility afforded by explicit Sebs.
{"title":"Explicit Semantic-Base-Empowered Communications for 6G Mobile Networks","authors":"Fengyu Wang , Yuan Zheng , Wenjun Xu , Junxiao Liang , Ping Zhang , Zhu Han","doi":"10.1016/j.eng.2025.08.039","DOIUrl":"10.1016/j.eng.2025.08.039","url":null,"abstract":"<div><div>Increasing demands for massive data transmission pose significant challenges to communication systems. Compared with traditional communication systems that focus on the accurate reconstruction of bit sequences, semantic communications (SemComs), which aim to deliver information connotation, are regarded as a key technology for sixth-generation (6G) mobile networks. Most current SemComs utilize an end-to-end (E2E) trained neural network (NN) for semantic extraction and interpretation, which lacks interpretability for further optimization. Moreover, NN-based SemComs assume that the application and physical layers of the protocol stack can be jointly trained, which is incompatible with current digital communication systems. To overcome those drawbacks, we propose a SemCom system that employs explicit semantic bases (Sebs) as the basic units to represent semantic connotations. First, a mathematical model of Sebs is proposed to build an explicit knowledge base (KB). Then, the Seb-based SemCom architecture is proposed, including both a communication mode and a KB update mode to enable the evolution of communication systems. Sem-codec and channel codec modules are designed specifically, with the assistance of an explicit KB for the efficient and robust transmission of semantics. Moreover, unequal error protection (UEP) is strategically implemented, considering communication intent and the importance of Sebs, thereby ensuring the reliability of critical semantics. In addition, a Seb-based SemCom protocol stack that is compatible with the fifth-generation (5G) protocol stack is proposed. To assess the effectiveness and compatibility of the proposed Seb-based SemComs, a case study focusing on an image-transmission task is conducted. The simulations show that our Seb-based SemComs outperform state-of-the-art works in learned perceptual image patch similarity (LPIPS) by over 20% under varying communication intents and exhibit robustness under fluctuating channel conditions, highlighting the advantages of the interpretability and flexibility afforded by explicit Sebs.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 34-44"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145025298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.04.012
Hongwei Yu , He Ji , Yang Li , Jing Qi , Baiwen Ma , Chengzhi Hu , Jiuhui Qu
Historical legacy effects and the mechanisms underlying primary producer community succession are not well understood. In this study, environmental DNA (eDNA) sequencing technology and chronological sequence analysis in sediments were utilized to examine long-term changes in cyanobacterial and aquatic plant communities. The analysis results indicate that the nutritional status and productivity of aquatic ecosystems have been relatively high since 2010, which could reflect a period of eutrophication due to high long-term rates of organic matter deposition (33.22–42.08 g·kg−1). The temporal and spatial characteristics of community structure were related to environmental filtering based on trophic status between 1849 and 2020. Turnover in the primary producer community was confirmed through change-point model analyses with regime shifts toward new ecological states. On the basis of ecological data and geochronological techniques, it was determined that the quality of habitats at a local scale may affect ecological niche shifts between cyanobacterial and aquatic plant communities. These observations suggest how primary producers respond to rapid urbanization, serving as an invaluable guide for protecting freshwater biodiversity.
{"title":"Long-Term Succession in Cyanobacteria and Aquatic Plant Communities: Insights from Sediment Analysis","authors":"Hongwei Yu , He Ji , Yang Li , Jing Qi , Baiwen Ma , Chengzhi Hu , Jiuhui Qu","doi":"10.1016/j.eng.2025.04.012","DOIUrl":"10.1016/j.eng.2025.04.012","url":null,"abstract":"<div><div>Historical legacy effects and the mechanisms underlying primary producer community succession are not well understood. In this study, environmental DNA (eDNA) sequencing technology and chronological sequence analysis in sediments were utilized to examine long-term changes in cyanobacterial and aquatic plant communities. The analysis results indicate that the nutritional status and productivity of aquatic ecosystems have been relatively high since 2010, which could reflect a period of eutrophication due to high long-term rates of organic matter deposition (33.22–42.08 g·kg<sup>−1</sup>). The temporal and spatial characteristics of community structure were related to environmental filtering based on trophic status between 1849 and 2020. Turnover in the primary producer community was confirmed through change-point model analyses with regime shifts toward new ecological states. On the basis of ecological data and geochronological techniques, it was determined that the quality of habitats at a local scale may affect ecological niche shifts between cyanobacterial and aquatic plant communities. These observations suggest how primary producers respond to rapid urbanization, serving as an invaluable guide for protecting freshwater biodiversity.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 296-305"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.04.026
Huanyu Li , Ziwei Yang , Chuanyu Zhang , Xueyong Wei , Wenjing Wang , Ting Bai , Zhichao Deng , Bowen Gao , Manli Cui , Weixuan Jing , Mingzhen Zhang , Zhaoxiang Yu , Mingxin Zhang
Ulcerative colitis (UC) is a chronic, non-specific inflammatory disorder of the intestines whose etiology is influenced by various factors. Intestinal barrier impairment due to disturbances in the intestinal microenvironment is a key feature of UC. Current therapeutic strategies are constrained in their capacity to fully restore the intestinal barrier and achieve comprehensive resolution of inflammation in a coordinated manner. In this study, we constructed a pterostilbene (PSB)-loaded prebiotic microcapsule (PSB@MC) using a microfluidic electrospray method and characterized it using various means. Its safety, biodistribution, protective, and therapeutic effects on colitis were evaluated in various animal models. The potential mechanisms by which PSB@MC exerts its therapeutic effects were subsequently explored. The results indicated that PSB@MC exhibited favorable biocompatibility and facilitated targeted delivery of PSB to the colon. Moreover, the wrinkled morphology of PSB@MC contributed to prolonged drug retention in the colon. Oral PSB@MC administration restored intestinal microenvironment homeostasis by scavenging reactive oxygen species (ROS), decreasing pro-inflammatory cytokines, modulating gut microbiota and metabolism, and providing protective and therapeutic benefits against dextran sulfate sodium-induced colitis. Additionally, our research demonstrated that PSB@MC could activate the aryl hydrocarbon receptor/interleukin-22 (AHR/IL-22) pathway to enhance the integrity of the intestinal barrier. These results suggest that PSB@MC could be a new, secure, and efficient UC therapy option.
{"title":"Prebiotic Microcapsule-Encapsulated Pterostilbene Alleviates Ulcerative Colitis by Regulating the Intestinal Microenvironment and Activating AHR/IL-22 Pathway","authors":"Huanyu Li , Ziwei Yang , Chuanyu Zhang , Xueyong Wei , Wenjing Wang , Ting Bai , Zhichao Deng , Bowen Gao , Manli Cui , Weixuan Jing , Mingzhen Zhang , Zhaoxiang Yu , Mingxin Zhang","doi":"10.1016/j.eng.2025.04.026","DOIUrl":"10.1016/j.eng.2025.04.026","url":null,"abstract":"<div><div>Ulcerative colitis (UC) is a chronic, non-specific inflammatory disorder of the intestines whose etiology is influenced by various factors. Intestinal barrier impairment due to disturbances in the intestinal microenvironment is a key feature of UC. Current therapeutic strategies are constrained in their capacity to fully restore the intestinal barrier and achieve comprehensive resolution of inflammation in a coordinated manner. In this study, we constructed a pterostilbene (PSB)-loaded prebiotic microcapsule (PSB@MC) using a microfluidic electrospray method and characterized it using various means. Its safety, biodistribution, protective, and therapeutic effects on colitis were evaluated in various animal models. The potential mechanisms by which PSB@MC exerts its therapeutic effects were subsequently explored. The results indicated that PSB@MC exhibited favorable biocompatibility and facilitated targeted delivery of PSB to the colon. Moreover, the wrinkled morphology of PSB@MC contributed to prolonged drug retention in the colon. Oral PSB@MC administration restored intestinal microenvironment homeostasis by scavenging reactive oxygen species (ROS), decreasing pro-inflammatory cytokines, modulating gut microbiota and metabolism, and providing protective and therapeutic benefits against dextran sulfate sodium-induced colitis. Additionally, our research demonstrated that PSB@MC could activate the aryl hydrocarbon receptor/interleukin-22 (AHR/IL-22) pathway to enhance the integrity of the intestinal barrier. These results suggest that PSB@MC could be a new, secure, and efficient UC therapy option.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 219-233"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144305545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.10.029
Hongda Liu , Le Yang , Yu Yang , Huan Tang , Junling Ren , Hui Sun , Xin Sun , Songyuan Tang , Chong Qiu , Ye Sun , Jigang Wang , Guangli Yan , Ling Kong , Ying Han , Xijun Wang
Rheumatoid arthritis (RA) remains a therapeutic challenge because of the suboptimal efficacy and significant adverse effects of current treatments. Obakulactone (OL), a natural tetracyclic triterpenoid isolated from Phellodendri cortex, has emerged as a promising candidate for RA intervention. However, its underlying mechanism remains poorly understood. In this study, we investigated the therapeutic effects of OL and its molecular mechanisms in RA using a multifaceted approach. A complete Freund’s adjuvant (CFA)-induced RA rat model revealed that OL significantly alleviated joint swelling and restored the expression of CD3+ T cells and CD68+ macrophages in joints, and the polarization state of macrophages shifted from proinflammatory M1 (CD86) to anti-inflammatory M2 (CD206) dominant. In addition, OL alleviated pathological changes in lymphoid organs (thymus and spleen), effectively inhibited the differentiation of CD4+ T cells into T helper 17 (Th17) cells, and normalized serum levels of inflammatory cytokines (e.g., interleukin (IL)-6 and tumor necrosis factor-α (TNF-α)) and RA diagnostic markers (e.g., c-reactive protein (CRP) and rheumatoid factor (RF)). Multiomics profiling revealed that OL corrected the dysregulated biosynthesis and metabolism of unsaturated fatty acids (e.g., arachidonic acid and linolenic acid) in RA rats, with acyl coenzyme A (CoA) thioesterase 1 (ACOT1) identified as a critical regulator. In vitro studies have shown that OL significantly inhibits cell proliferation and inflammatory cytokine secretion and promotes the apoptosis of RA synovial fibroblasts (SFs). It inhibited the M1 polarization of Raw264.7 macrophages and promoted M2 polarization. Mechanistically, cellular thermal shift assays (CETSA), microscale thermophoresis (MST), surface plasmon resonance (SPR), and short hairpin RNA (shRNA) experiments revealed ACOT1 as the direct target of OL. OL enhanced ACOT1 ubiquitination-mediated proteasomal degradation, thereby reducing downstream stearoyl-CoA desaturase-1 expression and inhibiting the Janus kinase (JAK)–signal transducer and activator of transcription (STAT) and phosphoinositide 3-kinase (PI3K)–protein kinase B (AKT) signaling pathways, thus suppressing inflammation and fibrosis in SFs. This study establishes OL as a potential RA therapeutic agent and highlights ACOT1 as a novel target for RA intervention, offering insights into fatty acid metabolism reprogramming as a therapeutic strategy.
{"title":"Obakulactone Alleviates Rheumatoid Arthritis by Promotion of ACOT1 Degradation via the Ubiquitin‒Proteasome Pathway and Restoration of Unsaturated Fatty Acid Homeostasis","authors":"Hongda Liu , Le Yang , Yu Yang , Huan Tang , Junling Ren , Hui Sun , Xin Sun , Songyuan Tang , Chong Qiu , Ye Sun , Jigang Wang , Guangli Yan , Ling Kong , Ying Han , Xijun Wang","doi":"10.1016/j.eng.2025.10.029","DOIUrl":"10.1016/j.eng.2025.10.029","url":null,"abstract":"<div><div>Rheumatoid arthritis (RA) remains a therapeutic challenge because of the suboptimal efficacy and significant adverse effects of current treatments. Obakulactone (OL), a natural tetracyclic triterpenoid isolated from <em>Phellodendri cortex</em>, has emerged as a promising candidate for RA intervention. However, its underlying mechanism remains poorly understood. In this study, we investigated the therapeutic effects of OL and its molecular mechanisms in RA using a multifaceted approach. A complete Freund’s adjuvant (CFA)-induced RA rat model revealed that OL significantly alleviated joint swelling and restored the expression of CD3<sup>+</sup> T cells and CD68<sup>+</sup> macrophages in joints, and the polarization state of macrophages shifted from proinflammatory M1 (CD86) to anti-inflammatory M2 (CD206) dominant. In addition, OL alleviated pathological changes in lymphoid organs (thymus and spleen), effectively inhibited the differentiation of CD4<sup>+</sup> T cells into T helper 17 (Th17) cells, and normalized serum levels of inflammatory cytokines (e.g., interleukin (IL)-6 and tumor necrosis factor-α (TNF-α)) and RA diagnostic markers (e.g., c-reactive protein (CRP) and rheumatoid factor (RF)). Multiomics profiling revealed that OL corrected the dysregulated biosynthesis and metabolism of unsaturated fatty acids (e.g., arachidonic acid and linolenic acid) in RA rats, with acyl coenzyme A (CoA) thioesterase 1 (ACOT1) identified as a critical regulator. <em>In vitro</em> studies have shown that OL significantly inhibits cell proliferation and inflammatory cytokine secretion and promotes the apoptosis of RA synovial fibroblasts (SFs). It inhibited the M1 polarization of Raw264.7 macrophages and promoted M2 polarization. Mechanistically, cellular thermal shift assays (CETSA), microscale thermophoresis (MST), surface plasmon resonance (SPR), and short hairpin RNA (shRNA) experiments revealed ACOT1 as the direct target of OL. OL enhanced ACOT1 ubiquitination-mediated proteasomal degradation, thereby reducing downstream stearoyl-CoA desaturase-1 expression and inhibiting the Janus kinase (JAK)–signal transducer and activator of transcription (STAT) and phosphoinositide 3-kinase (PI3K)–protein kinase B (AKT) signaling pathways, thus suppressing inflammation and fibrosis in SFs. This study establishes OL as a potential RA therapeutic agent and highlights ACOT1 as a novel target for RA intervention, offering insights into fatty acid metabolism reprogramming as a therapeutic strategy.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 341-360"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145454645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.07.022
Jinke Ren , Yaping Sun , Hongyang Du , Weiwen Yuan , Chongjie Wang , Xianda Wang , Yingbin Zhou , Ziwei Zhu , Fangxin Wang , Shuguang Cui
Semantic communication (SemCom) has emerged as a transformative paradigm for future wireless networks, aiming to improve communication efficiency by transmitting only the semantic meaning (or its encoded version) of the source data rather than the complete set of bits (symbols). However, traditional deep-learning-based SemCom systems present challenges such as limited generalization, low robustness, and inadequate reasoning capabilities, primarily due to the inherently discriminative nature of deep neural networks. To address these limitations, generative artificial intelligence (GAI) is seen as a promising solution, offering notable advantages in learning complex data distributions, transforming data between high- and low-dimensional spaces, and generating high-quality content.
This paper explores the applications of GAI in SemCom and presents a comprehensive study. It begins by introducing three widely used SemCom systems enabled by classical GAI models: variational autoencoders, generative adversarial networks, and diffusion models. For each system, the fundamental concept of the GAI model, the corresponding SemCom architecture, and a literature review of recent developments are provided. Subsequently, a novel generative SemCom system is proposed, incorporating cutting-edge GAI technology—large language models (LLMs). This system features LLM-based artificial intelligence (AI) agents at both the transmitter and receiver, which act as “brains” to enable advanced information understanding and content regeneration capabilities, respectively. Unlike traditional systems that focus on bitstream recovery, this design allows the receiver to directly generate the desired content from the coded semantic information sent by the transmitter. As a result, the communication paradigm shifts from “information recovery” to “information regeneration,” marking a new era in generative SemCom. A case study on point-to-point video retrieval is presented to demonstrate the effectiveness of the proposed system, showing a 99.98% reduction in communication overhead and a 53% improvement in average retrieval accuracy compared to traditional communication systems. Furthermore, four typical application scenarios for generative SemCom are described, followed by a discussion of three open issues for future research. In summary, this paper provides a comprehensive set of guidelines for applying GAI in SemCom, laying the groundwork for the efficient deployment of generative SemCom in future wireless networks.
{"title":"Generative Semantic Communication: Architectures, Technologies, and Applications","authors":"Jinke Ren , Yaping Sun , Hongyang Du , Weiwen Yuan , Chongjie Wang , Xianda Wang , Yingbin Zhou , Ziwei Zhu , Fangxin Wang , Shuguang Cui","doi":"10.1016/j.eng.2025.07.022","DOIUrl":"10.1016/j.eng.2025.07.022","url":null,"abstract":"<div><div>Semantic communication (SemCom) has emerged as a transformative paradigm for future wireless networks, aiming to improve communication efficiency by transmitting only the semantic meaning (or its encoded version) of the source data rather than the complete set of bits (symbols). However, traditional deep-learning-based SemCom systems present challenges such as limited generalization, low robustness, and inadequate reasoning capabilities, primarily due to the inherently discriminative nature of deep neural networks. To address these limitations, generative artificial intelligence (GAI) is seen as a promising solution, offering notable advantages in learning complex data distributions, transforming data between high- and low-dimensional spaces, and generating high-quality content.</div><div>This paper explores the applications of GAI in SemCom and presents a comprehensive study. It begins by introducing three widely used SemCom systems enabled by classical GAI models: variational autoencoders, generative adversarial networks, and diffusion models. For each system, the fundamental concept of the GAI model, the corresponding SemCom architecture, and a literature review of recent developments are provided. Subsequently, a novel generative SemCom system is proposed, incorporating cutting-edge GAI technology—large language models (LLMs). This system features LLM-based artificial intelligence (AI) agents at both the transmitter and receiver, which act as “brains” to enable advanced information understanding and content regeneration capabilities, respectively. Unlike traditional systems that focus on bitstream recovery, this design allows the receiver to directly generate the desired content from the coded semantic information sent by the transmitter. As a result, the communication paradigm shifts from “information recovery” to “information regeneration,” marking a new era in generative SemCom. A case study on point-to-point video retrieval is presented to demonstrate the effectiveness of the proposed system, showing a 99.98% reduction in communication overhead and a 53% improvement in average retrieval accuracy compared to traditional communication systems. Furthermore, four typical application scenarios for generative SemCom are described, followed by a discussion of three open issues for future research. In summary, this paper provides a comprehensive set of guidelines for applying GAI in SemCom, laying the groundwork for the efficient deployment of generative SemCom in future wireless networks.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 45-61"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144719984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.04.007
Xiangge He , Pengfei Wen , Qingqing Su , Hui Yang , Lijuan Gu , Min Zhang , Hailong Lu
Marine seismic exploration is traditionally conducted using towed streamers to investigate the geological structure of sea shelves and identify mineral deposits. Conventional streamers typically use piezoelectric hydrophones or fiber-optic interferometric hydrophones, which are complex, costly, and challenging to manufacture. In this study, we introduced a fiber-optic marine towed streamer seismic acquisition system based on distributed acoustic sensing technology. This system features a simplified design by removing the need for optical components within the streamer, thereby streamlining system architecture and manufacturing. The system’s effectiveness was validated through a sea trial conducted in the slope zone of a basin, with water depths ranging from 500 to 2000 m. Notably, this study represents the first successful application of distributed fiber-optic towed streamers for marine seismic exploration, enabling the effective detection of complex sedimentary structures in the surveyed area. The results underscore the significant potential of distributed fiber-optic towed streamers for seismic exploration, paving the way for advancements in marine seismic technologies.
{"title":"Marine Seismic Exploration with Distributed Acoustic Sensing","authors":"Xiangge He , Pengfei Wen , Qingqing Su , Hui Yang , Lijuan Gu , Min Zhang , Hailong Lu","doi":"10.1016/j.eng.2025.04.007","DOIUrl":"10.1016/j.eng.2025.04.007","url":null,"abstract":"<div><div>Marine seismic exploration is traditionally conducted using towed streamers to investigate the geological structure of sea shelves and identify mineral deposits. Conventional streamers typically use piezoelectric hydrophones or fiber-optic interferometric hydrophones, which are complex, costly, and challenging to manufacture. In this study, we introduced a fiber-optic marine towed streamer seismic acquisition system based on distributed acoustic sensing technology. This system features a simplified design by removing the need for optical components within the streamer, thereby streamlining system architecture and manufacturing. The system’s effectiveness was validated through a sea trial conducted in the slope zone of a basin, with water depths ranging from 500 to 2000 m. Notably, this study represents the first successful application of distributed fiber-optic towed streamers for marine seismic exploration, enabling the effective detection of complex sedimentary structures in the surveyed area. The results underscore the significant potential of distributed fiber-optic towed streamers for seismic exploration, paving the way for advancements in marine seismic technologies.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 284-295"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2024.11.008
Mostafa Rastgou, Yong He, Qianjing Jiang
Increasing greenhouse gas (GHG) emissions, such as methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2), from agricultural practices and land use have increased concerns about global warming. Accurate quantification of the GHG using gas sensors is essential for effective management and sustainable agricultural practices. The objective of this study was to make an analytical comparison of the performance of various sensing materials for CH4-, N2O-, and CO2-based sensors in terms of sensitivity, response ratio, response time, and recovery time to establish an efficiency detection level of the GHG emissions. A literature review of 95 different studies showed that palladium–tin dioxide (Pd-SnO2) nanoparticles, indium oxide (In2O3) nanowires, and gold-lanthanum oxide-doped tin dioxide (Au-La2O3/SnO2) nanofibers had better performance compared to other sensing materials in CH4-, N2O-, and CO2-based sensors, respectively. The findings from reviewed studies revealed that nanoporous structures, nanowires, and nanofibers had faster response and recovery compared to conventional materials due to their big specific surface area (SSA). The designed ternary hybrid structure of sensing materials was more effective for CO2 gas detection than the double hybrid structure, unlike CH4- and N2O-based sensors. However, constructive suggestions for researchers were discussed in the conclusion based on the current research status and challenges to improve the performance of GHG sensors.
{"title":"An Analytical Comparison of the Performance of Various Sensing Materials and Mechanisms for Efficient Detection Capability of Greenhouse Gas Emissions","authors":"Mostafa Rastgou, Yong He, Qianjing Jiang","doi":"10.1016/j.eng.2024.11.008","DOIUrl":"10.1016/j.eng.2024.11.008","url":null,"abstract":"<div><div>Increasing greenhouse gas (GHG) emissions, such as methane (CH<sub>4</sub>), nitrous oxide (N<sub>2</sub>O), and carbon dioxide (CO<sub>2</sub>), from agricultural practices and land use have increased concerns about global warming. Accurate quantification of the GHG using gas sensors is essential for effective management and sustainable agricultural practices. The objective of this study was to make an analytical comparison of the performance of various sensing materials for CH<sub>4</sub>-, N<sub>2</sub>O-, and CO<sub>2</sub>-based sensors in terms of sensitivity, response ratio, response time, and recovery time to establish an efficiency detection level of the GHG emissions. A literature review of 95 different studies showed that palladium–tin dioxide (Pd-SnO<sub>2</sub>) nanoparticles, indium oxide (In<sub>2</sub>O<sub>3</sub>) nanowires, and gold-lanthanum oxide-doped tin dioxide (Au-La<sub>2</sub>O<sub>3</sub>/SnO<sub>2</sub>) nanofibers had better performance compared to other sensing materials in CH<sub>4</sub>-, N<sub>2</sub>O-, and CO<sub>2</sub>-based sensors, respectively. The findings from reviewed studies revealed that nanoporous structures, nanowires, and nanofibers had faster response and recovery compared to conventional materials due to their big specific surface area (SSA). The designed ternary hybrid structure of sensing materials was more effective for CO<sub>2</sub> gas detection than the double hybrid structure, unlike CH<sub>4</sub>- and N<sub>2</sub>O-based sensors. However, constructive suggestions for researchers were discussed in the conclusion based on the current research status and challenges to improve the performance of GHG sensors.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 317-331"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.eng.2025.07.028
Jianhua Zhang , Li Yu , Shaoyi Liu , Yichen Cai , Yuxiang Zhang , Hongbo Xing , Tao Jiang
Channels are one of the five critical components of a communication system, and their ergodic capacity is based on all realizations of a statistical channel model. This statistical paradigm has successfully guided the design of mobile communication systems from first generation (1G) to fifth generation (5G). However, this approach relies on offline channel measurements in specific environments, and thus, the system passively adapts to new environments, resulting in deviation from the optimal performance. As sixth generation (6G) expands into ubiquitous environments and pursues higher capacity, numerous sensing and artificial intelligence (AI)-based methods have emerged to combat random channel fading. However, there remains an urgent need for a proactive and online system design paradigm. From a system perspective, we propose an environment intelligence communication (EIC) based on wireless environmental information theory (WEIT) for 6G. The proposed EIC architecture operates in three steps. First, wireless environmental information (WEI) is acquired using sensing techniques. Then, leveraging WEI and channel data, AI techniques are employed to predict channel fading, thereby mitigating channel uncertainty. Finally, the communication system autonomously determines the optimal air–interface transmission strategy based on real-time channel predictions, enabling intelligent interaction with the physical environment. To make this attractive paradigm shift from theory to practice, we establish WEIT for the first time by answering three key problems: How should WEI be defined? Can it be quantified? Does it hold the same properties as statistical communication information? Subsequently, EIC aided by WEI (EIC-WEI) is validated across multiple air–interface tasks, including channel state information prediction, beam prediction, and radio resource management. Simulation results demonstrate that the proposed EIC-WEI significantly outperforms the statistical paradigm in decreasing overhead and performance optimization. Finally, several open problems and challenges, including regarding its accuracy, complexity, and generalization, are discussed. This work explores a novel and promising way for integrating communication, sensing, and AI capability in 6G.
{"title":"Wireless Environmental Information Theory: A New Paradigm Toward 6G Online and Proactive Environment Intelligence Communication","authors":"Jianhua Zhang , Li Yu , Shaoyi Liu , Yichen Cai , Yuxiang Zhang , Hongbo Xing , Tao Jiang","doi":"10.1016/j.eng.2025.07.028","DOIUrl":"10.1016/j.eng.2025.07.028","url":null,"abstract":"<div><div>Channels are one of the five critical components of a communication system, and their ergodic capacity is based on all realizations of a statistical channel model. This statistical paradigm has successfully guided the design of mobile communication systems from first generation (1G) to fifth generation (5G). However, this approach relies on offline channel measurements in specific environments, and thus, the system passively adapts to new environments, resulting in deviation from the optimal performance. As sixth generation (6G) expands into ubiquitous environments and pursues higher capacity, numerous sensing and artificial intelligence (AI)-based methods have emerged to combat random channel fading. However, there remains an urgent need for a proactive and online system design paradigm. From a system perspective, we propose an environment intelligence communication (EIC) based on wireless environmental information theory (WEIT) for 6G. The proposed EIC architecture operates in three steps. First, wireless environmental information (WEI) is acquired using sensing techniques. Then, leveraging WEI and channel data, AI techniques are employed to predict channel fading, thereby mitigating channel uncertainty. Finally, the communication system autonomously determines the optimal air–interface transmission strategy based on real-time channel predictions, enabling intelligent interaction with the physical environment. To make this attractive paradigm shift from theory to practice, we establish WEIT for the first time by answering three key problems: How should WEI be defined? Can it be quantified? Does it hold the same properties as statistical communication information? Subsequently, EIC aided by WEI (EIC-WEI) is validated across multiple air–interface tasks, including channel state information prediction, beam prediction, and radio resource management. Simulation results demonstrate that the proposed EIC-WEI significantly outperforms the statistical paradigm in decreasing overhead and performance optimization. Finally, several open problems and challenges, including regarding its accuracy, complexity, and generalization, are discussed. This work explores a novel and promising way for integrating communication, sensing, and AI capability in 6G.</div></div>","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 186-200"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144787583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial for the Special Issue on 6G: From Theory to Practice","authors":"Ping Zhang , Xuemin (Sherman) Shen , Jianhua Zhang","doi":"10.1016/j.eng.2025.12.003","DOIUrl":"10.1016/j.eng.2025.12.003","url":null,"abstract":"","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"56 ","pages":"Pages 1-2"},"PeriodicalIF":11.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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