Knowledge Of Structure Research Articles

Building Information Modeling Applications in Civil Infrastructure: A Bibliometric Analysis from 2020 to 2024

Building Information Modeling (BIM) has emerged as a transformative technology in the Architecture, Engineering, and Construction (AEC) industry, with increasing application in civil infrastructure projects. This study comprehensively reviews the research landscape of BIM applications in civil infrastructure through bibliometric analysis. Based on data from the Web of Science database, 646 relevant papers published between 2020 and 2024 were collected, and 416 papers were selected for in-depth analysis after screening. Using bibliometric methods, the analysis reveals the evolution of research trends, identifies key contributors and influential publications, and maps the knowledge structure of the field. Our study shows a significant increase in research output over the past five years, particularly in studies focusing on the integration of BIM with emerging technologies such as Digital Twins, the Internet of Things (IoT), and Machine Learning. The results indicate that the United States, China, and the United Kingdom lead in terms of research output and citation impact. Additionally, based on clustering results and representative keywords, several key research clusters were identified, including BIM in infrastructure lifecycle management, BIM collaboration in large-scale projects, and BIM for sustainable infrastructure design.

A Survey Study on the Current Status of Professionalism of Elementary School Science Teachers in Changsha County

As the main participants in the teaching of science curriculum, the professionalism of elementary school science teachers is very important to the teaching work of teachers, the scientific literacy of students as well as the reform and development of science education. Therefore, the professional literacy of elementary school science teachers in Changsha County was thoroughly researched and analyzed from three aspects: professional affective literacy, professional knowledge literacy and professional ability literacy. Through the questionnaire survey and interviews, it was found that some science teachers have the problems of lack of professional affective literacy, single knowledge structure and low professional ability literacy. These problems are mainly attributed to the teachers’ weak sense of professional development, the limitations of curriculum teaching and implementation ability, the schools’ insufficient attention to the science curriculum, and the insufficient investment in education funding. To address these problems, this paper proposes optimization paths such as clarifying development goals, strengthening practice reflection, deepening the learning and application of the new curriculum standards, raising the importance of science curriculum teaching, and increasing the investment in science education. Through these measures, we aim to enhance the professionalism of elementary school science teachers, improve the quality of teaching, cultivate students’ scientific literacy, and promote the sustainable development of science education.

Development overview and research hotspots of Information Science & Library Science based on SSCI data

This study uses the scientometric method to analyse the literature to summarise the development overview and research hotspots in the field of Library and Information Science (LIS), aiming at sorting out the knowledge structure of the discipline and providing references and information for deepening its research and development. This article takes 85 Social Science Citation Index (SSCI) journals in the field of LIS as the research object, from which 116,570 articles from 1900 to 2023 are collected as the basis of data analysis. It employs the scientometric method based on visualisation software to analyse four dimensions of the LIS discipline: annual publications, journal outputs distribution, production and cooperation, and present focus and research hotspots, finding that the overall development of the discipline is stable and shows some new topics.

The structure of the IL-11 signalling complex provides insight into receptor variants associated with craniosynostosis.

Interleukin 11 (IL-11), a member of the IL-6 family of cytokines, has roles in haematopoiesis, inflammation, bone metabolism, and craniofacial development. IL-11 also has pathological roles in chronic inflammatory diseases, fibrosis, and cancer. In this structural snapshot, we explore our recently published cryo-EM structure of the human IL-11 signalling complex to understand the molecular mechanisms of complex formation and disease-associated mutations. IL-11 signals by binding to its cell surface receptors, the IL-11 receptor α subunit (IL-11Rα) and glycoprotein 130 (gp130), to form a hexameric signalling complex. We examine the locations within the complex of receptor sequence variants that are associated with craniosynostosis and craniosynostosis-like phenotypes and speculate on potential molecular mechanisms leading to defects in signalling function. While these causative amino acid sequence changes in IL-11Rα are generally distal to interfaces between components of the complex, important structural residues are highly represented, including proline residues, cysteine residues involved in disulfide bonds, and residues within or surrounding the tryptophan-arginine ladder. We also note the locations and potential effects of amino acid substitutions within the extracellular domains of gp130 that are associated with craniosynostosis. As focus on the physiological and pathological functions of IL-11 grows, the importance of high-resolution structural knowledge of IL-11 signalling to understand disease-associated mutations and to inform therapeutic strategies will only increase.

Implikasi Postmodernisme Dalam Masyarakat Kontemporer (Analisis Paradigma Pemikiran Tokoh Jean Francois Lyotard)

This article aims to investigate the implications of postmodernism in contemporary society by analyzing the paradigm of thought of the figure Jean-François Lyotard. Lyotard is known as one of the leading thinkers in postmodern thought, and this research aims to understand how his idea of skepticism towards grand narratives influences and permeates the structures of power, knowledge, and language in the context of contemporary society. This study uses a qualitative approach with a focus on the analysis of key texts by Jean-François Lyotard, especially "The Postmodern Condition: A Report on Knowledge." Analysis is performed to identify key concepts such as grand narratives, language games, and changes in knowledge structure. In addition, literature studies on the application of these concepts in the context of contemporary society are also involved to support research findings. The research findings suggest that Lyotard's postmodern views have significant implications in contemporary society. Skepticism of grand narratives creates space for narrative plurality, uncertainty of knowledge, and diverse language games. These implications affect power structures by challenging central authority and paving the way for a diversity of values and views. In addition, Lyotard's concepts also had an impact on changes in the way society understood and conveyed knowledge.

Mapping the Knowledge Structure of Image Recognition in Cultural Heritage: A Scientometric Analysis Using CiteSpace, VOSviewer, and Bibliometrix

The application of image recognition techniques in the realm of cultural heritage represents a significant advancement in preservation and analysis. However, existing scholarship on this topic has largely concentrated on specific methodologies and narrow categories, leaving a notable gap in broader understanding. This study aims to address this deficiency through a thorough bibliometric analysis of the Web of Science (WoS) literature from 1995 to 2024, integrating both qualitative and quantitative approaches to elucidate the macro-level evolution of the field. Our analysis reveals that the integration of artificial intelligence, particularly deep learning, has significantly enhanced digital documentation, artifact identification, and overall cultural heritage management. Looking forward, it is imperative that research endeavors expand the application of these techniques into multidisciplinary domains, including ecological monitoring and social policy. Additionally, this paper examines non-invasive identification methods for material classification and damage detection, highlighting the role of advanced modeling in optimizing the management of heritage sites. The emergence of keywords such as ‘ecosystem services’, ‘models’, and ‘energy’ in the recent literature underscores a shift toward sustainable practices in cultural heritage conservation. This trend reflects a growing recognition of the interconnectedness between heritage preservation and environmental sciences. The heightened awareness of environmental crises has, in turn, spurred the development of image recognition technologies tailored for cultural heritage applications. Prospective research in this field is anticipated to witness rapid advancements, particularly in real-time monitoring and community engagement, leading to the creation of more holistic tools for heritage conservation.

Population genomics of a specialized insect, Tetraopes texanus (Coleoptera: Cerambycidae), across a fragmented grassland system

AbstractSpecialist insects are especially susceptible to loss of genetic diversity in the face of habitat destruction and fragmentation. Implementing effective conservation practices for specialist insects will benefit from knowledge of population structure and genetic diversity. Because insects are hyper-diverse, characterizing the population structure of all species within the insect community is untenable, even if focused within a particular habitat type. Thus, concentrating on a single species specialized to a particular habitat type is needed to infer general trends. Here, we investigate the range-wide population genetics of Tetraopes texanus Horn 1878 (Coleoptera: Cerambycidae), which provides a useful model of grassland insects due to its’ habitat specificity and unique biology. Tetraopes texanus occurs primarily in Texas and Oklahoma, into Northern Mexico, and possibly into eastern New Mexico but also occurs in Black Belt prairies of Mississippi and Alabama. Mitochondrial and nuclear DNA (RAD-seq) analysis identified two distinct population clusters of T. texanus corresponding to the Texas and Oklahoma population and the Mississippi and Alabama population. Demographic models indicate ongoing, though incomplete, isolation of the two populations, with estimated dates of divergence in the mid-Pleistocene, coinciding with the end of a glacial period and a shift in glacial interval. These results can inform conservation of grassland adapted insects and offers insight to the biogeography of the Gulf Coastal Plain.

A bibliometric analysis of bladder cancer and microRNA research: Trends and advances from 2008 to 2022.

Bladder cancer (BC) is a significant global health issue with high incidence and mortality rates. MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been found to be dysregulated in BC. Understanding the role of miRNAs in BC development could lead to targeted therapies and improved patient management. Our study presents a thorough examination of the correlation between BC and miRNA research from 2008 to 2022. With the help of 3 powerful methods, including VOSviewer, Biblioshiny, and CiteSpace software, we analyzed the retrieved documents from "Core Collection databases online" on the Web of Science. In total, 798 articles were extracted from the Web of Science, and the number of published papers showed an upward trend from 2008 to 2019. The total number of citations was 21,233, of which the highest paper was a review article written by Chan Jiajia et al in 2018 with 752 citations. Based on the result of the coauthor analysis, Seki Naohiko was the most productive writer and China had the highest volume of published articles. Co-citation analysis was used to reveal the knowledge structure of the research field. In addition to the keywords "Bladder cancer" and "miRNA," "Proliferation," "Biomarkers," and "Apoptosis" were the high-frequency used keywords. Recently, increasingly researchers have paid more attention to the field about BC and miRNA around the worldwide. Through in-depth communication and close collaboration, the veil of miRNA in BC has gradually been unveiled. Bibliometric analysis helps to identify hotspots in research and areas for future investigation.

CFO (Chief Financial Officer) Research: A Systematic Review Using the Bibliometric Toolbox

The chief financial officer (CFO) is a crucial executive position in an organisation, responsible for overseeing the financial operations and strategy of the company. Despite rising interest among academics and practitioners, the literature corpus on CFO research remains largely fragmented, which warrants the unpacking of the underlying intellectual knowledge structure of the domain. In response, this study aims to provide a concise overview of the trends and science relating to CFO research, comprehend potential gaps in the literature, and highlight crucial future research pathways. A quantitative bibliometric overview of 669 research articles from 1982 to 2022 provides a spectrum of intellectual clout that helps decipher performance trends and delineates six significant clusters of knowledge in CFO research. We selectively discuss the empirical findings and theoretical and conceptual advancements within each cluster. This study offers recommendations for future research, emphasising the growing role of CFOs in leadership and addressing the fragmentation in current research. The findings and contributions of this study could further elevate CFOs’ importance in the C-suite.

Exploring effective (health) coaching relationships with the long-term unemployed

ABSTRACT This is the first exploratory study that centres on understanding what constitutes effective coaching relationships. Despite existing evidence highlighting the importance of the coaching relationship in achieving successful outcomes, there is limited knowledge on the specific components that make these relationships effective. The purpose of this study is to gain a deeper understanding of the cognitive structures and personal constructs that underpin effective (health) coaching relationships from the perspectives of health coaches, placement officers, and long-term unemployed clients with health restrictions. By employing Personal Construct Psychology and qualitative methods like Repertory Grid Technique, the study seeks to provide deeper insights into how these relationships are construed and what factors contribute to their effectiveness. The analysis identified 27 key themes that contribute to effective coaching relationships, highlighting the importance of relational constructs like trust, empathy, client readiness, and the individualised nature of perceptions, with different factors playing significant roles for different individuals. Repertory Grid Technique and Personal Construct Psychology proved effective in uncovering these cognitive structures. The study’s results offer practical implications for enhancing coaching practices, especially for vulnerable populations.

Asymptotic Normalization Coefficient Investigation of the 17O(d, p) Transfer for Astrophysical Application to the 17O(n, α)14C Reaction at Low Energies

Indirect methods have proven to be a complementary approach for extending our knowledge of nuclear structure and low-energy cross sections. Among these, the neutron-induced reaction cross sections appear to be of particular interest since their role both for unstable and stable beams. In view of this, we report here the combined study of the 17O(n, α)14C reaction accomplished by the Trojan Horse Method (THM) and the asymptotic normalization coefficient (ANC) method. The low-lying 8038, 8125, 8213, and 8282 keV resonances in 18O are studied, and their Γ n are derived. A comparison with recent direct data and recent THM experimental data is presented. The independent ANC investigation corroborates our previous THM results, confirms the consistence of the two indirect investigations, and shows new frontiers for neutron-induced reactions with radioactive ion beams. Moreover, we examined the impact of adopting the newly recommended 17O(n, α)14C reaction rate on asymptotic giant branch stars' nucleosynthesis. Our findings reveal significant variations (≳10%) in the production of the neutron-rich heavy isotopes sensitive to neutron density, underlining the neutron-poisoning effect of 17O on the s-process.

Mapping the evolution and future directions of creative tourism: a comprehensive bibliometric analysis

ABSTRACT The main objective of this study is to deepen the understanding of the knowledge structure in the field of creative tourism and thereby enhance communication with advanced international theories and experiences. We utilized two visualization tools, VOSviewer and CiteSpace, to analyze 138 platform research papers from the Web of Science Core Collection, comprising 7050 references. Combining quantitative analysis (such as scientometric analysis, knowledge mapping, and keyword clustering) with content analysis (including thematic reading), this study primarily focuses on three aspects: firstly, revealing the basic characteristics of the literature, such as publication metrics, authors, and research institutions, to outline the foundational landscape of the field; secondly, identifying key research areas, content, and development trends to provide profound insights into the advancement of creative tourism and suggest directions for future research; thirdly, constructing a comprehensive knowledge framework to consolidate existing information and insights, facilitating a more structured and accessible understanding of creative tourism.

Три уровня международного политико-экономического анализа: новая перспектива для исследования международных проблем в эпоху многополярности

One of the key issues in current international relations studies is the structure of knowledge. The epistemological foundations of political and economic theories of international development are losing their relevance as the influence of theory on the practice of international relations wanes. The declining ability of international analysis to predict the future of world politics and economics emphasizes the need for a broader, interdisciplinary approach to the study of international relations. This study aims to explore the possibility of creating a new, practical and interdisciplinary model of analysis to address the problems of the modern international system. This approach to the systemic analysis of international relations involves broadening the scope of the study by integrating international political and economic (IPE) analysis and including three analytical levels: explanatory, normative and critical. The article defines the terminology, structure, principles and criteria of such an analysis based on the problems of modern political science. The author also points out the main difficulties in the formation of theoretical and methodological basis of the three-level analysis. Examples of analyzing problems, namely the impact of trade barriers on the instability of global supply chains and the international dimension of the energy crisis of the Federal Republic of Germany (2022 – present) are given, demonstrating the quality and consistency of the results of such analysis.

The Frontiers and Future Landscape of Research and Education on Value Rationality in Contemporary China

The importance of conducting in-depth research and education on value rationality in the new era is increasingly recognized. Therefore, it is essential to systematically grasp the themes, frontiers, and trends of research in this field, organizing the knowledge system to provide references for future studies. This necessitates clarifying the research achievements of scholars from different disciplines and institutions. Using the CiteSpace visualization analysis method, we can analyze, summarize, and synthesize research networks, hotspots, and knowledge structures, thereby forming a direction for advancing research. Through literature review methods and knowledge graph software analysis, it is believed that value rationality and instrumental rationality represent the rational attitudes individuals adopt when contemplating issues and putting them into practice. They are merely methods and should not be subjected to excessive value judgments. The relationship between value rationality and instrumental rationality is a focal point of societal concern, involving complex interdisciplinary issues with significant theoretical value and practical implications. In the future, the academic community needs to strengthen research collaboration, enhance the expansion of value rationality in various social practice fields, and conduct empirical studies to build consensus for the construction of Chinese society.

Insight into structural properties of viral G protein-coupled receptors and their role in the viral infection: IUPHAR Review 41.

G protein-coupled receptors (GPCRs) are pivotal in cellular signalling and drug targeting. Herpesviruses encode GPCRs (vGPCRs) to manipulate cellular signalling, thereby regulating various aspects of the virus life cycle, such as viral spreading and immune evasion.vGPCRs mimic host chemokine receptors, often with broader signalling and high constitutive activity. This review focuses on the recent advancements in structural knowledge about vGPCRs, with an emphasis on molecular mechanisms of action and ligand binding. The structures of US27 and US28 from human cytomegalovirus (HCMV) are compared to their closest human homologue, CX3CR1. Contrasting US27 and US28, the homotrimeric UL78 structure (HCMV) reveals more distance to chemokine receptors. Open reading frame 74 (ORF74; Kaposi's sarcoma-associated herpesvirus) is compared to CXCRs, whereas BILF1 (Epstein-Barr virus) is discussed as a putative lipid receptor. Furthermore, the rolesof vGPCRs in latency and lytic replication, reactivation, dissemination and immune evasion arereviewed, together with their potential as drug targets for virus infections and virus-related diseases.

A bibliometric analysis of the relationship between traumatic brain injury and Alzheimer's disease (1993-2023).

Traumatic brain injury (TBI) increases the risk of developing Alzheimer's disease (AD), and a growing number of studies support a potential link between the two disorders. Therefore, the objective of this study is to systematically map the knowledge structure surrounding this topic over the past and to summarize the current state of research and hot frontiers in the field. Data were retrieved from the Web of Science Core Collection (WOSCC) starting from the beginning until December 31, 2023, focusing on articles and reviews in English. Bibliometric tools including Bibliometrix R, VOSviewer, and Microsoft Excel were utilized for data analysis. The analysis included citations, authors, institutions, countries, journals, author keywords, and references. A total of 1,515 publications were identified, comprising 872 articles (57.56%) and 643 reviews (42.44%). The annual number of publications increased steadily, especially after 2013, with an R2 value of 0.978 indicating a strong upward trend. The USA was the leading country in terms of publications (734 articles), followed by China (162 articles) and the United Kingdom (77 articles). Meanwhile Boston University was the most productive institution. Collaborative networks show strong collaborative author links between the USA and the United Kingdom, as well as China. The analysis also showed that the Journal of Alzheimer's Disease was the most productive journal, while the article authored by McKee achieved the highest local citations value. The top three author keywords, in terms of occurrences, were "Alzheimer's disease," "traumatic brain injury," and "neurodegeneration." Thematic mapping showed a consolidation of research themes over time, decreasing from 11 main themes to 8. Emerging themes such as "obesity" and "diffusion tensor imaging" indicate new directions in the field. The research on AD after TBI has attracted a great deal of interest from scientists. Notably, the USA is at the forefront of research in this field. There is a need for further collaborative research between countries. Overall, this study provides a comprehensive overview of developments in TBI and AD research, highlighting key contributors, emerging topics, and potential areas for future investigation.

MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model

A crucial mechanism for controlling the actions of proteins is allostery. Allosteric modulators have the potential to provide many benefits compared to orthosteric ligands, such as increased selectivity and saturability of their effect. The identification of new allosteric sites presents prospects for the creation of innovative medications and enhances our comprehension of fundamental biological mechanisms. Allosteric sites are increasingly found in different protein families through various techniques, such as machine learning applications, which opens up possibilities for creating completely novel medications with a diverse variety of chemical structures. Machine learning methods, such as PASSer, exhibit limited efficacy in accurately finding allosteric binding sites when relying solely on 3D structural information.Scientific ContributionPrior to conducting feature selection for allosteric binding site identification, integration of supporting amino-acid–based information to 3D structural knowledge is advantageous. This approach can enhance performance by ensuring accuracy and robustness. Therefore, we have developed an accurate and robust model called Multimodel Ensemble Feature Selection for Allosteric Site Identification (MEF-AlloSite) after collecting 9460 relevant and diverse features from the literature to characterise pockets. The model employs an accurate and robust multimodal feature selection technique for the small training set size of only 90 proteins to improve predictive performance. This state-of-the-art technique increased the performance in allosteric binding site identification by selecting promising features from 9460 features. Also, the relationship between selected features and allosteric binding sites enlightened the understanding of complex allostery for proteins by analysing selected features. MEF-AlloSite and state-of-the-art allosteric site identification methods such as PASSer2.0 and PASSerRank have been tested on three test cases 51 times with a different split of the training set. The Student’s t test and Cohen’s D value have been used to evaluate the average precision and ROC AUC score distribution. On three test cases, most of the p-values (<0.05\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$< 0.05$$\\end{document}) and the majority of Cohen’s D values (>0.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$> 0.5$$\\end{document}) showed that MEF-AlloSite’s 1–6% higher mean of average precision and ROC AUC than state-of-the-art allosteric site identification methods are statistically significant.

3D Cryo-Electron Microscopy Reveals the Structure of a 3-Fluorenylmethyloxycarbonyl Zipper Motif Ensuring the Self-Assembly of Tripeptide Nanofibers.

Short peptide-based supramolecular hydrogels appeared as highly interesting materials for applications in many fields. The optimization of their properties relies mainly on the design of a suitable hydrogelator through an empirical trial-and-error strategy based on the synthesis of various types of peptides. This approach is in part due to the lack of prior structural knowledge of the molecular architecture of the various families of nanofibers. The 3D structure of the nanofibers determines their ability to interact with entities present in their surrounding environment. Thus, it is important to resolve the internal structural organization of the material. Herein, using Fmoc-FFY tripeptide as a model amphiphilic hydrogelator and cryo-EM reconstruction approach, we succeeded to obtain a 3.8 Å resolution 3D structure of a self-assembled nanofiber with a diameter of approximately 4.1 nm and with apparently "infinite" length. The elucidation of the spatial organization of such nano-objects addresses fundamental questions about the way short amphiphilic N-Fmoc peptides lacking secondary structure can self-assemble and ensure the cohesion of such a lengthy nanostructure. This nanofiber is organized into a triple-stranded helix with an asymmetric unit composed of two Fmoc-FFY peptides per strand. The three identical amphiphilic strands are maintained together by strong lateral interactions coming from a 3-Fmoc zipper motif. This hydrophobic core of the nanofiber is surrounded by 12 phenyl groups from phenylalanine residues, nonplanar with the six Fmoc groups. Polar tyrosine residues at the C-term position constitute the hydrophilic shell and are exposed all around the external part of the assembly. This fiber has a highly hydrophobic central core with an internal diameter of only 2.4 Å. Molecular dynamics simulations highlight van der Waals and hydrogen bonds between peptides placed on top of each other. We demonstrate that the self-assembly of Fmoc-FFY, whether induced by annealing or by the action of a phosphatase on the phosphorylated precursor Fmoc-FFpY, results in two nanostructures with minor differences that we are unable to distinguish.

Anisotropy of radiation-induced defects in Yb-implanted β-Ga2O3

RE-doped β-Ga2O3 seems attractive for future high-power LEDs operating in high irradiation environments. In this work, we pay special attention to the issue of radiation-induced defect anisotropy in β-Ga2O3, which is crucial for device manufacturing. Using the RBS/c technique, we have carefully studied the structural changes caused by implantation and post-implantation annealing in two of the most commonly used crystallographic orientations of β-Ga2O3, namely the (-201) and (010). The analysis was supported by advanced computer simulations using the McChasy code. Our studies reveal a strong dependence of the structural damage induced by Yb-ion implantation on the crystal orientation, with a significantly higher level of extended defects observed in the (-201) direction than for the (010). In contrast, the concentration and behavior of simple defects seem similar for both oriented crystals, although their evolution suggests the co-existence of two different types of defects in the implanted zone with their different sensitivity to both, radiation and annealing. It has also been found that Yb ions mostly occupy the interstitial positions in β-Ga2O3 crystals that remain unchanged after annealing. The location is independent of the crystal orientations. We believe that these studies noticeably extend the knowledge of the radiation-induced defect structure, because they dispel doubts about the differences in the damage level depending on crystal orientation, and are important for further practical applications.

Cascade contour-enhanced panoptic segmentation for robotic vision perception.

Panoptic segmentation plays a crucial role in enabling robots to comprehend their surroundings, providing fine-grained scene understanding information for robots' intelligent tasks. Although existing methods have made some progress, they are prone to fail in areas with weak textures, small objects, etc. Inspired by biological vision research, we propose a cascaded contour-enhanced panoptic segmentation network called CCPSNet, attempting to enhance the discriminability of instances through structural knowledge. To acquire the scene structure, a cascade contour detection stream is designed, which extracts comprehensive scene contours using channel regulation structural perception module and coarse-to-fine cascade strategy. Furthermore, the contour-guided multi-scale feature enhancement stream is developed to boost the discrimination ability for small objects and weak textures. The stream integrates contour information and multi-scale context features through structural-aware feature modulation module and inverse aggregation technique. Experimental results show that our method improves accuracy on the Cityscapes (61.2 PQ) and COCO (43.5 PQ) datasets while also demonstrating robustness in challenging simulated real-world complex scenarios faced by robots, such as dirty cameras and rainy conditions. The proposed network promises to help the robot perceive the real scene. In future work, an unsupervised training strategy for the network could be explored to reduce the training cost.