Visual Analysis Research Articles

Review on pattachitra

Kalamkari is a highly esteemed traditional art form that has long drawn admirers due to its intricate hand-painted designs on fabrics. This article explores the complex world of Kalamkari, a classic Indian art form that is well-known for its intricately painted textile pieces. Through a multifaceted investigation, the study seeks to understand Kalamkari's historical development, cultural value, and current relevance. The process includes a comprehensive reading of the material, a field investigation, a visual analysis of the artwork, and a comparison analysis between different locations and eras of history. While the field study entails interacting with artists and documenting their methods and processes, the literature review offers insights into the history, methods, and sociocultural aspects of Kalamkari. Visual analysis examines the narrative components, colours, and motifs in Kalamkari textiles to shed light on their artistic and symbolic meanings.

Studying Narratives in International Relations

Abstract Many scholars in international relations (IR) share an interest in narratives. With few, notable exceptions, IR scholars seem to lack clear methodological guidelines on how to conceptualize and study narratives in IR. We therefore develop a minimal definition of narratives and introduce a conceptual framework that shows how narrative analysis can be applied to questions and concepts within IR. We introduce narrative analysis as a multi-modal approach, which also draws on methodological insights from visual analysis, discourse analysis, and practice theory. The aim of the article is pedagogical, namely to translate insights from narratology to studies in IR and to show how everyday sources of the political, such as pop culture or social media, can be meaningfully analyzed. We argue that such an interpretive analysis implies adopting a critical and reflective stance to explore how narratives are shaped, how they appeal to specific political audiences, and whose interests are served by dominant political narratives. Such a perspective strongly resonates with current research debates in IR on practices, discourse, visuality, and emotions and puts a strong emphasis on power relations.

Virtual physiological analysis of non-culprit disease in patients with STEMI and multivessel disease: a substudy of the COMPLETE trial

Abstract Background In the Complete Revascularization with Multivessel PCI for Myocardial Infarction (COMPLETE) trial, patients with ST-segment-elevation myocardial infarction (MI) who underwent staged revascularization of non-culprit coronary stenoses experienced fewer major adverse cardiovascular events than those who underwent a culprit-only approach (1). Inclusion was, however, based on angiographic and not physiological criteria. Purpose To analyse, using computational modelling, the physiological significance of non-culprit lesions included in the COMPLETE trial, to compare these against angiographic measures of severity, and investigate interactions between physiology and the benefits of complete revascularization. Methods Angiograms with appropriate digital imaging and communications in medicine (DICOM) data from the COMPLETE trial (n=1327) underwent software-based 3-dimensional (3D) arterial reconstruction and analysis of 3D-quantitative coronary angiography (QCA) and virtual fractional flow reserve (vFFR) using computational fluid dynamics software. Physiological lesion significance was defined as vFFR ≤0.80 and was compared with operators’ visual angiographic analysis, core-laboratory 2D-QCA and 3D-QCA. Results vFFR was computed successfully in 635 patients (710 lesions). The median vFFR was 0.82 (interquartile range 0.73–0.91). 302 patients (48%) had at least one physiologically significant lesion and 333 (52%) had none. 321 (45%) lesions were physiologically significant and 389 (55%) were not. Physiologically significant lesions were angiographically more severe than non-significant lesions according to the operator’s visual angiographic assessment (mean stenosis 80% vs. 75%, P<0.0001), 2D-QCA (69% vs. 59%, p<0.0001), and 3D-QCA (56% vs. 43, P<0.0001). Percentage lesion stenosis was significantly different when measured visually, with 2D-QCA and with 3D-QCA (80% vs 62% vs 49%, P<0.0001). vFFR was weakly correlated with operators’ visual angiographic severity (Figure 1) and 2D-QCA, but more strongly with 3D-QCA (r=-0.21, -0.21, and -0.60, respectively; all p<0.0001). 3D-QCA predicted vFFR significance more accurately than visual and 2D-QCA (concordance 73% vs 49% vs 59%, respectively). There was no statistically significant interaction between physiological lesion significance and any of the trial coprimary or key secondary clinical outcomes, or on an exploratory outcome of ischaemia-driven revascularization without preceding MI (all interactions P>0.30) (Figure 2). Conclusions In this virtual physiological substudy of the COMPLETE trial, 52% of patients lacked any physiologically-significant lesions, 3D-QCA was a better predictor of physiological significance than either 2D-QCA or operator visual analysis, and the benefits of complete revascularization appeared to be independent of physiological lesion significance. Further research is warranted to compare angiography-guided and physiology-guided complete revascularization strategies.Figure 1.Figure 2.

Preliminary Investigation of Context-Aware AAC with Automated Just-in-Time Cloze Phrase Response Options for Social Participation from Children on the Autism Spectrum.

Social participation for emerging symbolic communicators on the autism spectrum is often restricted. This is due in part to the time and effort required for both children and partners to use traditional augmentative and alternative communication (AAC) technologies during fast-paced social routines. Innovations in artificial intelligence provide the potential for context-aware AAC technology that can provide just-in-time (JIT) communication options based on linguistic input from partners to minimize the time and effort needed to use AAC technologies for social participation. This preliminary study used an alternating treatment design to compare the effects of a context-aware AAC prototype with automated cloze phrase response options to traditional AAC for supporting three young children who were emerging symbolic communicators on the autism spectrum in participating within a social routine. Visual analysis and effect size estimates suggest the context-aware AAC condition resulted in increases in linguistic participation, vocal approximations, and visual attention for all three children. While this study was only an initial exploration and results are preliminary, context-aware AAC technologies have the potential to enhance participation and communication outcomes for young emerging symbolic communicators on the autism spectrum and more research is needed.

Microstructure of confectionery masses revealed by cryo-planing

Here we present a novel, combined cryo-scanning electron microscopy (cryo-SEM) and confocal laser scanning microscopy (CLSM) method for imaging of chocolate confectionery product microstructures of several millimeters down to about 100 nm. The SEM part of the method is based on cryo-fixation, cryo-polishing, and scanning electron microscopy, at low vacuum and low temperature using the backscattered electron signal. Starting with cryo-fixation of the chocolate sample in a desired state (cooled, ambient, or melted), the sample is cryo-planed in a cryo-ultramicrotome. Once a polished cut is obtained, the sample is analyzed using a cryo-SEM technique, with the unusual combination of low temperature and low vacuum settings, without heavy metal coating. Imaging is done based on material density contrast. Elemental composition of particles is recorded by energy dispersive x-ray spectroscopy (EDS). The combination of imaging contrast and EDS allows identification and measurement of the four main constituents of chocolate (cocoa solids, fat, sugar, and milk solids). Finally, the same cryo-polished sample sections of solid chocolate products are analyzed using a CLSM imaging technique to reveal complementary microstructural details. An obvious application of the method could be the visualization and quantitative analysis of the size, shape, and composition of chocolate confectionery products.

Clustering of artificial intelligence derived plaque features for risk stratification for future atrial fibrillation development

Abstract Introduction We previously demonstrated that artificial intelligence (AI)-derived coronary artery plaque features are associated with future development of atrial fibrillation (AF) among patients undergoing CCTA(1). Our results suggest that phenotyping a large dataset of plaque features using data science techniques may reveal associations not visible from univariate analysis. Purpose Use data science analysis of AI-CT plaque characteristics to identify subpopulations at higher risk of AF. Methods We applied dimensionality reduction and visual cluster identification to phenotype our population of patients based on their AI-CT plaque features. We used a single center CCTA registry of patients with prior clinically-indicated CCTA (N=2700) from 2017-2020. Cases of new AF were defined by onset of AF on ECG or telemetry after CCTA via EMR search. Patients with AF prior to CCTA, history of mitral valve surgery, or postoperative AF were excluded. Controls were selected 1:1 by nearest neighbor propensity matching (R. v. 4.0.3.) based on age, sex, tobacco use, HTN, HLD, and diabetes. Atherosclerotic plaques were quantitatively analyzed using a commercially available FDA-approved AI coronary analysis software yielding stenosis area and diameter, remodeling index, volume of calcified/non-calcified/low-density plaques, and number of 2 or more high risk plaques. Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction with cosine distance metric was used to reduce the plaque feature space from 80 dimensions (8 AI measurements per each of 10 anatomical vessel segments in all patients) to 2 dimensions on a scatter plot. Two non-contiguous clusters (i.e. plaque phenotypes) were identified based on visual analysis of UMAP feature reduction (Figure 1). Results 94 cases comprised the study cohort (47 cases and 47 controls). Mean age was 67±11 years. 38% were female. Mean CADRADS score was 1.8±1.52 and mean CAC was 325±622. Mean time from CT to AF was 281±300 days. The majority of AF patients (67%) fell into Cluster 1 (N=36), while Cluster 2 (N=58) contained most of the control subjects (75%). Treating Cluster 1 as a predictor of AF, the PPV and specificity of the UMAP reduction was 67% and 75% respectively, with NPV of 60% and sensitivity of 51% (Table 1). Left atrial volume index (LAVI) was significantly different between the 2 clusters, with mean 56.15±12.42 ml/m2 in Cluster 1 and 46.96±16.03 in Cluster 2 (p=0.0046). LAVI was also significantly different between control subjects in Cluster 1 vs 2, mean 54.84±11.6 vs 41.62±7.92 (p<0.001). Conclusions We demonstrated that UMAP-derived clustering of AI-CT plaque characteristics identifies novel phenotypes for future risk of AF among patients undergoing CCTA. Further, control patients in Cluster 1 were found to have a significantly higher LAVI compared to control subjects in Cluster 2, which supports that membership in Cluster 1 may increase risk of future development of AF.

A bibliometric and visualization analysis of entosis research from 2007 to 2024

ObjectiveIn 2007, entosis was proposed as a form of programmed cell death, distinct from apoptosis. This process involves a living cell (internalized cell) actively invading a neighboring live cell of the same type (host cell), forming a cell-in-cell structure. Recently, entosis has been increasingly associated with cancer, leading to significant advancements in research. Despite this progress, a comprehensive and unbiased review of the current state of entosis research is lacking. This study aims to evaluate the developments in the field of entosis over the past decade and highlight emerging research trends.Materials and methodsWe performed a literature search for studies published since the introduction of the entosis concept, using the Web of Science Core Collection database. The bibliometric analysis was conducted using VOSviewer, CiteSpace, Microsoft Excel, and the Bibliometrix R package.ResultsA total of 196 articles from 39 countries and 346 institutions were included. Between 2007 and 2024, research on entosis has seen rapid growth, with most publications originating from China and the United States. The United States also leads in total citations, with Memorial Sloan Kettering Cancer Center emerging as the top research institution. Sun Qiang is the most prolific author in this field, while Overholtzer M has the highest number of citations. Current Molecular Medicine has published the most articles related to entosis. Frequently occurring keywords include “entosis,” “cannibalism,” “autophagy,” and “apoptosis.” In recent years, keywords such as “phagocytosis,” “drug resistance,” and “human cancers” have surged, indicating a growing focus on understanding the role of entosis in tumor progression and exploring its potential as a therapeutic target for cancer treatment.ConclusionsThis study provides the first bibliometric analysis of entosis, detailing its evolution over the last decade. It highlights critical areas of interest, including the development of inhibitors targeting entosis and their potential clinical applications. This research aims to guide future investigations and serve as a valuable resource for scholars exploring entosis in cancer biology.

Heterogeneous courses of cardiovascular disease incidence in Europe 2000-2019 – what are the causes?

Abstract Background Data from the Global Burden of Disease (GBD) project distributed by the Institute for health metrics and evaluation (IHME) include incidence and prevalence data for almost all countries in the world. In course of own research, the data on cardiovascular disease (CVD) incidence in Western European countries were analysed and revealed great variation in the course of CVD incidence, that is difficult to interpret. We want to present the different courses of CVD incidence for selected countries and discuss possible reasons for this diversity with the audience. Methods GBD data on CVD incidence and mortality for 25 European countries from 2000-2019 for men and women were to graphically display courses of CVD incidence for visual analysis. Results The course of CVD incidence in Western Europe is country-specific - and, within a country, even sex-specific. Yet, in many countries besides the Baltic states and Czechia, CVD incidence reaches a minimum in 2010, increasing afterwards again. Different patterns of incident courses were visible: a) wave-shaped courses which increase e.g. in Austria, Belgium, France and in males in Finland only, but decrease for both sexes Germany, Norway, Portugal and Poland, and in males in Denmark b) u-shaped courses in Spain, Great Britain, France, Italy, and for Finnish and Dutch females c) linearly increasing for both sexes in Czechia, the Baltic states and in Swiss males d) linearly decreasing for women Norway, Belgium, Denmark and Austria. Conclusions The patterns of CVD incidence in Europe are multitude and country-specific even between sexes, reaching a minimum in 2010 in most countries. The validity of analyses combining these different patterns for regional analyses of CVD incidence such as in GBD reports do not take account for this diversity. Unless these differences can be explained by country-specific prevention or risk factor profile, the validity of data on CVD incidence seems to be limited. Key messages • CVD incidence in Europe between 2000 and 2019 is country-specific changing and very heterogeneous. • Analyses summarizing data for (Western/Eastern) Europe will miss this heterogeneity and might come to invalid conclusions regarding the development of CVD incidence.

Advances in Fuzzy Linguistics Research in the Last Two Decades - CiteSpace-based Visualisation and Analysis

This paper analyzes the research progress of fuzzy linguistics in the last two decades based on the visual analysis method of CiteSpace. It introduces the concept and development background of fuzzy linguistics. In this paper, the research progress in the field of fuzzy linguistics is explored in depth through visual analysis using CiteSpace, and the related research directions and development trends are discussed and summarized in detail. The results of these analyses are of certain reference significance for further in-depth research in the field of fuzzy linguistics and for advancing the technological development and application in the field of fuzzy linguistics.

‘Stop the Death Transports!’ Holocaust and slavery references in an Israeli campaign against animal live transports

ABSTRACT Animal rights organisations worldwide fight against live shipments of meat animals. The main Israeli NGOs leading the fight are Animals-Now, Israel against Live Shipments, and Let the Animals Live. Their visual rhetoric highlights the cruelty of these shipments. Combined with written messages, photographs of animal suffering appeal to viewers’ emotions and conscience. This article examined ‘Stop the Death Transports!’ – The most extensive campaign led by these NGOs, together with Animals Australia, in 2016. It analysed the campaign poster from the approaches of photography semiotics and visual contextual analysis, informed by theories of visual culture and animal ethics. The campaign represents an intermediate approach between the hardcore and softcore approaches, using visual and verbal references to the Holocaust and slavery. However, though the use of the Holocaust is highly charged for local Jewish viewers thus contributing to the understanding of the immorality of consuming meat, it may in fact assuage their conscience by shifting the moral burden from the meat eaters to the transporters.

“Your friendly AI assistant”: the anthropomorphic self-representations of ChatGPT and its implications for imagining AI

AbstractThis study analyzes how ChatGPT portrays and describes itself, revealing misleading myths about AI technologies, specifically conversational agents based on large language models. This analysis allows for critical reflection on the potential harm these misconceptions may pose for public understanding of AI and related technologies. While previous research has explored AI discourses and representations more generally, few studies focus specifically on AI chatbots. To narrow this research gap, an experimental-qualitative investigation into auto-generated AI representations based on prompting was conducted. Over the course of a month, ChatGPT (both in its GPT-4 and GPT-4o models) was prompted to “Draw an image of yourself,” “Represent yourself visually,” and “Envision yourself visually.” The resulting data (n = 50 images and 58 texts) was subjected to a critical exploratory visual semiotic analysis to identify recurring themes and tendencies in how ChatGPT is represented and characterized. Three themes emerged from the analysis: anthropomorphism, futuristic/futurism and (social)intelligence. Importantly, compared to broader AI imaginations, the findings emphasize ChatGPT as a friendly AI assistant. These results raise critical questions about trust in these systems, not only in terms of their capability to produce reliable information and handle personal data, but also in terms of human–computer relations.

Technology-assisted instruction with teacher prompts on fraction multiplication word problems: A single-case design with visual analysis and Bayesian multilevel modeling

ABSTRACT This study examines the effects of technology-assisted instruction with teacher prompts on the ability to visualize and solve fraction multiplication word problems for four middle school students with learning disabilities. A multiple-probe design across participants, a type of single-case design, showed a functional relationship between the intervention and the targeted mathematical outcomes. Although there were some fluctuations over time, students demonstrated improvements from the baseline to intervention phases (Tau ranged from 0.76 to 1.00 for visualization and was 1.00 for problem-solving). Researchers employed Bayesian cumulative link mixed effects models to examine the moderating effects of word problem question types. Students showed greater maintenance effects on problem-solving than on visualization tasks, as reflected in changes in level (logit coefficient = 2.6) and trend (logit coefficient = 0.22). Students and teachers perceived vocabulary and multiplication fact practices, as well as the cognitive and metacognitive features embedded in the technology-assisted intervention, to be useful in learning targeted mathematics concepts. This study underscores the role of technology integration in enhancing teachers’ instructional approach and in aiding students’ acquisition and retention of mathematical concepts and skills.

An image-based investigation on color associations among 100 Chinese emotion words

ABSTRACT Image data serves as a valuable resource for investigating relationships between colors and emotions. This study conducts an image-based visual corpus analysis on the color associations of 100 Chinese emotion words, aiming to uncover the pivotal roles of colors in understanding emotional concepts. The study addresses two primary objectives: (i) examining the interrelations among four affective properties (valence, arousal, prototypicality, and emotionality) and four image-based color attributes (Jz: a dimension depicting black–white color distinction, Az: a dimension for green-red, Bz: a dimension for blue–yellow, and color variability) associated with these emotion words; and (ii) assessing the efficacy of image-based color information in profiling affective (dis)similarities among different emotion words. The empirical results reveal (i) significant positive correlations between color variability and arousal, Jz and valence, Az and arousal, Bz and valence, as well as a negative correlation between Jz and prototypicality; (ii) the effectiveness of image-based color information in depicting the valence-dominated affective (dis)similarities among the 100 Chinese emotion words. This study contributes image-based empirical support to complement existing research on color-emotion mappings. Moreover, it advances methodological approaches by advocating for the utilisation of image data to address theoretical inquiries in cognitive science.

Clinically applicable optimized periprosthetic joint infection diagnosis via AI based pathology

Periprosthetic joint infection (PJI) is a severe complication after joint replacement surgery that demands precise diagnosis for effective treatment. We enhanced PJI diagnostic accuracy through three steps: (1) developing a self-supervised PJI model with DINO v2 to create a large dataset; (2) comparing multiple intelligent models to identify the best one; and (3) using the optimal model for visual analysis to refine diagnostic practices. The self-supervised model generated 27,724 training samples and achieved a perfect AUC of 1, indicating flawless case differentiation. EfficientNet v2-S outperformed CAMEL2 at the image level, while CAMEL2 was superior at the patient level. By using the weakly supervised PJI model to adjust diagnostic criteria, we reduced the required high-power field diagnoses per slide from five to three. These findings demonstrate AI’s potential to improve the accuracy and standardization of PJI pathology and have significant implications for infectious disease diagnostics.

Research hotspots and emerging trends in growth and development of macrofungi: a bibliometric review based on CiteSpace analysis.

Macrofungi (or mushrooms) are essential for agriculture, food, and ecology. Although research on the growth and development of macrofungi (GDM) can provide insights into their biological characteristics and metabolite synthesis mechanisms, further exploration is needed for a systematic and visual analysis of the current research progress on GDM. To comprehensively understand the research status and development trend of GDM, a total of 545 scientific literature related to GDM in the Web of Science Core Collection database from 2008 to 2024 were searched and selected as research objects. The general information (publication year, country, institution, and cited journal) and the specific information (co-authorship, keyword co-occurrence, and references with strong citation bursts) were mined and visualized in detail based on CiteSpace software. These analyses demonstrated that related research is still fashionable, and China is dominant and influential in this field. More frequent and in-depth cooperation among authors, institutions and regions is conducive to promoting the research on GDM. Additionally, the quantity and cluster analyses of keywords and references demonstrated that medicinal/edible macrofungi and sustainable development (e.g. mushroom substrate reuse) may be research hotspots and will remain popular in the coming years. This research aims to supply researchers with up-to-date knowledge and cutting-edge issues related to GDM by providing a visually appealing representations on quantitative GDM studies.

Research frontiers and hotspots in optical coherence tomography applications among patients with acute coronary syndromes: Bibliometric and visual analysis.

Research on the use of optical coherence tomography (OCT) in acute coronary syndrome (ACS) has increased in recent years. However, a comprehensive analysis of the trends and hotspots in OCT research is currently lacking. The objective of this study was to identify global trends in research on OCT in ACS from a bibliometric perspective and to provide researchers with new research hotspots. Relevant literature from 1998 to 2023 was retrieved from the Web of Science Core Collection. CiteSpace and VOSviewer software were used to collect and analyze publication trends in related fields. A total of 965 publications from 58 countries and 1389 institutions were included in the present study. We found that Japan produced the most publications (20.83%, 201), followed by the United States (19.90%, 192), and China (14.09%, 136). However, the United States has the highest total number of citations in this field. Harvard Medical School and Harbin Medical University had the highest numbers of publications and citations. The journal with the most publications was the International Journal of Cardiology. Plaque erosion, calcified nodules, and intracoronary imaging are the most recent research hotspots and frontiers. Our work summarizes 25 years of OCT research in the ACS, highlighting hotspots, key themes, and emerging frontiers to help guide future research.

Worldwide research trends on bone metastases of lung cancer: a bibliometric analysis

BackgroundLung cancer has the highest fatality rate among all malignancies worldwide. Within this disease, bone metastasis (BM) emerges as a particularly deleterious site of metastatic dissemination, marked by a dismal prognosis. The objective of this investigation is to shed light on the current international research efforts and the development trajectory on lung cancer BM through a bibliometric analysis (performance and visualization analysis).MethodData were obtained from the Web of Science Core Collection repository on lung cancer BM from 1 January 2012 to 1 January 2022. Subsequently, the collected data underwent scrutiny using the VOSviewer software to reveal patterns of co-authorship, co-citation, and keyword analysis, while the CiteSpace software facilitated the generation of keyword cluster maps and performed burst analyses.ResultsThe study included 327 papers of 2,154 authors, 587 organizations, and 41 countries, and explored the cooperation between them and the relationships between citations. Over the past decade, published papers showed a steady growth trend. China had the highest production with 189 papers, and USA had the highest collaboration with other countries, with 43 total link strength. Lung Cancer exhibited the highest frequency of co-cited journals, with a co-citation time of 412 and an IF/JCR partition of 6.081/Q1 in 2021. The most frequently co-cited article, authored by Tsuya A and published in Lung Cancer in 2007, amassed 70 co-citations. High-frequency keywords were categorized into four clusters: pathogenesis, treatment and clinical manifestations, prognosis, and diagnosis. In recent years, there has been a significant increase in the strong citation burst strength of keywords such as “predictor,” “skeletal-related events,” “efficacy,” “migration,” “docetaxel,” and “impact.” Lung adenocarcinoma is the most common type of tumor.ConclusionThis bibliometric study provides a comprehensive analysis of lung cancer BM in the recent 10 years. The field of early diagnosis, pathogenesis, and new treatments is entering a phase of rapid development and remains valuable for future research.

A bibliometric and visualization analysis of global trends and frontiers on macrophages in abdominal aortic aneurysms research.

Macrophages are key regulators of the inflammatory and innate immune responses. Researchers have shown that aberrant expression of macrophages contributes to the development of abdominal aortic aneurysms (AAA). However, a comprehensive bibliometric analysis exploring the research status and knowledge mapping of this area is lacking. This study aimed to explore the research status, knowledge mapping and hotspots of macrophages in AAA research from a bibliometric perspective. In this study, we retrieved articles published between 2000 and 2022 on macrophages associated with AAA research from the Web of Science Core Collection (WoSCC) database. The retrieved literature data were further analyzed using Citespace and VOSviewer software. A total of 918 qualified publications related to AAA-associated macrophages were retrieved. The number of publications in this field has been increasing annually. China and the United States were the 2 main drivers in this field, contributing to more than 64% of the publications. In addition, the US had the most publications, top institutions, and expert researchers, dominating in research on macrophages in AAA. The Harvard University was the most productive institution, with 60 publications. The journal with the most publications was Arteriosclerosis, Thrombosis, and Vascular Biology (86). Daugherty Alan was the most prolific author (28 publications) and he was also the most cited co- author. Furthermore, the exploration of established animal models, macrophage-related inflammatory-microenvironment, macrophage-related immune mechanism, clinical translation and molecular imaging research remained future research directions in this field. Our findings offered new insights for scholars in this field. They will help researchers explore new directions for their work.

Research Dynamics and Frontiers of Environmental, Social, and Governance Disclosure: Bibliometric Visual Analysis Based on CiteSpace

Abstract: With the increasing global attention on sustainable development and corporate social responsibility, studying the dynamics and frontiers of Environmental, Social, and Governance (ESG) disclosure is of great significance to academia, corporate practice, and policy-making. This study employs CiteSpace for bibliometric visual analysis, utilizing methods such as keyword co-occurrence analysis, cluster analysis, and research theme evolution analysis to comparatively analyze the differences in ESG research between domestic and international contexts. The study reveals the hotspots, trends, and development directions of ESG disclosure research. The findings indicate a steady growth in the number of publications in the ESG disclosure research field, with research themes shifting from singular environmental information disclosure to a more comprehensive focus on social responsibility and governance structures. This study not only provides researchers with new perspectives, expanding and deepening the themes of ESG research, but also offers references for companies to enhance ESG disclosure and for policy-making, thus holding significant theoretical and practical implications.

Iconografía precolombina en el arte urbano y el grafiti en Bogotá. Un acercamiento a la prácticade pintura mural precolombina en espaciosconvencionales y no convencionales

The past, far from being a remote time framed in remi-niscence and faint imagery, is latent and susceptible to change. The main objective of this paper was to applymethodologies provided by fields of knowledge such asethnography, sociology, and art history, in order to capture and delve into the presence of pre-Columbian iconography in urban art and graffiti in the city of Bogotá, in both conventional and unconventional spaces; taking an epistemological approach to the practice of mural painting with allusions to pre-Columbian elements. In this way, through urban drifts, iconographic and iconological visual analysis, mapping, and qualitative interviews, we examined over twenty mural paintings, from which theoretical approaches were derived in relation to the use of public space, on the one hand, and the use of symbols, on the other. The conclusion reached is that artistic interventions, by participating in the construction and reconstruction of the social fabric, allow us to understand space as a volatile phenomenon; likewise, in the exercise of reflecting on the presence of art in the city, it is critical to pay attention to the conditions of production under which a piece is made, insofar as images have historically been powerful semantic toolsthat embody a purpose. Finally, the paper is an argument in favor of observation as a space of learning. The present reflections were part of a research process developed for the class “Uses of the past in the present: The Iconography of Antiquity in the Contemporary Culture”, at the Universidad de los Andes, first semester of 2023.