Visual Analysis Research Articles

Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023.

Obesity, a multifactorial and complex health condition, has emerged as a significant global public health concern. Integrating machine learning techniques into obesity research offers great promise as an interdisciplinary field, particularly in the screening, diagnosis, and analysis of obesity. Nevertheless, the publications on using machine learning methods in obesity research have not been systematically evaluated. Hence, this study aimed to quantitatively examine, visualize, and analyze the publications concerning the use of machine learning methods in obesity research by means of bibliometrics. The Web of Science core collection was the primary database source for this study, which collected publications on obesity research using machine learning methods over the last 20 years from January 1, 2004, to December 31, 2023. Only articles and reviews that fit the criteria were selected for bibliometric analysis, and in terms of language, only English was accepted. VOSviewer, CiteSpace, and Excel were the primary software utilized. Between 2004 and 2023, the number of publications on obesity research using machine learning methods increased exponentially. Eventually, 3286 publications that met the eligibility criteria were searched. According to the collaborative network analysis, the United States has the greatest volume of publications, indicating a significant influence on this research. coauthor's analysis showed the authoritative one in this field is Leo Breiman. Scientific Reports is the most widely published journal. The most referenced publication is "R: a language and environment for statistical computing." An analysis of keywords shows that deep learning, support vector machines, predictive models, gut microbiota, energy expenditure, and genome are hot topics in this field. Future research directions may include the relationship between obesity and its consequences, such as diabetic retinopathy, as well as the interaction between obesity and epidemiology, such as COVID-19. Utilizing bibliometrics as a research tool and methodology, this study, for the first time, reveals the intrinsic relationship and developmental pattern among obesity research using machine learning methods, which provides academic references for clinicians and researchers in understanding the hotspots and cutting-edge issues as well as the developmental trend in this field to detect patients' obesity problems early and develop personalized treatment plans.

Sharing Stories, Food and Passports: Forced Migration, Museum and Memory Activism in Contemporary Germany

ABSTRACT This article uses the online exhibition ‘Arriving: Life after Forced Migration’ by the Marienfelde Refugee Center Museum in Berlin as a case study to investigate how museum activism can contribute to creating and disseminating memories about contemporary forced migration. Employing a close visual and textual analysis of the online exhibition combined with insights from recent discourses on museum activism, migration and memory studies, the article explores which forms of memory the exhibition creates, how these memories emerge and to which end they are used. The analysis firstly illustrates how the exhibition creates a space for communicative memory to surface within the portrayed refugee families through the sharing of stories, objects and food from ‘home’. Secondly, it goes on to argue that the exhibition engages in memory activism by humanizing the portrayed individuals, exposing discriminatory state practices and challenging the audience through provocative questions. Thirdly, the article submits that this online exhibition contributes to a growing transnational archive of forced migration memories. Comprised of a multitude of online platforms dedicated to collecting, preserving and sharing forced migration stories, this archive stimulates multidirectional memory making and allows counter narratives to surface within an increasingly divided Europe.

How to decipher the environmental resilience performance? A case study of Yangtze River Delta Urban Agglomeration

Improving environmental resilience performance (ERP) is a significant support for achieving sustainable development goals. This study introduces the three-dimensional analysis framework of "object-process-actor", capable of addressing multidimensional and multilevel issues. This framework systematically addresses the "three key questions" of what, how, and who to improve ERP. Results indicate that from 2011 to 2020, the ERP of the Yangtze River Delta Urban Agglomeration (YRDUA) was between 0.42 and 3.30. The violin plot and visualization analysis showed that its probability density and distribution status were stable, with significant regional differences. The ERP of economically developed cities such as Hangzhou and Shanghai is high, while the ERP of cities in the Yancheng-Chuzhou line is low, and the number of high-performing cities increases to 40.7% in 2020, which is a constantly improving development trend. Factors related to market actors have the greatest impact on ERP, with the explanatory power of FDI, green invention patents, and population concentration all exceeding 0.6, and the importance of government and social actors is also supported. The explanatory power of factor interactions was stronger than that of single factors, and land development degree ranked third in terms of its interaction power with other factors and was also a key factor influencing ERP. These findings provide new explanations and knowledge for improving ERP, which can provide references for policymakers and urban planners.

Visual Analysis of Hot Topics and Trends in Nutrition for Decompensated Cirrhosis Between 1994 and 2024

Objective An updated summary of the research profile of nutrition for the last 30 years for decompensated cirrhosis is lacking. This study aimed to explore the literature on nutrition for decompensated cirrhosis, draw a visual network map to investigate the research trends, and provide suggestions for future research. The Web of Science database retrieves the literature on nutrition for decompensated cirrhosis between 1994 and 2024. Methods We used the cooperative, co-occurrence, and co-citation networks in the CiteSpace knowledge graph analysis tool to explore and visualize the relevant countries, institutions, authors, co-cited journals, keywords, and co-cited references. Results We identified 741 articles on nutrition for decompensated cirrhosis. The number of publications and research interests has generally increased. The USA contributed the largest number of publications and had the highest centrality. The University of London ranked first in the number of articles issued, followed by the University of Alberta and Mayo Clinic. TANDON P, a “core strength” researcher, is a central hub in the collaborative network. Of the cited journals, HEPATOLOGY had the highest output (540, 15.3%). Conclusions Over the past three decades, the focus of research on nutrition in decompensated cirrhosis has shifted from “hepatic encephalopathy, intestinal failure, metabolic syndrome, and alcoholic hepatitis” to “sarcopenia and nutritional assessment.” In the future, nutritional interventions for sarcopenia should be based on a multimodal approach to address various causative factors. Its targeted treatment is an emerging area that warrants further in-depth research.

Mapping the relationship between atopic dermatitis and gut microbiota: a bibliometric analysis, 2014-2023.

Atopic dermatitis (AD) is a chronic inflammatory skin condition affecting a significant portion of the population, with prevalence rates of 25% in children and 7-10% in adults. AD not only poses physical challenges but also profoundly impacts patients' mental well-being and quality of life. The stability of gut microbiota is crucial for overall health and can influence AD progression by modulating immune function, skin barrier integrity, and neuroendocrine signaling, which may be an effective target for the prevention and treatment of AD. Thus, exploring the interactions between AD and gut microbiota, particularly in infants, can provide insights into potential preventive and therapeutic strategies. This study aimed to explore the correlation between AD and gut microbiota while providing an overview of current research trends and emerging areas of interest in this field. A comprehensive search was conducted on the Web of Science Core Collection (WOSCC) for relevant publications from January 1, 2014, to December 31, 2023. English-language articles and reviews were included. Two investigators independently screened the publications, and visual analysis was performed using CiteSpace, VOSviewer, Scimago Graphica, and Microsoft Excel software. A total of 804 articles were included, showing a significant increase in publications over the past decade. The United States, Wageningen University, and University Ulsan (represented by Hong SJ) had the highest number of published papers. Nutrients was the journal with the most publications, while the Journal of Allergy and Clinical Immunology had the highest number of citations and centrality among co-cited journals. Keyword visualization analysis identified "atopic dermatitis" and "gut microbiota" as central themes. Notably, there has been a notable shift in research focus over the years, with early studies concentrating on "Fecal microbiota," "caesarean section," and "first 6 months," while recent studies have highlighted the roles of "cells," "dysbiosis," and "prebiotics." This shift indicates growing interest in the underlying mechanisms and potential therapeutic interventions related to the intestinal microecology in AD treatment. The field of AD and gut microbiota research has evolved significantly, with an increasing focus on understanding the intricate interactions between gut microbiota and AD pathogenesis. Recent years have witnessed increased interest in understanding the relationship between AD and gut microbiota, with researchers conducting extensive studies exploring various aspects of this connection. This review analyzes research trends over the past decade, highlighting trends and hotspots in the study of AD, particularly in infants, and the role of microbiota. This review serves as a valuable reference for future investigations, aiming to provide deeper insights into this burgeoning field and suggests directions for future research.

Mapping knowledge domain of acupuncture for Parkinson's disease: a bibliometric and visual analysis.

This study points to probing the inclination and mapping knowledge domain of acupuncture for Parkinson's disease through bibliometrics. A search was conducted on 1 February 2024 using the Web of Science to identify papers published on acupuncture for Parkinson's disease. The analysis included scientific research, countries, organizations, authors/cited authors, keywords, journals, and cited references. Bibliometric data were analyzed using VOSviewer software, CiteSpace, GraphPad Prism, and Scimago Graphica. The studies on acupuncture for Parkinson's disease were visualized as a network map according to the publication year. The cumulative publication trend on acupuncture for Parkinson's disease is increasing year by year. China is the leading contributor in this field. International collaboration is predominantly concentrated in Europe, while institutional collaboration is chiefly limited to Chinese universities specializing in traditional Chinese medicine. Park HJ is the most prolific author, with "Movement Disorders" being the journal with the most publications. "Brain Research" is identified as a key journal, reflecting a focus on neuroscience. Kim SN is the most cited author, while Eisenberg DM is a prominent author in this field. Research topics such as mouse models, systematic reviews, and non-motor symptoms are frequently explored, with messenger RNA of substantia nigra emerging as a notable keyword in this field. Choi YG's 2009 paper, published in the Neuroscience Letters journal, is a critical reference in this field. Key papers include Eisenberg DM's 1998 study on randomized trials of acupuncture for non-motor symptoms of PD, as well as research focusing on the neuroinflammatory regulatory mechanisms of acupuncture for PD. The bibliometric analysis offers an exhaustive generality of the advancement and worldwide trends in acupuncture treatments for Parkinson's disease, shedding light on potential avenues for prospective research.

Temporary Visual Hallucinations in a 31-year-old Female Patient Post Falcotentorial Meningioma Resection with No History of Psychosis: A Case Report

Introduction: Falcotentorial meningiomas are rare, comprising 1%–2% of all intracranial meningiomas, arising at the junction of the falx cerebri and tentorium. These tumors may compress the quadrigeminal plate and/or splenium, leading to peduncular hallucinosis—vivid, colorful visual hallucinations of people and animals, which can persist even after tumor removal. Case Description: A 31-year-old woman with no psychosis history presented with a bilateral visual field deficit and left extremity weakness. Brain MR imaging revealed a lobulated mass attached to the right cerebellar tentorium, posterior falx cerebri, and adjacent venous sinuses. Visual field analysis showed homonym superior quadranopsia. Following craniotomy and tumor removal, histology confirmed a mixed-type meningioma. Post-surgery, the patient experienced vivid visual hallucinations that resolved in two weeks, but bilateral visual field deficits remained. A post-op CT showed reduced structural compression around the lesion with slight narrowing of the quadrigeminal cistern. Discussion : Visual hallucinations in falcotentorial meningioma patients, often as peduncular hallucinosis, occur due to compression of the quadrigeminal plate and/or splenium and may persist post-surgery if lesions are present in the cerebral peduncles or nearby midbrain areas. Conclusion: The patient's temporary hallucinations may have resulted from post-resection tissue edema causing quadrigeminal cistern narrowing or indicate lesions in the cerebral peduncles or adjacent midbrain regions.

Design and Coupled Moisture-Thermal Transfer Simulation of Opposite Cross-Section Polyethylene Terephthalate Knitted Fabric with Hygroscopic Quick-Drying Capability.

In addition to sportswear and outdoor equipment, moisture-absorbent quick-drying fabrics are also widely used in everyday clothing and home textiles. In this study, three types of weft-knitted fabrics were designed using Coolmax fiber and polypropylene fiber. The Coolmax/PP fabric exhibits good stretchability with a strain of 180.5% and achieves a high cumulative individual transfer capability of 691.6%, with a water absorption rate of 50.2%/s. The moisture conductivity gradient presented good moisture and heat conductivity in a simulated human body temperature environment using an infrared camera. Furthermore, mathematical modeling was constructed and visual simulation analysis was conducted to explore moisture-thermal transfer behavior. The simulation results closely align with experimental data, providing insights into designing flexible and wearable quick-drying fabrics for thermal management.

Fuzzy deep visual panic detection

Deep visual data analysis from social network has become an increasingly important area of research. In fact, this form of assessment makes it viable to recognize new information on social users which incorporates emotions. In order to recognize users’ emotions and other latent attributes, most of the existing approaches have used textual data and have obtained accurate results. However, little attention has been paid to visual data that have become increasingly popular in recent years.This work describes how to develop a conceptual representation model for social network analysis and social emotion analysis based on the integration of fuzzy logic and ontological modeling. The primary aim is to create an ontology that can extract new information about a social user’s mood, which can be classified as panic, no-panic, or neutral. Fuzzy logic is necessary to deal with subjective data, as users share imprecise and vague data on their social profiles. Fuzzy logic has been observed as a successful method to capture the expression of emotions due to the fuzzy nature of emotions and the ambiguous definitions of emotion words. The proposed work investigate the role of fuzzy logic in social network analysis. This study simulate a fuzzy deep system integrated with ontology for classifying social visual data (shared images) into panic, no-panic or neutral classes in order to determine the social users’ stress intensity. The Social distancing and the huge amount of shared data in Tunisia were calculated to demonstrate this classification. The experiments performed in this paper aim to create not only a novel annotated visual database named visual panic database, but also a new semantic model for modeling users’ profiles, in social network, based on the combination between ontology and deep learning techniques. In this context, we will work in the future on the combination between a user’s visual and textual data in order to improve the performance of this recognition. The proposed fuzzy system reflected the viral proliferation in stressed users and achieved an accuracy of 87%.

Memification of Students’ Experiences at South African Universities: A Critical Examination of Meme Value within UCT Just Kidding and Wits Just Kidding Memes

Memes are considered a communication tool that allows groups of individuals to form a community and express themselves through three semiotic resources: visuals, text and humour. They provide new references that contribute to the construction of identities. This is especially true within university student communities. In this study, we use two students’ meme pages in South Africa, UCT Just Kidding (@uctjustkidding) and Wits Just Kidding (@witsjustkidding), as case studies to investigate how students use memes to highlight their everyday experiences and the values attached to these memes. We also explore how memes portray significant issues affecting students’ development and progression within the broader South African higher education institutions. Using semi-structured interviews conducted with 7 meme creators and administrators, textual and visual analysis of 14 memes from both pages and Marx’s labour theory of value as a theoretical framework, we argue that students use memes to communicate and raise awareness on salient issues affecting them. We, therefore, underscore memes as a powerful tool for constructing social, political, economic and cultural realities among university students in particular and communities in general.

Sustaining the brand and branding sustainability: landscape as homeland in Greenland’s visual marketing

Arctic destinations are continually reshaping their global identities to manage external expectations about the region. Existing portrayals of Greenland often stereotype the area as untouched wilderness or oversimplify its social, economic, and cultural realities. Our study combines visual analysis of cultural landscape and cultural ecosystem services (CES) to unveil a novel narrative in Greenland’s sustainable tourism branding we termed ‘landscape as homeland’. Empirically this research is based on the photographic database of Greenland’s national destination marketing organization. We explore Greenland’s destination branding as a strategic tool to define local meanings of sustainable tourism, homeland, and “Arcticness” in a branding that distinctively positions itself amidst Arctic destinations. Using pictured landscape as a dwelling place discerns locally valued CES, and realigns tourist engagements toward a culturally and ecologically integrated relationship. Applications of these findings extend to other rapidly changing regions seeking to expand economic opportunities, harnessing the synergy between destination branding and sustainable tourism. We reflect on the efficacy of our integrated CES and cultural landscape research to reveal local framings of the tourism-sustainability tension. We highlight the role of destination marketing organizations to bridge the gap between local identity, visitor expectations, and sustainable tourism development.

Research trends and perspective of low-intensity pulsed ultrasound in orthopedic rehabilitation treatment based on Web of Science: A bibliometric analysis.

Ultrasound has a long history as a diagnostic and therapeutic tool. Low-intensity pulsed ultrasound (LIPUS), whose intensity is below 300 mW/cm2, has been widely used in orthopedic rehabilitation treatment. However, the detailed bioeffects and underlying mechanisms of LIPUS treatment need to be explored. To make a comprehensive view of the field, bibliometric and visualization analysis was used to reveal the global research trends of LIPUS in orthopedics and rehabilitation treatment between 1994 and 2023. All literature data on LIPUS were retrieved from the Web of Science Core Collection database. VOSviewer and CiteSpace were applied for the bibliometric and visualization analysis. A total of 760 publications were included. The distribution of publications generally showed an unstable rising trend. China had the highest number of publications (28.0%), and Chong Qing Medical University was the organization with the highest number of publications (5.8%). Ultrasound in Medicine and Biology had the highest number of publications (8.8%), while BMJ-British Medical Journal had the highest impact factor among the retrieved journals. Ling Qin from the Chinese University of Hong Kong was the most active researcher. Our overlay visualization map showed that the keywords such as pain, knee osteoarthritis, apoptosis, chondrocytes, cartilage, and autophagy, which link to osteoarthritis, have becoming the new research trends and hotspots. LIPUS is a popular and increasingly important area of orthopedic rehabilitation, and collaboration of authors from different countries should be further strengthened. Predictably, clinical application of LIPUS on chronic inflammation-related diseases and regenerative medicine, and in-depth biological mechanisms are the orientations of LIPUS in orthopedic rehabilitation treatment.

Research hotspots and future trends in lipid metabolism in chronic kidney disease: a bibliometric and visualization analysis from 2004 to 2023.

Disorders of lipid metabolism play a key role in the initiation and progression of chronic kidney disease (CKD). Recently, research on lipid metabolism in CKD has rapidly increased worldwide. However, comprehensive bibliometric analyses in this field are lacking. Therefore, this study aimed to evaluate publications in the field of lipid metabolism in CKD over the past 20years based on bibliometric analysis methods to understand the important achievements, popular research topics, and emerging thematic trends. Literature on lipid metabolism in CKD, published between 2004 and 2023, was retrieved from the Web of Science Core Collection. The VOSviewer (v.1.6.19), CiteSpace (v.6.3 R1), R language (v.4.3.2), and Bibliometrix (v.4.1.4) packages (https://www.bibliometrix.org) were used for the bibliometric analysis and visualization. Annual output, author, country, institution, journal, cited literature, co-cited literature, and keywords were also included. The citation frequency and H-index were used to evaluate quality and influence. In total, 1,285 publications in the field of lipid metabolism in CKD were identified in this study. A total of 7,615 authors from 1,885 institutions in 69 countries and regions published articles in 466 journals. Among them, China was the most productive (368 articles), and the United States had the most citations (17,880 times) and the highest H-index (75). Vaziri Nosratola D, Levi Moshe, Fornoni Alessia, Zhao Yingyong, and Merscher Sandra emerged as core authors. Levi Moshe (2,247 times) and Vaziri Nosratola D (1,969 times) were also authors of the top two most cited publications. The International Journal of Molecular Sciences and Kidney International are the most published and cited journals in this field, respectively. Cardiovascular disease (CVD) and diabetic kidney disease (DKD) have attracted significant attention in the field of lipid metabolism. Oxidative stress, inflammation, insulin resistance, autophagy, and cell death are the key research topics in this field. Through bibliometric analysis, the current status and global trends in lipid metabolism in CKD were demonstrated. CVD and DKD are closely associated with the lipid metabolism of patients with CKD. Future studies should focus on effective CKD treatments using lipid-lowering targets.

Influential mechanism of water occurrence states of waste-activated sludge: Specifically focusing on the pore characteristics dominated by cation-organic interactions

The solid pore characteristics are commonly considered as the important influential factors on waste-activated sludge (WAS) dewaterability, and should be related to the cohesive force of bio-flocs dominated by cation-organic interactions at solid-water interface. This study aimed to establish an approach for regulating the solid pore structure of WAS by cationic regulation. The influential mechanism of WAS dewaterability was accordingly explored from the perspective of the pore characteristics dominated by cation-organic interactions. Primarily, with the gradient removal or addition of bivalent cations, the varying pore structure of WAS flocs was tracked by in-situ synchrotron X-ray computed microtomography imaging technique (CMT). The three-dimensional visual model was established to quantify the pore structure parameters of WAS flocs. Following the visualization analysis, the artificial intelligence means, the gradient-weighted class activation mapping (Grad CAM) of three-dimensional convolutional neural network (3D-CNN), was applied for the first time to explore the linkages among solid surface properties, solid pore structure, water occurrence states and sludge dewaterability. It was found that the number and volume of isolated pores jointly determined the mobility and the fractions of vicinal water and interstitial water (p-value ≤ 0.02); also, the decreasing polar or acid-based interfacial free energy with the cationic addition was accompanied with the decreasing isolated pore mean-volume (Pearson coefficient=-0.77, p-value < 0.01). These results indicated that the pore structure characteristics determined the water occurrence states, but the solid porosity strongly depended on the interfacial properties. Accordingly, the molecular docking was applied to explore the interfacial reaction mechanism between Ca2+/Mg2+ and solid compositions in terms of complexation sites, molecular dynamics and free energy calculations. As a result, how the cation-organic interactions affected the pore characteristics through solid surface modification could be clarified, which is expected to serve as theoretical foundation for the development of novel sludge conditioning technologies, i.e., more efforts should be devoted to increasing the dense degree of sludge particles through weakening the hydration repulsion of solid surface.

Progress in adaptive governance research and hotspot analysis: a global scientometric visualization analysis

Adaptive governance has emerged as a prominent theoretical and methodological approach in environmental governance, recognized for its capacity to address evolving conditions and future uncertainties. Despite the extensive literature on adaptive governance since its inception in 2003, a comprehensive review of the literature spanning two decades remains to be conducted. This study addresses that gap by selecting 3274 articles from the Web of Science Core Collection and performing a global scientometric visualization analysis. Our analysis identifies the most productive institutions, authors, journals, publication trends, and research frontiers in adaptive governance research. The findings reveal that there has been a significant acceleration in global research on adaptive governance over the past two decades. Furthermore, the majority of contributions to the field of adaptive governance research have been made by scholars based in the United States, Australia, England, Canada, and the Netherlands. Additionally, existing studies in adaptive governance field focus mainly on subject categories of environmental studies, environmental sciences, and ecology. Finally, the concept of adaptive governance, environmental governance, social-ecological systems, climate change adaptation and social learning were identified as hot topics and emerging trends. This study provides researchers and practitioners with an extensive understanding of the salient research themes, trends, and patterns in global adaptive governance research in an intuitive manner.

Sequencing technology in sarcopenia: current research progress and future trends.

Muscle is an important tissue of the human body. Muscle atrophy is common in people of all ages, which will lead to human weakness and decline of motor function, which is one of the important causes of disability. The common methods of genomics research are transcriptome, proteomics and metabolomics, which are important means to explore the molecular pathology of diseases. In recent years, combinatorial research has been carried out on a large scale in the field of muscle atrophy. However, no author in this field has carried out bibliometrics and visual analysis. In this study, articles related to the histological study of muscular dystrophy since 2000 were searched from the Web of Science core database (WoSCC). We will retrieve the results through CiteSpace, VosViewer and R for data statistics and visual analysis. In this study, a total of 141 publications were collected, and the number of publications increased year by year. These 141 articles came from 1031 co-authors from 361 institutions in 31 countries and were published in 92 journals. A total of 6286 articles from 1383 journals were cited. Authors from American institutions have published the most articles and have been cited the most, and authors from other countries have also made considerable contributions. This is the first bibliometric and visual analysis of published research in the field of muscular dystrophy through systematic data retrieval and combined with a variety of bibliometric analysis tools. Through these data, we summarize the previous studies of scholars, and provide prospects for future research in the field.

A bibliometric analysis of the application of physical therapy in knee osteoarthritis from 2013 to 2022.

Knee osteoarthritis (KOA) is one of the most common chronic joint diseases. Physical therapy, a non-invasive approach, is extensively used in its treatment. Although bibliometrics is a reliable method to evaluate the significance and impact of research fields, systematic bibliometric analyses in this area are lacking. This study aims to perform a bibliometric analysis covering 2013 to 2022, to highlight the current state, key focuses, and trends in physical therapy for KOA. This study utilizes the Web of Science Core Collection to gather relevant literature on physical therapy and KOA from 2013 to 2022. CiteSpace and VOSviewer software facilitated the visual analysis of the annual publications, geographic and institutional distributions, journals, authors, references, and keywords in this field. The study analyzed 1,357 articles, showing an overall increase in publications over time from 71 countries and 2,302 institutions. The United States and Australia emerged as leaders in this field. The analysis identified 6,046 authors, with Kim L. Bennell as the most prolific and Bellamy N. receiving the most citations. BMC Musculoskeletal Disorders published the most articles, while Osteoarthritis and Cartilage received the most citations. High-impact articles were authored notably by McAlindon TE, Bannuru RR, Fernandes L, and Bennell KL. Keyword analysis highlighted a strong focus on patient self-management, exercise therapy, physical factor therapy, and remote rehabilitation. The bibliometric analysis confirms significant interest and ongoing research in physical therapy for KOA treatment from 2013 to 2022, indicating a growing field. Journals and authors in this area show influential and collaborative dynamics. Future research should focus on enhancing international and institutional collaboration and explore emerging trends like internet-guided treatments.

Multibeam water column image super-resolution by combining morphological and intensity features

ABSTRACT Multibeam water column images (WCI) play a crucial role in the detection and recognition of underwater targets. However, WCI is not a complete image of underwater space due to the gaps between beams inherent in multibeam systems. In this study, we design the WCI super-resolution network (WCISRN) based on Swin-transformer to adapt to the uneven and sparse distribution of water column data. To enable WCISRN to learn morphological features effectively, we produced simulated datasets for pre-training. Subsequently, we conduct self-supervised training on the measured WCI dataset to fine-tune the network parameters, aiming to better adapt WCISRN to the backscattering intensity features of WCI. Finally, by performing network cross-fusion, the pre-trained network and self-supervised training network are combined to form a new network that achieves a balance between image morphology and intensity features. The proposed method is evaluated through visual analysis and quantitative comparison using simulated and real-world datasets. The experimental results demonstrate that our method exhibits stronger detail restoration ability and clearer image morphology. The average peak signal-to-noise ratio (PSNR) on the test set improved from 23.75–26.14, indicating a significant enhancement in the imaging quality of WCI.

Makna Sampul Majalah Tempo tentang Pemilihan Umum edisi Januari 2024

Tempo magazine covers use strong visuals and striking illustrations to highlight the main topics of each issue. This research analyzes the visual meaning of three covers of the January 2024 edition of Tempo magazine—"Angan-anganan Satu Lapir," "Omon-omon Bansos," and "Operator President Jokowi"—using Charles Sanders Pierce's semiotic theory and visual analysis. This study examines elements such as illustrations, typography, colors and symbols on the cover to reveal the messages and themes conveyed. Qualitative methods are used to explore the message the magazine wants to convey. The research results show that cover design with the right use of color, typography, layout, visual identity, illustrations and infographics plays an important role in shaping readers' perceptions. Colors such as dark red and white reflect political pressure and honesty, while light blue creates a sense of stability. These symbols are effective in conveying the political dynamics of the 2024 Presidential Election in Indonesia and the impact of loyalty to President Jokowi on the election process and support for his son's candidacy.

Enhanced Differentiation of Amiodarone-Induced Thyrotoxicosis Types Using Semi-Quantitative 99mTc-MIBI Uptake Analysis: A Pilot Study.

BACKGROUND Technetium (99mTc)-labelled Methoxy-2-Isobutylisonitrile (MIBI) is a diagnostic lipophilic cationic radiotracer used to evaluate the cardiac, breast, thyroid, and parathyroid pathology. This study aimed to evaluate the role of MIBI combined with Tc-99m pertechnetate thyroid scintigraphy, thyroid ultrasonography, and measurement of thyrotropin, thyroid hormones, and autoantibodies to subtype amiodarone-induced thyrotoxicosis (AIT) and the contribution of semi-quantitative analysis of MIBI uptake. MATERIAL AND METHODS This cross-sectional study included 36 patients with AIT who underwent thyrotropin, thyroid hormone, and autoantibody analysis using chemiluminescent method, ultrasonography, pertechnetate, and MIBI thyroid scintigraphy with semi-quantitative uptake, including calculation of the target-to-background ratio (TBR) with 2 different background regions. The MIBI washout rate (WR) was analyzed in all groups. Statistical analysis was performed using descriptive statistics, correlations, and the receiver operating characteristic curve - area under the curve (ROC-AUC). The results were compared with the control group. RESULTS Based on visual and semi-quantitative analyses, patients were successfully categorized into AIT groups (AIT-1, AIT-2 and AIT-3) but the latter method enabled better differentiation of MIBI uptake between all groups. Additionally, ROC-AUC analysis determined cutoff values which enabled discerning between AIT-1 and AIT-2 groups, and AIT-1 and AIT-3 groups. WR showed no significant difference between all AIT groups and controls (P>0.05). CONCLUSIONS Visual MIBI analysis enabled differentiation between AIT-1 and 2 groups, but the method was substantially improved with semi-quantitative analysis, especially in defining AIT-3 group. However, multicenter collaboration with larger studies is needed to standardize the method and obtain more accurate and consistent results.