Visualization Platform Research Articles

A Critical Review of Canva as a Visual Media Platform for English Learning

This article reviews the use of online visual media platforms for English language learning, revealing that these platforms influence learners' motivation, participation, skill assessment, and collaborative learning environments. The review also highlights the need for further research on the integration of visual media in English language acquisition, particularly in reputable publications like Scopus and Google Scholar. This study also focuses on the writer's existing knowledge and aims to develop their own application of analysis based on their learning from related works. A total of 17 articles were retrieved from two online databases: the SCOPUS database and the Google Scholar website, using keywords related to the theme of online Visual media platforms accommodating online learning experiences and the effectiveness of onlinevisual media platforms. The study incorporated three research approaches: qualitative, quantitative, and mixed-method Research design methodology. The findings indicated the need of using all three research methods to get a legitimate and robust result for data interpretation in the field of education when using Canva as an online visual medium platform.

Heritage Iconographic Content Structuring: from Automatic Linking to Visual Validation

This article presents a global framework dedicated to the structuring of iconographic heritage collections. To alleviate the poor interlinking both between collections and contents, a first step of automatic linking exploiting content-based image retrieval approaches is evaluated and adapted to the visual variability of such heritage contents. To ensure understanding and analysis of the contents in a structured fashion, a 3D immersive web platform is also introduced alongside visual-based analysis tools. Finally, by exploiting both automatic linking and manual interventions in the visualization platform, an iterative, semi-automatic structuring pipeline is proposed to solve difficult cases missed by automatic structuring, and then improve structuring optimally. Here, we demonstrate the potential of the proposal on the geographic iconographic heritage of Paris, with a dataset of 10k images belonging to several institutions, thus poorly connected nor organized globally.

Real-time Vital Signs Monitoring and Data Management Using a Low-Cost IoT-based Health Monitoring System

This study describes the creation and evaluation of a low-cost internet of things (IoT)-based health monitoring system for the continuous monitoring of vital signs such as temperature, pulse rate, oxygen saturation (SpO2) and blood pressure (BP) (both systolic and diastolic). Along with an organic light-emitting diode (OLED) display and an ESP8266 microcontroller, the system includes BP, non-contact temperature, SpO2 and electrocardiogram (ECG) sensors. Using the visual programming tool, Node-RED, the data from these sensors are gathered, processed and transmitted to the Google Cloud platform for archival and visualisation. The process involved mounting the sensors and microcontrollers on a special printed circuit board and designing the circuit with EasyEDA. The device measures systolic, diastolic and pulse rates from the BP sensor, as well as temperature, ECG and SpO2 values. The system works by using three push switches to read and display these values on demand. The gathered data are simultaneously shown on the OLED and sent to the Node-RED dashboard, where it is then sent to a Google Spreadsheet for archiving and analysis. This research article gives a thorough overview of the health monitoring system, the way it was implemented, and how it was successfully validated in a real-time setting. This study examines certain vital signs but additional health measures, such as respiration rate or glucose monitoring, could be included. Machine learning algorithms could also be used for predictive analytics. This would uncover data anomalies and trends early, improving healthcare management.

Deep Transcriptomics Reveals Cell-Specific Isoforms of Pan-Neuronal Genes.

Profiling gene expression in single neurons using single-cell RNA-Seq is a powerful method for understanding the molecular diversity of the nervous system. Profiling alternative splicing in single neurons using these methods is more challenging, however, due to low capture efficiency and sensitivity. As a result, we know much less about splicing patterns and regulation across neurons than we do about gene expression. Here we leverage unique attributes of the C. elegans nervous system to investigate deep cell-specific transcriptomes complete with biological replicates generated by the CeNGEN consortium, enabling high-confidence assessment of splicing across neuron types even for lowly-expressed genes. Global splicing maps reveal several striking observations, including pan-neuronal genes that harbor cell-specific splice variants, abundant differential intron retention across neuron types, and a single neuron highly enriched for upstream alternative 3' splice sites. We develop an algorithm to identify unique cell-specific expression patterns and use it to discover both cell-specific isoforms and potential regulatory RNA binding proteins that establish these isoforms. Genetic interrogation of these RNA binding proteins in vivo identifies three distinct regulatory factors employed to establish unique splicing patterns in a single neuron. Finally, we develop a user-friendly platform for spatial transcriptomic visualization of these splicing patterns with single-neuron resolution.

AI-Enhanced Data Visualization: Transforming Complex Data into Actionable Insights

Purpose: The purpose of this study is to explore how artificial intelligence (AI) becomes a part of data visualization. Thus, data from complex datasets are transformed into dynamic, interactive, and personalized visual experiences that will help in deeper insights and actionable knowledge. The research is supposed to design a holistic system and rules for using AI to make data visualization more effective and super interactive for the users. Methodology: The methodology involves the in-depth examination of artificial intelligence-based data visualization tools and platforms by using case studies. The study analyses the impact of AI technologies such as machine learning, natural language processing, and augmented and virtual reality on the scalability, interactivity, and personalization of data visualizations. The sentence also talks about the analysis of the moral factors that are part of the process of introducing AI in data visualization. Findings: The findings indicate that AI greatly improves the process and the quality of data visualization, thus, it makes possible the management of big, complicated, multi-dimensional datasets in a more efficient and precise way. The AI-driven tools give the users the opportunity to see the actions that are happening in real-time, predict the results, and personalize the tools according to their individual needs, thereby increasing the decision-making processes. Furthermore, ethical issues like data privacy, bias, and transparency must be well managed. This research has the distinctive feature of providing a theoretical framework that emphasizes the importance of AI in the development of data visualization technologies. Unique contribution to theory, policy and practice: In practice, it gives the rules for the implementation of AI tools to achieve more effective and user-focused visualizations. The policy focuses on the necessity of ethical standards in AI deployments, which means the data visualization practices should be transparent, accountable, and bias-free, thus creating trust and reliability in the AI applications.

Mechanism Analysis and Optimization Design of Exoskeleton Robot with Non-Circular Gear–Pentabar Mechanism

To address the complex structure of existing rod mechanism exoskeleton robots and the difficulty in solving the motion trajectory of multi−rod mechanisms, an exoskeleton knee robot with a differential non−circular gear–pentarod mechanism is designed based on non−circular gears with arbitrary transmission ratios to constrain the degrees of freedom of the R-para-rod mechanism. In this study, the kinematic model of a non-circular gear–five−rod mechanism is established based on motion mapping theory by obtaining the normal motion positions of the human lower limb. An optimization design software for the non-circular gear–five−rod mechanism is developed using the MATLAB 2018b visualization platform, with the non−circular active gear as the sole input variable. A set of ideal parameters is obtained through parameter adjustment and optimal parameter selection, and the corresponding trajectories are compared with human trajectories. The three−dimensional model of the mechanism is established according to the obtained parameters, and the motion simulation of the non−circular gear–five−bar mechanism demonstrates that the mechanism can better reproduce the expected human knee joint motion posture, meeting the working requirements of an exoskeleton knee robot.

Coordination assembly and NIR photothermal conversion of Metal-organic framework based on 5-(2-cyanophenoxy) isophthalic acid

The development of new photothermal conversion materials in the field of metal-organic frameworks (MOFs) shows broad prospects, but their design synthesis and proper mechanism analysis are still full of huge challenge. Here, four novel MOFs were constructed with 5-(2-cyanophenoxy) isophthalic acid, {Ni(2-CB-IPA)(bpp)(H2O)}n (1), {Ni2(2-CB-IPA)2(bpa)2(H2O)2}n (2), {Co(2-CB-IPA)(bpp)}n (3), {Mn2(2-CB-IPA)2 (bpp)(H2O)2}n (4). (Where 2-CB-IPA = 5-(2-cyanophenoxy) isophthalic acid, bpa = 1,2-bis(4-pyridine)-ethane; and bpp = 1,3-bis(4-pyridyl)propane). The absorption peak at 730 nm in the near-infrared region indicates that different charge transfer interactions affect the photothermal conversion ability. Under laser irradiation (730 nm, 0.45 W cm−2), such compounds exhibit different and distinct warming processes (1 from 20.8 to 91.8 °C; 2 from 20.1 °C to 86.2 °C; 3 from 20.6 to 77.1 °C) except for compound 4. The excellent crystallinity of these materials after irradiation demonstrates excellent thermal stability and cycling durability. Subsequently, further research on the structure-activity relationship revealed that strong π - π interactions are also the reason for the excellent performance of NIR photothermal conversion of 1 under the premise of high NIR absorption. This work provides a visual platform for the photothermal phenomena of crystalline materials.

Development of Parametric Modeling and Visualization Platform for Interior Design

Development of Parametric Modeling and Visualization Platform for Interior Design

Prevalence and trends in physical therapy interventions for erectile dysfunction: A Scopus-based bibliometric analysis (1989-2022).

Erectile dysfunction (ED) is a condition that affects many males. Physical therapy (PT) is the one potential treatment for ED that may improve blood flow, muscle strength, and other factors that may contribute to the issue. Data on the prevalence and trends of research on PT for ED are lacking. This study aimed to evaluate the literature trends in PT for ED via bibliometric and visualized analysis. Data on publications were collected from Scopus covering the period between 1989 and 2022. To refine the data, bibliometric analyses were conducted using Microsoft Access, Microsoft Excel, an online visualization platform, and BiblioAnalytics. Power BI and Bibliomaster were used to generate figures and tables, while Biblioshiny and VOSviewer were used for visualization. A total of 494 documents were identified. The year 2019 generated the largest number of publications, with a total of 54. These studies have received 12,917 citations related to PT for ED. The most common document type was the original article with 283 publications. The University of California, USA, was the most productive institution on this topic, with 21 publications and 2,035 citations. The USA led all countries with 114 publications on the topic. The Journal of Sexual Medicine secured the top ranking with an h-index of 18. The main topics studied were erectile dysfunction, shockwave therapy, and physiotherapy. The number of publications on PT for ED has demonstrated an upward trend over the last three decades.

US County-Level Variation in Availability and Prevalence of Black Physicians in 1906

Black physicians are substantially underrepresented in the US health care workforce, with detrimental effects on the health and health care experiences of Black individuals. These contemporary gaps can be traced to the early days of the medical profession using the first edition of the American Medical Directory (AMD). To identify state- and county-level patterns related to the training and availability of Black physicians relative to their White counterparts in the 1906 AMD. For this cross-sectional study, data for 41 828 physician entries in 18 US states in or adjacent to the South as well as the District of Columbia were extracted from the 1906 AMD and aggregated to 1570 counties. Data analysis was performed between September 2023 and January 2024. County-level exposure variables included population density, racial composition, and illiteracy rate among US-born White residents as well as an index of terrain ruggedness and the number of lynchings in the previous decade. Median values of physicians' distance from place of practice to place of medical training (by race of physician) were also used as an exposure variable. There were 4 county-level outcomes: (1) presence of any Black physician, (2) proportion of Black physicians per Black population, (3) proportion of White physicians per White population, and (4) community representativeness (reported as the community representativeness ratio). The cross-sectional analysis used generalized additive mixed models with state-level random effects. Across 1570 counties, Black physicians comprised 746 (1.8%) of the 41 828 physicians in the dataset. Black physicians tended to train further from their place of practice than their White counterparts. The proportion of Black physicians per 1000 Black residents was 0.08 compared with 1.62 for White physicians; these proportions varied substantially by state. At the county level, the presence of any Black physician was associated with percentage Black population (odds ratio [OR], 28.94 [95% CI, 9.77 to 85.76]; P ≤ .001), population density (OR, 2.63 [95% CI, 2.03 to 3.40]; P ≤ .001), and distance to the nearest Black medical school (OR, 0.62 [95% CI, 0.42 to 0.92]; P = .02). A variety of structural disadvantages are illustrated in this cross-sectional study of county-level sociodemographic and geographic characteristics associated with the prevalence of Black physicians in the earliest days of the profession. To demonstrate its broader utility for health disparities research, the dataset has been made publicly available with a visualization platform.

Targeting starvation therapy for diabetic bacterial infections with endogenous enzyme-triggered hyaluronan-modified nanozymes in the infection microenvironment

The high-glycemic microenvironment of diabetic wounds promotes bacterial proliferation, leading to persistent infections and delayed wound healing. This poses a significant threat to human health, necessitating the development of new nanodrug visualization platforms. In this study, we designed and synthesized cascade nano-systems modified with targeted peptide and hyaluronic acid for diabetic infection therapy. The nano-systems were able to target the site of infection using LL-37, and in the microenvironment of wound infection, the hyaluronic acid shell of the nano-systems was degraded by endogenous hyaluronidase. This precise degradation released a cascade of nano-enzymes on the surface of the bacteria, effectively destroying their cytoskeleton. Additionally, the metals in the nano-enzymes provided a photo-thermal effect, accelerating wound healing. The cascade nano-visualization platform demonstrated excellent bactericidal efficacy in both in vitro antimicrobial assays and in vivo diabetic infection models. In conclusion, this nano-system employs multiple approaches including targeting, enzyme-catalyzed therapy, photothermal therapy, and chemodynamic therapy to kill bacteria and promote healing. The Ag@Pt-Au-LYZ/HA-LL-37 formulation shows great potential for the treatment of diabetic wounds.

Web-based Dashboard on ECMO Utilization in Germany: An Interactive Visualization, Analyses, and Prediction Based on Real-life Data

In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software. Patient-level and hospital-level data were merged resulting in a solid base for ECMO use analysis and ECMO demand forecasting with high spatial granularity at the level of 413 county and city districts in Germany.The ECMO Dashboard (https://www.ecmo-dash.de/), an innovative visual platform, presents the retrospective utilization patterns of ECMO support in Germany. It features interactive maps, comprehensive charts, and tables, providing insights at the hospital, district, and national levels. This tool also highlights the high prevalence of ECMO support in Germany and emphasizes districts with ECMO surplus – where patients from other regions are treated, or deficit – origins from which ECMO patients are transferred to other regions. The dashboard will evolve iteratively to provide stakeholders with vital information for informed and transparent resource allocation and decision-making.Accessible public routine data could support evidence-informed, forward-looking resource management policies, which are urgently needed to increase the quality and prepare the critical care infrastructure for future pandemics.

Data Acquisition, Processing, and Aggregation in a Low-Cost IoT System for Indoor Environmental Quality Monitoring

The rapid spread of Internet of Things technologies has enabled a continuous monitoring of indoor environmental quality in office environments by integrating monitoring devices equipped with low-cost sensors and cloud platforms for data storage and visualization. Critical aspects in the development of such monitoring systems are effective data acquisition, processing, and visualization strategies, which significantly influence the performance of the system both at monitoring device and at cloud platform level. This paper proposes novel strategies to address the challenges in the design of a complete monitoring system for indoor environmental quality. By adopting the proposed solution, one can reduce the data rate transfer between the monitoring devices and the server without loss of information, as well as achieve efficient data storage and aggregation on the server side to minimize retrieval times. Finally, enhanced flexibility in the dashboard for data visualization is obtained, thus enabling graph modifications without extensive coding efforts. The functionality of the developed system was assessed, with the collected data in good agreement with those from other instruments used as references.

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation.

The LSPR biosensor chip is a groundbreaking tool popular in laboratory settings for identifying disease markers. However, its use in clinical environments is not as widespread. One notable gap is the lack of a universal signal processing tool for LSPR biosensing. To escalate its precision, there is an emerging need for software that not only optimizes signal processing but also incorporates self-verification functionalities within LSPR biochemical sensors. Enter the visual LSPR sensor software-an innovative platform that processes real-time transmission or reflection spectra. This advanced software adeptly captures the nuanced structural changes at the nanostructure interface prompted by environmental fluctuations. It diligently records and computes a suite of parameters, including the resonance wavelength shift, full width at half maximum, sensitivity, and quality factor. These features empower users to tailor processing algorithms for each data capture session. Transcending traditional instruments, this method accommodates a multitude of parameters and ensures robust result validation while tactfully navigating nanostructure morphology complexities. Forsaking third-party tool dependencies, the software tackles challenges of precision and cost-effectiveness head-on, heralding a significant leap forward in nanophotonics, especially for high-throughput LSPR biosensing applications. This user-centric innovation marks substantial progress in biochemical detection. It is designed to serve both researchers and practitioners in the field of nanophotonic sensing technology, simplifying complexity while enhancing reliability and efficiency.

Pilot study comparing a new virtual reality–based visual field test to standard perimetry in children

PurposeTo assess the feasibility and performance of Vivid Vision Perimetry (VVP), a new virtual reality (VR)–based visual field platform. MethodsChildren 7-18 years of age with visual acuity of 20/80 or better undergoing Humphrey visual field (HVF) testing were recruited to perform VVP, a VR-based test that uses suprathreshold stimuli to test 54 field locations and calculates a fraction seen score. Pearson correlation coefficients were calculated to evaluate correlation between HVF mean sensitivity and VVP mean fraction seen scores. Participants were surveyed regarding their experience. ResultsA total of 37 eyes of 23 participants (average age, 12.9 ± 3.1 years; 48% female) were included. All participants successfully completed VVP testing. Diagnoses included glaucoma (12), glaucoma suspect (7), steroid-induced ocular hypertension (3), and craniopharyngioma (1). Sixteen participants had prior HVF experience, and none had prior VVP experience, although 7 had previously used VR. Of the 23 HVF tests performed, 9 (39%) were unreliable due to fixation losses, false positives, or false negatives. Similarly, 35% of VVP tests were unreliable (as defined by accurate blind spot detection). Excluding unreliable HVF tests, the correlation between HVF average mean sensitivity and VVP mean fraction seen score was 0.48 (P = 0.02; 95% CI, 0.09-0.74). When asked about preference for the VVP or HVF examination, all participants favored the VVP, and 70% were “very satisfied” with VVP. ConclusionsIn our cohort of 23 pediatric subjects, VVP proved to be a clinically feasible VR-based visual field testing, which was uniformly preferred over HVF.

Hydrazone-linked covalent organic framework functionalized with cysteine as a fluorescence sensor and Exploration of paper chip for p-nitrophenol detection

The large use and emission of p-nitrophenol (p-NP) seriously pollute the environment and endanger human health. In this work, a hydrazone-linked fluorescent covalent organic framework (BATHz-COF) was simply synthesized at room temperature and covalently linked N-acetyl-L-cysteine (NALC) via the "thiol-ene" click reaction, where carboxyl groups were introduced to improve dispersion and fluorescence intensity. As a rapid, good selectivity and reusability fluorescence sensor, the obtained COF-NALC has been used for quantitative analysis of p-NP predicated on the internal filtering effect (IFE). Under optimal conditions, COF-NALC enabled quantitative detection of p-NP with a linear range of 5–50 μM and the detection limit was 1.46 μM. The application of COF-NALC to the detection of p-NP in river water samples was successful, and the satisfactory recoveries were 98.0%–109.3%. Furthermore, the fluorescent COF paper chips constructed by in situ growth were combined with a smartphone to build a visual platform for the quick and real-time detection of p-NP, providing an excellent illustration for the development of intelligent fluorescence sensing in environmental analysis.

A unified framework for digital twin development in manufacturing

The concept of digital twin (DT) is undergoing rapid transformation and attracting increased attention across industries. It is recognised as an innovative technology offering real-time monitoring, simulation, optimisation, accurate forecasting and bi-directional feedback between physical and digital objects. Despite extensive academic and industrial research, DT has not yet been properly understood and implemented by many industries, due to challenges identified during its development. Existing literature shows that there is a lack of a unified framework to build DT, a lack of standardisation in the development, and challenges related to coherent goals of DT in a multi-disciplinary team engaged in the design, development and implementation of DT to a larger scale system. To address these challenges, this study introduces a unified framework for DT development, emphasising reusability and scalability. The framework harmonises existing DT frameworks by unifying concepts and process development. It facilitates the integration of heterogeneous data types and ensures a continuous flow of information among data sources, simulation models and visualisation platforms. Scalability is achieved through ontology implementation, while employing an agent-based approach, it monitors physical asset performance, automatically detects faults, checks repair status and offers operators feedback on asset demand, availability and health conditions. The effectiveness of the proposed DT framework is validated through its application to a real-world case study involving five interconnected air compressors located at the Connected Facility at Devonport Royal Dockyard, UK. The DT automatically and remotely monitors the performance and health status of compressors, providing guidance to humans on fault repair. This guidance dynamically adapts based on feedback from the DT. Analyses of the results demonstrate that the proposed DT increases the facility’s operation availability and enhances decision-making by promptly and accurately detecting faults.

Novel data visualization and risk analytic algorithm in a low-middle income country.

To discuss the use of T3™, a data aggregation, visualization, and risk analytic platform in a single centre and its framework for implementation of such a tool in clinical care. We share experience of a tool implemented in a tertiary care Intensive Care Unit (ICU) with limited resources. Superusers were identified and trained. Implementation involved monitoring, evaluation, and user engagement data for continuous emphasis on the use of this tool. Persistent display of T3 data enhanced nursing operational efficiency. Its use was expanded to use in nurses rounds and handover, mortality and morbidity meetings, clinical team teaching through selected teaching cases and analysis of stored data with different research questions. However, lack of infrastructure and technological comprehension, paucity of multidisciplinary teams makes it a challenge in its implementation. Clear framework of implantation and pre-designed studies to determine the clinical usage and effectiveness are important for wide-spread use of such tools.

Analysis and Zonation of Freeze–Thaw Action in the Chinese Plateau Region Considering Spatiotemporal Climate Characteristics

Concerns about the durability of transportation infrastructure due to freeze–thaw (F–T) cycles are particularly significant in the Chinese plateau region, where concrete aging and performance deterioration pose substantial challenges. The current national standards for the frost resistance design of concrete structures are based predominantly on the coldest monthly average temperature and do not adequately address the comprehensive effects of the spatiotemporal variance, amplitude, and frequency of F–T cycles. To address this issue, this study introduced a spatiotemporal distribution model to analyze the long-term impact of F–T action on concrete structures by employing statistical analysis and spatial interpolation techniques. Cluster analysis was applied to create a nationwide zonation of F–T action level from data on the freezing temperature, temperature difference, and the number of F–T cycles. Furthermore, this study explored the similarity between natural environmental conditions and laboratory-accelerated tests using hydraulic pressure and cumulative damage theories. A visualization platform that incorporates tools for meteorological data queries, environmental characteristic analyses, and F–T action similarity calculations was designed. This research lays theoretical groundwork and provides technical guidance for assessing service life and enhancing the quantitative durability design of concrete structures in the Chinese plateau region.

Development and key technologies for architectural design and technical solutions of CIM platform: A review

The integration of building information modeling (BIM), geographic information systems (GIS), 5G, IOT, cloud computing, big data, artificial intelligence, and other technologies in urban management has become a new and rapidly developing trend in recent years. However, most of the existing research on the construction of city information modeling (CIM) platforms based on the integration of BIM and GIS technologies focuses on integration technologies, and there is a lack of theories, methods, and standards for further data analysis and mathematical modeling. This paper analyzes and summarizes the actual situation of the application of recent research papers in the BIM field and the application of CIM platform pilot projects, reviews the application of BIM and GIS technologies in smart cities, and discusses future trends. For example, the construction of a basic platform for smart cities requires the establishment of a three-dimensional visual CIM platform with functions such as the planning review, architectural design plan review, construction drawing review, completion acceptance filing. A smart city is built by analyzing the cyber security risks faced during the construction. The technical, management, and operational measures of the security system provide guidance and reference for the secure construction of smart cities. This involves promoting the reform of the construction work system driven by data resources obtained from government information, and the establishment a new digital government construction management system through the “separation of management and transportation.” These analyses highlight the evolution of the CIM platform construction. The results indicate that the use of key technology integration in the construction of a CIM platform requires a system theory that goes beyond integration technology and mathematical modeling methods for a detailed application. It involves analyzing the deep integration of key technologies and business processes in the CIM platform.