Graphical Visualization Research Articles

Sector trends of total factor productivity: where is the growth potential?

Objective: to identify industry trends in aggregate factor productivity, labor productivity and capital productivity in economic sectors. The hypotheses are: there is a continuing slowdown in aggregate factor productivity in the Russian economy sectors; there is a gap in aggregate factor productivity in various complexes of industries. Methods: Cobb–Douglas production function, multiple regression, Domar aggregation, Gini coefficient, graphical visualization. Results: the study revealed a more efficient use of labor resources in contrast to capital, the latter being accumulated everywhere. The highest increase in labor productivity was noted in financial and insurance activities, manufacturing industries, professional, scientific and technical activities. There is a cyclical dynamics of aggregate factor productivity, its most stable growth and a positive cumulative technological shift marked from 2017 until 2021. They are observed in the manufacturing and investment complexes of the Russian economy (financial and insurance activities), and in agriculture.A decrease in total factor productivity was found in the mining industry, transportation and storage, hotels and catering, construction, education, and healthcare. Scientific novelty: it consists in a change in the total factor productivity and the total technological shift in the context of sectors and complexes of sectors of the Russian economy from 2011 to 2021. Practical significance: the study results can be used for the policy of stimulating internal sources of economic growth, to improve sectoral recommendations of innovation policy.

Wavy mathematical modeling of dynamically reactive shear thinning materials under the influence of gravity and wavy structures amplitude

PurposeResultant leading equations are formed with non-linear partial differential equations by adopting a low Reynolds theory approximation. For a better and easier understanding of the role of physical features of the main problem, the equations are reduced to non-dimensional ordinary differential equations by incorporating the locally similar and non-similar dimensionless variables. In light of practical importance, all the significant findings are approximated by solving the equations with the assistance of a modified bvp4c built-in package. The effective speed, temperature and volume fraction of the same materials are displayed to address the behaviors of different controlling influences.Design/methodology/approachThis work is inaugurated to investigate thermal cycling, thermal striping and thermal stratification, which cause thermally induced damage during the wavy confined flow domains. Such physical constraints are imposed on the wavy surface while considering the wavy dynamics of shear thinning materials. The impact of gravity is assumed on the vertical wavy surface, which is observed as the main source for the wavy flow occurrence. The surface’s amplitude plays a critical role in generating a high temperature difference. The same phenomenon is further extended with the applications of thermal radiation, mixed convection and dynamical homogeneous/heterogeneous reactions.FindingsFor instance, the higher stratification factor causes a reduction in the liquid wavy speed and temperature, and the rising chemically reactive rate factor declines the volume fraction during the typical wavy motion of the materials. Moreover, the larger amplitude and mixed convective factor reduced and uplifted the speed of the materials, respectively. The surface resistive forces are monitored with the graphical visualization of local similar skin friction and are determined larger by varying the Weissenberg and mixed convective factors. The affective liquid speed, temperature and volume fraction are plotted to address the behaviors of different controlling factors. These impacts are listed, i.e. with higher stratification factors, a reduction is noticed in the liquid velocity and temperature. On the other hand, an opposite depict is noticed for higher heat generation factors. The reduction in volume fraction is reported with variation in the reaction factor and Schmidt number.Originality/valueAfter carefully assessing the previously referenced work, it is evident that the literature has yet to incorporate thermally stratified Williamson fluid. Meanwhile, the motion of the materials is noticed due to the gravitationally affected wavy surface. Such physical phenomenon is further approximated by testing a dynamical reaction during its motion. An effective presentation of all the outcomes is portrayed via graphs and approximated numerical results.

How the Handcraft Typography Can Enhance Children’s Language Learning Experience

This study used a design experiment that instructs children on how to approach each letter to investigate typography design methodologies and manual techniques. Since children are still in the early stages of learning and the content they are exposed to is of great significance, the topic of children's education is always one that the entire community is intensely interested in discussing. According to researchers, typography is a popular medium and expressive technique in technology development, and art education is important for improving human communication. Typography with illustration may also help children achieve a clear sense of each letter's collocation by means of expression, recognition, and understanding through children's cognitive development by adding handcraft activities to each letter's characters. To approach new design considerations in typography and typeface experimentation, the current research analyses children's learning materials to consider their learning obstacles. Using an innovative design approach method in children's learning materials, this study demonstrates how children's drive to learn may be inspired and encouraged by a more engaging learning environment, leading to improved learning outcomes. Using paper-folding graphic visualization can also help kids understand the shape of each letter.

Visualization Methods for DNA Sequences: A Review and Prospects.

The efficient analysis and interpretation of biological sequence data remain major challenges in bioinformatics. Graphical representation, as an emerging and effective visualization technique, offers a more intuitive method for analyzing DNA sequences. However, many visualization approaches are dispersed across research databases, requiring urgent organization, integration, and analysis. Additionally, no single visualization method excels in all aspects. To advance these methods, knowledge graphs and advanced machine learning techniques have become key areas of exploration. This paper reviews the current 2D and 3D DNA sequence visualization methods and proposes a new research direction focused on constructing knowledge graphs for biological sequence visualization, explaining the relevant theories, techniques, and models involved. Additionally, we summarize machine learning techniques applicable to sequence visualization, such as graph embedding methods and the use of convolutional neural networks (CNNs) for processing graphical representations. These machine learning techniques and knowledge graphs aim to provide valuable insights into computational biology, bioinformatics, genomic computing, and evolutionary analysis. The study serves as an important reference for improving intelligent search systems, enriching knowledge bases, and enhancing query systems related to biological sequence visualization, offering a comprehensive framework for future research.

Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.

This scoping review aims to identify and evaluate the landscape of Polygenic Risk Score (PRS)-based methods for genomic prediction from 2013 to 2023, highlighting their advancements, key concepts, and existing gaps in knowledge, research, and technology. Over the past decade, various PRS-based methods have emerged, each employing different statistical frameworks aimed at enhancing prediction accuracy, processing speed and memory efficiency. Despite notable advancements, challenges persist, including unrealistic assumptions regarding sample sizes and the polygenicity of traits necessary for accurate predictions, as well as limitations in exploring hyper-parameter spaces and considering environmental interactions. We included studies focusing on PRS-based methods for risk prediction that underwent methodological evaluations using valid approaches and released computational tools/software. Additionally, we restricted our selection to studies involving human participants that were published in English language. This review followed the standard protocol recommended by Joanna Briggs Institute Reviewer's Manual, systematically searching Ovid MEDLINE, Ovid Embase, Scopus and Web of Science databases. Additionally, searches included grey literature sources like pre-print servers such as bioRxiv, and articles recommended by experts to ensure comprehensive and diverse coverage of relevant records. This study identified 34 studies detailing 37 genomic prediction methods, the majority of which rely on linkage disequilibrium (LD) information and necessitate hyper-parameter tuning. Nine methods integrate functional/gene annotation, while 12 are suitable for cross-ancestry genomic prediction, with only one considering gene-environment (GxE) interaction. While some methods require individual-level data, most leverage summary statistics, offering flexibility. Despite progress, challenges remain. These include computational complexity and the need for large sample sizes for high prediction accuracy. Furthermore, recent methods exhibit varying effectiveness across traits, with absolute accuracies often falling short of clinical utility. Transferability across ancestries varies, influenced by trait heritability and diversity of training data, while handling admixed populations remains challenging. Additionally, the absence of standard error measurements for individual PRSs, crucial in clinical settings, underscores a critical gap. Another issue is the lack of customizable graphical visualization tools among current software packages. While genomic prediction methods have advanced significantly, there is still room for improvement. Addressing current challenges and embracing future research directions will lead to the development of more universally applicable, robust, and clinically relevant genomic prediction tools.

Tunnel Cross-Section Deformation Monitoring Based on Mobile Laser Scanning Point Cloud.

Mobile laser scanning (MLS) has emerged as a pivotal tool for accurately collecting tunnel point cloud data and enabling the detection of tunnel deformation. This study introduces a novel approach for the precise monitoring of tunnel cross-section deformation, a critical factor in assessing stability and lining safety. The MLS system used in this study is the Self-mobile Intelligent Laser Scanning System (SILSS) for data acquisition. A comparison with corresponding data acquired by Leica P16 demonstrates that the data collected by SILSS are accurate. The methodology developed utilizes ellipticity parameters and deformation analysis indices based on the ellipse-fitting analysis of circular shield tunnel deformation. A key innovation is the robust denoising of data using the Random Sample Consensus (RANSAC) method, ensuring accurate ellipse fitting and extraction of tunnel lining. Subsequently, an algorithm segmented the tunnel cross-section lining into individual shield tunnels, enabling the calculation of ellipticity parameters for shield tunnels, which are the objects for deformation analysis. The experimental results underscore the novelty and effectiveness of this approach in monitoring deformation across different indices. The method proves to be a reliable tool for assessing tunnel health, providing a detailed evaluation of the cross-section's condition through statistical and graphical visualization. This study significantly advances shield tunnel monitoring, offering a practical and precise methodology for tunnel deformation analysis based on MLS point cloud data.

NUMERICAL SIMULATION OF DOUBLE SKIN FACADES IN WINTER CLIMATES

The presented study reveals the analysis of the thermal behaviour of double skin facades (DSF) in winter conditions, using numerical simulation tools. The aim of the study is the development of a 3D simulation model, capable to evaluate the thermal behaviour of the modular elements in the DSF systems. This is essential requirement in the prediction and visualization of the facade’s thermal behaviour in the design stage and in the assessment of the real behaviour of such facade, when the specified modular elements are changed by the customer. The presented numerical simulation model aims to adequately reproduce the resulting set of thermal characteristics of the modular elements, to determine with sufficient accuracy their distribution in the real objects, implemented inthe models in DSF systems. An algorithm is developed in the study and graphical visualization of three models of double facade systems with and without DSF are analysed under winter conditions, using data from a meteorological station located in North-Eastern Bulgaria. A software product was used to represent the processes of heat and mass transfer, in which the corresponding boundary and initial conditions were set, based on which the results and analyses were obtained. The use of such numerical modelling is effective enough to predict the expected thermal behaviour of DSF systems. Thus, when selecting a DSF facade system, awareness of the thermal behaviour is ensured, and the financial efficiency of the project is more easily determined. Such a customized approach not only improves the sustainability and efficiency of buildings, but also satisfies the unique preferences and requirements of the customers.

Exploring perceptions and experience of colposcopy: insights from a cross-sectional survey and thematic analysis

BackgroundColposcopy is a vital component of the NHS cervical screening programme, crucial for early detection and treatment of cervical abnormalities to prevent invasive disease. Despite its benefits, non-attendance rates remain significant. This study aimed to understand perspectives of colposcopy and identify factors influencing attendance, in an overall attempt to improve colposcopy attendance at Northumbria Healthcare NHS Foundation Trust (NHCT). MethodsAn online survey, targeting women and people with a cervix, was distributed through various local organisations including NHCT, local councils and Voluntary and Community Sector organizations, garnering 452 responses between March and May 2023. Previous colposcopy experiences were explored, as were opinions of an example invitation letter, the Trust's colposcopy website, and suggestions for future colposcopy campaigns. An inductive thematic analysis was conducted on the qualitative feedback received. Findings61·5% of respondents reported prior experience of colposcopy. Reasons cited for this being a mostly or very positive experience, commonly fell into themes of having positive interactions with staff, feeling well-informed about the procedure or overall satisfaction with the clinical service. Conversely, those with neutral or negative experiences often cited pain or discomfort, associated anxiety, inadequate pre/post-procedure care or poor communication during their appointment. Respondents recommended a future colposcopy campaign be educational, emphasising its life-saving potential and the regularity with which it is required after a cervical smear. They cited the importance of being inclusive, delivering a clear message, and including patient stories to ensure relatability to the intended audience. Some suggested avoiding negative tones and graphic visuals. Proposed locations included social media, healthcare settings, public facilities, public transport, toilets and changing rooms. InterpretationColposcopy remains daunting for many. Enhancing the availability and accessibility of information regarding its importance and the procedure itself, along with ensuring staff are well-equipped to reassure and comfort patients, could improve the experience and uptake of this essential procedure. FundingNo funding to declare.

Profiling public perception of emerging technologies: Gene editing, brain chips and exoskeletons. A data-analytics framework

Three AI developments, classified as forms of human enhancements, center around progress at the intersection of AI, nanotechnology and biotechnology. Our research advances the understanding of AI and human enhancement by data-driven analytics and offers practical tools for future research and societal applications. It is based on a survey that was launched by PRC in February 2021 to more than 5,000 respondents from the U.S. It consists of about 100 questions that are grouped using a prefix code by the 3 above-mentioned human enhancement, science role, concerns and excitements, perceived algorithm fairness and demographics. To investigate this survey and extract insights regarding the general attitude, a data analytics framework is proposed that consists of clustering using DBSCAN and K-means, ANOVA for clusters, PCA, t-SNE and UMAP for graphical visualization, prediction and advanced customers’ profiles analyses. Both clustering methods indicate distinct profiles for AI customers. Most of them are moderate, but two smaller groups define the tech-ethics advocates and tech-forward visionaries. For prediction, in the multi-class classification task, the ROC-AUC score is 0.852 and average F1 Score is 0.987. Following the results, both technology creators and legislators must work collaboratively to ensure that technological advancements are ethically grounded, widely accepted and aligned with societal values.

Precise Tool to Target Positioning Widgets (TOTTA) in Spatial Environments: A Systematic Review.

TOTTA outlines the spatial position and rotation guidance of a real/virtual tool (TO) towards a real/virtual target (TA), which is a key task in Mixed reality applications. The task error can have critical consequences regarding safety, performance, and quality, such as surgical implantology or industrial maintenance scenarios. The TOTTA problem lacks a dedicated study and it is scattered in different domains with isolated designs. This work contributes to a systematic review of the TOTTA visual widgets, studying 70 unique designs from 24 papers. TOTTA is commonly guided by the visual overlap -an intuitive, pre-attentive "collimation" feedback- of simple shaped widgets: Box, 3D Axes, 3D Model, 2D Crosshair, Globe, Tetrahedron, Line, Plane. Our research discovers that TO and TA are often represented with the same shape. They are distinguished by topological elements (e.g. edges/vertices/faces), colors, transparency levels, and added. shapes, widget quantity, and size. Meanwhile some designs provide continuous "during manipulation feedback" relative to the distance between TO and TA by text, dynamic color, sonification, and amplified graphical visualization. Some approaches trigger discrete "TA reached feedback" such as color alteration, added sound, TA shape change, and added text. We found the lack of golden standards, including in testing procedures, as current ones are limited to partial sets with different and incomparable setups (different target configurations, avatar, background, etc.). We also found a bias in participants: right-handed, young male, non-color impaired.

Vasectomy Discussions in South Korea: Central Themes and Public Interest on Question-and-Answer Social Platforms.

The purpose of this paper is to explore public perceptions and key issues related to vasectomy in South Korea. In particular, this paper seeks to analyze how vasectomy is discussed on question-and-answer (Q&A) social platforms including NAVER Jisik iN (knowledge exchange service between NAVER users) and to identify topics that capture public interest. In this study, based on data collected on NAVER Jisik iN from July 2019 to July 2024 with the keyword 'vasectomy,' this paper performs a co-occurrence matrix analysis on the Q&A data to identify key terms related to the topic. By applying connection centrality and community detection techniques, this paper visualizes and examines the network graph to uncover relationships between words and identify the primary topics of discussion. The co-occurrence matrix analysis reveals that keywords such as 'surgery,' 'vasectomy,' and 'contraception' play a central role in discussions about vasectomies. Both the Q&A data highlight the vasectomy procedure and contraceptive effectiveness as primary topics of discussion. The visualization graphs intuitively display the centrality and strength of connections between these keywords, as well as the interrelatedness of topics through distinct community groups. The analysis shows that the questions primarily focused on the surgical procedure, while the answers were more concerned with contraceptive effectiveness and physiological aspects. These results suggest that the public's interest in vasectomy is closely linked to its effectiveness, potential side effects, and related social issues.

Integrated multi-omics predictive analysis of atherosclerosis: a sub-study from the Mineralocorticoid Receptor Antagonism in Diabetic Atherosclerosis (MAGMA) trial

Abstract Background/Introduction Mineralocorticoid receptor (MR) antagonists (MRA) are beneficial in cardiorenal outcomes in randomized controlled trials but the mechanisms are unclear. MAGMA was an NHLBI sponsored randomized, double-blind, placebo controlled, 12-month trial comparing Spironolactone (n = 37) vs. placebo (n = 42) in Type 2 diabetics with CKD stages 3-4 on maximal renin-angiotensin system (RAS) blockade and a prior atherosclerotic event and/or left ventricular (LV) hypertrophy. The primary outcome of percent (%) change in total aortic wall volume (TWV) at 12 months, measured by magnetic resonance imaging (MRI), was significantly reduced by Spironolactone. Purpose/Originality The purpose of this analysis was to understand mechanistic pathways of MRAs using a multi-omics approach that could help tease out molecular mechanisms of benefit. Revealing for the first time which of these integrated pathways are predictive of the primary outcome will help design treatments for targeted interventions. Methods Plasma and peripheral blood mononuclear cells from patients randomized to Spironolactone or placebo at baseline and 3-months were measured for aptamer-based proteomic biomarkers (7,596 proteins) and 10-X platform-based single-cell RNA-sequencing (scRNAseq), respectively. Pre-selected candidate predictors were used as inputs of a predictive model of changes of TWV. We fit a Mixed-Multivariate Random Forest (RF) model, a variation of the RF supervised tree-based machine learning method to take the experimental design into account in the regression formulation. The two sources of "omics predictors" were integrated into a supervised multi-omics model to jointly explain the outcome using an extension of Sparse Generalized Canonical Correlation Analysis (SGCCA). Integrated multiome functional analyses with graphical visualizations were carried out by statistical enrichment analysis using Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) against databases of gene ontologies, biological pathways, putative regulatory motifs, proteins, or disease annotations. Results The plasma proteome in response to Spironolactone revealed downregulation of MR targets including fibrosis, immune activation/inflammation, leukocyte activation, proliferation and pathways involved in cytokine stimulation. scRNAseq pathways revealed negative regulation of cytokines production such as IL-2 and redistribution of multiple cell types. Predictors of plaque progression involved cytokine-receptor, complement-coagulation, cell adhesion and axonal guidance targets. Multiome integrated functional analyses results of predictive pathways will be presented. Conclusions The changes in plasma proteomic profile with Spironolactone were consistent with the phenotype of reduced atherosclerosis and downregulation of multiple inflammatory, immune response and profibrotic pathways.

Thermal analysis of mathematical model of heat and mass transfer through bioconvective Carreau nanofluid flow over an inclined stretchable cylinder

In this proceeding the main focus to scrutinize the heat and mass transfer rate increment due to the involvement of motile microorganisms in the Carreau nanofluid flow through an inclined stretchable cylinder under the consequences of activation energy and thermal radiation. This phenomenon has many physical applications in the field of civil, mechanical and seismographic engineering. The research focuses on creating and analyzing new nanocomposites with applications in energy storage, showcasing the transformative impact of nanotechnology on the advancement of high-performance materials. First of all, for the numerical treatment of the above physical model mathematical model is developed in the form of partial differential equations (PDE's) by considering all involving quantities. The resultant model is highly nonlinear and of higher order. Appropriate similarity variables are defined to transform this system of PDE's into first order ordinary differential equations (ODE's). For numerical results we develop a numerical algorithm from nonlinear ODE's and use ‘bvp4c’ built in package of MATLAB. Numerical results are acquired from software in the form of graphical visuals and tabular data as narrated in the results and discussion section. Using this tabular data streamlines are constructed for the better understanding of heat and mass transfer through this phenomenon under the defined constraints. From results, velocity profile increased by the augmentation of values of curvature parameter. Thermal profile is stronger when values of thermophoresis parameter is boosted, Concentration of nanoparticle profile get smoother when temperature coefficient increased, and motile microorganism's density profile is enlarged upon inclining the values of bioconvection lewis number.

Routine outcome monitoring and feedback in alcohol and other drug treatment: A qualitative study of client perspectives on implementation.

Routine outcome monitoring (ROM) and feedback is an evidence-supported strategy for evaluating alcohol and other drug (AOD) treatment outcomes. However, the implementation of ROM and feedback into AOD services remains a significant challenge. Research aimed at understanding client perspectives on ROM and feedback is needed to facilitate successful implementation. This study examined experiences with and perceptions of ROM and feedback in a sample of clients receiving AOD treatment. Interviews and online surveys were conducted with N = 26 people (13 male; Mage = 36.12 years, SD = 10.29) enrolled in an AOD treatment program in Australia. Data analysis of the transcripts was guided by thematic analysis, while descriptive statistics were used to analyse quantitative survey data. Four major themes were identified in the qualitative data: (i) ROM and feedback is valuable to AOD treatment; (ii) clear and concise outcome measures with an integrated feedback loop are vital to reliable ROM; (iii) desire for visual and verbal feedback that highlights progress; and (iv) ROM and feedback can be emotionally challenging. Participants valued ROM when it was clearly integrated within AOD treatment and they received feedback on their responses. Potential facilitators to implementing and improving the provision of ROM and feedback in AOD treatment include: (i) a clear, treatment-based rationale to foster client buy-in for ROM and maximise AOD treatment benefit; (ii) brief outcome measure surveys; and (iii) graphical visualisations of ROM feedback.

A Comprehensive Analysis on Non-Communicable Diseases by Quantitative Approach: Using Graphical Visualization

Non-communicable diseases (NCDs) have already become major killers in Bangladesh. Once NCDs are developed, they become chronic health and economic problems. Their primary prevention is linked to their common risk factors. This study was conducted to visualize the trend of the diseases along with the age factor in rural areas of Bangladesh. A quantitative method was used throughout the research to reach the desired goal of this study. The data was collected from a medical association to use in this research and for processing the graphical visualization some preprocessing techniques are also applied on the raw data. After completing the research, the researchers found the percentage of the patients according to the diseases and the disease count along with the patients’ age. The outcome is totally represented in graphical visualization. This research will help to find the numeric measurement of a particular disease considering age factor which can help to reduce the issues in medical sectors.

Modeling of Electric MHD Flow of Nanoparticles in a CMC-Water Based Casson Hybrid Nanofluid over a Porous Medium

The principal focus of this exploration is to study the computationally simulate the combined convection of CMC-water-based Casson hybrid nanofluid through a stretching sheet with electric magnetic force in a porous medium. Copper (Cu) and Silver (Ag) nanoparticles are included to enhance the heat transfer performance of CMC-water. The physical problem is formulated with mathematical PDEs, and to solve this, initially we used similarity transformation technique to reduce the PDEs into ODEs, then Runge-Kutta Fehlberg method (RKFM) of order four with shooting technique is adopted for further reduction from the non-linear ODEs to first order DEs. The influence of key parameters such as the magnetic field parameter (M), porous medium parameters (K), electric field factor (E), radiation parameter (Nr), permeability parameter (λ), Casson parameter (β), and Eckert number (Ec) on relevant physical quantities is illustrated through tables and graphical visualizations. The impact of these parameters on velocity and temperature profiles, as well as on the skin friction coefficient and Nusselt number of the nanofluid, is observed. Our results indicate that an increase in the Casson parameter values leads to a decrease in the velocity of the host fluid in the case of opposite flow, and a similar behavior is observed with the nanoparticle porous medium parameter (K) in the case of assisting flow. Furthermore, the use of the Runge-Kutta Fehlberg Method (RKFM) is found to be more accurate and reliable in dealing with the problem studied in this work.

Visualising the school: a critical study on co-designing a Moodle-based learning management system

ABSTRACT Critical research on data visualisations in education has so far mostly focused on the representation of numeric data in dashboards or graphs. Consequently, the question of how schools are made visible and (re)enacted through visual structures on data-mediated interfaces more broadly – what we call Graphic Data Visualisations (GDV) – has remained under-researched. Addressing that research gap, this study specifically scrutinises the role of GDV as non-human actors within the design process of a Moodle-based learning management system (LMS) in four schools. Following a critical co-design approach, the potential of GDV to reflect on how the visual design shapes educational practices, and to adapt it according to pedagogical and organisational needs is explored. Focusing on ‘critical incidents’ in the design process, we found that local practices substantially influenced the data-based, visual enactment of a school through specific GDV. At the same time, the use of certain GDV enhanced a general critical engagement with datafication among school actors.

Phase trajectories, chaotic behavior, and solitary wave solutions for (3+1)-dimensional integrable Kadomtsev–Petviashvili equation in fluid dynamics

This paper focuses on finding exact soliton solutions and further examining the qualitative characteristics of these solutions for a nonlinear partial differential equation known as the (3+1)-dimensional integrable Kadomtsev–Petviashvili equation that portrays a unique dispersion effect. The (3+1)-dimensional integrable Kadomtsev–Petviashvili equation models the evolution of weakly nonlinear dispersive waves in three spatial dimensions “x,y,z” and time “t”. It balances nonlinearity and dispersion, leading to solitary wave solutions that are stable and localized. This equation is crucial in understanding complex wave phenomena in fields like fluid dynamics, plasma physics, and optics. Initially, the traveling wave transformation is employed to convert the nonlinear partial differential equations into the non-linear ordinary differential equations. Then, we use the Riccati equation approach to find solitary wave solutions for the resulting ordinary differential equation. To better comprehend the physical significance of these derived solutions, we illustrate them using various visual representations. Diverse novel collections of solitary wave solutions are obtained such as bright solitons, dark solitons, and dark singular solitons. Second, we convert the nonlinear ordinary differential equation into a linear dynamical system using the planar dynamical transformation. Then, we undertake a qualitative analysis of the dynamical system to study its chaotic characteristics and bifurcation phenomena. Phase portraits of bifurcation are observed at the equilibrium points of the planner dynamical system. We discuss various tools to identify the chaos (random and unpredictable behavior) in dynamical systems. Graphical visualization of qualitative analysis of the system is also depicted in 3-D phase portraits, 2-D phase portraits, Poincaré mapping, and time series. Additionally, the Runge–Kutta technique is used to do a thorough sensitivity analysis of the dynamical system. Using this analytical procedure, it is verified that the stability of the solution has negligible impact while there is little change in the beginning circumstances. This paper aims to provide vital views to scientists and researchers seeking to advance their experimental operations. Furthermore, this research might be expanded by incorporating solitons and situations and investigating wave dynamics. The methods employed provide a direct and uncomplicated approximation of all solutions when compared to the previously established techniques. Various combinations and values of the physical parameters are utilized to explore the optical soliton solutions of the resultant system.

CURRENT ISSUES AND DEVELOPMENT PROSPECTS OF MODERN DIGITAL TECHNOLOGIES IN THE WORK OF THE «102 (112)» SERVICE

The work deals with current issues of information provision of the National Police based on a retrospective analysis of literary sources. The use of information technologies in the National Police of Ukraine is a critically important step for increasing the efficiency and transparency of police activities. It can also be added that these technologies ensure the efficiency, speed and completeness of the work of law enforcement agencies. The methodological basis of scientific work is a system of general scientific and special methods of analysis: systematization and generalization (definition of the main categories, their relationship, formation of conclusions and proposals); monographic and system-structural analysis; assessment and situational; graphic (visualization of theoretical research results); factor analysis; expert and tabular analyses. The object of the research is modern digital call-centers on the example of Call Way and AVAYA, as a component of the information support of the national police in the services of the «102» and «112» lines. The subject of the research is the theoretical, scientific and methodological provisions and applied aspects of effective formation of the work of emergency services, information support of the national police in the services of the «102» and «112» lines. It was found that the use of modern digital technologies can significantly increase the efficiency and quality of service to citizens in emergency situations. Modern digital call centers were analyzed by the evaluation-situational method using the example of Call Way and AVAYA. Prospective directions for the development of the automation of the «102 (112)» service have been determined, namely the introduction of voice recognition; use of artificial intelligence (AI); expansion of communication channels; introduction of video calls; data analysis for forecasting; integration with other security systems; application of augmented reality (AR); ensuring mobility; reliability and data protection; creation of interactive instructions, which will become a perspective for further research in this direction.

Top 50 most cited articles on social media and healthcare: an altmetric analysis

Introduction. With the surge of data in today's information landscape, transforming this data into actionable knowledge has become increasingly difficult. Tracking and analyzing scientific literature effectively is essential. This study compiles an altmetric list of the 50 most-cited articles on social media and healthcare, aiming to identify critical research and assess its impact on current healthcare trends. Methods. The analysis focused on the terms "Social Media Platforms" and "Healthcare" using the Altmetric database. Articles were ranked by altmetric mentions and analyzed with Microsoft Excel. Data visualization was facilitated through tables, graphs, and keyword graphical visualization using VOSviewer. Results. Key aspects identified include the impact of social media on mental health, medical misinformation, the role of social media in public health communication, and its effects on user behavior. The analysis revealed an average altmetrics score (AAS) of 433.58, with scores ranging from 49 to 4,493. The United States and Great Britain were prominent in the most-cited publications. Leading journals included the Journal of Medical Internet Research and PLOS ONE. Primary themes were mental health, health misinformation, public health, social media behavior, and specific health issues. The Spearman correlation between citations and the altmetric index was rs = 0.369 (p < 0.05), indicating a moderate positive relationship. Conclusion. Altmetric analysis is a valuable complement to traditional bibliometric methods, helping to identify emerging trends and challenges in social media data use. Recommendations include revising analytical approaches and implementing measures to enhance data reliability.