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This study investigated how congruence between pictogram complexity and typographic complexity influences visual processing and perceived appropriateness in multimodal communication. Drawing on theories of visual communication, legibility and aesthetic perception, the study examined whether simple or complex pictograms harmonise more effectively with sans-serif or serif typefaces. Ninety participants viewed stimuli from three thematic categories (cobbler, herbal pharmacy and gluten-free restaurant), while their eye movements were recorded using a Tobii Pro Fusion eye-tracking device. Measures included reading time, fixation count and saccade count, together with subjective evaluations of pictogram-typeface suitability. The results show that reading time was the most sensitive indicator of formal congruence. In the cobbler and gluten-free restaurant categories, simple pictograms increased reading time with sans-serif typography but decreased it with serif typography. In the herbal pharmacy category, simple pictograms and sans-serif typography independently supported faster reading performance. Subjective evaluations showed no significant differences between combinations, indicating that participants perceived all pairings as similarly appropriate despite measurable differences in processing efficiency. The findings suggest that the effectiveness of pictogram-typeface combinations depends on both formal complexity and thematic context. Eye-tracking proved valuable for revealing subtle cognitive processing differences not reflected in subjective judgements.
The sleep monitoring terminal display (SMTD) designated for sleep cabins provides data visualizations of sleep profiles, yet poses challenges concerning visually informed interfaces. Given the scarcity of research on the SMTD interface, this study aims to evaluate the influence of SMTD-related factors, including stimulus areas of interest (AOIs), user experiences and tasks, on user visual perceptions while interacting with the SMTD system. Eye-tracking experimental contexts drawn from authentic settings are used to examine how the SMTD interfaces affect visual perceptions under varying tasks. Forty valid samples were collected, and pupil sizes (PSs), task performances, satisfaction, and usability were statistically compared and evaluated. The findings indicated that tasks had no significant effects, but user experiences and stimuli AOIs had significant main effects on PSs. In addition, task completion time ratio and tracking ratio between the two tasks varied; physical demand exceeded mental demand in task 1, whereas it was the opposite in task 2. The effectiveness of post-optimized interfaces was additionally substantiated through combining subjective ratings and objective metrics. The SMTD study provides novel insights for digital interface development and helps enhance users' integrated visual perception.
This study aimed to evaluate predefined two-dimensional speckle-tracking parameters (2D-STE) to distinguish between growth-restricted fetuses (FGR) and healthy controls (FC) and to identify novel parameters using an exploratory approach. The study comprised 112 fetuses, 56 in the FGR cohort and 56 gestational-age-matched healthy fetuses in the FC cohort. We analyzed global longitudinal strain (GLS), as well as segmental strain, displacement, and velocity using 2D Cardiac Performance Analysis software. Dyssynchrony (DYS) was calculated as the difference in time to peak of GLS or segmental parameters inter- and intraventricular. We also measured changes in ventricular length, diameter and area. Additionally, we tested a prototype software with a tracked M-mode approach, which measured annular displacement. Dyssynchrony parameters were generally higher in the FGR cohort than in the FC cohort. Particularly the GLS-DYS was noticeably higher in the FGR cohort than in the FC cohort (median 19.85 vs. 8.40 ms; p<0.001). Also strain-dyssynchrony, displacement- and velocity-dyssynchrony were increased. FGR fetuses showed right ventricular alterations with lower RV-GLS and reduced longitudinal shortening and area change (25.58 vs. 22.06; p=0.040; 0.75 vs. 0.78; p=0.015; 0.58 vs. 0.67; p=0.024), while LV-GLS and LV-geometry did not differ noticeably. The prototype software did not sufficiently discriminate between groups. FGR was associated with higher cardiac dyssynchrony and altered right-ventricular function and geometry. GLS-based dyssynchrony may complement Doppler for risk stratification and monitoring in suspected placental insufficiency. These results should be considered in the context of the limited sample size. Prospective studies with larger cohorts should validate these parameters and establish standardized reference values.
Reproducible eye-movement research requires a documented path from device exports to structured, quality-checked, and reportable data objects. Gazepoint GP3 and Gazepoint Analysis provide accessible gaze, fixation, pupil, timing, media, and area-of-interest data, but their folder-based CSV exports are not automatically analysis-ready. Existing R tools support important stages of eye-tracking and pupillometry analysis, but they generally assume that data have already been organised into suitable structures; they do not provide a Gazepoint-aware workflow beginning with export-folder checks, all-gaze/fixation pairing, sampling and tracking-quality diagnostics, and preservation of preprocessing decisions through reporting. This article presents gp3tools, an open-source R package (R version 4.6.1) that converts Gazepoint GP3/Gazepoint Analysis exports into structured R objects, diagnostic summaries, preprocessing outputs, model-ready tables, interoperability objects, and reproducible reports. Rather than introducing a new statistical estimator, the package provides an export-aware workflow scaffold for import checking, quality control, pupil preprocessing, area-of-interest, fixation and transition summaries, model preparation, interoperability, and reporting. A synthetic Gazepoint-style demonstration dataset was used to evaluate workflow execution without exposing private participant data. The demonstration identified all expected file pairs and produced sample-level gaze/pupil tables, fixation tables, sampling-quality summaries, area-of-interest summaries, review flags, and reporting outputs. A small, private real-export compatibility check further showed that the workflow could process one empirical Gazepoint folder without manual restructuring. These results support a bounded software-evaluation claim: gp3tools executes the tested Gazepoint-style workflow and returns expected diagnostic and reporting objects, but the evidence does not establish hardware accuracy, preprocessing accuracy, computational scalability, general robustness across all Gazepoint exports, or substantive psychological or perceptual effects.
Long-term changes in forest management are documented across reports, plans, and scientific papers written for different purposes and with changing vocabularies. This makes it difficult to show how a documentary record was converted into a temporal claim. FORM-TRACE is a formula-based workflow that records corpus decisions, extraction quality, domain terms, and calculations before interpretation. We demonstrate it with Harvard Forest and New England documents dated 1908-2026. Of 257 PDFs inspected, 215 met the analytical criteria; 201 were extracted and scored, 14 were flagged as unreadable, scanned, or corrupted, and 42 methods-support references were kept outside the scored corpus. The method provides: • A corpus manifest and extraction log that expose inclusion, exclusion, and coverage gaps; • A keyword-domain matrix and five numbered equations that produce document- and period-level indicators; • Saved score tables, plot data, and validation records that allow independent checking without redistributing copyrighted PDFs. FORM-TRACE measures documented attention rather than management performance and keeps interpretation separate from scoring.
Biosensors enable the in situ measurement of metabolites in living systems over time and space. Fully genetically encoded metabolite biosensors (fGEMBs) use fluorescent proteins (FPs) linked to ligand binding domains (LBDs) to transduce the ligand binding event to a measurable change in the fluorescence behavior of the FP. Because these sensors are genetically encoded, they can be expressed in cells using standard protein expression approaches, and the fluorescence changes are quantified using fluorimetry, fluorescence microscopy, and/or flow cytometry. While there are general sensor design principles to follow, an fGEMB must be engineered for each metabolite based on a particular LBD. This development process can be slow, but there are strategies emerging to increase testing throughput and improve structure-guided design. While genetically-encoded FPs remain popular, there are now numerous chemigenetic and nucleic acid-based metabolite sensors (cGEMBs) that incorporate small molecule fluorophores. De novo design of LBDs is rapidly advancing as well, and the field may soon exhibit a shift away from relying on nature's catalog of LBDs. Despite the engineering challenges, the metabolite biosensor field has expanded significantly in recent years to meet the demand for new and better-performing sensors that visualize metabolites within their cellular environments.
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Atrial fibrillation (AF) can be sustained by intramural reentrant circuits within three-dimensional arrhythmogenic hubs formed by fibrotically-insulated myobundles. However, the efficacy of different multi-electrode mapping (MEM) to identify the micro-reentrant pathways sustaining AF remains undefined. An anisotropic atrial tissue structure (30 × 30 × 4 mm), incorporating a sub-endocardial laterally-insulated myobundle (15 × 2.5 × 1.5 mm) was simulated reflecting persistent AF conditions. Simulations included endocardial unipolar, bipolar, and omnipolar electrograms, with local activation time maps calculated for reentry visualization. N = 656 MEM configurations were evaluated, varying inter-electrode distances (1, 3, 6 and 9 mm), orientations (parallel and perpendicular), contact distances to the wall (0.25 and 1.0 mm), and electrode positions (in 1-mm increments) relative to the reentrant circuit. Conduction along the reentrant pathway was identified by electrograms within <3 mm of the micro-reentrant circuit, and confirmed by their comparison to action potential traces. However, detection on electrogram (EGM) traces was highly dependent on catheter configuration and distance to the atrial wall. Dense unipolar MEM configurations (1-6 mm spacing) facilitated pathway identification, while bipolar MEM required electrode pairs to align with the myobundle for effective detection. Omnipolar configurations offered no significant advantages over unipolar for modest inter-electrode spacings (1-6 mm) but improved detection accuracy at larger spacings (9 mm). Mapping was affected by micro-reentrant track width, though reentrant mapping still detected tracks thinner than electrode spacing. Track thickness and conduction velocity did not impair detection and sometimes improved it. Unipolar MEM configurations (1-6 mm spacing) with optimal contact enabled the detection of sub-endocardial reentry pathways sustaining AF in 50-100% of simulated cases. Combining unipolar and omnipolar mapping approaches (3 mm spacing) may enhance the detection rates of AF micro-reentry. These findings provide critical insights into optimizing MEM techniques for human AF reentrant circuit detection and may improve the efficacy of AF ablation procedures.
Although biosensors for specific cellular ions are widely available, real-time monitoring of overall ionic strength in living organisms remains challenging. Here, we present a genetically encoded nuclear translocation ionic sensor (GENTIS) that enables direct visualization of ionic stress in vivo. Using this sensor alongside longitudinal tracking via an automated microfluidic platform, we find that Caenorhabditis elegans larvae experience highly synchronized, rhythmic elevations in intestinal ionic strength during the molt, a stage during which developmentally timed sleep occurs. Cytosolic proton accumulation through inhibition of vacuolar-type adenosine triphosphatases (V-ATPases) triggers GENTIS nuclear translocation and evokes behavioral quiescence, characterized by reduced feeding, locomotion, and activation of sleep-active neurons. Apical membrane V-ATPases naturally undergo disassembly during molting and stress, conditions that cause proton accumulation and sleep. Notably, this proton-linked sleep is suppressed by proton buffering with ammonium. Together, these findings establish GENTIS as a powerful tool for tracking ionic strength dynamics in vivo and reveal that proton ionic rhythms contribute to the regulation of sleep.
Bats navigating clutter must steer around obstacles to avoid collision, while simultaneously planning future flight trajectories. In this study, we investigated active sensing strategies of two bat species negotiating turns under matched geometric constraints. We compare the Egyptian fruit bat (Rousettus aegyptiacus), a lingual echolocator that can actively direct its sonar beam axis using tongue driven mechanisms, and the short-tailed fruit bat (Carollia perspicillata), a laryngeal nasal echolocator whose head aim and nose leaf shape emission directionality. Bats flew through a felt lined, 'L' shaped corridor designed to elicit turns. A 32-channel ultrasonic array and 3D video tracking system captured their sonar emissions and flight trajectories. In both species, bats reduced flight speeds and increased angular deviation between sonar beam aim (acoustic gaze) and flight direction before the apex of high angle turns. A directional prediction analysis showed that sonar gaze reliably anticipated the direction of the subsequent heading change in both species (77% in R. aegyptiacus; 70% in C. perspicillata). However, baseline flight and echolocation behavior differed between species: C. perspicillata flew faster and, produced higher sonar pulse rates than R. aegyptiacus, consistent with species differences in body size, wing morphology, and sensory ecology. Together, these data demonstrate that fruit bats prospectively orient acoustic gaze to guide upcoming trajectory changes, extending "steering by hearing" beyond prey tracking by insectivorous bats to navigation of cluttered space by frugivorous bats.
Although moderate exercise benefits health, excessive amounts of prolonged, high-intensity exercise may damage tissues and cause inflammation-related diseases. There is a growing interest in exercise-related health monitoring and tracking; however, a handy, noninvasive, and accurate method for wearable detection of exercise-induced inflammation still lacks. Here, this work reports a wireless and passive immunosensor for the noninvasive, low-cost, and simple monitoring of C-reactive protein (CRP) in sweat as an inflammatory marker to evaluate exercise-induced inflammation. The sensor has a sandwich structure, in which the middle layer is an immuno-sensitive hydrogel whose internal network structure cracks with the entry of CRP. A pair of coils converts the change of hydrogel into a shift of radio frequency (RF). The limit of detection (LoD) is as low as pg mL-1, covering the concentration range of human sweat CRP. The sensor can be used in direct detection for sweat samples from subjects, demonstrating a correlation between exercise-induced inflammation and exercise intensity. By tracking daily sweat CRP, the wearable passive immunosensor provides a methodology to quantify exercise intensity in terms of inflammation and has potential in customizing personal exercise protocols.
A solid synthetic pathway for the localized formation of vertically aligned and well-distributed individual gold nanoparticles (AuNPs) in transparent ion-track-etched polyvinylidene fluoride membranes is herein reported. After a successful preconcentration of the Au-(III) precursor within the functionalized cylindrical nanochannels of these membranes, i.e., ion-track-etched radiografted with poly-(4-vinylpyridine) (P4VP), a Au-(IIII)-to-Au(0) chemical reduction was performed to in situ grow AuNPs inside the nanopores. Four classical reducing agents [ascorbic acid, hydroquinone, sodium citrate, and sodium borohydride (NaBH4)] were studied, which led, at first glance, to similar composites. The reducing power of each reducing agent has been shown to affect the AuNP nucleation and growth processes. At room temperature, the reduction led to the synthesis of well-dispersed AuNPs along the whole pore length, with the exception of sodium citrate, which was found to be too weak to reduce efficiently the gold precursor. When energy was provided to the system by operating the reaction at 70 °C, the reduction was boosted and the synthesis with sodium citrate gave similar results to those obtained with the other reducing agents at 20 °C, i.e., well-distributed AuNPs of around 30 nm of mean size. Increasing the number of reduction cycles resulted in an increase in AuNP size and, in the case of hydroquinone, in the elongation of the gold nanocrystals. This phenomenon was attributed to template-assisted AuNP growth in the nanopores. Despite the low amount of gold in the material (less than 0.2 %), the alignment of individual AuNPs all along the high aspect ratio nanopores (50:10,000) had a significant effect on the optical properties of the whole material, with the appearance of plasmonic properties for the nanocomposite membranes (λplasmon around 530 nm) and a further decrease of the effective refractive index of the nanoporous membranes.
In recent decades, the monitoring of volcanoes has been revolutionized by the launch of Earth-observing satellites and advances in thermal infrared remote sensing. These developments have revealed a wide range of thermal responses of volcanic surfaces to subsurface processes, even demonstrating that eruptions are often preceded by measurable thermal anomalies. This recognition highlights the need for robust tools to systematically detect and track such anomalies, making full use of existing satellite datasets and maximizing the value of current instruments in orbit. To address this challenge, we present the Subtle Surface Thermal Anomalies Recognizer (SSTAR), a versatile and user-friendly application designed to analyze diffuse thermal anomalies, i.e., subtle thermal unrest (~ 1 K) across large areas (several km2). SSTAR leverages data from NASA's Terra and Aqua satellites, which host the Moderate Resolution Imaging Spectroradiometers (MODIS), and builds upon a robust statistical framework. By processing pixel-level data, SSTAR tracks the temporal evolution of diffuse thermal anomalies at specific target sites and maps their spatiotemporal distribution across extended areas. Key features include filtering tools that distinguish between long-term (years) and short-term (weeks) anomalies, as well as uncertainty quantification using bootstrapping. The application is standalone, features an interactive interface for streamlined analysis, and is accessible to newcomers to satellite-based thermal remote sensing. At the same time, specialized users can customize the underlying scripts for other specific research needs. As a demonstration, we apply SSTAR to Shishaldin volcano (Alaska), revealing the emergence of significant thermal anomalies around the summit crater and flanks prior to eruptions. We envision SSTAR as a valuable resource for studying subtle thermal unrest at active volcanoes and hydrothermal systems, where the detection of faint and spatially coherent anomalies may help identify subsurface fluid pathways. Its flexible design enables integration with additional satellite datasets, positioning SSTAR as a forward-looking tool for advancing space-based volcanic thermal monitoring. Building on this capability, daily updated diffuse thermal anomalies are provided for target volcanoes through an open web platform hosted at Geosciences Barcelona-CSIC (https://sstar.geo3bcn.csic.es/), to support surveillance agencies and expert committees in alert-level assessments. The online version contains supplementary material available at 10.1186/s40623-026-02497-6.
Liver metastases are associated with systemic immune tolerance and primary resistance to immune checkpoint inhibitors (ICIs) by establishing complex physical and metabolic barriers within the tumor immune microenvironment (TIME). We developed a non-invasive macroscopic fractal dynamics framework to map these microenvironmental barriers across scales, aiming to predict ICI efficacy in colorectal cancer liver metastases (CRLM) and lung squamous cell carcinoma (SCC). This single-center, retrospective, proof-of-concept cohort study consecutively enrolled 472 patients with CRLM or SCC liver metastases. Patients were divided into a training cohort (n=400, 2019-2024) and an independent validation cohort (n=72, 2025). Vascular fractal acceleration (Afd ) and metabolic fractal dimension (Df ) were extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) and 18F-FDG PET, respectively. To eliminate baseline histological confounding, macroscopic fractal probes were Z-score normalized strictly within their respective histological cohorts. Cross-scale validation utilized digital pathology and platelet-poor plasma (PPP) cytokine profiling. An extreme gradient boosting (XGBoost) model was explicitly trained to predict a composite "High TIME Barrier" phenotype-defined by restricted CD8+ infiltration and low PD-L1 expression-to generate the Immuno-Radiomics Joint Score (IRJS). An exploratory survival analysis was subsequently conducted to evaluate its association with progression-free survival (PFS) among the 185 patients receiving ICI therapy. We evaluated early dynamic drift (ΔAfd ) at week 3 for its utility in tracking physical barrier remodeling. CRLM and SCC displayed distinct fractal trajectories indicative of metabolic and physical barriers, respectively. High Afd correlated with dense fibrovascular stroma and severe spatial exclusion of CD8+ T cells. High Df corresponded to severe hypoxia, CD163-enriched macrophage infiltration, and systemic immune exhaustion, characterized by elevated circulating TGF-β and exhausted IFN-γ. The IRJS demonstrated strong diagnostic performance for the High TIME barrier phenotype (temporal validation AUC: 0.912). In the ICI sub-cohort, multivariable Cox regression confirmed that an increase in the continuous baseline IRJS was a robust, independent risk factor associated with primary ICI resistance and shorter PFS. Macroscopic fractal dynamics offer a non-invasive, cross-scale method to evaluate the "physical-metabolic" dual microenvironmental barriers in liver metastases. The combined IRJS and dynamic ΔAfd tracking system show potential as exploratory, non-invasive surrogates to identify the systemic immune exhaustion phenotype. Pending external multi-center validation, these tools may generate hypotheses for associating macroscopic spatial barriers with primary ICI resistance and informing multidisciplinary interventions.
To compare and rank the effects of different sports and outdoor activities on myopia control in children and adolescents using network meta-analysis. We systematically searched PubMed, Web of Science, Embase, the Cochrane Library, and major Chinese databases from database inception to Dec 31, 2025, for randomized controlled trials involving school-aged children and adolescents with myopia or at risk of myopia progression. Data were analysed using network meta-analysis in Stata 18.0. Treatment effects were expressed as mean differences (MDs) with 95% CIs, and interventions were ranked using the surface under the cumulative ranking curve (SUCRA). Sixteen randomized controlled trials involving 9,084 participants were included. Racket sports ranked highest for slowing axial elongation (MD -0.30 mm, 95% CI -0.58 to -0.01; SUCRA 94.9%), followed by increased outdoor time (MD -0.08 mm, 95% CI -0.13 to -0.02; SUCRA 55.7%). For refractive outcomes, visual tracking exercise ranked highest for improving spherical equivalent (MD 0.38 D, 95% CI -0.04 to 0.80; SUCRA 83.7%), followed by racket sports (MD 0.29 D, 95% CI 0.00 to 0.59; SUCRA 77.0%). Subgroup analyses showed that increased outdoor time remained effective in children aged 8.5 years or younger and in interventions lasting more than 24 weeks. Sensitivity analyses supported the robustness of the findings. Sports and outdoor activities may affect myopia control differently across outcomes. Racket sports showed the most consistent signal for slowing axial elongation, while visual tracking exercise and racket sports ranked higher for spherical equivalent. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420261339612, identifier (CRD420261339612).
Probing platinum (Pt) nanoparticle (NP) stability, free from convolution with corrosion of the underlying carbon support, under the start-stop conditions of a proton exchange membrane fuel cell, is challenging. To address this problem with a focus on tracking NP morphology changes, we use identical-location transmission electron microscopy, in combination with corrosion-resistant, electron-transparent, boron-doped diamond electrodes. Automated image analysis is developed to enable faster and easier processing. Information concerning NP area, positional changes, and relationship to nearest neighbor distance is extracted on an NP-by-NP basis by tracking the same NPs, pre- and post-accelerated stress testing in perchloric acid under conditions which promote carbon corrosion for sp2 carbons. Measurements are made in several locations with ca. 200 NPs analyzed per image. A significant fraction of the NPs, 40%-50%, are found to be area stable, with only a small number growing and the remaining decreasing very slightly in area (less than a single atom layer) due to transient dissolution. The average distance of travel of an NP after accelerated stress testing is ∼0.36 nm (n = 545). This data highlights both the stability of the Pt-BDD interaction and the potential for BDD use as an electrocatalyst support, under high anodic potentials.
Fluorescence molecular imaging stands as a crucial method for tracking physiological or pathological biomarkers within living organisms. In clinical practice, this technology is increasingly applied to assist physicians in decision-making during interventional or surgical procedures. To develop imaging tracers, targeting molecules are covalently labeled with fluorescent organic dyes. Yet, it is often overlooked that such modifications to the molecule can influence and even alter its pharmacokinetics and distribution within the body. This review aims to provide an overview of the advancements in fluorophores commonly used in translational and clinical fluorescence molecular imaging, with a specific focus on long-wavelength cyanine dyes. Additionally, we will illustrate how the fluorophore's structure and labeling parameters influence the in vivo behavior of molecules, underscoring the importance of considering these aspects when designing fluorescent tracers.
Immunotherapy stands as one of the most promising approaches in cancer treatment, with engineered T cell therapies, particularly chimeric antigen receptor T cell (CAR-T), leading the charge. However, relapse in some patients post-treatment suggests that research in this field remains incomplete. Tumor heterogeneity and the complexities of the immune microenvironment hinder a comprehensive understanding of the changes engineered T cells undergo once introduced into the human body. Single-cell lineage tracing (SCLT) technology facilitates the investigation of cellular development by monitoring the fate and differentiation of individual cells and their descendants within an organism. Employing methodologies such as CRISPR-based labeling and mitochondrial DNA tracking, SCLT allows for dynamic analysis of T cell clonal evolution, exhaustion mechanisms, and memory cell generation. This approach offers single-cell resolution data that contribute to resolving pertinent clinical challenges. This article provides a comprehensive review of recent developments and characteristics of the SCLT multi-omics approach. It elucidates the manner in which SCLT addresses the conventional constraints associated with spatiotemporal resolution and introduces a novel methodology for generating DNA barcodes to monitor CAR-T cells via CRISPR technology. These contributions offer valuable perspectives for the enhancement of cell therapy strategies.
This study analyzes the relationship between verbal interaction and eye behavior among 112 primary school students in urban and rural classrooms in Chile, using wireless eye-tracking technology. The results reveal statistically significant differences based on socioeducational context and sex. Linear regression analyses show that gaze is a significantly more robust predictor of class participation in rural contexts (R2 adjusted = 0.671) than in urban contexts (R2 adjusted = 0.342). Furthermore, eye behavior explained 71% of the variance in male students, compared to 37.7% in female students. While female students focused their attention primarily on teachers, male students relied on a shared visual distribution between the teacher and peers to regulate their participation in class. In conclusion, the gaze acts as a differentiated scaffolding whose importance intensifies in boys and rural environments. These findings suggest distinct maturational trajectories that require teachers to implement visually intentional instructional strategies to ensure communicative efficiency in the classroom.
The increase in sophisticated electronic gambling products offered by gambling manufacturers facilitates an increase in the accessibility of gambling platforms and modes. This study proposes utilising Artificial Intelligence (AI) to enhance self-awareness and self-control within electronic gaming machines. The study adopts a case study that follows an exploratory research design, as the causal explanation argument suggests that the Electronic Gaming Machine (EGM) device causes problem gambling. Secondary data on gambling were obtained and analysed. The machine-learning pattern recognition and classification model; a learning approach which learns from a trained dataset to make decisions or predictions, was employed. The dataset was trained iteratively using the scaled conjugate gradient backpropagation with the input and output target samples divided into training, validation, and test datasets. Furthermore, the softmax was used for classifying the dataset into three classes: responsible, intermediate, and irresponsible gambling. The confusion matrix was used to analyse the percentages of correct and incorrect classifications. The results obtained indicated that the accuracy of the developed model was 99.20%, while the precision was 85.70%. The recall achieved 85.70%, while the F1-score reached 80.50%. The closeness of these performance indices to 1, coupled with the negligible value of mean square error, indicates that the developed classification model is robust and suitable for classification problems. Thus, this study contributes to knowledge by developing an AI model that can track players and reduce harm in a land-based gambling environment.