Experimental Phase Research Articles

Analysis of Artificial Neural Networks on Predicting Dementia

Dementia, a chronic neurological disorder characterized by memory loss and impaired cognitive ability, has affected tens of millions of people globally and projections estimate this number to rise in the coming decade. Despite its widespread impact, dementia remains one of many diseases with no true cure or definitive method of diagnosis. This study aims to explore the question of how artificial neural networks can be used to predict dementia. Analyzing current research on neural networks for disease diagnosis highlights a notable gap, known as the "black box conundrum," indicating the challenge of tracing steps leading to a given output. Another gap in the literature is the absence of comparative data on factors influencing successful neural network algorithms. Conducting a comprehensive cross-continental comparative analysis across North America, Asia, and Europe, and utilizing an experimental design with the UCI ML Repository’s Parkinson’s Database, this study specifically aims to fill the identified gaps. The findings reveal key elements for successful neural networks: a data sample exceeding 100, clinically intelligible data values, and a backpropagation model. In the experimental phase, a comparison between a backpropagation model and logistic regression, paired with Shapley value analysis, elucidated a 94.87% accuracy for the former, surpassing the latter's 92.3%. These findings extend beyond dementia, providing valuable insights for neural network applications in all healthcare settings. Future research endeavors should focus on refining and optimizing neural networks with the ultimate goal of achieving 100% accuracy and maximized efficiency.

Experimental Study of a Homogeneous Charge Compression Ignition Engine Using Hydrogen at High-Altitude Conditions

One of the key factors of the current energy transition is the use of hydrogen (H2) as fuel in energy transformation technologies. This fuel has the advantage of being produced from the most primary forms of energy and has the potential to reduce carbon dioxide (CO2) emissions. In recent years, hydrogen or hydrogen-rich mixtures in internal combustion engines (ICEs) have gained popularity, with numerous reports documenting their use in spark ignition (SI) and compression ignition (CI) engines. Homogeneous charge compression ignition (HCCI) engines have the potential for substantial reductions in nitrogen oxides (NOx) and particulate matter (PM) emissions, and the use of hydrogen along with this kind of combustion could substantially reduce CO2 emissions. However, there have been few reports using hydrogen in HCCI engines, with most studies limited to evaluating technical feasibility, combustion characteristics, engine performance, and emissions in laboratory settings at sea level. This paper presents a study of HCCI combustion using hydrogen in a stationary air-cooled Lombardini 25 LD 425-2 modified diesel engine located at 1495 m above sea level. An experimental phase was conducted to determine the intake temperature requirements and equivalence ratios for stable HCCI combustion. These results were compared with previous research carried out at sea level. To the best knowledge of the authors, this is the first report on the combustion and operational limits for an HCCI engine fueled with hydrogen under the mentioned specific conditions. Equivalence ratios between 0.21 and 0.28 and intake temperatures between 188 °C and 235 °C effectively achieved the HCCI combustion. These temperature values were, on average, 100 °C higher than those reported in previous studies. The maximum value for the indicated mean effective pressure (IMEPn) was 1.75 bar, and the maximum thermal efficiency (ITEn) was 34.5%. The achieved results are important for the design and implementation of HCCI engines running solely on hydrogen in developing countries located at high altitudes above sea level.

Review of hydrogen-based propulsion systems in the maritime sector

The maritime industry is undergoing a technology transition that aims to increase the use of low-emission fuels. There is a significant trend visible of new ships being ordered with alternative fuel propulsion. In the future shipping’s fuel market will be more diverse and it will rely on multiple energy sources. One of the very promising ways to meet the International Maritime Organisation’s decarbonization requirements is to operate ships with sustainable hydrogen propulsion. One of the possible options to limit greenhouse gases emissions is the production of low-carbon ‘green’ hydrogen by water electrolysis using low-carbon electricity. This hydrogen can then be used directly in fuel cells to produce electricity or in the internal combustion engines, without having a carbon impact and pollutant emissions. Hydrogen can also be converted into its derivatives. This paper presents a review of recent studies of ships’ hydrogen propulsion systems, different aspects of production, transportation, storage, and using liquid/gaseous H2 and its derivatives as a fuel in the shipping industry. H2 propulsion in maritime transport is still in the experimental phase. In most cases, these experiments serve as a kind of platform for evaluating the applicability of different technological solutions. This article presents existing ships’ hydrogen and its derivates propulsion systems, projects, and existing conceptual studies.

The role of posterior parietal cortex in detecting changes in feedback contingency.

Well-practiced or learned behaviors are extremely resilient. For example, it is extremely difficult for a trained typist to forget how to use a keyboard configuration that they are familiar with. While they can be trained on a new keyboard configuration, the original skill quickly comes back when the old keyboard configuration is used again. This resiliency of learned skills is both a blessing and a curse. It makes useful skills durable, but it also makes maladaptive behaviors difficult to extinguish. Crossley et al. (2013) proposed a computational model and behavioral paradigm aimed at unlearning skills using various feedback contingency manipulations during an extinction phase. They showed that partially-valid feedback during extinction removed evidence for fast reacquisition, which they interpreted as evidence for unlearning. In this article, we replicated the Crossley et al. paradigm using fMRI. Univariate analyses showed differences in BOLD signals between the different experiment phases in the frontoparietal attention network. The superior and inferior parietal lobules (SPL and IPL, respectively) showed the largest cluster differences both between experimental phases and between extinction conditions. In contrast, the prefrontal cortex only showed differences in cluster of activities between extinction conditions. Multivariate pattern analysis was also used with seeds in the SPL and IPL. The results showed that these brain areas were critical in detecting changes in experimental phases. Overall, the fMRI results found mixed evidence for the Crossley et al. model and suggest that while unlearning prevents fast reacquisition, the absence of fast reacquisition does not necessarily implies that unlearning occurred.

Application of LightGBM hybrid model based on TPE algorithm optimization in sleep apnea detection.

Sleep apnoea syndrome (SAS) is a serious sleep disorder and early detection of sleep apnoea not only reduces treatment costs but also saves lives. Conventional polysomnography (PSG) is widely regarded as the gold standard diagnostic tool for sleep apnoea. However, this method is expensive, time-consuming and inherently disruptive to sleep. Recent studies have pointed out that ECG analysis is a simple and effective diagnostic method for sleep apnea, which can effectively provide physicians with an aid to diagnosis and reduce patients' suffering. To this end, in this paper proposes a LightGBM hybrid model based on ECG signals for efficient detection of sleep apnea. Firstly, the improved Isolated Forest algorithm is introduced to remove abnormal data and solve the data sample imbalance problem. Secondly, the parameters of LightGBM algorithm are optimised by the improved TPE (Tree-structured Parzen Estimator) algorithm to determine the best parameter configuration of the model. Finally, the fusion model TPE_OptGBM is used to detect sleep apnoea. In the experimental phase, we validated the model based on the sleep apnoea ECG database provided by Phillips-University of Marburg, Germany. The experimental results show that the model proposed in this paper achieves an accuracy of 95.08%, a precision of 94.80%, a recall of 97.51%, and an F1 value of 96.14%. All of these evaluation indicators are better than the current mainstream models, which is expected to assist the doctor's diagnostic process and provide a better medical experience for patients.

The effect of AI-powered chatbots in social studies education

AbstractThe aim of this research is to investigate the educational potential of AI-powered chatbots in Social Studies learning-teaching processes. The study was conducted using embedded design, evaluated within the framework of mixed methods research. The study group consists of 78 6th-grade students studying in three different classes, along with one teacher who implemented the practices and guided the process. During the experimental phase of the study, lessons in the experimental group were taught by the practitioner teacher using an AI-powered chatbot named “SosyalciBot”. Meanwhile, lessons in two control groups were taught following the constructivist approach. At the end of the process, it was determined that the experimental group students’ post-test and permanency test scores were significantly higher than the control group students’ scores in both post-test and permanency test. In the semi-structured interviews, both students and the practitioner teacher provided positive evaluations of the pedagogical and design features of the chatbot, indicating that these features positively impacted the learning-teaching process. They also identified some shortcomings while offering suggestions for improvement. Based on the study findings, it is evident that chatbots have a high potential to contribute to Social Studies education. However, to fully harness this potential and achieve optimal effectiveness, further advancements and refinements in chatbot technology are required. At this point, it is recommended to conduct theoretical or applied studies focusing on developing chatbots with high communication capacity and explore innovative and constructive ideas regarding the integration of chatbots into educational environments.

Exploring optimal pathways for enterprise procurement management systems based on fast neural modeling and semantic segmentation

Corporate procurement management assumes a pivotal role within the contemporary business landscape, yet confronts an array of challenges as markets continue to evolve and globalize. Conventional procurement management systems frequently grapple with issues of inefficiency, resource depletion, and noncompliance, necessitating the exploration of innovative avenues for optimization. This paper delves into the realm of risk mitigation associated with collusion behavior in the administration of intelligent procurement systems, presenting a novel procurement collusion identification model founded on a convolutional neural network (CNN) with reinforcement learning techniques. This framework commences with the application of a CNN and Long Short-Term Memory (LSTM) network for in-depth feature analysis and initial identification of historical procurement data, subsequently leveraging reinforcement learning methodologies to enhance the model's autonomy and intelligence for the purpose of optimization. Throughout the experimental phase, diverse domains of procurement data were meticulously selected for analysis. The empirical findings unequivocally demonstrate the model's proficiency, with an average recognition accuracy of 95.1% across five publicly available datasets. This performance surpasses existing machine learning methodologies employed in contemporary research and common recognition networks, thereby offering a pioneering reference point for the intelligent administration and optimization of future procurement systems.

Experimental and numerical investigation of free vibration behaviour of sandwich plates with natural-fibre-based laminated composite cores

ABSTRACT This article presents an experimental and numerical investigation into the free vibration behaviour of fibre-reinforced composite sandwich plates. The proposed symmetrical three-layer sandwich plate contains aluminium as face layers and jute/epoxy laminated composite as a core layer. The experimental phase of this research involves the fabrication of jute/epoxy composite sandwich plates and the measurement of their natural frequencies through a non-destructive modal testing approach using the impact hammer technique. A numerical model is developed using the finite element method in the ABAQUS platform to simulate the free vibration response of the jute/epoxy composite sandwich plates. Comparisons between the experimental and numerical results demonstrate a good agreement, validating the accuracy and reliability of the finite element model. Furthermore, an extensive numerical investigation is conducted to examine the impact of various geometric and structural parameters on the dynamic response of the sandwich plates. The study’s outcomes aid in designing and optimising composite sandwich structures, facilitating the development of sustainable and high-performance engineering solutions.

A note on the Hendrickson-Lattman phase probability distribution and its equivalence to the generalized von Mises distribution.

Hendrickson & Lattman [Acta Cryst. (1970), B26, 136-143] introduced a method for representing crystallographic phase probabilities defined on the unit circle. Their approach could model the bimodal phase probability distributions that can result from experimental phase determination procedures. It also provided simple and highly effective means to combine independent sources of phase information. The present work discusses the equivalence of the Hendrickson-Lattman distribution and the generalized von Mises distribution of order two, which has been studied in the statistical literature. Recognizing this connection allows the Hendrickson-Lattman distribution to be expressed in an alternative form which is easier to interpret, as it involves the location and concentration parameters of the component von Mises distributions. It also allows clarification of the conditions for bimodality and access to a simplified analytical method for evaluating the trigonometric moments of the distribution, the first of which is required for computing the best Fourier synthesis in the presence of phase, but not amplitude, uncertainty.

Solid-liquid phase equilibria of quaternary systems LiCl+KCl+NaCl+H2O and LiCl+KCl+MgCl2+H2O at 308.2K

The phase equilibria of quaternary systems LiCl+KCl+NaCl+H2O and LiCl+KCl+MgCl2+H2O at 308.2 K were investigated by isothermal dissolution equilibrium method. The results reveal that the phase diagram of the quaternary system LiCl+KCl+NaCl+H2O consists of one invariant point, three univariable curves and three equilibrium solid crystallization fields (LiCl·H2O, NaCl and KCl). Two double salts appear in the quaternary system LiCl+KCl+MgCl2+H2O, namely KCl·MgCl2·6H2O and LiCl·MgCl2·7H2O, and the phase diagram is composed of three invariant points, seven univariable curves and five crystallization fields (LiCl·MgCl2·7H2O, MgCl2·6H2O, LiCl·H2O, KCl and KCl·MgCl2·6H2O). Moreover, the solubilities of salts in two quaternary systems are predicted by applying the Pitzer model. The calculated phase diagrams were in good accordance with the experimental phase diagrams. The results clearly show that lithium chloride crystallizes as LiCl·2H2O at low temperatures; however, it is precipitated as LiCl·H2O at 308.2 K. Compared with KCl·MgCl2·6H2O, LiCl·MgCl2·7H2O has a smaller crystallization zone. The phase equilibria in invariant points of quaternary systems LiCl+KCl+NaCl+H2O and LiCl+KCl+MgCl2+H2O at 308.2 K have been explored for the first time.

MULTIMEDIA PHOTOGRAMMETRY 2.0. A FIRST STEP FOR UNDERWATER CULTURAL HERITAGE APPLICATION

Abstract. The research is framed in multimedia photogrammetry, a specific domain aimed at acquiring geometric information about static objects immersed or semi-submerged in a liquid through one or more cameras external to the liquid. If the liquid is water, this field belongs to the broader field of applied metrology for analysing and understanding the aquatic world. Specifically, the various passive sensing techniques for acquiring Underwater Cultural Heritage (UCH) in shallow water are central to understanding the research domain's underlying issues. Our research is framed in the domain, implementing the automatic analysis to estimate a priori (and correcting a posteriori) the camera's behaviour under certain conditions for acquiring submerged or semi-submerged objects. The first analytical results are framed in a two-year project, which aims to define a behaviour model in a controlled environment with encoded targets and stereo-photogrammetry, automatically extracting the camera orientation parameters under different water height conditions. A planar reproduction of a CH artefact, which simulates an immersed architectonic floor, has been applied to validate the process in a first case study, testing the system's capacity to extract the correct coordinates of the image. At the end of this first experimental phase, the aim is to define a model for the behaviour of water deformation. It will make it possible to predict and correct the water refraction by calculating the correct coordinates within the liquid. In the future, this model will be tested under different and incrementally more complex acquisition conditions. The global project's primary goal is to arrive at the application of this model in an uncontrolled environment for the survey of UCH in shallow water.

Effect of Game-Specific Training on Dribbling among Hockey Players

This study sought to determine the effects of game-specific training on hockey players’ dribbling. For this study, thirty male hockey players from Namakkal, Tamilnadu, were selected at random to serve as subjects. They were between the ages of 18 and 25. The participants were split into two equal classes after being selected at random. The control group (CG) and experimental group (game-specific training) were created. For six weeks, the study group practiced game-specific training in addition to their regular activities three days a week. The experimental treatment was only available at night. The experimental group did not receive any training. Both groups took a pre-test before the training to gauge their dribbling prowess through a subjective evaluation. A post-test was conducted once the experimental phase was completed. The significance level was set at 0.05 and the ANCOVA test was employed.

A quasi-experimental mixed-method pilot study to check the efficacy of the "SOUND" active and passive music-based intervention on mental wellbeing and residual cognition of older people with dementia and dementia professionals' burnout: a research protocol.

The SOUND method offers an innovative blended intervention based on music circle-activities and cognitive stimulation approaches which was co-designed by musicians, health professionals, older people with dementia, family caregivers and researchers, for its application in dementia settings. The purpose of the paper is to describe the detailed procedure of the quasi-experimental pilot study. The experimental phase of SOUND uses a mixed-method design encompassing qualitative and quantitative observations, cognitive testing, self-report and interviewer-assisted questionnaires to investigate the effectiveness of the intervention for 45 people with dementia and 45 professionals (15 in every study country: Italy, Portugal, Romania). The pilot study will be the first implementation of the SOUND intervention aiming to investigate the feasibility and preliminary effects of the method. The novelty of SOUND is its multicomponent method, including the most evidenced features for improving the wellbeing of participants.

Advancing the path to in-vivo imaging in freely moving mice via multimode-multicore fiber based holographic endoscopy.

Hair-thin multimode optical fiber-based holographic endoscopes have gained considerable interest in modern neuroscience for their ability to achieve cellular and even subcellular resolution during in-vivo deep brain imaging. However, the application of multimode fibers in freely moving animals presents a persistent challenge as it is difficult to maintain optimal imaging performance while the fiber undergoes deformations. We propose a fiber solution for challenging in-vivo applications with the capability of deep brain high spatial resolution imaging and neuronal activity monitoring in anesthetized as well as awake behaving mice. We used our previously developed multimode-multicore fiber to record fluorescently labeled neurons in anesthetized mice. Our exhibits a cascaded refractive index structure, enabling two distinct regimes of light transport that imitate either a multimode or a multicore fiber. The has been specifically designed for use in the initial phase of an in-vivo experiment, allowing for the navigation of the endoscope's distal end toward the targeted brain structure. The multicore regime enables the transfer of light to and from each individual neuron within the field of view. For chronic experiments in awake behaving mice, it is crucial to allow for disconnecting the fiber and the animal between experiments. Therefore, we provide here an effective solution and establish a protocol for reconnection of two segments of with hexagonally arranged corelets. We successfully utilized the to image neurons in anaesthetized transgenic mice expressing enhanced green fluorescent protein. Additionally, we compared imaging results obtained with the with larger numerical aperture (NA) fibers in fixed whole-brain tissue. This study focuses on addressing challenges and providing insights into the use of multimode-multicore fibers as imaging solutions for in-vivo applications. We suggest that the upcoming version of the increases the overall NA between the two cladding layers to allow for access to high resolution spatial imaging. As the NA increases in the multimode regime, the fiber diameter and ring structure must be reduced to minimize the computational burden and invasiveness.

Comparative Studies of Microstructural, Mechanical and Tribological behaviour of A319 alloy cast in solid waste mold and conventional sand Mold

Abstract This study investigates the potential of utilizing industrial solid waste (blast furnace slag, ferrochrome slag, and red mud) as mold materials to improve the solidification rate and wear resistance of A319 alloy. Unlike conventional molds such as silica sand and olivine sand, industrial solid waste poses an eco-friendly alternative, contributing to waste valorization. The motivation for this research drives the need for sustainable and efficient waste management practices in the industrial sector. By exploring the utilization of industrial solid waste as a mold material, study aims to address the current challenges in disposal, reduce environmental impact, and enhance the overall performance of A319 alloy through improved solidification and wear resistance. The experimental phase involved multi-factor reciprocating sliding wear tests conducted on a sample using a linear reciprocating tribometer, employing a steel ball as a counter face. The investigation of reciprocating wear characteristics aimed to assess the correlations between solidification rate and wear properties of a specimen cast in an industrial solid waste mold as well as a sand mold. Notably, tribological test results revealed a low wear rate of 3.3 mg/Km for the blast furnace slag mold. The scanning electron microscopy (SEM) image of the wear surface showed adhesive wear mechanisms. This study contributes valuable insights into the potential environmental and performance advantages of repurposing industrial solid waste for foundry applications.

Experimental Study on The Performance Characteristics of 4 Stroke CI Engine using Biodiesel Blend from Coconut Oil

To address the challenges faced by the government in the realm of petroleum imports, a promising strategy was adopted in the utilization of biodegradable and renewable sources of biodiesel, such as coconut oil. This research employed two distinct methodologies: Transesterification for biodiesel synthesis and a comprehensive assessment of fuel properties. Subsequently, an experimental phase assessed biodiesel within an engine environment to analysis performance metrics. Results showed that B30 (30% coconut oil, 70% diesel oil) has density of 0.850 g/cm³, B50 (50% coconut oil) at 0.861 g/cm³, and B100 (Pure coconut oil) at 0.893 g/cm³. The values differed from regional standards. As per ASTM D6751, B30 has a viscosity of 2.31 cSt, B50 3.22 cSt, and B100 is 7.02 cSt. Engine performance revealed B50 with the highest torque at 11.787 Nm, while B0 (pure hydrocarbon diesel) has a thermal efficiency of 38%. B0’s lowest SFC (Specific Fuel Consumption) is 261.12 g/kWh at 2000 watts load and 1000 rpm. Biodiesel coconut oil provided comparable power and torque (0.3% difference from B0) but consumed more fuel (21.6 % higher usage than B0). Keywords: Biodiesel, Coconut oil, Engine performance, Fuel properties, Transesterification.

Effects of Resistance Training on Leg-strength and Back-strength in 18-25 Years Women

In the contest of human life there is essentiality of being good. Being good not only means to feel good but also to look good and live well. Now a day’s physical education spreads the wide network in the worldwide. It mainly having two faces they are science and arts. The resistance training is one of the scientific training method in physical education and sports sciences. In this study the researcher has carried on experiments to investigate the effects of resistance training on leg strength and back strength variables before, during and after resistance training. The researcher has taken 50 subjects, and they are divided into two group one is experimental and anther one is control group. The experimental training phase of twelve weeks, the subjects were given resistance training programme trice a week. The exercise are Shoulder Press, Bent-Knee Sit-Ups, Half Squat, Over head press and Dead lift. The collected data’s were analyzed by using SPSS software version 2.0. The result of the study shows that there were significant differences obtained on selected Motor fitness components such as Leg Strength and Back Strength variables of Resistance Training on women in the age group of 18 to 25 years.

Do We Need Fasting Prior to Coronary Angiography? The CORO-NF Randomized Pragmatic Study

BackgroundSimilar to procedures requiring general anesthesia, current guidelines recommend fasting for 6 hours for solids and for 2 hours for liquids prior to coronary angiography, but without data supporting such recommendation. The CORO-NF study aimed at assessing whether a shorter fasting period prior to elective coronary angiography associates with improved patient satisfaction without more complications compared with the standard fasting approach. MethodsWe conducted a single-center, randomized, prospective, pragmatic study in 2 sequential phases: a “conventional protocol phase,” continuing the usual practice (F Group); and an “experimental phase” (NF Group), reducing minimum fasting duration to 2 hours. Patients received a questionnaire to express a satisfaction score ranging from 1 (maximum complain/no approval) to 5 (minimum or no complain/full approval). All patients admitted acutely were enrolled in a control A Group registry. Fasting time and every major complication and periprocedural complications were analyzed. ResultsFasting time was 821 ± 357 minutes in the F Group and 230 ± 146 minutes in the NF Group (P < .001). The satisfaction score was higher in the NF Group (4.2 ± 0.7 vs 2.9 ± 1.2, P < .001), even at multivariable analysis considering fasting time (P < .001). No intraprocedural food ingestion-related adverse events occurred in either of the 2 experimental groups, as well as in the parallel A Group, with no excess of peri- and postprocedural complications in the NF Group. ConclusionsThe significantly higher satisfaction scores among patients undergoing a shorter-than-recommended fasting period prior to coronary angiography, not counterbalanced by decreased safety, underscores the potential benefits of revising the traditional 6-hour fasting protocols.

Exploring the mechanism of action of Sparganii Rhizoma-Curcumae Rhizoma for in treating castration-resistant prostate cancer: a network-based pharmacology and experimental validation study

Sparganii Rhizoma-Curcumae Rhizoma (SR-CR) is a classic drug pair for the treatment of castration-resistant prostate cancer (CRPC), but its mechanism has not been clarified. The study aims to elucidate the potential mechanism of SR-CR in the management of CRPC. The present study employed the TCMSP as well as the SwissTargetPrediction platform to retrieve the chemical composition and targets of SR-CR. The therapeutic targets of CRPC were identified through screening the GeneCards, Disgenet, and OMIM databases. Subsequently, the Venny online platform was utilized to identify the shared targets between the SR-CR and CRPC. The shared targets were enrichment analysis using the Bioconductor and Kyoto encyclopedia of genes and genomes (KEGG) databases. The active ingredients and core targets were verified through molecular docking and were validated using PC3 cells in the experimental validation phase. A total of 7 active ingredients and 1126 disease targets were screened from SR-CR, leading to a total of 59 shared targets. Gene Ontology (GO) analysis resulted in 1309 GO entries. KEGG pathways analysis yielded 121 pathways, primarily involving cancer-related signaling pathways. The results from molecular docking revealed stable binding interactions between the core ingredients and the core targets. In vitro cellular assays further demonstrated that SR-CR effectively suppressed the activation of the Prostate cancer signaling pathway in PC3 cells, leading to the inhibition of cell proliferation and promotion of apoptosis. The SR-CR exert therapeutic effects on CRPC by inhibiting cell proliferation and promoting apoptosis through the Prostate cancer signaling pathway.

Metaversal sustainability: conceptualisation within the sustainable tourism paradigm

Purpose This paper aims to address the novel phenomenon of tourism in the metaverse and analyse possible scenarios that could influence the resilience of a sustainable tourism paradigm in response to this new phenomenon. Design/methodology/approach Based on Kuhn’s paradigmatic framework, this paper offers an innovative perspective for the integration of new theories and practise-relevant phenomena. It emphasises the relevance and commensurability of different paradigmatic dimensions and outlines the scenarios for the integration of metaversal sustainability. Findings The phenomenon of tourism in the metaverse of the 21st century poses a new challenge to the existing paradigm of sustainable tourism, which traditionally focuses on the economic and ecological sustainability of planet Earth’s physical environment. The adoption of a metaversal sustainability scenario for the virtual and mixed reality is key to a responsible implementation of the paradigm of sustainable tourism development that considers all its environments, whether fantastic or realistic. Research limitations/implications This study has its limitations, as metaversal tourism is still in the experimental phase. A more comprehensive understanding of the metaverse and its terminology is still evolving. There is potential to adapt the sustainable tourism paradigm to new technological environments if the metaverse is recognized as one in the future. Practical implications There are practical implications for tourism policy and practise. Tourism stakeholders need to adapt to the changing tourism landscape by recognising the metaverse as a viable environment committed to sustainable development. This will enable innovative strategies to govern, lead, promote and manage metaversal tourism and ensure that it is in line with the long-term goal of sustainability. Social implications The metaverse holds considerable potential for transforming social perception and behaviour. Integrating the metaverse into the sustainability pillars of the sustainable development paradigm implies a forward-looking approach that takes into account the dynamics of people’s evolving desires and preferences. This inclusion advocates for sustainable development in all environments in which people live and explore. Originality/value This research stands out for its pioneering role in advancing a sustainable tourism paradigm that goes beyond the traditional planetary dimensions. By examining the impact of tourism in the metaverse, it proposes a path towards a more holistic and future-oriented paradigm of sustainable tourism in both the physical and virtual worlds. The coining of the term “metaversal sustainability” contributes to the lexicon of paradigms for both tourism and societal sustainable development.