Interactive Exploration Research Articles

Automating board-game based learning. A comprehensive study to assess reliability and accuracy of AI in game evaluation

Game-Based Learning (GBL) and its subset, Board Game-Based Learning (bGBL), are dynamic pedagogical approaches leveraging the immersive power of games to enrich the learning experience. bGBL is distinguished by its tactile and social dimensions, fostering interactive exploration, collaboration, and strategic thinking; however, its adoption is limited due to lack of preparation by teachers and educators and of pedagogical and instructional frameworks in scientific literature. Artificial intelligence (AI) tools have the potential to automate or assist instructional design, but carry significant open questions, including bias, lack of context sensitivity, privacy issues, and limited evidence. This study investigates ChatGPT as a tool for selecting board games for educational purposes, testing its reliability, accuracy, and context-sensitivity through comparison with human experts evaluation. Results show high internal consistency, whereas correlation analyses reveal moderate to high agreement with expert ratings. Contextual factors are shown to influence rankings, emphasizing the need to better understand both bGBL expert decision-making processes and AI limitations. This research provides a novel approach to bGBL, provides empirical evidence of the benefits of integrating AI into instructional design, and highlights current challenges and limitations in both AI and bGBL theory, paving the way for more effective and personalized educational experiences.

Contribution of Virtual Reality to the Reproduction of Social Interaction Characteristics in Neuropsychology: A Systematic Review of the Literature

Abstract Sociocognitive difficulties are observed in many pathologies associated with brain lesions or atypical brain functioning. The development of virtual reality offers an opportunity to assess this dimension from an interactionist perspective and to increase the ecological validity of the material used. However, this approach can be operationalized and conceptualized in a variety of ways. To understand these aspects, we conducted a systematic review of articles found in the PubMed, PubMed Central, and ScienceDirect databases, following PRISMA-P guidelines. A corpus of 48 articles was identified and analyzed in terms of the experimental devices used, to gauge the extent to which they reproduced the characteristics of real-world social interactions, as well as the associated conceptions. Results suggested that interactionist research lies on a continuum between ecological validity (studies exploring interactions via general functions) and a high level of experimental control (exploration of interactions with respect to specific processes). They are discussed in terms of the operationalization and objectification of interactionism.

Design of Indoor and Outdoor Space Environment in Kindergartens based on Children’s “Three Natures”

Nature is the natural source of children, the mind is the psychological activity of children’s self-awareness and understanding of the world, and personality is the stable social quality formed by children in social interaction and practice. Adhere to the “three characteristics” of children as the foundation of kindergarten space creation, in line with the laws of children’s physical and mental development, deepen children’s interaction with the environment and deepen their understanding of the world and themselves. The specific methods that can be adhered to in practice are as follows: follow nature and create a natural material space, inspire the mind and create a warm and harmonious psychological space; respect individuality and present a rich interactive exploration space.

PHCDTI: A multichannel parallel high-order feature crossover model for DTIs prediction

The exploration of non-covalent interactions between drugs and proteins (NCIs) has significantly improved the performance of drug–target interactions (DTIs) prediction models. However, existing methods for simulating NCIs are limited to single or multiple interactions, ignoring the combinatorial effects (i.e., high-order crossover between drugs and proteins (HOC-D&P)) that can arise when multiple NCIs coexist. To overcome this limitation, a multi-channel parallel high-order prediction model (PHCDTI) is proposed, aiming to simulate the complex interactions between drugs and proteins, thereby modeling HOC-D&P. Firstly, a tri-channel parallel model structure is constructed, allowing each channel to independently learn the interaction patterns between drug molecules and amino acid groups. Secondly, the three channels are designed from low-order to high-order, incorporating linear, inner-product, and pair-interaction feature crossover methods to simulate the complex interactions between drug molecules and amino acid groups. The stacking of residual connections enables the model to effectively model HOC-D&P. Additionally, by utilizing multi-head attention mechanisms for inner product and squeeze-excitation networks (SENET) for pair-interaction, the interpretability of the NCIs modeling process and the specific representation of drug molecules or amino acid groups are achieved. PHCDTI was evaluated on three benchmark datasets in four experimental settings, and the results indicated that it outperformed the most recent baseline model. In all cases, the average accuracy, precision, recall, AUC, and AUPR of PHCDTI are improved over the best baseline model by 3.56%, 6.06%, 3.99%, 2.50%, and 8.11%, respectively. Moreover, strong information filtering capabilities were exhibited by PHCDTI, with the effectiveness of the three-channel design confirmed by ablation studies. Finally, a case study on the human γ-aminobutyric acid receptors (GABARs) demonstrated that PHCDTI can serve as a powerful tool for real-world drug screening and design.

Immersive and Interactive 3D Visualization of Large-Scale Geoscientific Data

Abstract Virtual reality (VR) technology has great potential in supporting planetary scientists and the field of geosciences by offering immersive and interactive experiences for data exploration and analysis. This paper shows the opportunities presented by the use of VR technology in the geosciences domain while also identifying the open challenges associated with this integration. Our focus is on highlighting the several benefits that VR brings, including stereo vision, head tracking, and collaborative capabilities. These features can foster knowledge exchange and interdisciplinary research. Nevertheless, the adoption of VR presents certain challenges that need to be addressed. These include maintaining high refresh rates, handling large heterogeneous datasets, and striking a balance between visualization fidelity and performance. Fortunately, significant advancements have been made in high-performance data analysis, progressive data streaming, and real-time visualization, enabling interactive exploration of large-scale datasets within VR environments. To support a broader adoption among domain experts, we propose a visualization approach that scales both with display and with data size. As such, the system can be used to interactively explore large-scale datasets in immersive environments like CAVEs or powerwalls, on HMDs, or on traditional desktop setups. This approach allows for seamless transitions between desktop and VR experiences, leveraging immersive environments for collaboration and outreach activities. In this paper, we present an architectural framework, hardware environments, use cases, lessons learned, and the future potential of VR in this field. Through this scalable system, we anticipate transformative advancements in scientific exploration, collaboration, and knowledge dissemination.

Genome sequencing of Elaeocarpus spp. stem blight pathogen Pseudocryphonectria elaeocarpicola reveals potential adaptations to colonize woody bark

BackgroundElaeocarpus spp. stem blight, caused by Pseudocryphonectria elaeocarpicola, is a destructive disease, which will significantly reduce the productivity and longevity of Elaeocarpus spp. plants, especially in the Guangdong Province of China. However, few information is available for P. elaeocarpicola. To unravel the potential adaptation mechanism of stem adaptation, the whole genome of P. elaeocarpicola was sequenced by using the DNBSEQ and PacBio platforms.ResultsP. elaeocarpicola harbors 44.49 Mb genome with 10,894 predicted coding genes. Genome analysis revealed that the P. elaeocarpicola genome encodes a plethora of pathogenicity-related genes. Analysis of carbohydrate-active enzymes (CAZymes) revealed a rich variety of enzymes participated in plant cell wall degradation, which could effectively degrade cellulose, hemicellulose and xyloglucans in the plant cell wall and promote the invasion of the host plant. There are 213 CAZyme families found in P. elaeocarpicola, among which glycoside hydrolase (GH) family has the largest number, far exceeding other tested fungi by 53%. Besides, P. elaeocarpicola has twice as many genes encoding chitin and cellulose degradation as Cryphonectria parasitica, which belong to the same family. The predicted typical secreted proteins of P. elaeocarpicola are numerous and functional, including many known virulence effector factors, indicating that P. elaeocarpicola has great potential to secrete virulence effectors to promote pathogenicity on host plants. AntiSMASH revealed that the genome encoded 61 secondary metabolic gene clusters including 86 secondary metabolic core genes which was much higher than C. parasitica (49). Among them, two gene cluster of P. elaeocarpicola, cluster12 and cluster52 showed 100% similarity with the mycotoxins synthesis clusters from Aspergillus steynii and Alternaria alternata, respectively. In addition, we annotated cytochrome P450 related enzymes, transporters, and transcription factors in P. elaeocarpicola, which are important virulence determinants of pathogenic fungi.ConclusionsTaken together, our study represents the first genome assembly for P. elaeocarpicola and reveals the key virulence factors in the pathogenic process of P. elaeocarpicola, which will promote our understanding of its pathogenic mechanism. The acquired knowledge lays a foundation for further exploration of molecular interactions with the host and provide target for management strategies in future research.

Exploring animal behaviour multilayer networks in immersive environments - a conceptual framework.

Animal behaviour is often modelled as networks, where, for example, the nodes are individuals of a group and the edges represent behaviour within this group. Different types of behaviours or behavioural categories are then modelled as different yet connected networks which form a multilayer network. Recent developments show the potential and benefit of multilayer networks for animal behaviour research as well as the potential benefit of stereoscopic 3D immersive environments for the interactive visualisation, exploration and analysis of animal behaviour multilayer networks. However, so far animal behaviour research is mainly supported by libraries or software on 2D desktops. Here, we explore the domain-specific requirements for (stereoscopic) 3D environments. Based on those requirements, we provide a proof of concept to visualise, explore and analyse animal behaviour multilayer networks in immersive environments.

Exploration of supramolecular interactions, Hirshfeld surface, FMO, molecular electrostatic potential (MEP) analyses of pyrazole based Zn(II) complex

The supramolecular interactions of title compound [Zn(HL2)](ClO4)2(MeOH)2] (1) where, HL2=((Z)-N’-(5-methyl-1H-pyrazole-3-carbonyl)pyrazine-2-carbohydrazonamide) are explored in detail. With a detailed scrutiny of visualizing of title compound 1, the crystal packing is mainly directed by strong hydrogen bonding interactions observed N–H⋯N and N–H⋯O but, in addition, weak interactions such as C–H⋯π, π⋯π are also sighted to stabilize the crystal self-assembly. Electronic structure of the complex is determined using DFT calculations at B3LYP level with mixed basis set. Theoretically calculated structural parameters are in good match with the experimentally obtained parameters from XRD. TDDFT calculation is performed to simulate the UV–Vis absorption spectra of the complex. Molecular reactivity and stability of the complex has been assessed through frontier molecular orbital analysis and also through evaluation of molecular electrostatic potential (MEP). Hirshfeld surface analysis, which uses molecular surface contours and 2D fingerprint plots to visually analyze intermolecular interactions in crystal structures, has been used to examine molecular morphologies. The Hirshfeld surface and fingerprint plots are accompanied by crystal structure analysis allowed for the discovery of the important intermolecular interactions.

On the issue of treating HIV in people with syndemic mental-health and substance-use disorders.

People with HIV and comorbid substance use problems may be among those who benefit most from long-acting HIV antiretroviral treatment, but they are routinely excluded from Phase 3 clinical trials. Their inclusion would permit an examination of the clinical value of long-acting therapies for people with adherence problems and an exploration of syndemic interactions between HIV, mental health conditions, and substance use problems, which compound into a major challenge in the efforts to end the HIV epidemic.

Investigation of pyridine-bearing thiazolidinone derivatives as promising inhibitors of thymidine phosphorylase and α-glucosidase: Theoretical and computational approaches to develop multitarget drugs

The present study reports the new pyridine-containing analogs bearing thiazolidinone moieties (1–15), which were synthesized and their biological activity was assessed against thymidine phosphorylase and α-glucosidase enzymes. Some of the analogues with the same basic structure but different substituents were discovered to have strong potential against the targeted enzymes, while other analogues were found to have medium to moderate activity in the tested series. These analogues showed a varied range of inhibition in the case of thymidine phosphorylase, 1 (IC50 = 5.70 ± 0.20 µM), 5 (IC50 = 4.50 ± 0.50 µM), 6 (IC50 = 4.60 ± 0.20 µM) and 12 (IC50 = 6.30 ± 0.20 µM), compared with standard 7-Deazaxanthine, 7DX (IC50 = 32.68 ± 1.20 µM). Similarly, excellent inhibitory profiles were also shown by these analogues in the case of alpha-glucosidase inhibition activity, 1 (IC50 =1.80 ± 0.20 µM), 5 (IC50 =1.40 ± 0.10 µM) 6 (IC50 =2.50 ± 0.60 µM) and 12 (IC50 =3.10 ± 0.30 µM) when compared with standard drug acarbose (IC50 = 3.30 ± 1.30 µM). These analogues were also subjected to molecular docking studies against using the PDB id of 1UOU for thymidine phosphorylase (PDB Id: 1UOU) and alpha-glucosidase ((PDB Id: 3w37), for exploration of binding interactions of molecules with active site of the enzymes. ADME studies also predicted the drug-like properties of these analogues.

Singular dielectricnanolaser with atomic-scale field localization.

Compressing the optical field to the atomic scale opens up possibilities for directly observing individual molecules, offering innovative imaging and research tools for both physical and life sciences. However, the diffraction limit imposes a fundamental constraint on how much the optical field can be compressed, based on the achievable photon momentum1,2. In contrast to dielectric structures, plasmonics offer superior field confinement by coupling the light field with the oscillations of free electrons in metals3-6. Nevertheless, plasmonics suffer from inherent ohmic loss, leading to heat generation, increased power consumption and limitations on the coherence time of plasmonic devices7,8. Here we propose and demonstrate singular dielectric nanolasers showing a mode volume that breaks the optical diffraction limit. Derived from Maxwell's equations, we discover that the electric-field singularity sustained in a dielectric bowtie nanoantenna originates from divergence of momentum. The singular dielectric nanolaser is constructed by integrating a dielectric bowtie nanoantenna into the centre of a twisted lattice nanocavity. The synergistic integration surpasses the diffraction limit, enabling the singular dielectricnanolaser to achieve an ultrasmall mode volume of about 0.0005 λ3 (λ, free-space wavelength), along with an exceptionally small feature size at the 1-nanometre scale. To fabricate the required dielectric bowtie nanoantenna with a single-nanometre gap, we develop a two-step process involving etching and atomic deposition. Our research showcases the ability to achieve atomic-scale field localization in laser devices, paving the way for ultra-precise measurements, super-resolution imaging, ultra-efficient computing and communication, and the exploration of light-matter interactions within the realm of extreme optical field localization.

The Creation and Exploration of Human-Computer Interaction in New Media Art Image Representation

The Creation and Exploration of Human-Computer Interaction in New Media Art Image Representation

Exploration of diverse interactions of nonionic poly(vinylpyrrolidone) (PVP) and anionic sodium carboxymethylcellulose (NaCMC) polymers in aqueous imidazolium-based surface active ionic liquid solutions

The binding interactions in complex formation between surface active ionic liquids (SAILs) and polymers (nonionic or anionic) are gaining attention because of their potential applications in novel materials. Therefore, the use of a variety of measurements is required for a better understanding of the interactions involved in polymer/SAIL formation. Here, we have investigated the interactions of nonionic poly(vinylpyrrolidone) (PVP) and anionic sodium carboxymethylcellulose (NaCMC) polymers with SAIL 1-tetradecyl-3-methylimidazolium chloride [C14mim][Cl] in aqueous solution using different measurements such as conductivity, surface tension, fluorescence spectroscopy, dynamic light scattering (DLS) and rheometric measurements. The surface tension, conductivity and fluorescence profiles for SAIL-NaCMC systems provide distinct breakpoints that correspond to four different aggregation states: the concentration at which SAIL monomers begin to attach to the polymer chain (C1), the critical aggregation concentration C2 (cac), the saturation concentration (CS) and the critical micelle concentration (cmc). In the case of SAIL-PVP systems, the surface tension and fluorescence profiles confer three transition states: C2 (cac), CS and cmc and only two transition states have been observed in conductivity curves. The cooperative binding of SAIL to the NaCMC/PVP chain at the solution interface was analyzed by calculating various thermodynamic and interfacial parameters. Strong complexation was observed between NaCMC-SAIL molecules compared to PVP-SAIL systems at the air-solution surface. This is due to the non-ionic character of the PVP chain, which shows weak interactions with SAIL in comparison to NaCMC. Furthermore, DLS and fluorescence measurements were used to investigate the interactions between SAIL and polymers.

Unleashing the power of deep neural networks: An interactive exploration of static and dynamic architectures

Unleashing the power of deep neural networks: An interactive exploration of static and dynamic architectures

Informative design exploration of tower building geometry typology and solar potential using SOM-MLPNN with generalized form-description-based parametric modelling

To synchronize designers early in the design process and help them understand the building forms and performance metrics needed to meet both qualitative and quantitative requirements is crucial for sustainable building designs. While the prevalent design exploration technique, which integrates self-organizing mapping with a Supervised Learning-based Agent Model (SOM-MLPNN), offers insights into design geometry and solar potential, it still has limitations in the range of the design exploration space, the efficiency and accuracy of data approximation, and the uncertainty in dealing with performance metrics related to more complex environmental factors. Using the solar potential of tower buildings as an example, this study proposes a method based on SOM-MLPNN by integrating a Generalized Tower Generator (GTG) and form description, testing its usability for the inclusion of complex surrounding environments, and improving its design exploration breadth as well as the efficiency and accuracy of data approximations. The results demonstrate improved efficiency and accuracy in data approximation across an expansive design space, facilitating visual and interactive exploration of design-performance relationships. The proposed method emphasizes the critical interplay between building geometry and environment-related performance, providing designers with a refined toolkit for discerning the correlation between design and performance, thereby enhancing their design decision-making abilities.

PARTICIPATORY ECOLOGICAL THEOLOGY

John B. Cobb Jr., a well-known theologian, philosopher, and environmentalist in the United States, has developed his participatory ecological theology from process philosophy to process theology. Some scholars believe it belongs to a distorted form of anthropocentrism, while others suggest it belongs to biocentrism. This study seeks to explore how participatory ecological theology from the perspective of John B. Cobb, Jr. based on a participatory ecological approach to the discourse of environmental ethical methods, especially from a theological perspective. However, through Cobb’s attention to and exploration of environmental crises and interactions with other environmentalists, his ecological theology is shown to be a new form of participatory ecological theology that recognizes the intrinsic value of all existence and affirms the participatory ecological order of nature. He challenges the traditional Christian doctrine of “dominion”. He points to a more responsible concept for humanity, that is, to serve all parts of the natural world as responsible creations, just as serving God.

Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs’ signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, ‘Cellchat’ revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

Vitamin D Receptor (VDR) Gene Polymorphisms and High-Turnover Renal Osteodystrophy or Secondary Hyperparathyroidism in End-Stage Renal Disease: A Systematic Review.

Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are often complicated by high-turnover renal osteodystrophy (HTRO) and secondary hyperparathyroidism (SHPT), characterized by disturbances in mineral metabolism and skeletal abnormalities. Genetic variations within the vitamin D receptor (VDR) gene, known as VDR gene polymorphisms, have been implicated in modulating the susceptibility to HTRO and SHPT. This systematic review aims to evaluate the existing literature on the association between VDR gene polymorphisms and the development of these complications in ESRD and hemodialysis patients. A comprehensive literature search across multiple databases was conducted, and studies investigating VDR gene polymorphisms and HTRO or SHPT in ESRD or hemodialysis patients were included. The included studies examined various VDR gene polymorphisms, such as BsmI, ApaI, TaqI, and FokI, and their associations with clinical outcomes like parathyroid hormone (PTH) levels, bone mineral density, and the development of SHPT or HTRO. The findings suggest that certain VDR gene polymorphisms, notably the ApaI "aa"genotype, BsmI "bb"genotype, TaqI "tt"genotype, and FokI variant, may contribute to the pathogenesis of SHPT and HTRO by affecting PTH levels, bone turnover markers, and vitamin D sensitivity. However, the studies had relatively small sample sizes and were conducted in different populations, limiting generalizability. Further larger-scale studies, functional investigations, and exploration of gene-environment interactions are warranted to elucidate the underlying mechanisms and facilitate personalized treatment approaches for CKD and ESRD patients with mineral and bone disorders.

Exploration of evolutionary mechanisms shaping KZFP and retrotransposon interactions

Exploration of evolutionary mechanisms shaping KZFP and retrotransposon interactions

VISAtlas: An Image-Based Exploration and Query System for Large Visualization Collections via Neural Image Embedding.

High-quality visualization collections are beneficial for a variety of applications including visualization reference and data-driven visualization design. The visualization community has created many visualization collections, and developed interactive exploration systems for the collections. However, the systems are mainly based on extrinsic attributes like authors and publication years, whilst neglect intrinsic property (i.e., visual appearance) of visualizations, hindering visual comparison and query of visualization designs. This paper presents VISAtlas, an image-based approach empowered by neural image embedding, to facilitate exploration and query for visualization collections. To improve embedding accuracy, we create a comprehensive collection of synthetic and real-world visualizations, and use it to train a convolutional neural network (CNN) model with a triplet loss for taxonomical classification of visualizations. Next, we design a coordinated multiple view (CMV) system that enables multi-perspective exploration and design retrieval based on visualization embeddings. Specifically, we design a novel embedding overview that leverages contextual layout framework to preserve the context of the embedding vectors with the associated visualization taxonomies, and density plot and sampling techniques to address the overdrawing problem. We demonstrate in three case studies and one user study the effectiveness of VISAtlas in supporting comparative analysis of visualization collections, exploration of composite visualizations, and image-based retrieval of visualization designs. The studies reveal that real-world visualization collections (e.g., Beagle and VIS30K) better accord with the richness and diversity of visualization designs than synthetic collections (e.g., Data2Vis), inspiring composite visualizations are identified in real-world collections, and distinct design patterns exist in visualizations from different sources.