Interactive Exploration Research Articles

Co-pyrolysis of waste paper and tyre: Exploration of interaction of volatiles of varied origin and the influence on product evolution

Waste paper and tyre are typical solid wastes with distinct composition. Their pyrolysis could generate varied volatiles that may interact with each other or with resulting char. In this study, the co-pyrolysis of waste paper and tyre was investigated at 400 and 600 ºC, with the focus on understanding the interaction of the volatiles on evolution of the products. The results show that the interaction of the volatiles at 400 ºC forms more gaseous products like CO and CO2, while the interactions of the heavier organics at 600 ºC forms more oil (49.3% vs 42.6%). The interaction of the volatiles also affects the generation of sulfur-containing organics and diminishes the paper-derived aldehydes and ketones or the heavy organics with the π-conjugated structures in the oil. In addition, the volatile-char interactions exist and form the char of higher carbon content through promoting carbonization and deoxygenation reactions, generating char of higher thermal stability and higher hydrophilicity via tailoring functional group, pore structures and morphologies of the char.

Investigating Electrode-Ionomer Interface Phenomena for Electrochemical Energy Applications.

The endeavor to develop high-performance electrochemical energy applications has underscored the growing importance of comprehending the intricate dynamics within an electrode's structure and their influence on overall performance. This review investigates the complexities of electrode-ionomer interactions, which play a critical role in optimizing electrochemical reactions. Our examination encompasses both microscopic and meso/macro scale functions of ionomers at the electrode-ionomer interface, providing a thorough analysis of how these interactions can either enhance or impede surface reactions. Furthermore, this review explores the broader-scale implications of ionomer distribution within porous electrodes, taking into account factors like ionomer types, electrode ink formulation, and carbon support interactions. We also present and evaluate state-of-the-art techniques for investigating ionomer distribution, including electrochemical methods, imaging, modeling, and analytical techniques. Finally, the performance implications of these phenomena are discussed in the context of energy conversion devices. Through this comprehensive exploration of intricate interactions, this review contributes to the ongoing advancements in the field of energy research, ultimately facilitating the design and development of more efficient and sustainable energy devices.

Pyrazoline Derivatives as Promising MAO-A Targeting Antidepressants: An Update.

Depression is one of the key conditions addressed by the Mental Health Gap Action Programme (mhGAP) of WHO that can lead to self-harm and suicide. Depression is associated with low levels of neurotransmitters, which eventually play a key role in the progression and development of mental illness. The nitrogen-containing heterocyclic compounds exhibit the most prominent pharmacological profile as antidepressants. Pyrazoline, a dihydro derivative of pyrazole, is a well-known five-membered heterocyclic moiety that exhibits a broad spectrum of biological activities. Many researchers have reported pyrazoline scaffold-containing molecules as potential antidepressant agents with selectivity for monoamine oxidase enzyme (MAO) isoforms. Several studies indicated a better affinity of pyrazoline-based moiety as (monoamine oxidase inhibitors) MAOIs. In this review, we have focused on the recent advancements (2019-2023) in the development of pyrazoline-containing derivatives exhibiting promising inhibition of MAO-A enzyme to treat depression. This review provides structural insights on pyrazoline-based molecules along with their SAR analysis, in silico exploration of binding interactions between pyrazoline derivatives and MAO-A enzyme, and clinical trial status of various drug molecules against depression. The in-silico exploration of potent pyrazoline derivatives at the active site of the MAOA enzyme will provide further insights into the development of new potential MAO-A inhibitors for the treatment of depression.

MBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants, and isogenic strain populations.

DNA barcoding has become a powerful tool for assessing the fitness of strains in a variety of studies, including random transposon mutagenesis screens, attenuation of site-directed mutants, and population dynamics of isogenic strain pools. However, the statistical analysis, visualization, and contextualization of the data resulting from such experiments can be complex and require bioinformatic skills. Here, we developed mBARq, a user-friendly tool designed to simplify these steps for diverse experimental setups. The tool is seamlessly integrated with an intuitive web app for interactive data exploration via the STRING and KEGG databases to accelerate scientific discovery. The tool is implemented in Python. The source code is freely available (https://github.com/MicrobiologyETHZ/mbarq) and the web app can be accessed at: https://microbiomics.io/tools/mbarq-app.

The Impact of Chatbot Technology on Enhancing Historical Learning in K-12 Education

This paper discusses the integration of chatbot technology into K-12 education has ushered in a transformative era of historical learning. This innovative approach fosters engagement, personalized guidance, and interactive exploration of historical subjects, revolutionizing the way students absorb and retain historical knowledge. By offering real-time responses to queries, tailoring content to individual learning styles, and simulating immersive historical experiences, chatbots empower educators to create dynamic and inclusive learning environments. The impact of chatbot technology on K-12 historical education is a testament to its potential in nurturing a deeper understanding and appreciation of the past, paving the way for more informed and culturally literate citizens of the future.

Surgical phase and instrument recognition: how to identify appropriate dataset splits

PurposeMachine learning approaches can only be reliably evaluated if training, validation, and test data splits are representative and not affected by the absence of classes. Surgical workflow and instrument recognition are two tasks that are complicated in this manner, because of heavy data imbalances resulting from different length of phases and their potential erratic occurrences. Furthermore, sub-properties like instrument (co-)occurrence are usually not particularly considered when defining the split.MethodsWe present a publicly available data visualization tool that enables interactive exploration of dataset partitions for surgical phase and instrument recognition. The application focuses on the visualization of the occurrence of phases, phase transitions, instruments, and instrument combinations across sets. Particularly, it facilitates assessment of dataset splits, especially regarding identification of sub-optimal dataset splits.ResultsWe performed analysis of the datasets Cholec80, CATARACTS, CaDIS, M2CAI-workflow, and M2CAI-tool using the proposed application. We were able to uncover phase transitions, individual instruments, and combinations of surgical instruments that were not represented in one of the sets. Addressing these issues, we identify possible improvements in the splits using our tool. A user study with ten participants demonstrated that the participants were able to successfully solve a selection of data exploration tasks.ConclusionIn highly unbalanced class distributions, special care should be taken with respect to the selection of an appropriate dataset split because it can greatly influence the assessments of machine learning approaches. Our interactive tool allows for determination of better splits to improve current practices in the field. The live application is available at https://cardio-ai.github.io/endovis-ml/.

Exploring Neophytadiene from Ampelocissus araneosa: A Molecular Docking Approach to Inhibit Biofilm Formation in Staphylococcus aureus

Background: The urgent need to combat antimicrobial resistance and biofilm production has prompted the exploration of alternative remedies, such as plant extracts, as viable substitutes for antibiotics.
 Aim: This study aims to assess the phytocompound from A. araneosa and elucidate its inhibitory mechanisms against biofilm formation by S. aureus through molecular docking techniques.
 Methodology: Plant material collection and extract preparation were conducted, followed by GCMS analysis of A. araneosa and protein modeling of Biofilm_IcaR from S. aureus. Drug 3D prediction and drug docking studies were performed using Neophytadiene and Metronidazole, with the Patch Dock server for the exploration of molecular interactions between the compounds and protein targets.
 Results and Implications: The study identified bioactive compounds from A. araneosa, including neophytadiene, 3-eicosyne, phytol, and stigmasterol, known for their robust antimicrobial properties. Molecular docking studies demonstrated that neophytadiene exhibited a higher binding affinity to the Biofilm_IcaR protein compared to the control drug, Metronidazole, suggesting its efficacy as an inhibitor. These findings provide molecular insights into the potential of neophytadiene as a therapeutic agent against biofilm-producing S. aureus, with implications for the development of novel antimicrobial treatments.

Theoretical exploration of amentoflavone and bilobetin interactions with BPIFB4: implications for longevity and cardioprotection

Theoretical exploration of amentoflavone and bilobetin interactions with BPIFB4: implications for longevity and cardioprotection

The Omics Dashboard for Interactive Exploration of Metabolomics and Multi-Omics Data.

The Omics Dashboard is a software tool for interactive exploration and analysis of metabolomics, transcriptomics, proteomics, and multi-omics datasets. Organized as a hierarchy of cellular systems, the Dashboard at its highest level contains graphical panels for the full range of cellular systems, including biosynthesis, energy metabolism, and response to stimulus. Thus, the Dashboard top level surveys the state of the cell across a broad range of key systems in a single screen. Each Dashboard panel contains a series of X-Y plots depicting the aggregated omics data values relevant to different subsystems of that panel, e.g., subsystems within the biosynthesis panel include amino acid biosynthesis, carbohydrate biosynthesis and cofactor biosynthesis. Users can interactively drill down to focus in on successively lower-level subsystems of interest. In this article, we present for the first time the metabolomics analysis capabilities of the Omics Dashboard, along with significant new extensions to better accommodate metabolomics datasets, enable analysis and visualization of multi-omics datasets, and provide new data-filtering options.

CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs

Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these tools are typically limited to known circRNAs from specific databases. Moreover, these existing tools usually require complex installation procedures which can be time-consuming and challenging for users. There is a lack of a user-friendly web application that facilitates interactive exploration and visualization of circRNA interaction networks. CircNetVis is an interactive online web application to enhance the analysis of human/mouse circRNA interactions. The tool allows three different input formats of circRNAs including circRNA IDs from CircBase, circRNA coordinates (chromosome, start position, end position), and circRNA sequences in the FASTA format. It integrates multiple interaction networks for visualization and investigation of the interplay between circRNA, microRNAs, mRNAs and RNA binding proteins. CircNetVis also enables users to interactively explore the interactions of unknown circRNAs which are not reported from previous databases. The tool can generate interactive plots and allows users to save results as output files for offline usage. CircNetVis is implemented as a web application using R-shiny and freely available for academic use at https://www.meb.ki.se/shiny/truvu/CircNetVis/.

Manipulations of Electronic and Spin States in Co-Quantum Dot/WS2 Heterostructure on a Metal-Dielectric Composite Substrate by Controlling Interfacial Carriers.

Charge and spin are two intrinsic attributes of carriers governing almost all of the physical processes and operation principles in materials. Here, we demonstrate the manipulation of electronic and spin states in designed Co-quantum dot/WS2 (Co-QDs/WS2) heterostructures by employing a metal-dielectric composite substrate and via scanning tunneling microscope. By repeatedly scanning under a unipolar bias, switching the bias polarity, or applying a pulse through nonmagnetic or magnetic tips, the Co-QDs morphologies exhibit a regular and reproducible transformation between bright and dark dots. First-principles calculations reveal that these tunable characters are attributed to the variation of density of states and the transition of magnetic anisotropy energy induced by carrier accumulation. It also suggests that the metal-dielectric composite substrate is successful in creating the interfacial potential for carrier accumulation and realizes the electrically controllable modulations. These results will promote the exploration of electron-matter interactions in quantum systems and provide an innovative way to facilitate the development of spintronics.

The physiological effect of polystyrene nanoplastic particles on fish and human fibroblasts

Numerous studies have identified the detrimental effects for the biosphere of large plastic debris, the effect of microplastics (MPs) and nanoplastics (NPs) is less clear. The skin is the first point of contact with NPs, and skin fibroblasts have a vital role in maintaining skin structure and function. Here, a comparative approach is taken using three fibroblast cell lines from the zebrafish (SJD.1), human male newborn (BJ-5ta) and female adult (HDF/TERT164) and their response to polystyrene NP (PS-NPs) exposure is characterized. Cells were exposed to environmentally relevant PS-NP sizes (50, 500 and 1000 nm) and concentrations (0.001 to 10 μg/ml) and their uptake (1000 nm), and effect on cell viability, proliferation, migration, reactive oxygen species (ROS) production, apoptosis, alkaline phosphatase (ALP) and acid phosphatase (AP) determined. All fibroblasts took up PS-NPs, and a relationship between PS-NP particle size and concentration and the inhibition of proliferation and cell migration was identified. The inhibitory effect of PS-NPs on proliferation was more pronounced for human skin fibroblasts. The presence of PS-NPs negatively affected fibroblast migration in a time-, size- and concentration-dependent manner with larger PS-NPs at higher concentrations causing a more significant inhibition of cell migration, with human fibroblasts being the most affected. No major changes were detected in ROS production or apoptosis in NP challenged fibroblasts. While the ALP activity was increased in all fibroblast cell lines, only fish fibroblasts showed a significant increase in AP activity. The heterogeneous response of fibroblasts induced by PS-NPs was clearly revealed by the segregation of HDF, BJ.5ta and SJD.1 fibroblasts in principal component analysis. Our results demonstrate that PS-NP exposure adversely affected cellular processes in a cell-type and dose-specific manner in distinct fibroblast cell lines, emphasizing the need for further exploration of NP interactions with different cell types to better understand potential implications for human health.

Web-based visualization and rendering of aerial LiDAR point cloud for urban flood simulation

Purpose In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management. Design/methodology/approach This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed. Findings The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making. Originality/value The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

Impulse dynamics and augmented reality for real-time interactive digital twin exploration and interrogation

Impulse dynamics and augmented reality for real-time interactive digital twin exploration and interrogation

Unraveling the developmental dynamic of visual exploration of social interactions in autism.

Atypical deployment of social gaze is present early on in toddlers with autism spectrum disorders (ASDs). Yet, studies characterizing the developmental dynamic behind it are scarce. Here, we used a data-driven method to delineate the developmental change in visual exploration of social interaction over childhood years in autism. Longitudinal eye-tracking data were acquired as children with ASD and their typically developing (TD) peers freely explored a short cartoon movie. We found divergent moment-to-moment gaze patterns in children with ASD compared to their TD peers. This divergence was particularly evident in sequences that displayed social interactions between characters and even more so in children with lower developmental and functional levels. The basic visual properties of the animated scene did not account for the enhanced divergence. Over childhood years, these differences dramatically increased to become more idiosyncratic. These findings suggest that social attention should be targeted early in clinical treatments.

VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations

Word vector embeddings have been shown to contain and amplify biases in the data they are extracted from. Consequently, many techniques have been proposed to identify, mitigate, and attenuate these biases in word representations. In this article, we utilize interactive visualization to increase the interpretability and accessibility of a collection of state-of-the-art debiasing techniques. To aid this, we present the Visualization of Embedding Representations for deBiasing (VERB) system, an open-source web-based visualization tool that helps users gain a technical understanding and visual intuition of the inner workings of debiasing techniques, with a focus on their geometric properties. In particular, VERB offers easy-to-follow examples that explore the effects of these debiasing techniques on the geometry of high-dimensional word vectors. To help understand how various debiasing techniques change the underlying geometry, VERB decomposes each technique into interpretable sequences of primitive transformations and highlights their effect on the word vectors using dimensionality reduction and interactive visual exploration. VERB is designed to target natural language processing (NLP) practitioners who are designing decision-making systems on top of word embeddings and researchers working with the fairness and ethics of machine learning systems in NLP. It can also serve as a visual medium for education, which helps an NLP novice understand and mitigate biases in word embeddings.

Preclinical exploration of the DNA damage response pathway using the interactive neuroblastoma cell line explorer CLEAN.

Neuroblastoma (NB) is the most common cancer in infancy with an urgent need for more efficient targeted therapies. The development of novel (combinatorial) treatment strategies relies on extensive explorations of signaling perturbations in neuroblastoma cell lines, using RNA-Seq or other high throughput technologies (e.g. phosphoproteomics). This typically requires dedicated bioinformatics support, which is not always available. Additionally, while data from published studies are highly valuable and raw data (e.g. fastq files) are nowadays released in public repositories, data processing is time-consuming and again difficult without bioinformatics support. To facilitate NB research, more user-friendly and immediately accessible platforms are needed to explore newly generated as well as existing high throughput data. To make this possible, we developed an interactive data centralization and visualization web application, called CLEAN (the Cell Line Explorer web Application of Neuroblastoma data; https://ccgg.ugent.be/shiny/clean/). By focusing on the regulation of the DNA damage response, a therapeutic target of major interest in neuroblastoma, we demonstrate how CLEAN can be used to gain novel mechanistic insights and identify putative drug targets in neuroblastoma.

Cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data

BackgroundHighly multiplexed imaging enables single-cell-resolved detection of numerous biological molecules in their spatial tissue context. Interactive visualization of multiplexed imaging data is crucial at any step of data analysis to facilitate quality control and the spatial exploration of single cell features. However, tools for interactive visualization of multiplexed imaging data are not available in the statistical programming language R.ResultsHere, we describe cytoviewer, an R/Bioconductor package for interactive visualization and exploration of multi-channel images and segmentation masks. The cytoviewer package supports flexible generation of image composites, allows side-by-side visualization of single channels, and facilitates the spatial visualization of single-cell data in the form of segmentation masks. As such, cytoviewer improves image and segmentation quality control, the visualization of cell phenotyping results and qualitative validation of hypothesis at any step of data analysis. The package operates on standard data classes of the Bioconductor project and therefore integrates with an extensive framework for single-cell and image analysis. The graphical user interface allows intuitive navigation and little coding experience is required to use the package. We showcase the functionality and biological application of cytoviewer by analysis of an imaging mass cytometry dataset acquired from cancer samples.ConclusionsThe cytoviewer package offers a rich set of features for highly multiplexed imaging data visualization in R that seamlessly integrates with the workflow for image and single-cell data analysis.It can be installed from Bioconductor via https://www.bioconductor.org/packages/release/bioc/html/cytoviewer.html. The development version and further instructions can be found on GitHub at https://github.com/BodenmillerGroup/cytoviewer.

TooManyCellsInteractive: A visualization tool for dynamic exploration of single-cell data.

As single-cell sequencing technologies continue to advance, the growing volume and complexity of the ensuing data present new analytical challenges. Large cellular populations from single-cell atlases are more difficult to visualize and require extensive processing to identify biologically relevant subpopulations. Managing these workflows is also laborious for technical users and unintuitive for nontechnical users. We present TooManyCellsInteractive (TMCI), a browser-based JavaScript application for interactive exploration of cell populations. TMCI provides an intuitive interface to visualize and manipulate a radial tree representation of hierarchical cell subpopulations and allows users to easily overlay, filter, and compare biological features at multiple resolutions. Here we describe the software architecture and demonstrate how we used TMCI in a pan-cancer analysis to identify unique survival pathways among drug-tolerant persister cells. TMCI will facilitate exploration and visualization of large-scale sequencing data in a user-friendly way. TMCI is freely available at https://github.com/schwartzlab-methods/too-many-cells-interactive. An example tree from data within this article is available at https://tmci.schwartzlab.ca/.

The View of English Learning Activities and Deep Reading: An Exploration of Interaction and Integration

The View of English Learning Activities and Deep Reading: An Exploration of Interaction and Integration