Community Platform Research Articles

Towards an open and integrated cyberinfrastructure for river morphology research in the big data era

The objective of this paper is to present the initial illustration of a cyberinfrastructure named the RIver MORPHology Information System (RIMORPHIS) that addresses the current limitations related to river morphology data and tools. RIMORPHIS is supported by a data model for storing river morphology data. A new specification for data and semantics on river morphology datasets has been developed to support the web-based platform for discovering and visualization of river morphology data. Several geoprocessing tools are developed that enable scientific analysis and practical studies, including the coordinate transformation, cross-section generation and bathymetry mesh generation. Our vision for RIMORPHIS is to create a self-sustained community platform with tools to support scientific discoveries on river morphology and to enable multidisciplinary research for riverine environments. To accomplish this vision, we created a community to gather input and build partnerships. The RIMORPHIS cyberinfrastructure addresses the community needs related to data access, processing and visualization. The current implementation of RIMORPHIS is scalable for new data and tools.

Chemical Physics Reviews as a platform for the chemical physics community: The first four years

<i>Chemical Physics Reviews</i> as a platform for the chemical physics community: The first four years

Uncovering How Information Quality Shapes Diverse User Engagement on Content Community Platforms: Harnessing Deep Learning for Feature Extraction

Uncovering How Information Quality Shapes Diverse User Engagement on Content Community Platforms: Harnessing Deep Learning for Feature Extraction

Сеульський та Європейський консенсуси з питань розвитку: чи можлива спільна платформа по Україні?

In the context of the tasks of the post-war recovery of Ukraine’s economy and social sphere, a comparative analysis has been carried out of the conceptual foundations of international development assistance provided by the G20 countries, in particular the newly industrialized countries, within the framework of the Seoul Consensus on Development, announced at the G-20 Seoul Summit (2010), and the European Union and its member states within the framework of the new European Consensus on Development (2017). It is shown that the former focuses on growth primarily through investment in infrastructure and solving long-term structural problems of development, and the latter on increasing well-being and fighting poverty. The Seoul Consensus, despite the participation of Western donors, including the EU, in its formulation, largely reflects the principles and messages of newly emerging donors representing the leading new industrial states. The Seoul Consensus is currently a unique strategic compromise on international development aid not only between the West represented by its leading world powers and the European Union, on the one hand, and the largest new industrial states of the modern world - on the other, but also between the Beijing Consensus and the Mumbai Consensus - alternative strategies of socio-economic modernization and sustainable economic growth put forward by China and India, respectively, in their active competition for leadership among the countries of the Global South. The change in the geopolitical and geo-economic landscape has forced the EU to review the criteria for the distribution and prioritization of development aid in order to be able to compete and cooperate with new donors such as China, South Korea, Saudi Arabia, Turkey, etc. The new European consensus emphasizes the instrumentalization and securitization of development, with less attention to democracy and human rights. This shift objectively narrows the gap between traditional and new donors of international development assistance. The author substantiates the prospect of further analysis of the convergent potential of the above-mentioned consensuses in the direction of developing based on the unique geopolitical and geo-economic positioning of Ukraine in the modern world, the "Kyiv Consensus on Development" as a joint conceptual, strategic and political platform of the international donor community for the post-war reconstruction of Ukraine.

Managing Anxiety and Uncertainty Through Social Networking Sites, How Effectively Can Youth Communicate Online?

This study examines the usage patterns of social networking sites among Malaysian youths and their Anxiety/Uncertainty Management levels. According to the anxiety and uncertainty management theory, members of a group should be cooperative, trustworthy, tolerant of diversity, and happy in order to affect their membership attitude and behavior. These days, youth choose to spend their time on social networking sites since they provide an effective virtual community platform for communication. Malaysian youths exhibit a nuanced understanding of personal and social identity, motivation to interact, reactions to others, social categorizations, situational processes, connection to others, ethical interactions, and overall communication effectiveness. This study surveyed 600 respondents, the findings highlight a deep-rooted integration of digital communication into the daily lives of Malaysian youths, with a significant majority having extensive experience of 11 to 20 years on SNS platforms. SNS platforms significantly reduced communication uncertainty, fostering positive relationships and smoother communication through active, passive, and interactive strategies. Locality plays a crucial role in anxiety and uncertainty management, with rural youths demonstrating better management compared to their urban counterparts, attributed to stronger social cohesion, tighter networks, and communal lifestyles. The study suggests that addressing anxiety and uncertainty can improve communication quality in virtual settings, particularly in rural areas. Social media can promote cultural integration and acceptance among diverse groups. A balanced approach to communication, emphasizing ethical interactions, can maximize its benefits. The findings can be used to design targeted interventions and promote positive digital engagement practices among Malaysian youths. Keywords: Virtual community, social networking sites, anxiety and uncertainty management, effective communication, digital communication.

River morphology information system: A web cyberinfrastructure for advancing river morphology research

The study of river systems is challenged by the complexity and volume of data required to understand and predict river morphology changes. The River Morphology Information System (RIMORPHIS) addresses these challenges with an open-access web-based cyberinfrastructure for advanced river morphology research. Built on the National Hydrography Dataset Plus High Resolution, RIMORPHIS integrates publicly available bathymetry data and third-party resources into a cohesive database architecture for real-time use and analysis. The platform, structured around a PostgreSQL database with PostGIS extension, offers tools for geospatial visualization using Deck.GL, data analytics with Python-based geospatial processing, and eHydro Cross Section Surveys integration via API. By providing on-demand access to relevant datasets and tools for data analytics and geospatial visualization, RIMORPHIS enhances data accessibility and interoperability, supporting informed decision-making in river basin management. This paper presents the development and functionalities of RIMORPHIS and its contributions to hydrological information systems as a self-sustained community platform.

Public Libraries May Facilitate More Inclusive Programming with the Collaboration of Trained Partners for Patrons with Dementia

A Review of: Dai, J., Bartlett, J. C., &amp; Moffatt, K. (2023). Library services enriching community engagement for dementia care: The Tales &amp; Travels Program at a Canadian Public Library as a case study. Journal of Librarianship and Information Science, 55(1), 123–136. https://doi.org/10.1177/09610006211065170 Objective – To explore the potential of public libraries to contribute to community-based dementia care, and to examine the lived experiences of users partaking in the program. Design – Case study. Setting – A public library in Montreal, Canada. Subjects – Public library patrons with dementia and their caregivers engaging in Tales &amp; Travels, a program for participants with early- and middle-stage dementia who learn about a new country through multi-sensory experiences. Methods – Semi-structured dyadic interviews with eleven people with dementia and their caregivers, as well as interviews with four program facilitators. Researchers implemented unobtrusive participant observation and thematically analyzed results. Main Results – Researchers discovered two primary themes via thematic analysis of interview transcripts: “community platform” and “librarians’ roles” came out of the data most often when discussing the program. Participants and caregivers felt a sense of familiarity and normalcy in a public library and appreciated the de-emphasis on dementia as the focus of the programming. Librarians felt the partnership with the Alzheimer Society allowed them to push past their uncertainties in their capacity to provide quality programming for this user group and found that collaborative relationship integral to the program’s success. Conclusion – With an intentional setting, collaborative partners with expertise in this user group, and person-centered programming, libraries can be a welcoming location to offer engaging and inclusive programs for patrons with dementia. However, these elements are of a high priority given the vulnerability of the population, and librarians who are willing to be trained in inclusivity, safety, and hospitality should handle programming. Replication of this study in other libraries would strengthen the conclusion of the case study.

Mobile health applications for individuals with psoriatic arthritis

Abstract Objectives Mobile health applications (apps) hold promise as tools for symptom tracking and management of chronic rheumatic diseases such as PsA. Apps for PsA have not been systematically evaluated. We conducted a comprehensive review of apps designed for patients with PsA. Methods The iOS and Android app stores were searched using the term ‘arthritis’ and individual app descriptions were reviewed for ‘psoriatic arthritis’. Apps were downloaded and rated using the Mobile Application Rating Scale (MARS). Additionally, the apps were evaluated to determine functionality, use of symptom scales and potential for integration within clinical care. Results The search was conducted in spring 2024 and 130 apps were found that mentioned ‘arthritis’. Seven had specific mentions of PsA in their description. We found several other relevant apps by following recommendations in the app stores. In total, 10 apps for patients with PsA were identified. MARS scores suggest they were moderate to excellent in quality. The functionality of the 10 apps differed: 7 allowed for symptom tracking, 3 allowed for data export to health records, 2 allowed for medication tracking and 1 contained a patient community platform. The symptom tracking capabilities varied widely and we could find only one published study of any of the apps. Conclusions We analysed apps for PsA to identify potential unmet needs and found that there are few publicly available apps, their functionality varies tremendously and testing of these apps is almost non-existent. There appears to be room for improvement of apps for PsA.

Research on image segmentation processing of coal particle flocs combined with clarity detection

ABSTRACT In the image analysis of the hydrophobic flocculation process of coal particles, the recognition accuracy of floc characteristic parameters is affected by bubbles, floc superposition, and floc morphology. An image processing method was studied and designed based on the PyCharm Community platform for clarity recognition and floc segmentation of coal particle floc characteristics. Firstly, the critical value of image clarity was determined to be 1.31 by using the Laplace convolution accounting method after the average gray level correction, and the fuzzy flocs whose clarity was less than the critical value were eliminated. Then, by comparing the segmentation effect of the threshold, edge, and region segmentation algorithm on the flocs, the histogram bimodal method was determined to be the best image processing segmentation method for fine coal floc collection. The fractal theory was used to verify the effect of image processing. The results showed that the surface fractal dimension of the floc image after deblurring and segmentation was maintained near 2.05, indicating that the processed image can obtain more stable and reliable floc characteristic parameters.

Strategi Pengelolaan Konten pada Akun Instagram @syca.official dalam Membangun Customer Engagement

Instagram plays a very strong role, especially in the era of digital marketing. There are many features that support the growth of a brand in an industry, particularly in the beauty industry. Beauty industry has a very ripid development, especially with the emergence of various new products that are increasingly tailored to Indonesian consumers. The rapid development of trends and cosmetic products makes digital marketing era increasingly popular. Moreover, currently social media, especially Instagram has supported influential trends in digital marketing. @syca.official has become one of the local cosmetic brands that has grown significantly and plays special role in this Indonesian beauty industry. Not only does @syca.official market products through digital campaigns, but it also serves as a community platform for women and beauty enthusiasts to share information, reviews, and support each other through their created content. Among the many local cosmetic brands that continue to grow, @syca.official stands out with its unique content concept and campaigns, thereby enhancing customer engagement. In executing this strategy, @syca.official employs several methods, starting from sharing more relevant content, optimizing content quality according to the target audience and current trends, structuring content flow based on consumer interests, and fostering a connection between the brand and its consumers.

Optimization and Innovation of the Operation Model of Mobile Social E-commerce under AI Empowerment: Taking the Female Community Platform “Little Red Book” as an Example

This article takes the female community platform “Little Red Book” as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence (AI) empowerment. Firstly, the relevant concepts were defined, and then the unique attributes of mobile community e-commerce were analyzed. As a typical representative of mobile community e-commerce, Little Red Book introduces the background and characteristics of its platform, analyzes its mobile community operation mode, and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology, to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.

Pricing strategy and its impact on the effort of community leader and platform: Uniform or differentiated pricing?

This paper is motivated by the rapid development of community group buying (CGB), where the CGB platform dramatically relies on the community leader to provide last-mile services and fulfill consumers’ orders. Considering two types of community leaders, the friend role and seller role, this work adopts a game-theoretical model and investigates how the pricing strategy, uniform pricing strategy (N) or differentiated pricing strategy (Y), affects players’ performance and decisions on effort level. This study shows that the commission rate is an essential factor in stimulating the role transformation of community leaders. A significantly large commission rate results in the friend role community leader with lower trust value changing into the seller role. Generally, the community leader works harder under the uniform pricing scenario except in situations with a significant commission rate and moderate sensitivity coefficient of trust value. However, the effort level of the platform is jointly influenced by the pricing strategy, commission rate, and the role of a community leader. Moreover, regardless of the commission rate, when the community leader is a friend role and the trust value is high, both the platform and community leader can gain higher profits under the uniform pricing scenario than the differentiated pricing case. It indicates that a win–win situation can be achieved.

The Stochastic Evolution Game of Knowledge-Sharing Incentive in Virtual Communities under Intelligent Recommendation Systems

To effectively solve the issue of unsmooth knowledge sharing in virtual communities under intelligent recommendation systems, we analyzed the impact of key factors on the strategy selection and evolution path in different scenarios.Based on the principles of bounded rationality and benefit maximization, we consider the principles of evolutionary game theory and the influence of random interference. A random evolutionary game model is constructed to analyze strategy selection in the process of knowledge sharing incentives between virtual community platforms and users. We obtained the evolutionary equilibrium strategies under different parameter restrictions and analyzed the evolutionary stability of the dynamic game process of knowledge sharing incentives.The research shows that interference from random factors affects both the speed and the trend of strategy evolution in virtual community platforms and users. In order to improve the enthusiasm of users to share, virtual community need to increase the proportion of users with positive feedback, improve the recommendation incentive mechanism, and reduce the user loss coefficient. Based on the above research conclusions, some countermeasures and suggestions for improving the performance of virtual community knowledge sharing under intelligent recommendation systems are proposed, which provides theoretical guidance for knowledge sharing among virtual community members.

Review of Influencing Factors of Patients' Medical Choice Behavior in Online Health Community

The development of information technology has made online medical communities a new avenue for addressing medical resource shortages. However, the complexity of information and the asymmetry between physicians and patients makes patients confused when they consult in online health community (OHC). This study systematically analyzed and summarized relevant theories and factors influencing patients' medical choice behavior through literature review. The objective is to offer guidance for patients' decisions in selecting physicians and to support the sustainable development of online medical community platforms, as well as to provide practical insights for further exploration in this field. Objective: This review examines recent theories and factors influencing patients' medical choice behavior in online health community (OHC), aiming to offer insights for patient choice regarding physician selection and the sustainable development of online medical platforms. Methods: A literature analysis was conducted to summarize studies on patients' medical choice behavior in OHC, identifying relevant theories and influencing factors. Results: The analysis identified seven key theories in the study of patients' medical choice behavior: signal theory, trust theory, social capital theory, social exchange theory, the stimulus-organism-response (SOR) model, the elaboration likelihood model (ELM), and the opportunity-motivation-ability (OMA) framework. Factors such as physicians' professional capital, online effort, service quality, online reputation, patient preferences and disease heterogeneity significantly influence patients' medical choice behavior. Conclusion: There is a trend toward integrating multiple theories in understanding patients' medical choice behavior in OHC; however, interdisciplinary research remains limited. Most studies focus on patients’ medical choice behavior from the physicians' perspective, while research from the patients' viewpoint is lacking. This study suggests two future research directions: enhancing the integration of multidisciplinary theories and expanding the scope of research subjects.

Enhancing taxonomy-based extraction: Leveraging information from online community platforms for digital skills demand identification in job ads

The rapid technological changes have revolutionised how we function, including how we search for work and what skills we need to be equipped with to perform the tasks at the workplace. As employers more often recruit using online job advertisements, their content becomes a natural source of information for analytical purposes on the skills demanded in the labour market, especially for analysing emerging skills like digital. There are still some challenges with the extraction of information from online content. However, the extraction improvements go hand in hand with new technological developments like natural language processing techniques. This article presents the experimental method of updating the classification of digital skills to keep it up to date for information extraction applied to online job advertisements. The evaluation proved this method successfully identified terms related to programming skills but failed to identify terms associated with artificial intelligence sufficiently. The latter is related to the fact that the AI field is among the fastest developing areas of technology advancement, and new terms (e.g. Chatgpt) always appear.

Transition from Paediatric to Adult Diabetes Care in People with Type1 Diabetes: An Online Survey from France.

The transition from paediatric to adult diabetes care (TPA) of children/adolescents with type1 diabetes (T1D) represents a unique challenge and remains a critical phase in the T1D care pathway. This study aims to describe and understand the experience of the transition process from a participant's perspective in young adults who are living in France with T1D and to measure their satisfaction. An online questionnaire was presented to people with T1D in France on a global online participant community platform. The questionnaire was developed by a scientific committee including paediatric and adult diabetologists and refined by a group of participants. Thematic qualitative analysis was performed on the responses. A total of 104 respondents were included in the survey (mean age 24.4years [95%CI 23.8-25.0]; 61.5% female). The mean age at the time of transition was 18.4years (95%CI 17.8-18.9), and 56% of respondents had their first adult diabetology follow-up in the same institution. During TPA, of the 76 participants who experienced personal issues, 74% experienced at least one issue with their diabetes management in the months following the transition. In the following months, 61% experienced new or unexpected problems in monitoring their diabetes after transition and 44% reported unusual glycaemic imbalances, including hypoglycaemia (8%) and hyperglycaemia (9%) requiring hospitalisation. Presence of personal issues during TPA was significantly associated with occurrence of problems with diabetes management or glycaemic imbalance. Three factors identified for a successful transition were (i) early meeting with the 'adult' diabetes care team, (ii) letting the participants choose the right age to leave paediatric clinic and (iii) having good diabetes control at the beginning of the TPA process. Most young adults with T1D report experiencing issues around TPA with significant consequences on their disease management. Hence, it is necessary to identify these issues to better support them and improve diabetes management during this phase.

An Online Nanoinformatics Platform Empowering Computational Modeling of Nanomaterials by Nanostructure Annotations and Machine Learning Toolkits.

Modern nanotechnology has generated numerous datasets from in vitro and in vivo studies on nanomaterials, with some available on nanoinformatics portals. However, these existing databases lack the digital data and tools suitable for machine learning studies. Here, we report a nanoinformatics platform that accurately annotates nanostructures into machine-readable data files and provides modeling toolkits. This platform, accessible to the public at https://vinas-toolbox.com/, has annotated nanostructures of 14 material types. The associated nanodescriptor data and assay test results are appropriate for modeling purposes. The modeling toolkits enable data standardization, data visualization, and machine learning model development to predict properties and bioactivities of new nanomaterials. Moreover, a library of virtual nanostructures with their predicted properties and bioactivities is available, directing the synthesis of new nanomaterials. This platform provides a data-driven computational modeling platform for the nanoscience community, significantly aiding in the development of safe and effective nanomaterials.

Navigating the human-monkeypox virus interactome: HuPoxNET atlas reveals functional insights.

Monkeypox virus, a close relative of variola virus, has significantly increased the incidence of monkeypox disease in humans, with several clinical symptoms. The sporadic spread of the disease outbreaks has resulted in the need for a comprehensive understanding of the molecular mechanisms underlying disease infection and potential therapeutic targets. Protein-protein interactions play a crucial role in various cellular processes and regulate different immune signals during virus infection. Computational algorithms have gained high significance in the prediction of potential protein interaction pairs. Here, we developed a comprehensive database called HuPoxNET (https://kaabil.net/hupoxnet/) using the state-of-the-art MERN stack technology. The database leverages two sequence-based computational models to predict strain-specific protein-protein interactions between human and monkeypox virus proteins. Furthermore, various protein annotations of the human and viral proteins such as gene ontology, KEGG pathways, subcellular localization, protein domains, and novel drug targets identified from our study are also available on the database. HuPoxNET is a user-friendly platform for the scientific community to gain more insights into the monkeypox disease infection and aid in the development of therapeutic drugs against the disease.

Design of knowledge transaction protection mechanism in the open innovation community based on blockchain technology

Open innovation communities (OICs) are important for the development of modern enterprises. However, there are still many safety hazards and trust crises on community platforms. This paper proposes an approach that combines blockchain technology and an OIC, as blockchain technology provides a direction for solving trust and security problems in community platform transactions. Moreover, the design of smart contracts can ensure the implementation of transactions and improve their reliability. In this study, the participants in an OIC and three types of infringement problems were analyzed. The Byzantine Fault Tolerant (BFT) algorithm was applied to design the logic of smart contracts and the coupling between idea platforms and the blockchain. The protection mechanism of an OIC was established based on blockchain smart contract supervision to provide a better knowledge co-creation environment for OICs.

Open Innovations in Co-Creation Community Platform: Bonding, Crowding and Complementor’ s Engagement

Open Innovations in Co-Creation Community Platform: Bonding, Crowding and Complementor’ s Engagement