Analytical Framework Research Articles

Risk of bias in cross-sectional studies: Protocol for a scoping review of concepts and tools

Cross-sectional studies are commonly used to study human health and disease, but are especially susceptible to bias. This scoping review aims to identify and describe available tools to assess the risk of bias (RoB) in cross-sectional studies and to compile the key bias concepts relevant to cross-sectional studies into an item bank. Using the JBI scoping review methodology, the strategy to locate relevant RoB concepts and tools is a combination of database searches, prospective review of PROSPERO registry records; and consultation with knowledge users and content experts. English language records will be included if they describe tools, checklists, or instruments which describe or permit assessment of RoB for cross-sectional studies. Systematic reviews will be included if they consider eligible RoB tools or use RoB tools for RoB of cross-sectional studies. All records will be independently screened, selected, and extracted by one researcher and checked by a second. An analytic framework will be used to structure the extraction of data. Results for the scoping review are pending. Results from this scoping review will be used to inform future selection of RoB tools and to consider whether development of a new RoB tool for cross-sectional studies is needed.

The social media sentiment analysis framework: deep learning for sentiment analysis on social media

Researching public opinion can help us learn important facts. People may quickly and easily express their thoughts and feelings on any subject using social media, which creates a deluge of unorganized data. Sentiment analysis on social media platforms like Twitter and Facebook has developed into a potent tool for gathering insights into users' perspectives. However, difficulties in interpreting natural language limit the effectiveness and precision of sentiment analysis. This research focuses on developing a social media sentiment analysis (SMSA) framework, incorporating a custom-built emotion thesaurus to enhance the precision of sentiment analysis. It delves into the efficacy of various deep learning algorithms, under different parameter calibrations, for sentiment extraction from social media. The study distinguishes itself by its unique approach towards sentiment dictionary creation and its application to deep learning models. It contributes new insights into sentiment analysis, particularly in social media contexts, showcasing notable advancements over previous methodologies. The results demonstrate improved accuracy and deeper understanding of social media sentiment, opening avenues for future research and applications in diverse fields.

A framework for multivariate analysis of compound extremes based on correlated hydrologic time series

While hydrologic design has primarily relied on use of annual maxima values, many events of hydrologic interest such as active and break spells in monsoonal rains, heat waves, flash flooding from snowmelt, etc. manifest at time scales of days to weeks, and require daily (or finer resolution) data for proper characterization. Often combinations of several hydrologic variables herald highly impactful events and are labelled as compound extremes. Using a time-varying interval-censored estimation method of copula models, a novel multivariate approach for dealing with compound extremes under temporal dependence amongst variables and when data contain significant ties is developed here to enable the determination of design magnitudes and associated risk. The efficacy of this method is demonstrated over the Godavari River Basin, India, using daily precipitation and temperature data from a recent period (1977 to 2020) during the monsoon season. A conservative approach is proposed for estimating the design magnitudes of hydrologic variables in multivariate settings. The significance of ties and temporal dependence amongst precipitation and temperature data in estimation of design magnitudes of cold-wet compound extremes at specified probabilities of exceedance is explored at various spatial scales. Ties and temporal dependence are both shown to have a profound influence on design estimates. Since ties and temporal variation in dependence amongst hydrologic variables are ubiquitous features of most hydrologic data, this framework would be applicable for characterization of other compound extremes in hydrology.

A MMEM-BN–Based Analyzing Framework for Causal Analysis of Ship Collisions

A MMEM-BN–Based Analyzing Framework for Causal Analysis of Ship Collisions

ChimericFragments: computation, analysisand visualization of global RNA networks.

RNA-RNA interactions are a key feature of post-transcriptional gene regulation in all domains of life. While ever more experimental protocols are being developed to study RNA duplex formation on a genome-wide scale, computational methods for the analysis and interpretation of the underlying data are lagging behind. Here, we present ChimericFragments, an analysis framework for RNA-seq experiments that produce chimeric RNA molecules. ChimericFragments implements a novel statistical method based on the complementarity of the base-pairing RNAs around their ligation site and provides an interactive graph-based visualization for data exploration and interpretation. ChimericFragments detects true RNA-RNA interactions with high precision and is compatible with several widely used experimental procedures such as RIL-seq, LIGR-seqor CLASH. We further demonstrate that ChimericFragments enables the systematic detection of novel RNA regulators and RNA-target pairs with crucial roles in microbial physiology and virulence. ChimericFragments is written in Julia and available at: https://github.com/maltesie/ChimericFragments.

EEG motor imagery decoding: a framework for comparative analysis with channel attention mechanisms

Objective. The objective of this study is to investigate the application of various channel attention mechanisms within the domain of brain-computer interface (BCI) for motor imagery decoding. Channel attention mechanisms can be seen as a powerful evolution of spatial filters traditionally used for motor imagery decoding. This study systematically compares such mechanisms by integrating them into a lightweight architecture framework to evaluate their impact. Approach. We carefully construct a straightforward and lightweight baseline architecture designed to seamlessly integrate different channel attention mechanisms. This approach is contrary to previous works which only investigate one attention mechanism and usually build a very complex, sometimes nested architecture. Our framework allows us to evaluate and compare the impact of different attention mechanisms under the same circumstances. The easy integration of different channel attention mechanisms as well as the low computational complexity enables us to conduct a wide range of experiments on four datasets to thoroughly assess the effectiveness of the baseline model and the attention mechanisms. Results. Our experiments demonstrate the strength and generalizability of our architecture framework as well as how channel attention mechanisms can improve the performance while maintaining the small memory footprint and low computational complexity of our baseline architecture. Significance. Our architecture emphasizes simplicity, offering easy integration of channel attention mechanisms, while maintaining a high degree of generalizability across datasets, making it a versatile and efficient solution for electroencephalogram motor imagery decoding within BCIs.

Information transfer pathways: signal propagation in complex global topologies

Abstract In the real world, many dynamic behaviors can be explained by the propagation of perturbations, such as the transfer of chemical signals and the spread of infectious diseases. Previous researchers have achieved excellent results in approximating the global propagation time, revealing the mechanism of signal propagation through multiple paths. However, the known frameworks rely on the extension of physical concepts rather than mathematically rigorous derivations. As a result, they may not perfectly predict time or explain the underlying physical significance in certain specific cases. In this paper, we propose a novel method for decomposing network topology, focusing on two modules: the tree-like module and the path-module. Subsequently, we introduce a new framework for signal propagation analysis, which can be applied to estimate the propagation time for two fundamental global topology modules and provide a rigorous proof for the propagation time in global topology. Compared to previous work, our results are not only more concise, clearly defined, efficient, but also are more powerful in predicting propagation time which outperforms some known results in some cases, for example, biochemical dynamics. Additionally, the proposed framework is based on information transfer pathways, which can be also applied to other physical fields, such as network stability, network controlling and network resilience.

L1 Education in Times of Globalization, Digitalization and Super-Diversity

This introduction first briefly sketches the (history of the) International Mother Tongue Education Network (IMEN). IMEN was founded in 1981 as an information and research network that over the years initiated an empirical-interpretive research program focusing on comparative analyses of the rhetoric and practices of L1 education across a dozen of European countries. Main elements of IMEN’s methodology that will be discussed below were the development of different types of research collaboration, a theoretical framework for comparative analysis, and a method for international triangulation. It then describes how, at the turn of the century, IMEN’s way of doing slow science became increasingly threatened by the requirements of publish or perish mainstream research, and how its research program was confronted with the challenges posed to L1 education by processes of globalization, digitalization, and super-diversity, becoming manifest in the superdiverse nature of student bodies, their sociolinguistic and ethnocultural doings, and the increasingly digitalized modes of teaching and learning they are exposed to. All these elements, in one way or another, also have an impact on the teaching-learning practices in mainstream L1 education and consequently must be addressed by IMEN-like studies. Finally this contribution briefly introduces the contributions to this special issue and suggests that they are a strong argument for a renewed interest in international comparative discussion on and around L1 education and a plea to further collaborative research from an empirical interpretive ethnographic perspective on teachers’ professional practical knowledge and classroom practices that can guide our understanding of the ubiquitous school subject L1 education that aims at preparing students for a global, digital, and super-diverse society.

Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomics.

Chronic Kidney Disease (CKD) and Metabolic dysfunction-associated steatohepatitis (MASH) are metabolic fibroinflammatory diseases. Combining single-cell (scRNAseq) and spatial transcriptomics (ST) could give unprecedented molecular disease understanding at single-cell resolution. A more comprehensive analysis of the cell-specific ligand-receptor (L-R) interactions could provide pivotal information about signaling pathways in CKD and MASH. To achieve this, we created an integrative analysis framework in CKD and MASH from two available human cohorts. The analytical framework identified L-R pairs involved in cellular crosstalk in CKD and MASH. Interactions between cell types identified using scRNAseq data were validated by checking the spatial co-presence using the ST data and the co-expression of the communicating targets. Multiple L-R protein pairs identified are known key players in CKD and MASH, while others are novel potential targets previously observed only in animal models. Our study highlights the importance of integrating different modalities of transcriptomic data for a better understanding of the molecular mechanisms. The combination of single-cell resolution from scRNAseq data, combined with tissue slide investigations and visualization of cell-cell interactions obtained through ST, paves the way for the identification of future potential therapeutic targets and developing effective therapies.

A Framework for Rapidly Predicting the Dynamics of Flexible Solar Arrays in the China Space Station with a Verification Based on On-Orbit Measurement Data

The Chinese space station is a complex structure with large flexible appendages. Obtaining the on-orbit response characteristics of such a structure under different working conditions is a traditional and classic challenge in the field of dynamics. To address the on-orbit dynamics of the China Space Station, the basic equations for dynamic reduction, assembly and data recovery of linear and nonlinear substructures are derived based on the reduction and recovery theory, and a fast coupling analysis framework for flexible systems with nonlinear attachments is formed. This coupling analysis framework is adopted to quickly acquire the dynamic response of the China Space Station during in-orbit operation, thereby guiding the design. Taking SZ-15 radial docking to the Chinese Space Station as the object, the substructure of six nonlinear flexible arrays is reduced, the full flexible dynamic equation of the space station is assembled, and the response of each part of the flexible wing during the docking process is analyzed and recovered. By designing a reasonable and reliable flexible wing test scheme in-orbit, the acceleration at the root and top of the flexible wing during the docking of SZ-15 is obtained. The measured data in-orbit show that the acceleration analysis results of the typical parts of the flexible wing have a good agreement, which verifies the correctness of the fast coupling analysis framework of the flexible system. Hence, the dynamic coupling characteristics analysis of the main structure of the space station and the flexible wing based on this method can better guide the rationality of the design of the dynamic characteristics of the Chinese Space Station.

Creative dance – practising and improving … what? A study in physical education teacher education

Creative dance, that is to say, movements, with or without music, which allow participants to express ideas, thoughts, and feelings, are sometimes accompanied by a ‘there is no right or wrong way to move’ rhetoric. This may reinforce the impression among physical education teacher education (PETE) students, who often have limited experience of (creative) dance, that there is nothing to practise in creative dance and that this activity is merely directionless movement. In this paper, however, based on Aggerholm's notion of practising movements, we explore an occasion in a PETE course where a magic moment occurred, indicating that the students had practised and ‘figured out’ something that made this moment possible. The purpose of the paper is to explore the knowledge in movement that PETE students were practising as they participated in creative dance. The purpose is also to shed light on what pedagogical practice contributed to enabling such practising. Video documentation and short interviews with students in one PETE course and one continuing professional development course for physical education teachers indicate that the magic moment was made possible as the students’ practised making sense of moving in non-predetermined – creative – ways and appreciating the expressive dimension of movement. Laban's movement analysis framework seemed, along with the teachers’ knowledge of movement, to be an important element in the pedagogical practice that made the magic moment possible.

Sports integrities: a conceptual and methodological framework for analysis and policymaking

ABSTRACT Since the manipulation of sport competitions became one of the main threats to sport integrity, both the academy and international organizations have sought to establish a coherent conceptual framework that defines what criteria determine a manipulation and what are the factors that might cause it. Although the literature has shown that the manipulation of sport competition is a multifaceted phenomenon that includes individual, relational, organizational and institutional variables, most of the authors have focused their explanations on individual factors, and institutional prevention campaigns continue to understand match-fixing as a problem of moral failure of on-field sports actors. This work proposes a novel dynamic framework for analysis based on the theoretical roots on Morin’s paradigm of complexity and Archer’s critical realism. In addition to articulating the micro, meso, and macro factors together, the paper defends the idea of three conceptions of integrity, personal, competition and institutional, often operating simultaneously in the same space. Each one of these integrities, operates across individual, organizational and structural levels, acting recursively on the others, generating the gears of the global sports integrity. We then discuss the reasons, structures, opportunities and incentives that each of these integrities creates and fuels. We argue that the errors and ineffectiveness of the fight against the manipulation of sport competitions are largely due to a lack of understanding of, and appreciation for, the different conceptions of integrity and their interactions that require different approaches and differentiated public policies. We conclude with innovative possibilities for more effective policy-making processes in this space.

Analysis and design framework for the development of indoor scene understanding assistive solutions for the person with visual impairment/blindness

This paper discusses the challenges of the current state of computer vision-based indoor scene understanding assistive solutions for the person with visual impairment (P-VI)/blindness. It focuses on two main issues: the lack of user-centered approach in the development process and the lack of guidelines for the selection of appropriate technologies. First, it discusses the needs of users of an assistive solution through state-of-the-art analysis based on a previous systematic review of literature and commercial products and on semi-structured user interviews. Then it proposes an analysis and design framework to address these needs. Our paper presents a set of structured use cases that help to visualize and categorize the diverse real-world challenges faced by the P-VI/blindness in indoor settings, including scene description, object finding, color detection, obstacle avoidance and text reading across different contexts. Next, it details the functional and non-functional requirements to be fulfilled by indoor scene understanding assistive solutions and provides a reference architecture that helps to map the needs into solutions, identifying the components that are necessary to cover the different use cases and respond to the requirements. To further guide the development of the architecture components, the paper offers insights into various available technologies like depth cameras, object detection, segmentation algorithms and optical character recognition (OCR), to enable an informed selection of the most suitable technologies for the development of specific assistive solutions, based on aspects like effectiveness, price and computational cost. In conclusion, by systematically analyzing user needs and providing guidelines for technology selection, this research contributes to the development of more personalized and practical assistive solutions tailored to the unique challenges faced by the P-VI/blindness.

Investigating the Health Claims and Regulatory Considerations of Kangen Water: a Comprehensive Analysis with Python and Spiritual Insights

In recent years, Kangen water has emerged as a subject of intense interest due to its purported health benefits attributed to its alkaline nature. Produced via a process known as ionization, Kangen water exhibits a higher pH level compared to regular tap water, purportedly offering numerous health advantages. However, the scientific evidence supporting these claims remains ambiguous and inconclusive. This paper embarks on a thorough exploration of Kangen water, beginning with an elucidation of the electrolysis process fundamental to its creation. Following this, the alleged health benefits are scrutinized against the backdrop of existing scientific literature, delving into studies examining its impact on various health parameters. Furthermore, an in-depth analysis of the regulatory framework surrounding Kangen water is provided, shedding light on the legal and compliance aspects governing its production, distribution, and marketing. Additionally, pragmatic considerations such as cost-effectiveness, maintenance requirements, and consumer preferences are meticulously examined to offer a holistic perspective on the practical implications of Kangen water consumption. By synthesizing scientific research, regulatory insights, and practical considerations, this paper endeavors to furnish a comprehensive understanding of Kangen water, enabling consumers to make informed decisions regarding its usage while facilitating regulatory agencies in formulating appropriate guidelines to ensure public health and safety.

Traumatic Discourse in Scholastique Mukasonga’s Cockroaches and Illuminée Nganemariya’s Miracle in Kigali

This study examines the traumatic journeys of Scholastique Mukasonga in Cockroaches and Illuminée Nganemariya in Miracle in Kigali. The thematic focus of these literary tests explicates the challenges faced by these authors and how they have affected their sociological and psychological wellbeing. 1994 in Rwanda, a genocide presumed to be one of the deadliest attacks on the human race occurred, its effects spanning every sphere: political, religious, economic and educational sectors since its occurrence. The resulting violence and its lingering traumatic effects have spanned over three decades of literary discussions. Some Rwandans documented their experiences before, during and after the Genocide. This study adopts trauma theory as a theoretical framework for the interpretive analysis of the prose narratives. These literary narrations exposed the extent of the violence and its lasting traumatic effects on the people. This study foregrounds that literary works are used as post-conflict peace-building materials; they are information materials to the public and a means of offloading burdens to the writers.

A machine learning-based approach for automatic motion/constraint and mobility analysis of parallel robots

Abstract Motion and constraint identification are the fundamental issue throughout the development of parallel mechanisms. Aiming at meaningful result with heuristic and visualizable process, this paper proposes a machine learning-based method for motions and constraints modeling and further develops the automatic software for mobility analysis. As a preliminary, topology of parallel mechanism is characterized by recognizable symbols and mapped to the motion of component limb through programming algorithm. A predictive model for motion and constraint with their nature meanings is constructed based on neural network. An increase in accuracy is obtained by the novel loss function, which combines the errors of network and physical equation. Based on the predictive model, an automatic framework for mobility analysis of parallel mechanisms is constructed. A software is developed with WebGL interface, providing the result of mobility analysis as well as the visualizing process particularly. Finally, five typical parallel mechanisms are taken as examples to verify the approach and its software. The method facilitates to attain motion/constraint and mobility of parallel mechanisms with both numerical and geometric features.

Nigeria's Climate Change Act 2021: A pathway to net-zero carbon emission, energy security and sustainability.

The global push for net-zero carbon emissions by 2050 requires countries to adopt sustainable energy sources, address energy poverty and promote energy security. Nigeria is grappling with an energy crisis, and the recently enacted Climate Change Act 2021 offers the prospect of addressing this while advancing energy sustainability. The study evaluates the Act's potential in promoting energy security and global net-zero carbon emissions. Nigeria faces challenges in recovering from the COVID-19 pandemic and combating climate change, prompting countries to take domestic and international measures to reduce greenhouse gas emissions. Through doctrinal legal research and conceptual analysis, the study examines Nigeria's Climate Change Act, proposing solutions to enhance its commitment to global net-zero carbon emissions. It conducts a comparative legal analysis of climate change frameworks in Kenya, Nigeria and the Democratic Republic of Congo, providing insights and suggesting reforms to Nigeria's Act for Energy Security. While the existing laws are adequate, weak enforcement by regulatory agencies and a lack of political will hinder compliance. Public awareness regarding individual contributions to climate change is also lacking. The study recommends increased funding for regulatory institutions and proactive public awareness. Complying with the Paris Agreement and Sustainable Development Goal 13 is vital for a sustainable energy future.

A novel automated framework for fine-grained sentiment analysis of application reviews using deep neural networks

A novel automated framework for fine-grained sentiment analysis of application reviews using deep neural networks

Comparative Legal Analysis of IT Legislation of Russia and Sweden

INTRODUCTION. This article provides a compre­hensive analysis of the regulatory frameworks govern­ing the information technology (IT) sector in both Russia and Sweden and encompasses a comparative assessment of key legal instruments, concepts, and regulatory approaches, including the responsibility for cybercrimes, licensing procedures, standardization practices, and the safety of critical informational in­frastructure. Additionally, this article examines the roles and functions of major governing authorities in both countries.MATERIALS AND METHODS. The article is based on relevant legal acts of Russia and Sweden. While there are certain specific laws focused entirely on the informational technologies, some provisions can be found in other types of legal documents (for example criminal codes or governmental regulations). Employ­ing a comparative approach, the study delineates the scope and authority of state institutions involved in the IT sphere.RESEARCH RESULTS. Both Russian and Sweden exhibit similarities when it comes to definition of es­sential concepts such as critical infrastructure, reflect shared concerns regarding for example security issues. Main laws in the area of information technology con­tain a spectrum of key terms, including but not limited to information and communication network / elec­tronic communication network, information system operator, and information protection / network and information system security. Although the list of key definitions may appear quite similar, the Swedish leg­islation tends to offer broader definitions with the in­tention of encompassing larger domains within IT technologies, while the Russian legislators focus on more specific terms. However, while Sweden aligns closely with European Union (EU) regulatory frame­work, Russia adopts a more expansive approach, ad­dressing emerging technological challenges such as AI. In conclusion, achieving effective IT regulation neces­sitates finding a balance between international con­sistency and national adaptability to ensure strong cybersecurity, foster innovation, and maintain regula­tory flexibility in a dynamic digital environment.DISCUSSION AND CONCLUSIONS. Sweden’s re­liance on implementing EU regulations has its benefits such as harmonisation, interoperability, adopting the internationally recognised practices, easier market ac­cess, etc. However, this approach may limit the coun­try's ability to meet its specific needs and may mean additional administrative burdens associated with compliance with EU directives. Moreover, changes in EU regulations could lead to a necessity to update do­mestic laws, potentially causing regulatory vacuum or legal collisions, especially in such sphere as the IT sec­tor. Nowadays, when for example the AI and its risks are on the daily agenda one can not look away and wait for the international community to agree on the applicable regulation.

Integrating Climate Change Risks and Sustainability Goals into Saudi Arabia’s Financial Regulation: Pathways to Green Finance

This study examines the integration of climate change risks and sustainability goals within Saudi Arabia’s financial regulatory framework to enhance green finance initiatives aligned with Vision 2030. A qualitative research design synthesises insights from a comprehensive literature review, semi-structured interviews with domain experts, and a detailed analysis of critical Saudi green finance frameworks and legislation. This research identifies mechanisms for embedding sustainability in the financial sector and addresses the challenges, opportunities, and strategic directions essential for Saudi Arabia within the global context of sustainable finance. The findings reveal a robust foundation laid by Vision 2030 initiatives yet underscore the need for enhanced regulatory frameworks, increased market readiness, and greater societal engagement. This study highlights a significant literature gap in understanding Saudi Arabia’s unique approach to green finance amid its economic diversification and sustainability goals. Contributing to original insights, this research underscores the critical role of Saudi Arabia in the global energy market and its substantial economic and environmental transformations. It offers detailed analyses and recommendations that enrich the discourse on sustainable finance, impacting policymakers, financial practitioners, and scholars.