Analytical Framework Research Articles

An adaptive phase field approach to 3D internal crack growth in rocks

Modeling the 3D internal crack under compression entails complex fracture mechanics (mode I-II-III fracture), resulting in substantial computational costs and challenges in characterizing fracture morphology characterization for Phase Field Method (PFM) simulations. In the present paper, we developed a 3D adaptive crack propagation model integrated into the PFM to study the internal cracks in rocks. The proposed locally refined solution was implemented within the isogeometric analysis (IGA) framework, utilizing PHT-splines and employing the phase field variable as an error indicator to accurately capture non-smooth crack surfaces. The simulation begins with a coarser mesh, and the spatial discretization is adaptively refined in real-time as the computation progresses and the phase variable threshold is reached. By comparing our results with previous numerical tests, we validated the effectiveness of our model in simulating crack growth. Notably, a smaller length scale parameter led to a higher peak force in notched square plates under tension, and our adaptive PFM successfully reduced errors caused by length scale parameters. We further validated our model by comparing it with uniaxial compression experiments on 3D-printed resin samples with internal penny-shaped cracks, achieving good agreement with the experimental data. Using the 3D adaptive PFM, we predicted changes in crack morphology and fracturing mechanisms by varying the inclination angles of internal penny-shaped cracks. Our numerical results showed that as the inclination angle increased, wing cracks initiated closer to the end tips of the original crack, and their length decreased due to the wings wrapping effect. The corresponding fracturing mechanisms transition from mode I-III fracture (0°) to mode I-II-III fracture (30°, 45°, 60°), and eventually to mode I fracture (90°) as inclination angles increase. Comparing 2D and 3D models, we found that the growth of wing cracks in 3D was significantly influenced by the intermediate principal stress. We conclude that the extended 3D adaptive PFM-based model accurately predicted complex mechanical behavior and crack growth patterns in rock.

A cognitive effective framework for analysis, monitoring and identifying variant of coronavirus disease

A cognitive effective framework for analysis, monitoring and identifying variant of coronavirus disease

Securitisation and its extensions: a framework for analysis of Russia’s war on Ukraine

ABSTRACT This analysis aims to address certain shortcomings found within securitisation theory and its practical usage. Russia’s aggression against Ukraine necessitates a profound transformation of the research vocabulary of security studies, as well as an expansion of its scholarly instruments. This article investigates the potential modifications and adjustments of the concept of securitisation, which due to its broad explanatory scope could be recalibrated to reflect the radically altered security landscape in Europe. In this context, three ancillary concepts are introduced as extensions to the original terminology of the Copenhagen School: primary self-securitisation, secondary securitisation and counter-securitisation. The analysis seeks to move beyond the theory’s traditional emphasis on speech acts, to more precisely define the interplay between securitisation and the agency, and to expand the role of the audience beyond merely affirming or disputing securitising moves.

A comparative analysis of recent life cycle assessment guidelines and frameworks: Methodological evidence from the packaging industry

In recent years, a number of new guidelines and frameworks for Life Cycle Assessment (LCA) have emerged, trying to support analysts in dealing with certain methodological issues and “gaps” of the ISO 14040-44, that are still the main LCA reference standards. This trend can be considered as positive, because the lack of shared, standardised and more detailed rules regarding LCA has affected for years the consistency of LCA analyses and their potential comparisons. However, the proliferation of guidelines and frameworks can also have negative consequences, first of all related to the potential resulting confusion and the lack of a clear reference for LCA analysts. These potential risks are particularly accentuated for multinational companies, which deal with many clients, in different markets, countries and sectors, and have to conform their analyses to different requirements each time.Focusing on the plastic packaging industry, this study compares six LCA guidelines and frameworks to highlight their similarities and differences. The documents selected to be analysed were: three documents applicable to products in general (ILCD, PAS 2050 and PEF), two packaging-specific guidelines (Pathfinder Framework and SPICE Methodological Guidelines) and a product specific standard for the packaging industry (PCR 2013:19). The methodological aspects analysed and compared, grouped according to the LCA stages, are: units of analysis; system boundaries; allocation methods; cut-off criteria; end-of-life; packaging; storage; biogenic CO2 emissions; carbon removals and carbon content; land use; offsets; impact categories and indicators; LCA methods and models; normalisation and weighting; data quality; sensitivity analysis. The aim is to understand to what extent potential differences may impact on companies and LCA analysts who conduct the assessments. Results highlight that the six guidelines and frameworks analysed are not always aligned and that, although some misalignments can be easily addressed, others could negatively affect the reliability of the analyses conducted.

Systematic Analysis of the use of Innovative Approaches in Operational and Investigative Activities: The Republic of Azerbaijan Case

The new conditions of law enforcement, technological and digital evolution have had a significant impact on the emergence of new approaches to investigation. The goal of this article is to systematically investigate the application of innovative approaches to investigative activities, taking into account the experience of the Republic of Azerbaijan. The author used the content analysis of the legislative framework and professional scientific literature, which made it possible to summarise the existing traditions of applying innovations in other countries and compare them with the Azerbaijani practice using the systematisation method. The results of the study indicate that due to the deep integration of digital technologies into operational and investigative activities, a problem has arisen with respect to the legal framework for preserving the fundamental rights and freedoms of citizens. Achieving justice in this matter is an important option, for the implementation of which there is a need to use European standards. Adherence to this vector allows preserving the democratic nature of operational and investigative procedures. The article also establishes that the main innovative methods of organising operational and investigative activities in the Republic of Azerbaijan are the use of information technologies with a view to increasing the efficiency of detecting unlawful acts and combating crime. The conclusions also emphasise that international cooperation in the field of law also allows for effective detective operations through cooperation with neighbouring countries and other EU countries.

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

AbstractPower systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System, thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Efficiency of large integer multiplication algorithms: A comparative study of traditional methods and Karatsuba's algorithm

The large integer multiplication is the basis of many computer science algorithms, ranging from cryptography to complex calculations in various scientific fields. Contemporary society excessively depends on complex computing tasks. Hence, the need for good algorithms is becoming increasingly apparent as well. This text gives the reader an in-depth knowledge of the multiplication algorithms of large integers by contrasting traditional algorithms with the new Algorithm developed by Karatsuba. This research methodology involves a comparative analysis of the components using an advanced analysis framework that primarily focuses on execution times, efficiency metrics, and resource utilization. Incontrovertibly, the experimental results confirm the Karatsuba algorithm's undoubted hastiness compared to the conventional approaches. This study extends our grasp of the evolution of algorithms in computational optimization, enabling people to get unique and relevant findings that will benefit numerous areas where large integer multiplications are involved. In addition to these findings, the study also highlights the importance of algorithm selection in ensuring computational efficiency and accuracy in large integer multiplications across various applications.

Investigating Latent Interaction Effects in Multiple-Group Analysis in the Structural Equation Modeling Framework

This study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for estimating latent interactions within multiple-group analysis frameworks using simulation studies and empirical data, we assess their relative merits. Our simulation study results demonstrated the superiority of the Latent Moderated Structural Equations (LMS) approach over the Unconstrained Product Indicator (UPI) method in power and providing more accurate estimates of differences in latent interactions between groups. Utilizing multiple-group analysis on real-world data, we evaluated its efficacy in identifying latent interaction differences between groups. Empirical data analysis did not reveal discrepancies between LMS and UPI in terms of detecting differences in latent interactions between boys and girls, although they indicated varying sizes of differences in interaction effects. The study concludes with recommendations for examining differences in latent interactions and suggests avenues for future research. Our findings aim to deepen the understanding of intricate relationships among variables, group differences, and the moderating effects of latent variables, ultimately facilitating the development of more accurate theoretical models.

The orthodoxy of the classical and neoclassical economic model: on the shoulders of giants

The objective of this reflection article is to vindicate great thinkers in economics who shaped the main theoretical postulates, philosophy and methodology of science, exposing their conceptual and theoretical framework for a comprehensive understanding of their most relevant contributions. In the development of the article, a historical description of the evolution of orthodox economic thought is offered, within a framework of analysis of recognition of economic doctrines from their historical, institutional, political, cultural and social situation, where their contributions are still significant for the interpretation of current reality, not in an absolute way due to the limitations of the assumptions, methods and historical interpretation of the authors, but with inputs that, objectively analyzed, provide validity and usefulness to economics professionals, and in general to all social scientists, for the exercises of positive economics of description, analysis and systematization of economic phenomena and of normative economics of intervention of reality through economic policy. The historical framework of the exhibition is until the 19th century, keeping in mind that, if the economy was built from classical and neoclassical orthodoxy, the alternative and subsequent currents are necessarily heirs, direct or indirect, of these giants of thought.

Information relations for social change: exploring the information behaviour of academics undertaking impact work

Introduction. This paper examines academics’ information behaviour in undertaking research for societal impact. It explores how researcher-stakeholder relationships provide sites of information exchange where academics develop skills and knowledge needed to undertake impact work. Method. This qualitative study involved semi-structured interviews with 27 academics at 18 institutions across Australia. Participants were recruited across disciplines and at various career stages. Analysis. Constructivist grounded theory was used as a methodology, with Fiske's Relational Models Theory as a framework for analysis. Results. Results show that information behaviours relating to impact work were enacted within relationships with industry, community, and government partners. These relationships were characterised by four elements: curiosity, reciprocity, trust, and engagement. Conclusion. The paper presents a model of Relational-Informational Impact Practice to guide individual researchers’ information behaviours and to inform university support programs for researchers engaged in societal impact work. The model outlines the interplay between curiosity, reciprocity, trust, and engagement, and impact-relevant information behaviours, such as information needs identification, sharing practices, and serendipity.

Development and testing of an automated tool to leverage building energy models for thermal resilience analysis

Unlike building energy use analysis, thermal resilience analysis to understand how buildings perform during disruptive events has not been widely adopted or standardized. To ensure best practices are applied consistently, this paper proposes a new automated toolbox to leverage building performance models developed for energy analysis purposes, for thermal resilience analysis. To demonstrate the functionality and robustness of the toolbox for automating the analysis and reporting of thermal resilience, example simulations are completed with models gathered from different sources. Major contributions from this study include the establishment of a standardized transparent simulation framework for thermal resilience analysis, as well as the proposal of techniques for overcoming challenges associated with a diversity of model sources including different modelling habits/preferences by modellers and different versions of EnergyPlus. Recommended future work includes the development of standardized modelling configurations reflecting extreme events; the inclusion of more comprehensive metrics, and the refining analytics report through consultation with stakeholders.

Use of phase plate cryo-EM reveals conformation diversity of therapeutic IgG with 50 kDa Fab fragment resolved below 6 Å

While cryogenic electron microscopy (cryo-EM) is fruitfully used for harvesting high-resolution structures of sizable macromolecules, its application to small or flexible proteins composed of small domains like immunoglobulin (IgG) remain challenging. Here, we applied single particle cryo-EM to Rituximab, a therapeutic IgG mediating anti-tumor toxicity, to explore its solution conformations. We found Rituximab molecules exhibited aggregates in cryo-EM specimens contrary to its solution behavior, and utilized a non-ionic detergent to successfully disperse them as isolated particles amenable to single particle analysis. As the detergent adversely reduced the protein-to-solvent contrast, we employed phase plate contrast to mitigate the impaired protein visibility. Assisted by phase plate imaging, we obtained a canonical three-arm IgG structure with other structures displaying variable arm densities co-existing in solution, affirming high flexibility of arm-connecting linkers. Furthermore, we showed phase plate imaging enables reliable structure determination of Fab to sub-nanometer resolution from ab initio, yielding a characteristic two-lobe structure that could be unambiguously docked with crystal structure. Our findings revealed conformation diversity of IgG and demonstrated phase plate was viable for cryo-EM analysis of small proteins without symmetry. This work helps extend cryo-EM boundaries, providing a valuable imaging and structural analysis framework for macromolecules with similar challenging features.

Parental Migration and the Social and Mental Well-Being Challenges among Indonesian Left-Behind Children: A Qualitative Study.

Parental labour migration, of either one or both parents, has been associated with various challenges among left-behind children (LBC). However, there is a limited understanding of the LBC's own views and experiences of social and mental well-being and how the new daily life circumstances they encounter following their parents' migration impact them. This study aimed to understand the influence of parental migration and its aftermath on the social and mental well-being of adolescents (referred to as LBC) in two rural districts in Indonesia. Employing a qualitative design, data were collected through individual in-depth interviews with LBC (n = 24) aged 14 to 18 years, recruited using the snowball sampling technique. Data were thematically analysed, guided by a qualitative data analysis framework. The findings showed that parental migration negatively impacted the social well-being of LBC. This impact was reflected in negative labelling from friends and changes in familial roles which influenced their social interactions and activities with peers. Parental migration was also associated with challenges to the mental well-being of LBC. These manifested in the LBC experiencing fractured emotional bonds, leading to negative emotions, including stress, anxiety, sadness, depression, frustration, loss of motivation, and self-imposed isolation, which were associated with their parents' migration and abrupt disruptions in parent-child communication. The transition to new life situations with caregivers after parental migration and the dynamics within the caregivers' households were additional factors that detrimentally affected their mental well-being. Unmet basic needs and educational needs due to financial hardships faced by mothers and caregivers further exacerbated mental health challenges for the children. The findings indicate the importance and improvement of policies and interventions in Indonesia (e.g., counselling services, non-cash food assistance, family hope program, direct cash assistance) that cover and address the diverse needs of mothers or caregivers and the LBC.

Mechanistic Insights into Plasma Oxidation of Ag Nanofilms: Experimental and Theoretical Studies.

Plasma oxidation of metals has been studied extensively to fabricate nanoporous oxides with the merits of room temperature treatment and facile control of the oxidation rate. Plasma oxidation of Ag, motivated by studies on atomic oxygen corrosion of Ag, is one of the most studied systems. However, several important questions remain unaddressed and even overlooked traditionally: the critical role played by atomic O in promoting oxidation, evolution of microstructures during plasma exposure, and a sound framework for quantitative oxidation kinetic analyses. In this paper, the O2 plasma oxidation behavior of Ag films deposited on Si substrates was systematically studied both experimentally and theoretically. The effects of plasma pressure and power on the microstructural evolution and oxidation kinetics of Ag films of various thicknesses were investigated using comprehensive characterization, as well as numerical analysis of plasma chemistry for deriving atomic O concentration. The findings here provide a full picture and deep mechanistic insights into the morphology and microstructure evolution of Ag films and the growth of dense or porous Ag2O and AgO oxide layers by plasma oxidation, revealing the intricate interplay between atomic O, vacancy creation, Ag ion diffusion, Kirkendall effect, formation of pores, and interfacial void coalescence. The methodology developed here can be easily transferred to help understand the plasma oxidation behavior of other metals.

Trajectory-based global sensitivity analysis in multiscale models

This research introduces a novel global sensitivity analysis (GSA) framework for agent-based models (ABMs) that explicitly handles their distinctive features, such as multi-level structure and temporal dynamics. The framework uses Grassmannian diffusion maps to reduce output data dimensionality and sparse polynomial chaos expansion (PCE) to compute sensitivity indices for stochastic input parameters. To demonstrate the versatility of the proposed GSA method, we applied it to a non-linear system dynamics model and epidemiological and economic ABMs, depicting different dynamics. Unlike traditional GSA approaches, the proposed method enables a more general estimation of parametric sensitivities spanning from the micro level (individual agents) to the macro level (entire population). The new framework encourages the use of manifold-based techniques in uncertainty quantification, enhances understanding of complex spatio-temporal processes, and equips ABM practitioners with robust tools for detailed model analysis. This empowers them to make more informed decisions when developing, fine-tuning, and verifying models, thereby advancing the field and improving routine practice for GSA in ABMs.

Characterizing culture’s influence in land systems

AbstractGroup-shared attributes, coded in cultural systems, heavily influence how land is used. Despite recent advances in behavioural theory, the central role of culture in land-use decision-making and linked sustainability outcomes is underexplored. We expanded on institutional analysis and system-dynamics frameworks to analyse 66 studies that causally link culture to land use. We found that most studies focus on norms, practices, values or meanings. These can lead actors to maintain a particular land use, which is coded into cultural systems, adding to the land system’s resilience. Internal group events or changes in structural factors can also lead to shifting norms and values, changing land use or destabilizing systems, leading to new system dynamics or resistance to new feedbacks. Our findings further link cultural underpinnings of land systems to positive and negative sustainability outcomes. We call for further research on the role of culture in land-system dynamics.

Playing with data differently: engaging with autism and gender through participatory arts/music and a performative framework for analysis.

There are increasing demands for Participatory Arts-Based (PAB) programs involved in health research to better evidence outcomes using robust quantitative evaluation methodologies taken from science, such as standardized questionnaires, to inform commissioning and scale-up decisions. However, for PAB researchers trying to do this, barriers arise from fundamental interdisciplinary differences in values and contexts. Researchers are required to navigate the tensions between the practice-based evidence produced by the arts and the evidence-based practice sought by psychologists. Consequently, there is a need for interdisciplinary arts-science collaborations to produce alternative methods of evaluation that are better aligned to PAB approaches, and which combine systematic rigor with a sensitivity to the values, contexts and strengths of this approach. The current article centers on the development of an alternative transdisciplinary analytic tool, the Participatory arts Play Framework (PP-Framework), undertaken as part of an arts-psychology collaboration for a UK AHRC-funded PAB research project: Playing A/Part: Investigating the identities and experiences of autistic girls. We present details of three stages in the development of the PP-Framework: 1. preliminary emergence of the framework from initial video analysis of observational data from participatory music and sound workshops run for 6 adolescent autistic girls (aged 11-16); 2. identification and application of modes of engagement; and 3. further testing of the framework as an evaluation tool for use in a real-world setting, involving professional musicians engaged in delivery of a creative music project at a center for homeless people. The PP-Framework maps types of participation in terms of performative behaviors and qualities of experience, understood as modes of play. It functions as a vehicle for analyzing participant engagement, providing a tool predicated on the processes of working in creative participatory contexts while also being sensitive to the esthetic qualities of what is produced and capable of capturing beneficial changes in engagement. It offers a conceptual approach for researchers to undertake observation of participatory arts practices, taking account of embodied engagement and interaction processes. It is informed by understandings of autistic performativity and masking in conjunction with an ecological understanding of sense making as being shaped by environments, social relations and sensing subjectivity. The framework has the potential to be a bi-directional tool, with application for both practitioners and participants.

Qualitative and Quantitative Analysis of Three-Dimensional Fluorescence Spectra by Improved Parallel Factor Analysis with Internal Standard Sample Embedding.

The strategy of parallel factor analysis, combined with the internal standard method, has been increasingly applied to the qualitative and quantitative analysis of three-dimensional fluorescence spectra of unknown mixed fluorophores. Nevertheless, the disparity in the number of fluorophores included in the internal standard sample set and the number included in test samples may impact the qualitative and quantitative outcomes of parallel factor analysis. In this work, we systematically established the framework of the parallel factor analysis with internal standard sample embedding (ISSE-PARAFAC) strategy. We applied this framework to six datasets representing two scenarios and a real dataset and conducted a detailed discussion on the effects of the disparity between the number of fluorophores in the internal standard sample set and the number in the test set on both qualitative and quantitative results. Additionally, we introduced an enhancement to PARAFAC by aggregating fluorophores with similar emission wavelengths, corresponding to the peaks of emission loadings (spectra) obtained from PARAFAC, as a single fluorophore. This aggregation aimed to mitigate the strong correlation between similar fluorophores. The results imply that the presence of irrelevant fluorophores in the internal standard sample set, whether increased or decreased, does not significantly affect the qualitative and quantitative analysis of target fluorophores in the test set. Moreover, we demonstrated that the improved parallel factor analysis with internal standard sample embedding not only fully decomposes the uncorrelated mixed fluorophores for qualitative analysis but also allows the established linear concentration model for fluorescent components to predict the corresponding fluorophore concentration of test samples, enabling quantitative analysis at the ppm level (mg/L).

P63 Comparative Analysis of Health Technology Assessment Agency Frameworks for Digital Health Technologies

P63 Comparative Analysis of Health Technology Assessment Agency Frameworks for Digital Health Technologies

In-silico mechanistic analysis of adsorption of Iodinated Contrast Media agents on graphene surface

The study aims at assessing the potential of graphene-based adsorbents to reduce environmental impacts of Iodinated Contrast Media Agents (ICMs). We analyze an extensive collection of ICMs. A modeling approach resting on molecular docking and Density Functional Theory simulations is employed to examine the adsorption process at the molecular level. The study also relies on a Quantitative Structure-Activity Relationship (QSAR) modeling framework to correlate molecular properties with the adsorption energy (Ead) of ICMs, thus enabling identification of the key mechanisms underpinning adsorption and of the key factors contributing to it. A collection of distinct QSAR-based models is developed upon relying on Multiple Linear Regression and a standard genetic algorithm method. Having at our disposal multiple models enables us to take into account the uncertainty associated with model formulation. Maximum Likelihood and formal model identification/discrimination criteria (such as Bayesian and/or information theoretic criteria) are then employed to complement the traditional QSAR modeling phase. This has the advantage of (a) providing a rigorous ranking of the alternative models included in the selected set and (b) quantifying the relative degree of likelihood of each of these models through a weight or posterior probability. The resulting workflow of analysis enables one to seamlessly embed DFT and QSAR studies within a theoretical framework of analysis that explicitly takes into account model and parameter uncertainty. Our results suggest that graphene-based surfaces constitute a promising adsorbent for ICMs removal, π-π stacking being the primary mechanism behind ICM adsorption. Furthermore, our findings offer valuable insights into the potential of graphene-based adsorbent materials for effectively removing ICMs from water systems. They contribute to ascertain the significance of various factors (such as, e.g., the distribution of atomic van der Waals volumes, overall molecular complexity, the presence and arrangement of Iodine atoms, and the presence of polar functional groups) on the adsorption process.