Alternative Models Research Articles

Импульс мобилизации и электоральные результаты «партии власти»

The article examines the connection between protests and elections in an authoritarian context. Using the concept of mobilization momentum, the authors attempt to find out whether intensive and massive collective actions on the eve of elections can affect electoral mobilization and support for the “party in power”, and if so, in what direction. Based on the modern literature on this topic, the authors identify two alternative models of the possible electoral effect of the mobilization momentum. According to the first model, by breaking through the information blockade and signaling to citizens about the widespread dissatisfaction with the authorities’ policies, intense mass protests contribute to an increase in voters’ turnout and a decrease in support for pro-government forces. According to the second model, such protests may easily increase the electoral performance of the “party in power,” since they often lead to the mobilization of an electorate that is loyal to the ruling circles. The authors test these hypotheses against the evidence from the 2011— 2016 parliamentary electoral cycle in Russia using methods of standard multiple linear regression, difference-in-differences and synthetic control. The results are mixed. It appears that the mobilization momentum has a weak electoral effect or even a positive effect on the performance of the “party in power,” but its influence may depend on threshold values: in the most protesting cities, support for the United Russia turns out to be lower than it would be in the absence of the mobilization momentum. At the same time, the findings convincingly demonstrate that the evidence and data from the Russian context, combined with modern methods of analysis, opens up an excellent opportunity for research at the intersection of the spheres of political participation and electoral politics.

A meta-model of customer brand loyalty and its antecedents

This research consolidates existing knowledge about customer brand loyalty and its antecedents by developing and empirically validating an integrative meta-model. First, with a grounded theory literature review of 199 prior studies, the authors identify 275 antecedents of loyalty that they aggregate into four meta-concepts: (1) brand offer, (2) consumer–brand alignment, (3) brand experience, and (4) consumer–brand bonding. Second, the authors theoretically derive four alternative models that describe the interrelations of these meta-concepts and loyalty and empirically identify the most suitable one, using meta-analytical structural equation modeling. The findings, based on 1,261 effect sizes from 557 studies, provide support for a two-stage process, in which brand experience and consumer–brand bonding have direct effects on loyalty and mediate the effects of brand offer and consumer–brand alignment that precede them. The meta-model and associated empirical generalizations lay a robust, consolidated foundation for continued efforts to understand how to create and nurture loyalty.

Relationship between Concept Mastery and Scientific Literacy of High School Students' on Plant Growth and Development Concept

Scientific literacy and mastery of concepts are needed to prepare a generation that is ready and adaptive to face developments in science and technology in the 21st century. Therefore, there is a need to change the learning process through the application of appropriate learning models. The Project Based Learning (PjBL) model can be a solution in increasing students' scientific literacy and mastery of concepts. This research was conducted at SMAN 7 Mataram, West Nusa Tenggara (NTB) with a quasi experimental pretest-posttest design. The research subjects were 132 of the 10th grade students. The research instrument for scientific literacy and concept mastery uses essay questions. Data were analyzed descriptively and with inferential statistics, i.e correlation tests at a significance level of 1%. The results of data analysis show that the significance value is 0.00, so it can be concluded that there is a positive correlation between concept mastery and student literacy. The implication of the results of this research is that the use of the PjBL model can be used as an alternative model that can empower students' mastery of science concepts and literacy

Flavour-changing top quark decays in the alternative left-right model

We examine flavour-changing neutral-current decays of the top quark, t→qγ, t→qZ, t→qH, and t→qg (with q=u,c), in the Alternative Left-Right Model, a left right-symmetric model featuring exotic quarks and light bosons. These decays have a very small probability of occurring within the Standard Model, but they can be enhanced in this model through the presence of the exotic states. While associated signals may be detected directly at the LHC, rare decays have the advantage of offering means to probe new particles indirectly, through loop-contributions. We perform a comprehensive analysis of the model's parameter space to demonstrate the possible existence of enhancements in the corresponding branching ratios, of 106 for the branching ratios B(t→uZ) and B(t→uH), and in the range of 102−104 for the other decays, relative to the Standard Model. We subsequently determine the preferred parameter space regions of the model in terms of potential of being reached in the near future.

Are anxiety, depression, and stress distinguishable in Italian adolescents? an examination through the Depression Anxiety Stress Scales-21.

The adolescents' ability to discriminate between different negative emotional states is still under debate. The Depression Anxiety Stress Scales-21 (DASS-21) serves as a useful tool to unravel this issue, yet the literature on its structural validity in young people is ambiguous. Therefore, this study aimed to expand knowledge on the emotional experience of youth by investigating the factor structure and psychometric properties of the DASS-21 in Italian adolescents. Six hundred fifty-five students (60.6% girls) aged 14-18 (M = 16.3 ± 1.29) completed an online survey containing the DASS-21 and Positive and Negative Affect Schedule (PANAS). To evaluate the factor structure of the DASS-21, several alternative models were tested, also adopting an Exploratory Structural Equation Modeling (ESEM) procedure. Measurement invariance, reliability, validity, and latent means differences were addressed. The ESEM model with three correlated factors of Depression, Anxiety, and Stress yielded the best fit to the data, supporting a hierarchical structure of the DASS-21. In addition, this model was invariant across sex and age groups. The Anxiety scale predicted both positive and negative affect, while Depression predicted positive affect only. Finally, girls scored higher than boys on Anxiety and Depression, but no age differences emerged. Overall, our results indicate that anxiety, depression, and stress are distinguishable in Italian adolescents but, simultaneously, share an underlying condition of general distress, which may explain the comorbidity between internalizing problems. Such findings are discussed in terms of clinical and preventive implications for the adolescent population.

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) – sensitivity studies and evaluation using airborne measurements of power plant emissions

Abstract. The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: (i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results, (ii) the evaluation of the mixing properties of five different turbulence models using the well-mixed criterion, and (iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitivity study, we analyse the effects of the stability class, roughness length, zero-plane displacement factor, and source height on the three-dimensional plume extent as well as the distance between the source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbulence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM, and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height, except for the default turbulence model of ARTM 3.0.0 with deviations of up to 18 %. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland, measured by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Cessna aircraft during the Carbon Dioxide and Methane Mission (CoMet) campaign in 2018 allowed for evaluation of model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are of the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests, and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM versions 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 %, resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes, and the plume width, with a 30 % deviation in the peak CO2 concentration and a less than 25 % deviation in the measured CO2 plume width. Uncertainties in the simulations may arise from the different spatial and temporal resolutions of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representation of real plumes in very unstable atmospheric conditions through the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Zophobas morio larvae as a novel model for the study of Acinetobacter virulence and antimicrobial resistance.

The use of mammalian models for in vivo testing of bacterial virulence raises ethical concerns and is expensive and time-consuming. As an alternative, non-mammalian models are sought. Galleria mellonella larvae have been used as a model to study several bacterial pathogens. However, their maintenance is challenging, and commercial supply is low. In this study, we aimed to establish the Zophobas morio larvae as an alternative non-mammalian model for the evaluation of the pathogenicity and antimicrobial susceptibility of Acinetobacter baumannii. We infected Z. morio with Acinetobacter strains and determined the optimal temperature and inoculum. To visualize the bacterial distribution within the larvae, hematoxylin and eosin (H&E) staining was performed. Next, a survival model of infected larvae was established, and virulence was compared between strains. The effect of antimicrobial treatment in relation to antibiotic susceptibility was studied. Our results demonstrate that Z. morio can be used as a model system for in vivo studies of A. baumannii.

Evaluation of a New Droplet Growth Model for Small Droplets in Condensing Steam Flows

As the condensation phenomenon occurs in the low-pressure stages of steam turbines, an accurate modelling of the condensing flows is very crucial and has a significant impact on the development of highly efficient steam turbines. In order to accurately simulate condensing steam flows, it is essential to choose the right condensation model. Further research to enhance condensation models is of special importance because the outcomes of numerical studies of condensation models in recent years have not been entirely compatible with the experiments and there are still uncertainties in this area. Therefore, the main aim of this paper is to evaluate a proposed droplet growth model for modelling condensation phenomenon in condensing steam flows. The new model is derived to profit from the advantages of models based on the continuum approach for large droplets and those based on the kinetic theorem for small droplets, which results in the model being robust for a wide range of Knudsen numbers. The model is implemented into a commercial CFD tool, ANSYS Fluent 2022 R1, using UDFs. The results of the CFD simulations are validated against experimental data for linear cascades within the rotor and stator blade geometries of low-pressure steam turbine stages. The findings clearly demonstrate the superiority of the new model in capturing droplet growth, particularly for very small droplets immediately following nucleation. In contrast, widely used alternative droplet growth models tend to either underpredict or overpredict the droplet growth rate. This research significantly contributes to the ongoing efforts to enhance condensation modeling, providing a more accurate tool for optimizing the design and operation of low-pressure steam turbines, ultimately leading to a higher energy efficiency and a reduced environmental impact.

Research on the path of building carbon peak in China based on LMDI decomposition and GA-BP model.

The building sector contributes significantly to carbon emissions, impeding China's progress toward its 2030 carbon emissions peak target due to the limited utilization of renewable energy sources. This study aims to forecast the peak and timing of carbon emissions in China's construction industry to chart a low-carbon roadmap for the sector's future. Initially, an extended logarithmic mean divisia index (LMDI) decomposition model, based on the Kaya identity, is proposed to gauge the contribution levels of driving factors affecting building carbon intensity. Subsequently, a hybrid prediction model (IGA-BP) is constructed, employing an optimized two-hidden-layer neural network via a genetic algorithm, to forecast building carbon emissions and intensity. Additionally, four scenarios are outlined, each defining pathways to simulate emissions peak, carbon peak timing, and intensity within the Chinese building sector from 2020 to 2050. The research findings reveal: (1) The final emission factor of buildings primarily drives the surge in building carbon intensity, while the industrial structure stands as the most significant limiting factor. (2) Compared to alternative models, the proposed hybrid prediction model more effectively captures the evolution pattern of carbon emissions. (3) The prediction results indicate that China's building carbon intensity has reached its peak. Pathway 12 closely aligns with the sector's carbon emissions peak, projecting a peak value of 5.609 billion tons in 2029. To attain this pathway, China needs to develop more precise and feasible emission reduction strategies for its buildings. Overall, the research outcomes furnish robust references for decision-making in future efforts aimed at reducing building emissions.

Alternative model of Islamic deposit insurance for the Islamic banking system

Purpose This paper aims to develop a novel approach to Islamic deposit insurance, specifically addressing the deficiencies in the current prevailing models of Islamic deposit insurance. Design/methodology/approach The analysis in this paper adopts a qualitative content analysis approach to review the existing literature on Islamic deposit insurance and propose a new model. Findings The proposed model includes a revised scheme. In the event of a bank failure, the funds used to reimburse depositors of the failed bank are divided into two distinct categories. The first category includes nonrepayable premiums that have been previously paid by the failed bank and managed by the Islamic deposit insurance agency or Islamic deposit insurance corporation. The second category comprises qard hasan, an interest-free loan provided by the Islamic deposit insurance agency or Islamic deposit insurance corporation using the deposit insurance funds from the collective pool of premiums of other banks. Practical implications The proposed model ensures that well-managed banks are not unfairly burdened by the failures of their poorly managed counterparts, thus preventing a sense of unfairness and inefficiency. Implementing the proposed model may result in higher business practices and risk management standards, ultimately leading to better depositors’ protection and banking system’s stability. Originality/value This paper offers a significant contribution to the limited literature on Islamic deposit insurance. The proposed model enriches the discourse and offers valuable insights for the future development of Islamic banking.

Modeling and friction response analysis of rocking-sliding friction of drill string in directional wells

The main goal of this research is to conduct a quantitative assessment of how rocking influences friction during sliding. The kinetic equations were developed, accounting for the friction coefficient's velocity weakening effect. The model's precision and dependability were confirmed by comparing simulation results against experimental data. Furthermore, the study discovered that the Stribeck model presents benefits when compared to alternative models. Investigations were carried out to examine how rocking parameters affect axial friction during rocking motions. The findings indicate that variations in axial friction forces are predominantly observed during the phase of tangential acceleration. Crucially, the research demonstrates that modulating the rocking velocity's waveform can markedly decrease the average axial friction, even when the maximum rocking speeds remain the same.

Optimization of Laser-Based Method to Conduct Skin Ablation in Zebrafish and Development of Deep Learning-Based Method for Skin Wound-Size Measurement

Skin plays an important role as a defense mechanism against environmental pathogens in organisms such as humans or animals. Once the skin integrity is disturbed by a wound, pathogens can penetrate easily into a deeper part of the body to induce disease. By this means, it is important for the skin to regenerate quickly upon injury to regain its protective barrier function. Traditionally, scientists use rodents or mammals as experimental animals to study skin wound healing. However, due to concerns about animal welfare and increasing costs of laboratory animals, such as rodents, scientists have considered alternative methods of implementing replace, reduce, and refine (3Rs) in experimentation. Moreover, several previous studies on skin wound healing in fish used relatively expensive medical-grade lasers with a low calculation efficiency of the wound area, which led to human judgment errors. Thus, this study aimed to develop a new alternative model for skin wound healing by utilizing zebrafish together with a new rapid and efficient method as an alternative in investigating skin wound healing. First, in order to fulfill the 3Rs concept, the pain in the tested zebrafish was evaluated by using a 3D locomotion assay. Afterward, the obtained behavior data were analyzed using the Kruskal–Wallis test, followed by Dunn’s multiple comparisons tests; later, 3 watts was chosen as the power for the laser, since the wound caused by the laser at this power did not significantly alter zebrafish swimming behaviors. Furthermore, we also optimized the experimental conditions of zebrafish skin wound healing using a laser engraving machine, which can create skin wounds with a high reproducibility in size and depth. The wound closure of the tested zebrafish was then analyzed by using a two-way ANOVA, and presented in 25%, 50%, and 75% of wound-closure percentages. After imparting wounds to the skin of the zebrafish, wound images were collected and used for deep-learning training by convolutional neural networks (CNNs), either the Mask-RCNN or U-Net, so that the computer could calculate the area of the skin wounds in an automatic manner. Using ImageJ manual counting as a gold standard, we found that the U-Net performance was better than the Mask RCNN for zebrafish skin wound judgment. For proof-of-concept validation, a U-Net trained model was applied to study and determine the effect of different temperatures and the administration of antioxidants on the skin wound-healing kinetics. Results showed a significant positive correlation between the speed of wound closure and the exposure to different temperatures and administration of antioxidants. Taken together, the laser-based skin ablation and deep learning-based wound-size measurement methods reported in this study provide a faster, reliable, and reduced suffering protocol to conduct skin wound healing in zebrafish for the first time.

The Project-Based Learning Model for Javanese Language in Kurikulum Merdeka

The purpose of this research is to present the implementation of a project-based learning model in Javanese language subjects. Descriptive qualitative method is used as the procedural steps in this research. Data in the research are collected through interview techniques, observations, and documentation. The data analysis technique used is Miles and Huberman's, which involves the steps of 1) data collection, 2) data reduction, 3) data presentation, and 4) data conclusion. Informants include the school principal, teachers, and students. The results of this research show that the project-based learning model is implemented for the wayang (traditional Javanese puppet) material. The findings indicate that the Project-Based Learning Model is very suitable as an alternative Javanese language learning model in the Merdeka Curriculum. This Project-Based Learning Model for Javanese language is implemented by preparing students of class VII F, arranging activity schedules, supervising the implementation, assessing students, and conducting evaluations.

Transforming homeownership: an innovative financing model with a future value approach

Purpose This study aims to address the critical need for innovative financing solutions in the global housing sector, focusing specifically on Malaysia’s distinct housing finance system encompassing both conventional and Islamic loans. The primary objective is to develop a transformative housing finance model that addresses affordability challenges and reshapes the Malaysian housing landscape. Design/methodology/approach The study presents an alternate housing finance model for Malaysia, integrating lower monthly payments and reduced household debt. Key variables include house price appreciation rates, interest rates, initial guarantee fees and loan-to-value ratios. Inspired by the Help to Buy (HTB) scheme, the model aligns with proven global initiatives for enhanced affordability, balancing payment amounts, loan interest rates and acceptable price thresholds. Findings The study’s findings promise to address affordability disparities and reshape Malaysia’s housing finance landscape. The emphasis is on introducing a structured repayment plan that offers a sustainable path to homeownership, particularly for low-income families. Incorporating the future value adaptation concept, inspired by reverse mortgages and Islamic finance, enhances adaptability, ensuring long-term sustainability despite economic shifts. Practical implications The proposed model promotes widespread access to homeownership, offering practical solutions for policymakers to improve affordability, prompting adaptable risk management strategies for financial institutions and empowering potential homebuyers with increased flexibility. Originality/value The study introduces a transformative housing finance model for Malaysia, merging elements from reverse mortgages, Islamic finance and the HTB scheme, offering potential applicability to similar systems globally.

Using Quality Improvement as a Mechanism for Fostering Partnerships and Promoting Equity in a Health System Change Model.

Quality improvement (QI) processes provide a framework for systematically examining target outcomes and what changes can be made to result in improvement and ensure equity. We present a case study of how QI processes were used as a means of partnership building to enhance equity in designing materials for a Medicaid pilot program, North Carolina Integrated Care for Kids (NC InCK). The NC InCK model addresses social determinants of health by providing structured care integration across core child health and social service areas and using an alternative payment model to incentivize high quality child outcomes. During the two-year planning period prior to the NC InCK model launch, we used Plan-Do-Study-Act (PDSA) cycles to conduct usability testing as a QI strategy for a component of the NC InCK model: the Shared Action Plan (SAP). We conducted usability testing with four Family Council members, nine care managers, and one physician. Participants reviewed the SAP and provided feedback via a survey. After reviewing feedback with InCK leadership and the Family Council, we implemented recommendations that led to a SAP that uses clear and accessible language, that highlights family strengths and family-identified goals, and that is distinct from other care management plans. Usability testing forced refinement of materials before NC InCK launched, created opportunities for building and enhancing community partnerships and promoted equity within the NC InCK team and Family Council by considering multiple perspectives when deciding on SAP revisions.

Economic uncertainty and stock market asymmetric volatility: analysis based on the asymmetric GARCH-MIDAS model

PurposeWe aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.Design/methodology/approachWe construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.FindingsNegative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.Research limitations/implicationsMany GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.Practical implicationsOur conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.Social implicationsFirst, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.Originality/valueThis study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Do search queries predict violence against women? A forecasting model based on Google Trends

AbstractThis paper introduces a new indicator for reported intimate partner violence against women based on search query time series from Google Trends. This indicator is built up from the relative popularity of three topic‐related keywords. We propose a predictive model based on this specific Google index that is assessed relative to two alternative models: the first one includes the lagged variable, while the second one considers fatalities as a predictor. This comparative analysis is run in two different samples, whether the reported cases are a direct consequence of a violent direct or not. Our results show that the predictive model based on Google data significantly outperforms the other two models, regardless the sample and the forecast horizon. Then, using information gathered from Google queries may improve the allocation and management of resources and services to protect women against this form of violence and to improve risk assessment.

Trophic cascades within and across ecosystems: The role of anti-predatory defences, predator type and detritus quality.

Species in one ecosystem can indirectly affect multiple biodiversity components and ecosystem functions of adjacent ecosystems. The magnitude of these cross-ecosystem effects depends on the attributes of the organisms involved in the interactions, including traits of the predator, prey and basal resource. However, it is unclear how predators with cross-ecosystem habitat interact with predators with single-ecosystem habitat to affect their shared ecosystem. Also, unknown is how such complex top-down effects may be mediated by the anti-predatory traits of prey and quality of the basal resource. We used the aquatic invertebrate food webs in tank bromeliads as a model system to investigate these questions. We manipulated the presence of a strictly aquatic predator (damselfly larvae) and a predator with both terrestrial and aquatic habitats (spider), and examined effects on survival of prey (detritivores grouped by anti-predator defence), detrital decomposition (of two plant species differing in litter quality), nitrogen flux and host plant growth. To evaluate the direct and indirect effects each predator type on multiple detritivore groups and ultimately on multiple ecosystem processes, we used piecewise structural equation models. For each response variable, we isolated the contribution of different detritivore groups to overall effects by comparing alternate model formulations. Alone, damselfly larvae and spiders each directly decreased survival of detritivores and caused multiple indirect negative effects on detritus decomposition, nutrient cycling and host plant growth. However, when predators co-occurred, the spider caused a negative non-consumptive effect on the damselfly larva, diminishing the net direct and indirect top-down effects on the aquatic detritivore community and ecosystem functioning. Both detritivore traits and detritus quality modulated the strength and mechanism of these trophic cascades. Predator interference was mediated by undefended or partially defended detritivores as detritivores with anti-predatory defences evaded consumption by damselfly larvae but not spiders. Predators and detritivores affected ecosystem decomposition and nutrient cycling only in the presence of high-quality detritus, as the low-quality detritus was consumed more by microbes than invertebrates. The complex responses of this system to predators from both recipient and adjacent ecosystems highlight the critical role of maintaining biodiversity components across multiple ecosystems.

Use - clean - repeat: Understanding user, product, and context to design for long-term reuse

With escalating concerns about pollution and resource depletion caused by single-use products, the need to adopt reusable alternatives is widely acknowledged. This paper presents an investigation into the barriers and motivators to the long-term use of reusable products. The qualitative research consists of thirty-two semi-structured interviews with consumers, addressing the acquisition, usage, and discontinuation of the use of reusable products. From the results, we distinguished four product categories - intimate care, daily shopping, at home, and on the go - providing tailored insights into specific barriers. Next to this, we argue that willingness, ability, and routine are needed to increase the chances of successful long-term reuse. Based on these insights, we developed suggestions for designers including several design strategies and intervention points. We recommend incorporating the suggested product categories into future research, delving into persistent usage thresholds through case studies. Besides this, alternative reuse models should be further explored.

A triangular model of fractal growth with application to adsorptive spin-coating of polymers.

Over the last 40 years, applied mathematicians and physicists have proposed a number of mathematical models that produce structures exhibiting a fractal dimension. This work has coincided with the discovery that objects with fractal dimension are relatively common in the natural and human-produced worlds. One particularly successful model of fractal growth is the diffusion limited aggregation (DLA) model, a model as notable for its simplicity as for its complex and varied behavior. It has been modified and used to simulate fractal growth processes in numerous experimental and empirical contexts. In this work, we present an alternative fractal growth model that is based on a growing mass that bonds to particles in a surrounding medium and then exerts a force on them in an iterative process of growth and contraction. The resulting structure is a spreading triangular network rather than an aggregate of spheres, and the model is conceptually straightforward. To the best of our knowledge, this model is unique and differs in its dynamics and behavior from the DLA model and related particle aggregation models. We explore the behavior of the model, demonstrate the range of model output, and show that model output can have a variable fractal dimension between 1.5 and 1.83 that depends on model parameters. We also apply the model to simulating the development of polymer thin films prepared using spin-coating which also exhibit variable fractal dimensions. We demonstrate how the model can be adjusted to different dewetting conditions as well as how it can be used to simulate the modification of the polymer morphology under solvent annealing.