Interactive Model Research Articles

Method of experimental modeling of contact interaction in a worm – worm wheel pair

Method of experimental modeling of contact interaction in a worm – worm wheel pair

Enhancing Nahwu Mastery: Implementation of the Card Sort Method in Madrasah Aliyah

The Card Sort method is one of the learning methods that encourages students to actively participate in learning. This study aims to describe the implementation of the card sort method in Nahwu learning, map the supporting and inhibiting factors of the application of the card sort method in Nahwu learning and explore student perceptions of the card sort method in Nahwu learning at Madrasah Aliyah Al-Hidayah Karangploso Malang. This research applies qualitative descriptive research method. Data collection using observation, and documentation. The data analysis used is in the form of Interactive models Miles, Huberman, and Saldana, which include the stages of data condensation, data presentation, and conclusions. The implementation of the card sort method in Nahwu learning at Madrasah Aliyah Al-Hidayah Karangploso Malang shows positive potential. In the implementation of this learning, of course, there are supporting factors and inhibiting factors. Students respond positively to the use of this method. Students find learning Nahwu with the card sort method fun, helps understand the material faster, and increases their active involvement in the learning process

Dampak Perjudian Online Slot di Kalangan Pemuda Terhadap Semangat Kerja di Kecamatan Cisalak

The aim of this research is to describe the consequences of online slot gambling on the work spirit of youth in Cisalak District, Subang Regency. This study applies a qualitative approach to the form of descriptive research. The data collection methods used included observation and interviews, applying purposive sampling techniques for selecting informants. Data analysis was carried out by adopting an interactive model improved by Miles and Huberman. The results of the study show that young people in Cisalak District have knowledge about online slot gambling, and some of them have fallen into this practice, experiencing dependence which has resulted in decreased morale.

The Effect of Multilateral Economic Cooperation on Sustainable Natural Resource Development

The relationship between natural resource development and sustainable development has long been a focus in academia. In the context of a new global economic cooperation system, many scholars argue that such cooperation can lead to a “resource curse” effect in partner countries, hindering their sustainable development. This study analyzed panel data from 64 countries from 2008 to 2020, using the Belt and Road Initiative as a representative of multilateral economic cooperation (MEC) policies. The aim was to examine the actual impact of multilateral economic cooperation on the sustainable development levels of partner countries and to explore the underlying mechanisms influencing these outcomes. First, we measured and identified the sustainable development index (SDI) under natural resource development schemes and the “resource curse” effect in these countries. Then, we employed a double machine learning approach to evaluate the policy effects of MEC on sustainable resource development. We constructed an interactive double machine learning model to examine and validate the specific mechanisms of resource development effects. The results indicate that the level of sustainable resource development in MEC countries is relatively low, and a “resource curse” effect already exists. However, participating in MEC suppresses this “curse” effect. By promoting innovation cooperation, institutional improvement, structural optimization, trade openness, and pollution reduction, MEC effectively enhances the sustainable development levels of partner countries.

3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Despite that the segment anything model (SAM) achieved impressive results on general-purpose semantic segmentation with strong generalization ability on daily images, its demonstrated performance on medical image segmentation is less precise and unstable, especially when dealing with tumor segmentation tasks that involve objects of small sizes, irregular shapes, and low contrast. Notably, the original SAM architecture is designed for 2D natural images and, therefore would not be able to extract the 3D spatial information from volumetric medical data effectively. In this paper, we propose a novel adaptation method for transferring SAM from 2D to 3D for promptable medical image segmentation. Through a holistically designed scheme for architecture modification, we transfer the SAM to support volumetric inputs while retaining the majority of its pre-trained parameters for reuse. The fine-tuning process is conducted in a parameter-efficient manner, wherein most of the pre-trained parameters remain frozen, and only a few lightweight spatial adapters are introduced and tuned. Regardless of the domain gap between natural and medical data and the disparity in the spatial arrangement between 2D and 3D, the transformer trained on natural images can effectively capture the spatial patterns present in volumetric medical images with only lightweight adaptations. We conduct experiments on four open-source tumor segmentation datasets, and with a single click prompt, our model can outperform domain state-of-the-art medical image segmentation models and interactive segmentation models. We also compared our adaptation method with existing popular adapters and observed significant performance improvement on most datasets. Our code and models are available at: https://github.com/med-air/3DSAM-adapter

DEVELOPING VIRTUAL LEARNING MODELS TO ENHANCE CRITICAL THINKING AND MATERNAL NURSING PRACTICE COMPETENCY

The COVID-19 pandemic has significantly impacted nursing education, necessitating the development of virtual learning models and media to improve critical thinking and maternal nursing competencies. This study aimed to develop an interactive virtual learning model based on problem-based learning and to assess its effectiveness in enhancing nursing students' critical thinking skills in maternal nursing practice. The development model (Define, Design, Develop, and Disseminate) was applied to create a virtual learning model. Data was collected using questionnaires to assess the validity and practicality of the developed model. The results demonstrated that the virtual learning model developed using the problem-based learning approach was valid for application in the learning process. After testing, the virtual learning model was found to be practical and effective in optimizing the implementation of learning and in improving student learning outcomes. The study concluded that the developed virtual learning model is a valid and practical tool for enhancing critical thinking skills and maternal nursing practice competencies. These findings contribute to addressing the knowledge gap in the literature regarding the effectiveness of virtual learning models in improving maternal nursing practice competencies, particularly in the context of critical thinking. This study highlights the importance of integrating technology and innovative learning approaches to adapt to the challenges posed by the COVID-19 pandemic and prepare nursing students for the demands of the 21st century.

Female officials in Europe and their sport’s diversity climate

ABSTRACT Research Question Drawing from the Interactional Model of Cultural Diversity, the purpose of this study was to examine how individual-, interpersonal-, and sport-level factors related to female officials’ perceptions of their sport’s diversity climate. Research Methods The authors draw on data from a comprehensive, European-based survey of female officials in various sports. Respondents reported about their officiating biography, characteristics of their main sport, and individual characteristics (n = 3,214). Information about a sport’s level of subjectivity and contact with athletes was added to the data. Diversity climate was assessed using the mean of a 12-item scale. Results and Findings The results of regression analyses show that years officiating, officiating with more male than female officials, and education all held negative associations with the sport’s diversity climate. On the other hand, the presence of a mentor was positively associated with diversity climate. Implications Collectively, the findings suggest that different factors shape female officials’ perceptions of the diversity climate in their sport. Sport organizations need to be aware of these factors and develop measures to improve the diversity climate for female officials and ultimately foster their retention in the sport.

Perinatal Predictors and Mediators of Attachment Patterns in Preschool Children: Exploration of Children's Contributions in Interactions with Mothers.

Insecure and disorganized attachment patterns in children are linked to poor health outcomes over the lifespan. Attachment patterns may be predicted by variables that influence the quality of children's interactions with their primary caregivers/parents (usually mothers) such as prenatal and postnatal exposures and the children's own behaviours in interactions. The purposes of this exploratory study were to examine: (1) prenatal predictors of children's attachment patterns, and (2) postnatal mediators and moderators of associations between prenatal predictors and children's attachment patterns, with adjustment for relevant covariates. Mother-child dyads (n = 214) from the longitudinal Alberta Pregnancy Outcomes and Nutrition (APrON) cohort were studied using valid and reliable measures. Hayes' mediation analysis was employed to determine direct and indirect effects. Mothers' prenatal cortisol levels directly predicted disorganized (versus organized) child attachment in unadjusted models. Children's passivity (in adjusted models) and compulsivity (in unadjusted and adjusted models) in parent-child interactions mediated the pathway between mothers' prenatal cortisol levels and children's disorganized attachment patterns. Serial mediation analyses revealed that mothers' cortisol levels predicted their children's cortisol levels, which predicted children's compulsivity, and, ultimately, disorganized attachment in both unadjusted and adjusted models. No predictors were correlated with children's insecure (versus secure) attachment. This exploratory research suggests that prenatal exposure to mothers' cortisol levels and children's behavioural contributions to parent-child interaction quality should be considered in the genesis of children's attachment patterns, especially disorganization. Interventions focused on parent-child interactions could also focus on addressing children's behavioral contributions.

Research on the water-ground multimodal transport emergency scheduling model and decision-making method considering the actual road network inundation situation.

As urbanization continues to accelerate worldwide, urban flooding is becoming increasingly destructive, making it important to improve emergency scheduling capabilities. Compared to other scheduling problems, the urban flood emergency rescue scheduling problem is more complicated. Considering the impact of a disaster on the road network passability, a single type of vehicle cannot complete all rescue tasks. A reasonable combination of multiple vehicle types for cooperative rescue can improve the efficiency of rescue tasks. This study focuses on the urban flood emergency rescue scheduling problem considering the actual road network inundation situation. First, the progress and shortcomings of related research are analyzed. Then, a four-level emergency transportation network based on the collaborative water-ground multimodal transport transshipment mode is established. It is shown that the transshipment points have random locations and quantities according to the actual inundation situation. Subsequently, an interactive model based on hierarchical optimization is constructed considering the travel length, travel time, and waiting time as hierarchical optimization objectives. Next, an improved A* algorithm based on the quantity of specific extension nodes is proposed, and a scheduling scheme decision-making algorithm is proposed based on the improved A* and greedy algorithms. Finally, the proposed decision-making algorithm is applied in a practical example for solving and comparative analysis, and the results show that the improved A* algorithm is faster and more accurate. The results also verify the effectiveness of the scheduling model and decision-making algorithm. Finally, a scheduling scheme with the shortest travel time for the proposed emergency scheduling problem is obtained.

The Mosque as a Source of Community Prosperity: Lessons from the Jogokariyan Mosque

The research was conducted to analyze the role of programs to increase the independency and prosperity of community held by the Jogokariyan Mosque in Special Region of Yogyakarta. The research methode is qualitative method with the approach of Interactive Model Analysis was used along with the observation during the period of January, 2022 until March 2022. The study showed that Jogokariyan Mosque conducted programs in field of social, economic, health, education and covid-19 pandemic handling. In the social Jogokariyan Mosque’s have program Jogokaryan Ramadhan village, Jogokariyan Mosque’s Rice ATM, and Jogokariyan’s Public Market. In the economics Jogokariyan Mosque’s have program the development of Small Micro and Medium Enterprises (SMME), At the during the covid-19 pandemic Jogokariyan Mosque’s Special Program. Jogokariyan Mosque programs could be used as a lesson learned on how a mosque could improve its role in the community to accelerated the increase of community prosperity.

Social mix and social interaction: evidence from Los Angeles County

Research shows that policy tools to reduce residential segregation are also effective to reduce economic inequality and, for decades, achieving the adequate level of 'social mix' has been an important policy goal in housing and community policy fields. Yet whether social mix creates social interactions, thus producing favourable social outcomes, is still disputed. This study aims to expand the empirical record on the modus operandi of social mix and its policy viability, and to provide useful information on relevant contextual factors to prescribe effective social mix policies to improve social interaction. We fit interactive linear models to data from Los Angeles County in California, USA, to test the hypothesis that social mix (measured via residential income mix) promotes social interactions (in the form of civic, daily-life, and political activities and group memberships), and to examine whether arts and recreation centres (i.e. the places where social interactions occur to produce social mix) moderate the effect of residential income mix on favourable social outcomes. Results show that while residential income mix is negatively associated with social interactions, recreation centres help income-mixed communities increase social interactions among their residents. We also find evidence that communities with higher income mix levels manifest higher social interaction as there are more arts and recreation centres in their communities. Our findings shed light on why social mix policy works in some communities but does not work in others, elucidating why previous research displays conflicting claims.

Divergent effects of visual interfaces on teleoperation for challenging jobsite environments

In challenging work environments, teleoperation has been adopted for executing tasks over long distances, ensuring worker safety off-site. The physical distance from jobsites typically poses challenges to teleoperators, limiting their cognition and perception of sites. Particularly, these human-machine interface challenges vary depending on the work environment conditions. This paper analyzes the impact of different visual interfaces on teleoperators and their work performance in challenging jobsite environments, using interactive workplace modeling and simulation to execute teleoperation tasks. Based on experiments with 33 subjects in construction-related fields with industrial experience, the study observed data overload problems and distraction with effects varying by work environment. Additionally, the analysis includes how their eye gaze patterns could demonstrate these effects. The findings contribute valuable insights into human factors crucial for designing user-centered teleoperation interfaces in construction, forming the basis for an intuitive and informative interface design in task-specific settings.

Achievement of safer learning facilities standards in the disaster safe education unit program at Panggang elementary school

This study aims to discover and describe the achievement of safer learning facility standards for the disaster safe education unit program at Panggang elementary school, Bambanglipuro. This study is a descriptive evaluative research mixed methods approach with a sequential explanatory strategy. The sampling technique was carried out with saturated samples. Data collection techniques used observation, interviews, documentation studies, and questionnaires. Data validity uses internal validation, technical triangulation, and source triangulation. Quantitative data analysis uses a percentage formula calculation according to Sugiyono, while qualitative data analysis uses an interactive analysis model. However, each aspect still has gaps. The gaps that occur are not too significant, but still affect the achievement of safer learning facilities. Efforts are needed from Panggang elementary school Bambanglipuro to reduce or even eliminate existing gaps so that safe learning facilities in the disaster safe education unit program can be fully achieved. Keywords: program evaluation, disaster safe education unit program, safer learning facilities

Interactive Learning Model to Improve Student Activities and Learning Outcomes of SMP Negeri 29 Makassar

The educational process in higher education institutions no longer only prioritizes the acquisition of information, but rather focuses more on the development of skills and information processing. Therefore, it is necessary to increase student activity through group exercises or assignments and expression of ideas to peers. This has attracted the attention of researchers to observe how students learn in class when given an interactive learning model that is different from conventional methods. Based on the results of observations in class IX.6 SMP 29 Makassar, a problem was found where the monotonous learning process by the teacher and the initial pretest showed several students with low (D) and failed (E) scores. It can be concluded that the low learning outcomes are also influenced by the lack of student learning activities. This type of research is Classroom Action Research (CAR) with subjects of class IX.6 SMP 29 Makassar students. The research was conducted for two cycles with four meetings. The results of the study indicate that the application of an interactive learning model can improve student learning activities in the Introduction to Education course in Biology B class, Patompo University. The average percentage of student learning activities in cycle I was 56.55%, increasing to 81.55% in cycle II. Therefore, there was an increase of 25.00% from cycle I to cycle II. In addition, the use of interactive learning models also had a positive impact on student learning outcomes. The average post-test score of students in cycle I was 70, increasing to 81.43 in cycle II. Thus, there was an increase in the average value of learning outcomes of 11.43% from cycle I to cycle II.

Strategy For Development Of The Kampung Empon-Empon Program In Ngalian Widodomartani Village

This study aims to Assess the potential and activities that supports the Ngalian Empon-empon Village and also develop strategies needed for the development of the Empon-empon Kampung Program. This research is a descriptive research with a qualitative approach to the type of case study research. The data sources used are primary data and secondary data. Data collection techniques using interview techniques, observation, and documentation. Data validity using source triangulation. Data analysis techniques use interactive models, namely collecting data, reducing data, presenting data as well as drawing conclusions and verification. The result of this research are The potential that supports the Ngalian empon-empon village program includes physical and non-physical potential. Activities that have been carried out in the Empon-empon Village Program include planting empon-empon by utilizing the land in the yard of the house, planting empon-empon in demonstration plots for each RT and making processed empon-empon in the form of simplicia, pure powder, instant or syrup. The strategy needed for the development of the Empon-empon village program is the establishment of the Ngalian Empon-empon education village.

The Impact of Land Transfer on Sustainable Agricultural Development from the Perspective of Green Total Factor Productivity

China’s agricultural sector is transitioning from extensive management to intensive management, and land transfer brings about changes in land use and management methods, which may encourage the agricultural sector to enter a sustainable development track, but this mechanism has not been effectively proven. Using the SBM-GML index to construct a green total factor productivity index to measure the level of sustainable agricultural development in each province (or autonomous region or municipality directly under the central government) and provincial panel data from 2010 to 2022, we applied a panel interactive fixed-effects model to empirically test the impact of land transfer on sustainable agricultural development, with a focus on analyzing the heterogeneity and related mechanisms of this impact. The results indicate that (1) land transfer significantly promotes sustainable agricultural development, and this conclusion still held true after robustness tests such as controlling for regional omitted variables, replacing dependent variables, changing the sample size, IV estimation, and GMM estimation. (2) The mechanism testing found that land transfer mainly promotes sustainable agricultural development by increasing the desirable output, and has no significant effect on reducing non-point source pollution. At the same time, land transfer mainly improves the desirable output through factor allocation effects rather than scale operation effects, thereby promoting sustainable agricultural development. (3) The heterogeneity analysis found that the higher the quantile of agricultural development level is, the weaker the role of land transfer in promoting sustainable agricultural development, indicating that land transfer has a greater impact on areas with poor agricultural development foundations, and areas with poor agricultural development foundations are more likely to obtain sustainable development space through land transfer. The impact of different land transfer methods and land transfer objects on sustainable agricultural development was heterogeneous. Compared with non-market transfer methods such as exchange and transfer, market-oriented transfer methods such as leasing and equity had a more significant impact on sustainable agricultural development. Compared to transferring land to ordinary farmers, transferring land to new business entities such as family farms, professional cooperatives, and enterprises can significantly promote sustainable agricultural development.

Dynamic tank-in-series modelling and simulation of gas-liquid interaction in trickle bed reactor designed for gas fermentation

Trickle bed reactors (TBR), historically utilized in petroleum processing and wastewater treatment, now extend their applicability in biological gas conversions, including syngas biomethanation for renewable methane production. Despite operational benefits, optimizing TBR design and scale-up demands a good understanding of the reactor's hydraulic behavior and mass transfer phenomena. This study's novelty is TBR's hydraulic characterization in respect to liquid and gas flowrates and simulation of the gas-liquid interaction by a dynamic gas-liquid transfer model. Residence time distribution (RTD) experiments in 220 mL lab- and 5000 mL pilot-scale TBRs with co-current flow of gas and liquid were conducted to determine the liquid and gas working volume and the number of tanks for a dynamic tank-in-series (TIS) model. RTD experiments revealed 2–6 tanks for varying liquid flowrate (constant gas flowrate) and 5–8 tanks for varying gas flowrate (constant liquid flowrate). A dimensionless equation, fitted to RTD experimental data, predicted the liquid working volume of a TBR at various liquid flowrates and reactor configurations. TBR simulation by TIS model considering 8 well mixed gas and liquid phase tanks connected in series, resulted in an excellent model validation with an R2 at 0.99. Finally, the model simulated the mass transfer kinetics of H2, CO, and CO2 in water under varying gas and liquid flowrates for lab- and pilot-scale TBRs. Simulation results showed increased dissolved gas concentration with higher gas flowrate (constant liquid flowrate) for both scales TBR. It was also noticeable that under constant gas flowrate, the dissolved gas concentration initially decreased (0.01 < ReL < 17), then increased (17 < ReL < 34), and again decreased (34 < ReL < 105). This behavior was the same for both scales TBR and revealed an optimum ReL value irrespective of TBR size.

Optimized scheduling study of integrated energy system considering user response characteristics

ABSTRACT Integrated Energy Systems (IES) can effectively promote the utilization of renewable energy. Reducing the impact of uncertainties and achieving energy supply-demand balance has always been a key issue in energy scheduling. However, existing research often focuses only on energy prices when designing demand response strategies, neglecting user response characteristics, particularly the influence of environmental temperature and user consumption levels. Therefore, this paper proposes an IES optimization scheduling model that considers user load response characteristics, analyzing changes in user response loads under different environmental and consumption levels. Additionally, consumption levels and environmental parameters are introduced to build an interactive response model. Different incentive measures are designed based on load types to guide users in adjusting their electricity usage behavior, optimizing the supply-demand curve. Furthermore, to address source-load uncertainties, a two-stage robust optimization model is constructed and solved iteratively using the column-and-constraint generation (C&CG) algorithm. The results indicate that considering user response characteristics reduces the peak-to-valley differences in electrical, thermal, and cooling loads by 18.6%, 7.0%, and 13.3% respectively, and reduces total costs by 8.9%. This model can ensure reliable operation while improving the economic efficiency of the system.

Benchmarking of hydrodynamic plasma waveguides for multi-GeV laser-driven electron acceleration

Hydrodynamic plasma waveguides initiated by optical field ionization have recently become a key component of multi-GeV laser wakefield accelerators. Here, we present the most complete and accurate experimental and simulation-based characterization to date, applicable to current multi-GeV experiments and future 100 GeV-scale laser plasma accelerators. Crucial to the simulations is the correct modeling of intense Bessel beam interaction with meter-scale gas targets, the results of which are used as initial conditions for hydrodynamic simulations. The simulations are in good agreement with our experiments measuring evolving plasma and neutral hydrogen density profiles using two-color short pulse interferometry, enabling realistic determination of the guided mode structure for application to laser-driven plasma accelerator design. Published by the American Physical Society 2024

Digitally enhanced lubricant evaluation and improvement framework through developing digital characteristics (DC) for hot forging of aluminium alloys

The manufacturing sector is experiencing a never-before-seen surge in data generation, acquisition, and analytics. The promising potential of fundamental research following a data-driven approach may enable a more comprehensive understanding of forming operations and efficient optimisation of component quality. However, as a crucial component of metal forming operations, the investigation and insights from a data-centric perspective of hot forging processes is still absent. In the present study, the digital characteristics (DC) of the hot forging process was generated based on voluminous metadata extracted from experimentally verified FE simulations and localised sensors. Inherent and distinctive manufacturing nature throughout the life cycle of a hot-forged product have been revealed, spanning over the design, manufacturing, and application stages. The tribological DC was then extracted and analysed, and the data-guided interactive friction modelling was established to enable a digitally enhanced evaluation and improvement scheme of the lubricant product applied during the hot forging process. Significant potential has been demonstrated in implementing data-centric innovation techniques into traditional manufacturing paradigms to improve efficiency and process effectiveness.