Description Of Model Research Articles

Assessing groundwater quality and its association with child undernutrition in India

Background and objectivesGroundwater contamination poses a significant health challenge in India, particularly impacting children. Despite its importance, limited research has explored the nexus between groundwater quality and child nutrition outcomes. This study addresses this gap, examining the association between groundwater quality and child undernutrition, offering pertinent insights for policymakers. Data and methodsThe study uses data from the fifth round of the National Family Health Survey (NFHS) and the Central Groundwater Board (CGWB) to analyze the association between groundwater quality and child nutritional status. The groundwater quality data were collected by nationwide monitoring stations programmed by CGWB, and the child undernutrition data were obtained from the NFHS-5, 2019–21. The analysis included descriptive and logistic regression model. The study also considers various demographic and socio-economic factors as potential moderators of the relationship between groundwater quality and child undernutrition. FindingsSignificant variation in groundwater quality was observed across India, with numerous regions displaying poor performance. Approximately 26.53 % of geographical areas were deemed unfit for consuming groundwater. Environmental factors such as high temperatures, low precipitation, and arid, alluvial, laterite-type soils are linked to poorer groundwater quality. Unfit-for-consumption groundwater quality increased the odds of undernutrition, revealing a 35 %, 38 %, and 11 % higher likelihood of stunting, underweight, and wasting in children, with higher pH, Magnesium, Sulphate, Nitrate, Total Dissolved Solids, and Arsenic, levels associated with increased odds of stunting, underweight, and wasting. Higher temperatures (>25 °C), high elevations (>1000 m), and proximity to cultivated or industrial areas all contribute to heightened risks of child undernutrition. Children consuming groundwater, lacking access to improved toilets, or living in rural areas are more likely to be undernourished, while females, higher-income households, and those consuming dairy, vegetables, and fruits daily exhibit lower odds of undernutrition. Policy implicationsPolicy implications highlight the urgent need for investment in piped water supply systems. Additionally, focused efforts are required to monitor and improve groundwater quality in regions with poor water quality. Policies should emphasize safe sanitation practices and enhance public awareness about the critical role of safe drinking water in improving child health.

Chaotic neural network algorithm with competitive learning integrated with partial Least Square models for the prediction of the toxicity of fragrances in sanitizers and disinfectants

This study addresses the need for accurate structural data regarding the toxicity of fragrances in sanitizers and disinfectants. We compare the predictive and descriptive (model stability) potential of multiple linear regression (MLR) and partial least squares (PLS) models optimized through variable selection (VS). A novel hybrid chaotic neural network algorithm with competitive learning (CCLNNA)–PLS modeling strategy can offer specific optimization with satisfactory results, even for a limited dataset. While also exploring the preliminary comparative analysis, the goal is to introduce an adapted novel CCLNNA optimization strategy for VS, inspired by neural networks, along with exploring the influence of the percentage of significant descriptors in the optimization function to enhance the final model's capabilities.We analyzed an available dataset of 24 molecules, incorporating ADMET and PaDEL descriptors as predictor variables, to explore the relationship between the response/target variable (pLC50) and the meticulously optimized set of descriptors. The suitability of the selected PLS models (cross- and external-validated accuracy combined with percentage of significant descriptors at a level equal to or >80 %) underscores the importance of expanding the dataset to amplify the validation protocols, thus enhancing future model reliability and environmental impact.

Combining descriptive and predictive modeling to systematically design depth filtration-based harvest processes for biologics.

Advances in upstream production of biologics-particularly intensified fed-batch processes beyond 10% cell solids-have severely strained harvest operations, especially depth filtration. Bioreactors containing high amounts of cell debris (more than 40% particles <10 µm in diameter) are increasingly common and drive the need for more robust depth filtration processes, while accelerated timelines emphasize the need for predictive tools to accelerate development. Both needs are constrained by the current limited mechanistic understanding of the harvest filter-feedstream system. Historically, process development relied on screening scale-down depth filter devices and conditions to define throughput before fouling, indicated by increasing differential pressure and/or particle breakthrough (measured via turbidity). This approach is straightforward, but resource-intensive, and its results are inherently limited by the variability of the feedstream. Semi-empirical models have been developed from first principles to describe various mechanisms of filter fouling, that is, pore constriction, pore blocking, and/or surface deposit. Fitting these models to experimental data can assist in identifying the dominant fouling mechanism. Still, this approach sees limited application to guide process development, as it is descriptive, not predictive. To address this gap, we developed a hybrid modeling approach. Leveraging historical bench scale filtration process data, we built a partial least squares regression model to predict particle breakthrough from filter and feedstream attributes, and leveraged the model to demonstrate prediction of filter performance a priori. The fouling models are used to interpret and provide physical meaning to these computational models. This hybrid approach-combining the mechanistic insights of fouling models and the predictive capability of computational models-was used to establish a robust platform strategy for depth filtration of Chinese hamster ovary cell cultures. As new data continues to teach the computational models, in silico tools will become an essential part of harvest process development by enabling prospective experimental design, reducing total experimental load, and accelerating development under strict timelines.

Simplifying Land Cover-Geoprocessing-Model Migration with a PAMC-LC Containerization Strategy in the Open Web Environment

Land cover and its changes over time are significant for better understanding the Earth’s fundamental characteristics and processes, such as global climate change, hydrology, and the carbon cycle. A number of land cover-geoprocessing models have been proposed for land cover-data production with different spatial and temporal resolutions. With the massive growth in land cover data and the increasing demand for efficient model utilization, developing efficient and convenient land cover-geoprocessing models has become a formidable challenge. Although some model-migration methods have been proposed for handling the massive data, the intricacy of land cover-data and -heterogeneity models frequently prevent current strategies from directly meeting demand. In this paper, we propose the PAMC-LC-containerization approach to overcome the difficulties associated with moving existing land cover models in the open web environment. Based on the idea of model migration, we design a standardized model description and hierarchical encapsulation strategy for land cover models, and develop migration and deployment methods. Furthermore, we assess the viability and efficacy of the proposed approach by using coupled workflows for model migration and the introduction of visualization on the Mts-WH dataset and the Google dataset. The experimental results show that the PAMC-LC approach can simplify and streamline the model migration process, with important ramifications for increasing productivity, reusing models, and lowering additional data-transmission costs.

Information Search Within a Web Page: Modeling the Full Sequence of Eye Movement Decisions, Subjective Value Updating, and First Clicks

Online retail settings often present shoppers with large, complex choice sets where they need to quickly and dynamically weigh the benefits and costs of search within each web page. We build a model of information search within a web page using eye-tracking data collected during two incentive-compatible online shopping experiments, in which participants browsed the websites of two different clothing retailers (Experiments 1 and 2), as well as previously reported data from a laboratory experiment involving choices among snack food assortments (Experiment 3). Our model incorporates features that build upon recent advances in descriptive and normative models of information sampling and search in psychology and economics. First, our model captures how people decide where to look by treating eye fixations on clickable options as a series of “split-second” decisions that depend on estimates of option attractiveness and navigation effort. Second, our model assumes that the value of each option is learned via Bayesian updating. Third, the choice to end search on the web page depends on a dynamic decision threshold. Our model outperforms benchmarks that assume random search, instant learning, fixed thresholds, nonheterogeneous thresholds, and stochastic accumulator stopping rules. Explicitly modeling the sequence of eye fixation decisions results in accurate counterfactual simulations of the effects of hypothetical product orderings on search duration and quality as verified using experimental manipulation, and it can be applied flexibly to a wide range of web-page layouts. Systematic differences across experiments highlight the importance of accounting for product familiarity, choice-set size, and the role of category outside options. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Funding: This work was supported by the Jay H. Baker Retailing Center and the Wharton Behavioral Lab at the University of Pennsylvania. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02983 .

Developing Arabic Grammar Materials Based on Contextual Learning at Islamic Boarding School in Indonesia

This study aims to describe the development of contextual-based supplementary Nahwu teaching materials in five pesantren in Central Kalimantan using the Matan al-Ajrumiyyah text. The research uses a descriptive qualitative and quantitative EDDIE model approach. The subjects are seven ustadz. Data were collected through observation, interviews, documentation, and questionnaires. Experts validated the teaching materials. Qualitative data were analyzed using Miles and Huberman's method, involving data reduction, display, and conclusion drawing. Quantitative data from questionnaires were analyzed using the mean formula. The analysis revealed a need to shift from traditional to contextual-based learning, leading to the development of supplementary Nahwu teaching materials. The design phase identified the learning experiences and specific skills needed by the students. The designed materials included introductions (apperception), examples, explanations, exercises, conclusions, and reflections. The development phase involved creating supplementary materials to achieve the learning objectives, along with determining strategies, methods, and media. Expert validation showed an average validity score of 3.71, with a validity rate of 92.75%, categorizing it as very valid and usable without revision. Theoretical implications suggest that contextual-based Nahwu learning helps learners understand Nahwu and apply Arabic communication. Educational institutions teaching Nahwu can implement contextual-based learning to facilitate students' application of Nahwu.

دور أدوات الذكاء الصناعي في تعزيز أساليب إدارة الموارد البشرية: دراسة تطبيقية لعينة من الجامعات الأهلية - جامعة الإمام الصادق وجامعة القلم

We specialize in searching for artificial intelligence tools combined in their three dimensions (Workday, ADP Workforce, WFM) in the field of administrative cooperation for human resources management (distinctive electronic communication method, talent management method, diverse skills development method) in Artica private universities, and the goal of the appropriate situation has been identified. The hypothetical, which was placed within scientific learning for my learning, then formulating research hypotheses and testing them using compatible statistical methods and using the statistical program (SPSS). In general, descriptive models were adopted to explain the specialized and analytical frameworks for the research movements, so that the study population consisted of employees at the two universities at the three administrative levels, and the sample size was (61) individuals from managers and directors of departments, divisions, and the three administrative units. The research reached several results, the most important of which was the existence of a significant correlation between smart tools and human resources management methods and their dimensions in the technical study community. Finally, I am completely confident in providing the basis for artificial intelligence tools for new operations through procedures for initiating cooperative operations and cooperating with optimal resources in order to advance and maintain survival and continuity, as well as methods of human resources management.

Mathematical model of single-channel search for signals of mobile radio communications with one degree of detection in the frequency-time domain.

In the context of a full-scale invasion and military operations for Ukraine's independence, the issues of radio monitoring of radio emission sources of telecommunication networks and systems are gaining special attention and require fundamentally new approaches to the level of informatization, technical implementation and increase of their efficiency. Today, the technical means of radio interception, monitoring and direction finding in the networks of mobile radio communication systems are realized in the form of software and hardware complexes, the most important performance indicators of which are considered to be speed, accuracy of detection and probability of recognition of mobile radio communication means with their information content. At the same time, these issues still remain problematic and require further development of methods and techniques for searching and detecting signals of mobile radio communications in both frequency and time telecommunication channels and their information processing. To solve this issue, the authors propose a mathematical model for searching for mobile radio signals in the frequency-time domain with one degree of detection. The description of the mathematical model for determining the spectral components of signals in the frequency and time domains is carried out using the basic provisions of the theory of directed probability graphs, geometric probabilities with its well-known problem of meeting in a given time interval, and the theoretical foundations of statistical information processing. The analysis of the proposed model shows that the probability of successful completion of the search for a signal with one degree of detection in the frequency-time domain for a given time depends on the value of the signal duration, the number of analyzed frequency channels, the time of signal analysis in each channel, and the probabilities of errors of the first and second kinds The article presents the results of calculations of the value of the probability of successful completion of the signal search as a function of the search time at different values of the analysis time. It is shown that the application of the mathematical model of single-channel search for signals of mobile radio communication means with one degree of detection in the frequency-time domain in practice will make it possible to determine the quality of the radio monitoring process and increase the efficiency of evaluating the spectral components of radio signals in terms of speed, detection accuracy and probability of recognition of mobile radio communication means with further determination of their information content.

Thermodynamics of a minimal interacting heat engine: Comparison between engine designs.

Collective effects stemming from many interacting units have attracted remarkable recent interest, not only for their presence in several systems in nature but also for the possibility of being used for the construction of efficient engine setups. Notwithstanding, little is known about the influence of the engine design, and most studies are restricted to the simplest cases (e.g., simultaneous contact with two thermal baths), not necessarily constituting a realistic setup implementation. In order to investigate the design and its influence on the performance, we introduce the collisional also referred as sequential description for a minimal model for interacting heat engines, composed of two coupled nanomachines placed in contact with a distinct thermal reservoir and subjected to a nonequilibrium work source at each stage. Thermodynamic quantities are exactly obtained irrespective of the model details. Distinct kinds of work sources are investigated and the influence of the interaction, temperature, period, and time asymmetry has been undertaken. Results show that a careful design of interaction provides superior performance than the interactionless case, including optimal power outputs and efficiencies at maximum power greater than known bounds or even the system presenting efficiencies close to the ideal (Carnot) limit. As a complementary analysis, we also show that the case of the system simultaneously placed in contact with two thermal reservoirs constitutes a particular case of our framework.

Radiomic score for lung nodules as a prognostic biomarker in locally advanced rectal cancer patients: A bi-institutional study.

Undetermined lung nodules are common in locally advanced rectal cancer (LARC) and lack precise risk stratification. This study aimed to develop a radiomic-based score (Rad-score) to distinguish metastasis and predict overall survival (OS) in patients with LARC and lung nodules. Retrospective data from two institutions (July 10, 2006-September 24, 2015) was used to develop and validate the Rad-score for distinguishing lung nodule malignancy. The prognostic value of the Rad-score was investigated in LARC cohorts, leading to the construction and validation of a clinical and radiomic score (Cli-Rad-score) that incorporates both clinical and radiomic information for the purpose of improving personalized clinical prognosis prediction. Descriptive statistics, survival analysis, and model comparison were performed to assess the results. The Rad-score demonstrated great performance in distinguishing malignancy, with C-index values of 0.793 [95% CI: 0.729-0.856] in the training set and 0.730 [95% CI: 0.666-0.874] in the validation set. In independent LARC cohorts, Rad-score validation achieved C-index values of 0.794 [95% CI: 0.737-0.851] and 0.747 [95% CI: 0.615-0.879]. Regarding prognostic prediction, Rad-score effectively stratified patients. Cli-Rad-score outperformed the clinicopathological information alone in risk stratification, as evidenced by significantly higher C-index values (0.735 vs. 0.695 in the internal set and 0.618 vs. 0.595 in the external set). CT-based radiomics could serve as a reliable and powerful tool for lung nodule malignancy distinction and prognostic prediction in LARC patients. Rad-score predicts prognosis independently. Incorporation of Cli-Rad-score significantly enhances the persionalized clinical prognostic capacity in LARC patients with lung nodules.

Epidemiological and clinical trends of visceral leishmaniasis in Portugal: retrospective analysis of cases diagnosed in public hospitals between 2010 and 2020

BackgroundLeishmania infantum is endemic in the Mediterranean region, presenting mostly as visceral leishmaniasis (VL). In Portugal, reporting of VL cases to public health authorities is mandatory, but significant underreporting is likely. This study aimed to describe the epidemiological and clinical aspects of the VL cases diagnosed in hospitals of the Portuguese National Health Service (NHS), between 2010 and 2020.MethodsCollaboration was requested to every hospital of the Portuguese NHS in Mainland Portugal. Cases were screened through a search of diagnostic discharge codes or, if not available, by a search of positive laboratory results for Leishmania infection. Sociodemographic and clinical data was retrieved from medical records. Simultaneously, the National Health authority was contacted to request access to data of notified cases of VL between 2010 and 2020. Descriptive, hypothesis testing and multiple binary logistic regression models were performed.ResultsA total of 221 VL cases were identified. A significant increase in estimated national incidence was seen in the years after 2016 (P = 0.030). VL was predominantly diagnosed in people living with HIV (PLWH) and in children (representing around 60% of the new cases), but the outcome was generally poorer in non-HIV patients with associated immunosuppression, with significantly lower rates of clinical improvement at 7 (P = 0.003) and 30 days (P = 0.008) after treatment. Atypical presentations, with gastrointestinal and/or respiratory involvement, were seen in 8.5% of VL cases. Hemophagocytic lymphohistiocytosis was diagnosed in 40.0% of children under 5 years of age. Only 49.7% of incident VL cases were reported. Simultaneous involvement of the skin was confirmed in 5.9% of patients.ConclusionsVL presents a continuing threat in Portugal, especially to PLWH and children, and an increasing threat to other immunosuppressed groups. Recent increases in incidence should be closely monitored to allow prompt interventions. Programs to control the disease should focus on providing tools for earlier diagnosis and on reducing underreporting and promoting an integrated surveillance of human and animal disease. These data should be combined with asymptomatic infection and vector information, following a One Health approach.Graphical

On Parameterization of Dissipative Processes in Turbulent Transport Models for Description of Thermohydrodynamics and Biogeochemistry of Stratified Inland Water Bodies

On Parameterization of Dissipative Processes in Turbulent Transport Models for Description of Thermohydrodynamics and Biogeochemistry of Stratified Inland Water Bodies

Protocols versus practice: unravelling clinical checking variations in community pharmacies in England—a multi-method study

BackgroundStandardisation, a widely accepted concept for risk management, entails designing and implementing task-specific operating procedures. In community pharmacies, Standardised Operating Procedures (SOPs) are a mandatory requirement and are recognised as essential for upholding safety and quality.AimThis study aimed to investigate community pharmacists’ (CPs) compliance with SOPs when checking prescriptions, and the reasons for variations between standardised protocols and practice.MethodEight sets of SOPs underwent hierarchical task analysis (HTA) to generate a normative description of clinical checking execution as per protocols. Subsequently, twelve CPs were engaged in a simulated clinical checking exercise, verbalising their thoughts while checking virtual prescriptions. Transcribed data underwent content analysis, aligned with a descriptive model to uncover engagement patterns, and disparities between SOPs and CPs’ practices. Finally, a focus group discussion took place to contextualise the observed variations.ResultsHTA aided in constructing a clinical checking model with six primary subtasks and 28 lower subtasks. CPs often omitted subtasks during checks, diverging from prescribed protocols. These deviations, observed in controlled environment, reveal an ingrained aspect within the professional culture of pharmacists, where there may be a tendency not to strictly adhere to protocols, despite variations in work conditions. Contributing factors to this culture include the exercise of professional judgment, reliance on others, and prioritisation of patient preferences.ConclusionThis study highlights ongoing deviations from SOPs during clinical prescription checks in community pharmacies, suggesting a cultural tendency. Future research should delve into risk management strategies for these deviations and address the delicate balance between flexibility and stringent compliance.

A Global Paleosecular Variation Database for the Paleogene: Stationary Secular Variation Behavior Since the Triassic?

AbstractPaleosecular variation analysis is a primary tool for characterizing ancient geomagnetic behavior and its evolution through time. This study presents a new high‐quality directional data set, paleosecular variation of the Paleogene (PSVP), with and without correction for serial correlation, compiled from 1,667 sites from 45 different localities from the Paleogene and late Cretaceous (84–23 Ma). The data set is used to study the variability, structure, and latitude dependence of the geomagnetic field during that period by varying selection criteria and PSV models. Modeled values for the equatorial virtual geomagnetic pole (VGP) dispersion have over‐lapping uncertainty intervals within their uncertainty bounds between 8.3° and 18.6° for the past 250 Ma. We investigate the suitability of two descriptive models of PSV, Model G‐style quadratic fits and covariant Giant Gaussian Process models, and find that both styles of model fail to satisfactorily reproduce the latitude dependent morphology of PSV, but suggest that estimates of the equatorial VGP dispersion may still robustly characterize aspects of Earth's long‐term field morphology. During this time where the PSV behavior has not changed substantially, the reversal frequency has varied widely. The lack of a clear relationship between PSV behavior and reversal frequency is not trivially explained in the context of published findings regarding numerical geodynamo simulations.

Lessons learned from 10 years of wind tunnel tests on small wind turbines designed by students

This article discusses results from an international contest, open for university student teams (bachelor and master), involving the design, construction, and testing of small wind turbines in a large wind tunnel. The wind tunnel has an outlet of 2.85 x 2.85 m allowing a maximum rotor swept area of 2 m2 without significant tunnel effects. Both horizontal and vertical axis wind turbines are part of the competition. The turbines are evaluated by an external jury of industry experts based on criteria such as Annual Energy Production, cut-in wind speed, innovations, design, and sustainability. Although the contest has been initiated in 2013 with an educational focus, it has also evolved into a valuable database for scientific purposes by providing a decade worth of performance measurements for roughly 9-10 various turbine concepts each year. The collected data may serve as a unique validation resource for assessing the accuracy of design codes in modelling diverse turbine concepts thanks to detailed design reports with model descriptions accompanying each turbine (such turbine descriptions are often considered confidential for field measurements). The paper aims to explore the scientific value of this database by comparing calculations with measurements, offering explanations where possible, and reporting intriguing findings on unconventional concepts’ performance. Even though not all observations could be explained fully they provide food for thought. Recommendations are provided for both students to enhance their designs and for contest organizers to elevate the scientific value of the measurements in future contests.

Phase-space analysis of a two-section InP laser as an all-optical spiking neuron: dependency on control and design parameters

Using a rate-equation model we numerically evaluate the carrier concentration and photon number in an integrated two-section semiconductor laser, and analyse its dynamics in three-dimensional phase space. The simulation comprises compact model descriptions extracted from a commercially-available generic InP technology platform, allowing us to model an applied reverse-bias voltage to the saturable absorber. We use the model to study the influence of the injected gain current, reverse-bias voltage, and cavity mirror reflectivity on the excitable operation state, which is the operation mode desired for the laser to act as an all-optical integrated neuron. We show in phase-space that our model is capable of demonstrating four different operation modes, i.e. cw, self-pulsating and an on-set and excitable mode under optical pulse injection. In addition, we show that lowering the reflectivity of one of the cavity mirrors greatly enhances the control parameter space for excitable operation, enabling more relaxed operation parameter control and lower power consumption of an integrated two-section laser neuron.

Review of Non-Fiction Science Picture Books for Pre-School Children

Science education in the pre-school period can use different methods and techniques. One such method is the Turkish language practice of non-fiction and fiction science picture books for children. It is thought that non-fiction science picture books are important in terms of developing children's scientific vocabulary. This study aimed to examine non-fiction science picture books for children selected from different publishers. The research was carried out using the document analysis method, a descriptive research model. In the study, data on 59 science-themed picture books selected from different publishing houses were collected through the Picture Story Assessment Scale and the Assessment List for Children’s Non-Fiction Science Picture Books developed by the researcher. According to the results of the research evaluating non-fiction science picture books for pre-school children using the Assessment Scale for Children’s Picture Books, all the books are at an adequate level; the most narrated non-fiction science picture books are preferred; and the problem-solving process is included in most of the books. The most common scientific content among the standard science fields, is life science, especially environmental and weather events. The number of scientific words used is sufficient and most of the books are suitable for science education. It is thought that the science-themed children's picture books selected according to the evaluation list included in this study will be beneficial in terms of realizing science education effectively. Suggestions are made in light of the research results.

EXPERT ASSESSMENTS IN DECISION-MAKING PROBLEMS: THE METHOD OF MULTIPLICATIVE FUNCTIONS

Expert judgments and fuzzy set theory are two different concepts of systems analysis, but their combination improves the mathematical tool of multi-criteria analysis of decision-making problems. The method of expert evaluations belongs to the class of partially formalized methods based on the use of intuition and experience of decision-makers. The multi-criteria nature of the decision-making problem is manifested in the search for an alternative that simultaneously satisfies the constraint and optimizes the vector quantity, the elements of which correspond to the objective functions of the problem. The choice of the optimal alternative, in most cases, is also ambiguous and is based on subjective, undefined information about the object of decision-making, or selection criteria that do not have quantitative assessments. In this case, it can be said that the decision-making process is fuzzy. Multiplicative Function Method is one of the approaches to modeling fuzzy systems, problems related to fuzzy inference, or fuzzy model description. The purpose of the work is to study the possibility of combining the theory of fuzzy sets with a deterministic algorithm for a multi-criteria decision-making problem.

USE OF DIGITAL DOUBLE FOR COMPONENT MANUFACTURING

One of the contemporary approaches to production planning involves the application of digital twins technology, which aims to combine information from a real physical object and its virtual counterpart. The integration and synchronization of this information enable the realization of the manufacturing process with real-time tracking of the current state of the product and production. Utilizing the capabilities of modern computer technologies and digital twins creation technology allows for the assessment of the manufacturing process and its shortcomings even at the creation stage. The digital twins of the physical production process enable timely evaluation of design efficiency, avoidance of costly physical reconfigurations, attainment of maximum efficiency, shortened timelines, and reduced implementation costs through optimization. The model of the assembly process constructed in this way reflects the essential components and sequences. The foundation for implementing the digital twins of production is the model of the product itself, which serves as an integral part and basis of the entire digital model. Assessing the assembly of such a product objectively, its constituent elements, and the sequence of their assembly, allowed for the formulation of a description of the digital model of product assembly. The language used to describe the model is based on sets of relation types between components, assembly units of the product, and the constraints imposed on them within the given assembly. Such analytical notation of product components reflects the assembly process and constitutes a model of the technological assembly sequence. The proposed linguistic description of the product and the digital twins of the design enable the formalization of the three-dimensional assembly process during the design of assembly units and products, allowing for the modeling of their assembly process at the stage of design engineering.

PHYSICS TEACHERS’ EPISTEMOLOGICAL BELIEFS: CORE AND PERIPHERAL DIMENSIONS

This study aims to examine physics teachers’ beliefs about knowledge, science, teaching and learning science to understand the relationship among four belief systems. Participants were 59 high school physics teachers, who were interviewed once through a semi-structured interview protocol. The interviews were transcribed and analyzed through constant comparative method to categorize teachers’ beliefs in different levels: traditional, transitional, and constructivist and quantify the nominal data for descriptive, correlational statistics, and structural equation modeling. The results indicated that teachers mostly held transitional beliefs about knowledge and science while their beliefs were constructivist on teaching and learning science. There was a significant relationship between beliefs about knowledge and science as core beliefs and between beliefs about teaching and learning science as peripheral beliefs, positive correlation was found between core and peripheral beliefs. These findings offer a report as a guide to address teachers’ beliefs through the design of future professional development programs.