Developments In Field Research Articles

A review of derivative structures of the Miura-Ori

The scholarly paper conducts a thorough examination and evaluation of five primary derivatives of the Miura-Ori fold, a fundamental structure in the art of origami. Each derivative is meticulously studied through the creation of a tangible model, bringing the theoretical concepts to life. The space occupied by each model is precisely measured, providing a practical perspective to the study. These measurements are then compared and contrasted with the outcomes predicted by theoretical deductions, offering a comprehensive understanding of the accuracy of the theoretical models. The paper then transitions to encapsulate the most recent advancements and developments in the intriguing field of Miura-Ori folds. The potential applications of these primary derivatives are not limited to single-layered structures. The paper explores and deliberates on the exciting possibilities of utilizing these derivatives in multi-layered structures, opening up new avenues for practical applications. The paper concludes by charting the course for future research in this field.

Application of Convolutional Gated Recurrent Units U-Net for Distinguishing between Retinitis Pigmentosa and Cone–Rod Dystrophy

Abstract Artificial Intelligence (AI) has gained a prominent role in the medical industry. The rapid development of the computer science field has caused AI to become a meaningful part of modern healthcare. Image-based analysis involving neural networks is a very important part of eye diagnoses. In this study, a new approach using Convolutional Gated Recurrent Units (GRU) U-Net was proposed for the classifying healthy cases and cases with retinitis pigmentosa (RP) and cone–rod dystrophy (CORD). The basis for the classification was the location of pigmentary changes within the retina and fundus autofluorescence (FAF) pattern, as the posterior pole or the periphery of the retina may be affected. The dataset, gathered in the Chair and Department of General and Pediatric Ophthalmology of Medical University in Lublin, consisted of 230 ultra-widefield pseudocolour (UWFP) and ultra-widefield FAF images, obtained using the Optos 200TX device (Optos PLC). The data were divided into three categories: healthy subjects (50 images), patients with CORD (48 images) and patients with RP (132 images). For applying deep learning classification, which rely on a large amount of data, the dataset was artificially enlarged using augmentation involving image manipulations. The final dataset contained 744 images. The proposed Convolutional GRU U-Net network was evaluated taking account of the following measures: accuracy, precision, sensitivity, specificity and F1. The proposed tool achieved high accuracy in a range of 91.00%–97.90%. The developed solution has a great potential in RP diagnoses as a supporting tool.

A new mechanistic model to predict liquid loading in inclined natural gas wells

Accurately predicting the critical gas velocity and inclination angle is crucial for gas field development. However, the mechanism of liquid loading remains elusive due to insufficient attention given to the multivaluedness of flow structures and phase non-uniformity. This paper theoretically studied the flow pattern and gas-liquid configuration in wellbore based on the minimum energy principle. The Kelvin-Helmholtz instability of liquid film was analyzed, and a new correlation for the interfacial friction factor was proposed based on wave properties. The results indicated that the flow pattern transitioned from stratified to annular flow as the inclination angle increased. The gas-liquid interface presented a curved shape, with the interface curvature being influenced by various factors such as fluid properties, tube diameter, inclination angle, and gas and liquid velocities. As the inclination angle increases, the critical gas velocity first increases and then decreases, reaching a peak between 44° and 59°, aligning well with experimental and conventional results. Larger tube diameter, higher liquid density, and viscosity result in a higher critical gas velocity. Waves are more prone to develop in inclined pipes, and capillary waves can break up liquid film due to instability, leading to a discontinuous flow in inclined tubes. Film instability is exacerbated by a smaller diameter, higher liquid holdup, or greater inclination angle. Finally, a new model was devised to predict liquid loading in inclined natural gas wells, demonstrating better performance than existing models. In practice, the present model can achieve real-time prediction of critical gas velocity and continuously monitor the location of liquid accumulation in gas wells over the lifespan.

The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.

Force fields are a key component of physics-based molecular modeling, describing the energies and forces in a molecular system as a function of the positions of the atoms and molecules involved. Here, we provide a review and scientific status report on the work of the Open Force Field (OpenFF) Initiative, which focuses on the science, infrastructure and data required to build the next generation of biomolecular force fields. We introduce the OpenFF Initiative and the related OpenFF Consortium, describe its approach to force field development and software, and discuss accomplishments to date as well as future plans. OpenFF releases both software and data under open and permissive licensing agreements to enable rapid application, validation, extension, and modification of its force fields and software tools. We discuss lessons learned to date in this new approach to force field development. We also highlight ways that other force field researchers can get involved, as well as some recent successes of outside researchers taking advantage of OpenFF tools and data.

Selection of well opening schedules in pre-salt reservoirs using WAG-CO2

In field development projects involving many wells, the limitation of available rigs can increase the need for investments. In our literature research about the definition of well opening schedules, we found some proposals but could not find studies that deep dive into this topic, nor any that propose an approach that could be applied to the Brazilian pre-salt fields. Therefore, this research focuses on evaluating the influence in the NPV of well opening schedule of a project using WAG-CO2, inspired in pre-salt fields, and we propose a simple procedure to specify the well opening schedule without having to perform many simulations or complex analysis. We used the UNISIM-II-D-BO benchmark (synthetic simulation model with characteristics of a Brazilian pre-salt field) and a well configuration proposed in a previous study, with 11 producers and 10 injectors. First, we calculated the distance between the producer and injector wells and evaluated the well economic indicator (WEI) of each well by opening all at the same time at the beginning of the production schedule. We then evaluated 252 combinations of those injector wells, where five of them were injecting water and the other five were injecting gas, from where we defined three reference alternatives to check the repeatability of the results. With all these data, we tested predefined schedules: (1) with the 1st injector well injecting only gas or participating in the WAG cycle; (2) the producers' opening sequence based on their WEI; (3) the injectors’ opening based on their WEI or distance to producers; and (4) testing the relationship between producers and injectors (number of producers to open before the injectors), making sure that all the gas could be reinjected. For comparison purposes, we then run an optimization algorithm to select the schedule, using 2,660 simulations. At the end, we verified that the difference between the optimization with the algorithm (demanding thousands of simulations runs) and the proposed schedules (demanding few simulations) in the NPV was about 2%. Thus, to speed-up decision making, it is possible to have an opening schedule with good performance considering a simple procedure, as follows: 1st injector well collaborating with the WAG; producer wells opening from the highest to the lowest WEI; injector wells opening from the closest to the furthest distance to the producers; and the relationship between producers and injectors has to be investigated, not only aiming to find the best economic return, but also because of the environmental restriction (the need to reinject all the produced gas). This procedure reduces the number of simulations that must be performed if an engineer decides to use an optimization technique.

Nursing Informatics Research: A Bibliometric Analysis from 1989 to 2023.

Nursing informatics has evolved rapidly since its inception. Despite its growth, there remains a gap in comprehensive bibliometric analyses of the field's development and themes. The study aimed to provide an overview of the evolution and current status of nursing informatics by conducting a bibliometric analysis of the literature from 1989 to 2023. Utilizing the Science Citation Index Expanded edition of the Web of Science Core Collection, 483 original English-language articles were analyzed using Bibliometrix 4.1. The results revealed a steady increase in publications, with the United States as the leading contributor. Thematic analysis indicates a shift from basic informatics integration to advanced technologies like artificial intelligence, reflecting the dynamic nature and expanding scope of nursing informatics. These findings highlight the need for ongoing research, enhanced digital literacy, and interdisciplinary collaboration, emphasizing the field's critical role in advancing healthcare in the digital age.

Modulation strategies of electrocatalysts for 5-hydroxymethylfurfural oxidation-assisted water splitting

To address energy shortages and environmental issues, prioritizing renewable energy development and usage is crucial. Employing renewable sources for water electrolysis offers a sustainable method for hydrogen generation. Reducing the water electrolysis potential is vital for efficient clean energy conversion and storage. Substituting the anodic oxygen evolution reaction in conventional hydrogen production from water electrolysis with the more thermodynamically favorable 5-hydroxymethylfurfural (HMF) oxidation reaction can greatly decrease overpotential and yield the valuable product 2,5-furan dicarboxylic acid. The key to this process is developing effective electrocatalysts to minimize the potential of the HMF electrooxidation-hydrogen production system. Therefore, this review provides a comprehensive introduction to the modulation strategies that affect the electronic and geometric structure of electrocatalysts for HMF oxidation-assisted water splitting. The strategies encompass heteroatom doping, defect projection, interface engineering, structural design, and multi-metal synergies. The catalysts are assessed from various angles, encompassing structural characterization, reaction mechanisms, and electrochemical performance. Finally, current challenges in the catalyst design and potential development of this promising field are proposed.

Rapid well-test analysis based on Gaussian pressure-transients

Reservoir performance forecasting technology commonly involves flow testing and fluid sampling in appraisal wells. This study introduces a new Gaussian Pressure Transient (GPT) method for rapidly evaluating well-test data. The GPT method provides an alternative for the current rate transient analysis (RTA) methodology, which relies on specialized knowledge and involves subjective steps of tangent line-fitting based on flow regime assumptions. The newly proposed method was validated with field well-test data and is different from the traditional PTA method in that it directly fits Gaussian well performance curves to well-test data. The GPT method can be used (1) to determine the uncertain reservoir parameters, and (2) predict future well productivity under production conditions. Well-test data from an offshore condensate discovery with low well deliverability are analyzed. The test data encompass five individual tests, all revealing low gas and condensate flow rates based on GPT matches. The method involves estimations of the hydraulic diffusivity and can generate both short-term and long-term well-performance forecasts. A sensitivity analysis explores the impact of the various parameters on the recoverable resource volume, identifying which data acquisition would be needed to improve the production forecast's accuracy. Validation with field tests and commercial simulator outputs demonstrates the model's robustness in formation evaluation and predicting well performance. The study recommends hydraulic fracturing for future field development, and includes simulation results valuable for reservoir management and decision-making.

A Brief History of the Early Development of China's Social Philanthropy Field and Its Impact on the Later Development of the Philanthropy Field

Although charity has been developed in China for decades, its basic value attributes have not been truly stimulated in Chinese society. If we look at the development of philanthropy in China alone, we will not only fail to touch the core of the problem, but also deviate from it. Based on a brief analysis of the early development history, this paper finds that the problem has been foreshadowed in the earliest historical development. Through a combination of qualitative research methods, this paper realizes that the key to improving and even solving the problems in the field of public welfare and charity in Chinese society does not lie in the problems of the field itself, but rather in the political behaviors and modus operandi behind the problems that appear to be public welfare and charity.

Accounting for a capillary pressure jump in a saturated porous medium for a more correct calculation of hydrocarbon reserves

Relevance. The correct calculation of hydrocarbon reserves in various fields (oil, gas, gas condensate) is an important state task, because it allows you to properly organize field development in the future and ensure the rational use of natural resources of the state. In particular, the values of geological and recoverable reserves are assigned to a specific subsurface user and are recorded in departmental documents. Aim. To describe the effect associated with the calculations of the thermodynamic equilibrium of the mixture of hydrocarbons of the Karachaganak oil and gas condensate field at various formation depths with the capillary pressure jump taken into account. This makes it possible to clarify the value of the potential condensate-gas factor of reservoir gas and, as a result, to give a more accurate assessment of the geological reserves of hydrocarbon raw materials. Object. Analysis of the thermodynamic equilibrium of the hydrocarbon mixture of Karachaganak oil and gas condensate field, taking into account the capillary pressure jump, which takes place in a porous medium under reservoir conditions. Methods. Numerical modeling, analytical research. Results. Based on the previously developed methodology for calculating the phase equilibrium with the capillary pressure jump the correction of the potential condensate-gas factor of the formation gas of the Karachaganak oil and gas condensate field was carried out at various formation depths. The range of values of the condensate-gas factor difference for calculations both with and without capillary pressure jump was from 7,04 g/m3, with a condensate-gas factor value equal to 393 g/m3 for formation depth of 4000 m, to 64,47 g/m3, with a condensate-gas factor value equal to 547 g/m3 for formation depth of 4600 m. Based on the updated condensate-gas factor estimate, it is possible to clarify the condensate recovery coefficient during the development of a field without maintaining reservoir pressure or with partial maintaining reservoir pressure.

Navigating the Future of Organisational Health Services Research in Germany and beyond: a Position Paper.

Recent analyses have shown that in health services research in Germany, healthcare organisations are often considered primarily as a study setting, without fully taking their complex organisational nature into account, neither theoretically nor methodologically. Therefore, an initiative was launched to analyse the state of Organisational Health Services Research (OHSR) in Germany and to develop a strategic framework and road map to guide future efforts in the field. This paper summarizes positions that have been jointly developed by consulting experts from the interdisciplinary and international scientific community. In July 2023, a scoping workshop over the course of three days was held with 32 (inter)national experts from different research fields centred around OHSR topics using interactive workshop methods. Participants discussed their perspectives on OHSR, analysed current challenges in OHSR in Germany and developed key positions for the field's development. The seven agreed-upon key positions addressed conceptual and strategic aspects. There was consensus that the field required the development of a research agenda that can guide future efforts. On a conceptual level, the need to address challenges in terms of interdisciplinarity, terminology, organisation(s) as research subjects, international comparative research and utilisation of organisational theory was recognized. On a strategic level, requirements with regard to teaching, promotion of interdisciplinary and international collaboration, suitable funding opportunities and participatory research were identified. This position paper seeks to serve as a framework to support further development of OHSR in Germany and as a guide for researchers and funding organisations on how to move OHSR forward. Some of the challenges discussed for German OHSR are equally present in other countries. Thus, this position paper can be used to initiate fruitful discussions in other countries.

Fabrication and characterization of high-sensitivity, wide-range, and flexible MEMS thermal flow velocity sensors

With the rapid development of various fields, including aerospace, industrial measurement and control, and medical monitoring, the need to quantify flow velocity measurements is increasing. It is difficult for traditional flow velocity sensors to fulfill accuracy requirements for velocity measurements due to their small ranges, susceptibility to environmental impacts, and instability. Herein, to optimize sensor performance, a flexible microelectromechanical system (MEMS) thermal flow sensor is proposed that combines the working principles of thermal loss and thermal temperature difference and utilizes a flexible cavity substrate made of a low-thermal-conductivity polyimide/SiO2 (PI/SiO2) composite porous film to broaden the measurement range and improve the sensitivity. The measurement results show that the maximum measurable flow velocity can reach 30 m/s with a resolution of 5.4 mm/s. The average sensitivities of the sensor are 59.49 mV/(m s−1) in the medium-to-low wind velocity range of 0–2 m/s and 467.31 mV/(m s−1) in the wind velocity range of 2–30 m/s. The sensor proposed in this work can enable new applications of flexible flow sensors and wearable devices.

Implementation and insights from the MedXMentor structured mentorship program for undergraduate health science students at Mbarara University, Uganda

BackgroundMentorship is essential for education and career development in health-related fields, yet Sub-Saharan African universities often lack structured programs. To address this, the MedXMentor program was established at Mbarara University of Science and Technology (MUST) to provide structured mentorship to undergraduate health sciences students in Uganda. This paper outlines insights gained from implementing the MedXMentor hybrid mentorship program.MethodsUsing a mixed-methods approach, the study employed the Kirkpatrick Model of Evaluation to assess mentees’ reactions, learning, behavior, and goal achievement. Data were collected via Google Form surveys, feedback forms, mentoring logs, and session attendance records. Descriptive statistics and thematic analysis provided a comprehensive understanding of the program’s impact.ResultsThe program served 80 mentees, with 48 participating in one-on-one mentorship and 32 in group sessions. It enlisted 24 mentors, mainly from the medical field. Between April and September 2022, eight online group sessions were held, with an average attendance rate of 52%. These sessions focused on project planning, grant writing, and soft skills development, resulting in improved mentee comprehension and skill acquisition. Mentees reported an enhanced understanding of project planning, grant writing, communication, leadership, and teamwork. Their experiences were categorized into four themes: Mentor Engagement, Goal-Oriented Study, Skills and Professional Development, and High-Yield Mentor–Mentee Engagements.Conclusion and recommendationsImplementing the MedXMentor program proved effective in providing crucial mentorship and equipping students with vital academic and professional skills. The program highlighted its potential to bridge the mentorship gap in low-resource settings. By empowering future healthcare professionals in Africa, MedXMentor exemplifies how mentorship initiatives can drive significant advancements in healthcare education and practice.

Carbonate reservoir characterization and permeability modeling using Machine Learning ـــ a study from Ras Fanar field, Gulf of Suez, Egypt

Predicting facies and petrophysical properties along and between wells is challenging in carbonate reservoir modeling. In the Nullipore carbonate reservoir, Ras Fanar field, depositional and long-term diagenetic processes result in a high degree of heterogeneity and complex distribution of facies, which in turn affect the reservoir quality. This provides a significant obstacle to building accurate geological models. This study integrates thin sections, routine core analyses, and well logging data to overcome such difficulties and model the Nullipore carbonate facies and permeability. The detailed petrographic analysis revealed the existence of seven microfacies in the reservoir, which are summed up into three facies associations (FAs), each of which represents a specific reservoir rock type (RRT): (1) supratidal FA, (2) intertidal FA, and (3) shallow subtidal FA. The three FAs were correlated with the gamma-ray logs to create facies logs for the studied wells, which were further populated via the Truncated Gaussian Simulation method. Cross-validation was used to evaluate the model's accuracy. The analysis of the available core data infers that the three RRTs are prospective and have a wide permeability distribution. However, RRT3 constitutes the best reservoir quality. The sedimentological analysis revealed that the long-term diagenetic events, involving the dolomitization of limestone and the dissolution of allochems have a major role in improving the pore connectivity and permeability of the reservoir. Fracture characterization discloses that fractures play a significant role in fluid storage and migration. Three Machine Learning (ML) models, including Adaptive boosting (AdaBoost), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB), were developed to integrate the RRTs, porosity, and permeability to improve permeability prediction. Statistical analysis revealed that the XGB model outperforms other models and exhibits the highest prediction performance. The present study provides further insights into the characterization and modeling of facies and permeability of complex carbonate reservoirs. It can be applied in similar geological settings to better interpretation of depositional and diagenetic controls on reservoir quality assessment and aid in the field development plan.

Teacher engagement in professional learning communities in preschool contexts

ABSTRACT Despite the valuable insights provided by previous studies on the characteristics and contributing factors of professional learning communities (PLCs) in early childhood education contexts, there remains a lack of research investigating teacher engagement within PLCs and its influence on driving transformative change. The objective of this study was to examine teacher engagement in PLCs and its effects on teaching practices within preschool settings. Ten English teachers from two preschools in Hong Kong participated in the study through university-school partnerships. Data was collected through interviews, observations, and recall commentary. The findings revealed that frontline teachers actively engaged in various dimensions within the PLCs, including cognitive, behavioural, affective, and social aspects. These four dimensions were found to be interconnected and mutually inclusive. Increased teacher engagement within the PLCs resulted in changes in teaching practices, particularly towards play-based learning. In conclusion, this study emphasises the implications of these findings for government support and teacher development in the preschool field.

The development of grain resolved stress fields around notch tips in soft-textured zirconium polycrystals: A three-dimensional synchrotron X-ray diffraction study

Texture, microstructure, and local grain neighbourhood contribute to the development of localized stresses in polycrystals. For hexagonal close-packed materials, crystal's elastic and plastic anisotropy can also be a major contributing factor, yet there is a paucity of experimental studies focusing on the extent of contribution of such parameters on the magnitude of localized stresses at microscales. This study focuses on addressing this knowledge gap by deforming double-edge-notched soft-textured α-zirconium specimens in-situ, while measuring grain scale tensorial stresses using high energy synchrotron X-ray diffraction. The specimens were subjected to cyclic loads to study the evolution of stresses in the vicinity of both shallow and deep notches. The soft-texture of the specimens is such that there are no c-axes of grains aligned along the macroscopic loading direction thereby inhibiting deformation twinning. The “as-measured” microstructures and notch geometries were imported into a crystal plasticity finite element model for further analysis. Results show that despite the absence of c-axes of grains aligned along loading direction, the developed stresses were substantially influenced by crystallographic orientations. Stress drop was observed near the onset of plasticity with further loading and the orientation and position effects were highlighted. A plastic deformation mechanism was revealed where, upon specimen loading, the mechanical constraints enforced during grain-grain interactions led to hardening. Accordingly, a parameter was devised to quantify the grain level hardening arising from this mechanism. It was shown that grain-scale stress concentration factors vary significantly before the onset of plasticity, but they settle in the plastic zone and with the progression of cycles.

Integrated approach of predicting rock stability in high mountain valley underground caverns

High mountain valleys are characterized by the development of intricate ground stress fields due to geological processes such as tectonic stress, river erosion, and rock weathering. These processes introduce considerable stability concerns in the surrounding rock formations for underground engineering projects in these regions, highlighting the imperative need for rigorous stability assessments during the design phase to ensure construction safety. This paper introduces an innovative approach for the pre-evaluation of the stability of surrounding rocks in underground caverns situated within high mountain valleys. The methodology comprises several pivotal steps. Initially, we conduct inverse calculations of the ground stress field in complex geological terrains, combining field monitoring and numerical simulations. Subsequently, we ascertain stress-strength ratios of the surrounding rocks using various rock strength criteria. To assess the stability characteristics of the surrounding rocks in the 1# spillway cave within our project area, we employ numerical simulations to compute stress-strength ratios based on different rock strength criteria. Furthermore, we undertake a comparative analysis, utilizing data from the 5# Underground Laboratory (Lab 5) of Jinping II Hydropower Station, aligning the chosen rock strength criterion with the damage characteristics of Lab 5′s surrounding rocks. This analysis serves as the cornerstone for evaluating other mechanical responses of the surrounding rocks, thereby validating the pre-evaluation methodology. Our pre-evaluation method takes into account the intricate geological evolution processes specific to high mountain valleys. It also considers the influence of the initial geostress field within the geological range of underground caverns. This comprehensive approach provides a robust foundation for the analysis and assessment of the stability of surrounding rocks, especially in high mountain valley areas, during the design phase of underground engineering projects. The insights derived from this analysis hold substantial practical significance for the effective guidance of such projects.

A Developed Polar Coded Generalized Frequency Division Multiplexing Based on Bit-Interleaved Coded Modulation

Due to the tremendous development in the wireless communication field and the wide requirements of current generations, such as high data rates, extremely low power consumption, and high performance, it is necessary to think about techniques and methods that present improvement to meet the growing requirements. The introduction of the Generalized Frequency Division Multiplexing (GFDM) technique was one of the proposed methods; it is one of the candidate schemes for the current generations and beyond. GFDM was presented as an improved method over other multiplexing techniques, as it provided an improvement in the field of Out Of Band (OOB) and Peak Average Power Ratio (PAPR). At the same time, it provided a lower performance in BER with respect to SNR. In this paper, methods of enhancement were presented based on Matlab to improve the performance of the GFDM system, which was improved by adding a coding system based on Polar Coding (PC). The proposed method is presented to improve the performance of GFDM by using the Genetic Algorithm (GA) to improve the performance of the Pulse shaping Filter (PSF) in GFDM. The channel estimation is accomplished by means of the LS method, and the Artificial Neural Network (ANN) based on feed-forward backpropagation is used to enhance the estimation process. The proposed Genetic Algorithm Artificial Neural Network Polar Code Interleaver GFDM (GNPI-GFDM) presents an enhancement over the traditional GFDM of more than 3.5dB at BER=10-4over the Rayleigh fading channel

Research on Personal Medical Information Protection Based on Big Data

The rapid development of big data, cloud computing, and artificial intelligence has brought new opportunities to the development of the medical field. The emergence of electronic medical records and medical information systems has provided great convenience for people's medical treatment. However, the arrival of the big data era also poses new challenges to the protection of human medical privacy. The development and application of medical big data have led to explosive growth of data in the medical field, putting pressure on the management of medical institutions. The sharing of medical data between medical institutions and between medical institutions and third parties also poses significant security risks. Moreover, medical data leakage incidents have been continuously exposed in recent years, seriously infringing on the identity and privacy rights of patients. This article aims to explore the research on personal medical information protection based on big data. Firstly, the importance and necessity of protecting personal medical information were analyzed, as well as the current application status and existing problems of big data in medical information management. Secondly, a comparative analysis of domestic and international research on medical privacy protection was elaborated, including the analysis of medical information privacy protection standards in the United States, Europe, and Asia, and the differences and commonalities of international medical information privacy protection standards were compared and analyzed. Then, the theoretical basis of medical information privacy protection was summarized. Then, the application methods and technologies of big data in personal medical information protection were discussed. Finally, relevant countermeasures and suggestions for the protection of personal medical information in big data were discussed, including privacy protection technologies and policy recommendations, as well as ethical issues and norms for the protection of medical information privacy. Through this study, it is hoped that it can provide reference and inspiration for the protection of personal medical information in big data, and provide ideas and suggestions for future development directions.

From founding voices to future visions: languages and literacies in science education

ABSTRACT Over the past decades, languages and literacies have become a prominent focus in science education research and practice. While there is broad consensus on the central roles of disciplinary, representational, and cultural languages and their associated literacies in learning and teaching science, the field faces a critical moment. An ever-growing number of new theoretical and methodological perspectives have revealed rich facets of the multilingual and multimodal nature of learning processes in science. These developments prompt us to reflect on the distinct identity and impact of languages and literacies on the contemporary discourse in science education, especially in light of technological innovations (e.g. large-language models) and societal developments (e.g. multilingual contexts). This position paper offers an opportunity to assess the field's past developments and future directions, building on a recent meeting of the Special Interest Group (SIG) on Languages and Literacies in Science Education under the European Science Education Research Association (ESERA). We present viewpoints from four founding members of the SIG, discussing current trends, challenges, and visions for the future. Ultimately, this paper invites our global community to engage in informed dialogues on the role and value of languages and literacies in science education today.