Key Patterns Research Articles

Pedestrian Attribute Recognition via Spatio-temporal Relationship Learning for Visual Surveillance

Pedestrian attribute recognition (PAR) aims at predicting the visual attributes of a pedestrian image. PAR has been used as soft biometrics for visual surveillance and IoT security. Most of the current PAR methods are developed based on discrete images. However, it is challenging for the image-based method to handle the occlusion and action-related attributes in real-world applications. Recently, video-based PAR has attracted much attention in order to exploit the temporal cues in the video sequences for better PAR. Unfortunately, existing methods usually ignore the correlations among different attributes and the relations between attributes and spatio regions. To address this problem, we propose a novel method for video-based PAR by exploring the relationships among different attributes in both the spatio and temporal domains. More specifically, a spatio-temporal saliency module (STSM) is introduced to capture the key visual patterns from the video sequences, and a module for spatio-temporal attribute relationship learning (STARL) is proposed to mine the correlations among these patterns. Meanwhile, a large-scale benchmark for video-based PAR, RAP-Video, is built by extending the image-based dataset RAP-2, which contains 83,216 tracklets with 25 scenes. To the best of our knowledge, this is the largest dataset for video-based PAR. Extensive experiments are performed on the proposed benchmark as well as on MARS Attribute and DukeMTMC-Video Attribute. The superior performance demonstrates the effectiveness of the proposed method.

BIBLIOMETRIC ANALYSIS OF THE GREATEST NUCLEAR DISASTERS: WHAT IS KNOWN SO FAR AND WHAT ARE THE PROSPECTS?

Abstract. The high potential of nuclear power to combat climate change and support sustainable development plays a critical role in achieving the goal of the Paris Agreement. Moreover, with the ever-increasing demand for electricity, it is essential to consider nuclear power as a reliable source of energy. However, it should be noted that although the risk of a radiological accident is small, it always exists, and therefore it is crucial to have a complete understanding of the management of nuclear power. Herein, we present a statistical review of nuclear accident research at Chernobyl and Fukushima Nuclear Power Plants using bibliometric analysis to identify key patterns in scientific results and current issues in accident research. More than 10,000 articles have been collected from the SCOPUS database covering the periods 1986–2022 and 2011–2022 on Chernobyl and Fukushima, respectively. The results were obtained from two perspectives: first, we identified stages through which pre- and post-accident researches have evolved, and then we analysed the spatial correlation between energy-economic performance and scientific literature for the leading productive countries. From the analysis of research trends, it was found that the number of articles increased sharply immediately after the accident and slightly decreased over time. Among the most attractive subject categories in terms of the largest number of publications and received citations were environmental sciences, medicine and energy policy. The productive country ranking was mostly topped by the country in which the accident occurred. Spatial statistical analysis revealed a strong correlation between the scientific productivity and energy-economic performance of the leading countries.

Implementing action research to improve L2 classroom communication patterns: a grounded theory analysis approach

ABSTRACT The purpose of this paper is two-fold: it begins by exploring communication patterns in Iranian second language (L2) classrooms, then describes the implementation of action research in two different cycles to enable teachers to identify possible problems in their L2 classrooms and find ways to improve them. Through qualitative analysis of interviews, audio-records, observations, field notes and reflective journals, three main themes were identified, namely, communication patterns in L2 classroom, problems in these patterns, and action research and communication patterns. Two theoretical models for improving communication patterns in L2 classrooms were also established based on the key themes and patterns extracted from the data. The implications of the findings are likely to be of interest to teaching practitioners, teacher trainers, syllabus designers, materials developers, English as a Foreign Language (EFL) teachers, as well as action researchers. However, the findings of the present study should be interpreted within certain limitations, as set out in the article.

Identifying the Opportunities and Challenges of Project Bundling: Modeling and Discovering Key Patterns Using Unsupervised Machine Learning

Identifying the Opportunities and Challenges of Project Bundling: Modeling and Discovering Key Patterns Using Unsupervised Machine Learning

Intervention Strategies for Mitigating Drug and Substance Abuse Among Youths in Selected Local Government Areas of Benue State, Nigeria

This study investigated intervention strategies for reducing drug and substance abuse among youths in selected Local Government Areas (LGAs) of Benue State, Nigeria. The survey research design was employed in this study and qualitative data collection was made. Both primary and secondary data were collected through in-depth interviews conducted with key informants, including community leaders, parents, teachers, and healthcare professionals, to obtain qualitative insights into the underlying factors contributing to drug and substance use. The study adopted the qualitative data analysis which involved thematic and content analysis to identify key themes and patterns in the participants' narratives. Thematic and content analysis revealed various contributing factors to drug abuse and the distinct roles of key players in addressing the issue. Tailoring national campaigns to local contexts through domestication emerged as an effective approach, leveraging community engagement, local influencers, and continuous monitoring. The study emphasised the critical roles of the NDLEA, health practitioners, religious and traditional institutions, media, and NGOs in prevention efforts. The study discovers that various key players are identified, showcasing their distinct roles and responsibilities in addressing this pressing issue. The study showed that tailoring national campaigns to local contexts through domestication enhances effectiveness by customizing messages and interventions to the local culture of drug and substance abuse. The study recommended implementing comprehensive prevention programs, advocating for good parenting, strengthening law enforcement, and improving access to mental health services for affected youths. This study underscores the collective responsibility of stakeholders, including governmental agencies, community institutions, religious leaders, educators, parents, NGOs, and youths themselves, in addressing drug abuse among youths in Benue State. The study concludes that the significance of acknowledging drug abuse as a collective concern that requires the involvement of various stakeholders, including governmental agencies, community institutions, religious leaders, educators, parents, NGOs, and youths themselves. The prevalence of drug abuse among youths in the district underscores the need for immediate action and underscores the responsibility of each stakeholder to play a role in prevention, intervention, and rehabilitation efforts towards mitigating drug and substance abuse among youths in Benue State.

TSwinPose: Enhanced monocular 3D human pose estimation with JointFlow

Monocular estimation of 3D human poses is challenging due to ambiguity in depths and partial occlusion. Most recent works define this as a 2D-to-3D lifting task, taking 2D key point sequences and using spatial and temporal relationships. However, prior works focus on capturing spatio-temporal correlations but ignore the motion of joints that is needed for continuous estimation. To extend the potential of 2D-to-3D pose estimation, we propose TSwinPose, which learns multi-scale spatio-temporal representations from 2D key point locations and patterns of motion. The input 2D key point sequences are enhanced by JointFlow, which encodes the motion of each human joint. Based on Swin-Transformer, we designed a temporal domain Swin-Unet structure to model multi-scale spatio-temporal relationships of human joints across different temporal windows. The final 3D pose generated by multi-stage representations is consistent temporally and has a higher accuracy. Experiments conducted on three benchmark datasets, Human3.6M, MPI-INF-3DHP, and HumanEva-I, demonstrate that TSwinPose achieves performance that is on par with state-of-the-art methods. Moreover, the introduction of JointFlow as a plug-in extension enhances performance significantly, particularly benefiting long-term 2D-to-3D lifting human pose estimation methods.

CHD7 and SOX2 act in a common gene regulatory network during mammalian semicircular canal and cochlear development

Inner ear morphogenesis requires tightly regulated epigenetic and transcriptional control of gene expression. CHD7, an ATP-dependent chromodomain helicase DNA-binding protein, and SOX2, an SRY-related HMG box pioneer transcription factor, are known to contribute to vestibular and auditory system development, but their genetic interactions in the ear have not been explored. Here, we analyzed inner ear development and the transcriptional regulatory landscapes in mice with variable dosages of Chd7 and/or Sox2. We show that combined haploinsufficiency for Chd7 and Sox2 results in reduced otic cell proliferation, severe malformations of semicircular canals, and shortened cochleae with ectopic hair cells. Examination of mice with conditional, inducible Chd7 loss by Sox2CreER reveals a critical period (~E9.5) of susceptibility in the inner ear to combined Chd7 and Sox2 loss. Data from genome-wide RNA-sequencing and CUT&Tag studies in the otocyst show that CHD7 regulates Sox2 expression and acts early in a gene regulatory network to control expression of key otic patterning genes, including Pax2 and Otx2. CHD7 and SOX2 directly bind independently and cooperatively at transcription start sites and enhancers to regulate otic progenitor cell gene expression. Together, our findings reveal essential roles for Chd7 and Sox2 in early inner ear development and may be applicable for syndromic and other forms of hearing or balance disorders.

Identifying the effects of landscape pattern on soil conservation services on the Qinghai-Tibet Plateau

Land use patterns affect soil erosion processes and soil conservation services. Identifying key landscape pattern affecting soil conservation services is critical for improving soil conservation services and optimizing land use patterns. In this study, the Qinghai-Tibet Plateau (QTP), where ecosystem services are important, was selected as research area. Based on land use, meteorological, soil and vegetation data, the RUSLE model was used to estimate soil conservation quantitatively from 2000 to 2020. The temporal changes in landscape metrics were analyzed using Fragstats, and the response of soil conservation services to landscape metrics was analyzed by correlation analysis. The landscape pattern showed an obvious temporal change trend. In general, the overall landscape of the QTP became more diversified and fragmented, and the landscape shape tended to become more complicated. Patch density (PD), edge density (ED), landscape shape index (LSI), splitting index (SPLIT), Shannon's diversity index (SHDI), and Shannon's evenness index (SHEI) showed increasing trends, while largest patch index (LPI), mean patch area (AREA_MN), aggregation index (AI), and contagion index (CONTAG) showed decreasing trends. At the class level, the variations of landscape pattern metrics of different land use types were big difference. In the 20-year period, soil conservation services were generally on the rise. The spatial heterogeneity of soil conservation services decreased from the south-east to the north-west. PD and ED were positively correlated with soil conservation function, while AREA_MN and AI had a negative correlation with soil conservation function. The effect of landscape pattern metric variation on soil conservation capacity significantly differed among different land use types. Results of the research offer reasonable evidence for landscape management, water and soil retention function improvement and regional ecological protection on the QTP.

Metagenomic insights into the response of soil microbial communities to pathogenic Ralstonia solanacearum.

Understanding the response of soil microbial communities to pathogenic Ralstonia solanacearum is crucial for preventing bacterial wilt outbreaks. In this study, we investigated the soil physicochemical and microbial community to assess their impact on the pathogenic R.solanacearum through metagenomics. Our results revealed that certain archaeal taxa were the main contributors influencing the health of plants. Additionally, the presence of the pathogen showed a strong negative correlation with soil phosphorus levels, while soil phosphorus was significantly correlated with bacterial and archaeal communities. We found that the network of microbial interactions in healthy plant rhizosphere soils was more complex compared to diseased soils. The diseased soil network had more linkages, particularly related to the pathogen occurrence. Within the network, the family Comamonadaceae, specifically Ramlibacter_tataouinensis, was enriched in healthy samples and showed a significantly negative correlation with the pathogen. In terms of archaea, Halorubrum, Halorussus_halophilus (family: Halobacteriaceae), and Natronomonas_pharaonis (family: Haloarculaceae) were enriched in healthy plant rhizosphere soils and showed negative correlations with R.solanacearum. These findings suggested that the presence of these archaea may potentially reduce the occurrence of bacterial wilt disease. On the other hand, Halostagnicola_larseniia and Haloterrigena_sp._BND6 (family: Natrialbaceae) had higher relative abundance in diseased plants and exhibited significantly positive correlations with R.solanacearum, indicating their potential contribution to the pathogen's occurrence. Moreover, we explored the possibility of functional gene sharing among the correlating bacterial pairs within the Molecular Ecological Network. Our analysis revealed 468 entries of horizontal gene transfer (HGT) events, emphasizing the significance of HGT in shaping the adaptive traits of plant-associated bacteria, particularly in relation to host colonization and pathogenicity. Overall, this work revealed key factors, patterns and response mechanisms underlying the rhizosphere soil microbial populations. The findings offer valuable guidance for effectively controlling soil-borne bacterial diseases and developing sustainable agriculture practices.

Forest Landscape Restoration and Its Impact on Social Cohesion, Ecosystems, and Rural Livelihoods: Lessons Learned from Pakistan

This paper explores community perspectives on forest landscape restoration (FLR) initiatives and their impacts on ecosystems, livelihoods and social cohesion. The study is based on data collected from 08 focus group discussions (FGDs) conducted in local communities involved in FLR activities. A coding process was used to identify key themes and patterns that shed light on the impacts of FLR. The results show that FLR initiatives have led to social cohesion and conflict resolution, including the establishment of community-based organizations (CBOs), the involvement of community volunteers in various FLR tasks, a cooperative/collaborative approach to forest management, conflict resolution, and the empowerment of local communities. In addition, the results of the study showed that FLRs have successfully regenerated and restored the forest ecosystem, including restoration of biodiversity, plant diversity, improvement of animal populations and livestock health, soil health, and water quality. Ecosystem restoration has improved community livelihoods, including increased crop productivity, access to education, affordable health care, improved economic conditions, and food security. Based on the findings, policy recommendations include strengthening support for community FLR initiatives, promoting stakeholder collaboration, and promoting social equity.

Market volatility and crisis dynamics: a comprehensive analysis of U.S., China, India, and Pakistan stock markets with oil and gold interconnections during COVID-19 and Russia–Ukraine war periods

The objective of this paper is to explore the interconnectedness of volatility among the stock markets of U.S., China, India, and Pakistan in conjunction with oil and gold markets. Employing the novel Time-Varying Parameter Vector Autoregression (TVP-VAR) model for assessing connectedness, the study scrutinizes key patterns of dependency and interrelation between these markets. Furthermore, this study investigates the dynamic connectedness during the global health crisis due to COVID-19 and the geopolitical crisis due to Russia–Ukraine war periods to identify the changes in their relationship following the two crises episodes. The findings underscore the significance of volatility transmissions emanating from the U.S., a developed market, in shaping these dynamic linkages. It is observed that oil and gold returns play a limited role as sources of shocks for market returns in China, India, and Pakistan, suggesting a relatively lower contribution of oil and gold to equity market volatility. The results also emphasize the safe-haven characteristics of gold during periods of crisis such as the COVID-19 pandemic and the Russia–Ukraine war. Moreover, the study indicates that the volatility transmissions during the COVID-19 pandemic are more pronounced compared to the Russia–Ukraine war crisis. These findings hold notable implications for both investors and policymakers, emphasizing the need for a nuanced understanding of market dynamics and the development of risk-averse strategies, particularly in times of crisis.

Machine learning-based discrimination of bulk and surface events of germanium detectors for light dark matter detection

Surface events that exhibit incomplete charge collection are an essential background source in the light dark matter detection experiments with p-type point-contact germanium detectors. We propose a machine learning-based algorithm to identify bulk and surface events according to their pulse shape features. We construct the training and test set with part of the γ-source calibration data and use the rising edge of the waveform as the model input. This method is verified with the test set and another part of the γ-source calibration data. Results show that this method performs well on both datasets, and presents robustness against the bulk events’ proportion and the dataset size. Compared with the previous approach, the uncertainty is reduced by 16% near the energy threshold on the physics data of CDEX-1B. In addition, the key pattern identified in the waveform is verified to be consistent with its physical nature by digging into this algorithm.

Tracking δ13C and δ18O fluctuations uncovers stable modes and key patterns of paleoclimate

The examination of fluctuations in the correlations between δ13C and δ18O is of significant importance for the reconstruction of the Earth’s climate history. A key challenge in paleoclimatology is finding a suitable method to represent the correlated fluctuation system between δ13C and δ18O. The method must be able to handle data sets with missing or inaccurate values, while still retaining the full range of dynamic information about the system. The non-linear and complex correlations between δ13C and δ18O poses a challenge in developing reliable and interpretable approaches. The transition network, which involves embedding the δ13C and δ18O sequence into the network using phase space reconstruction, is a coarse-grained based approach. This approach is well-suited to nonlinear, complex dynamic systems, and is particularly adept at emerging knowledge from low-quality datasets. We have effectively represented the fluctuations in the correlation between δ13C and δ18O since 66 million years ago (Ma) using a system of complex network. This system, which has topological dynamical structures, is able to uncover the stable modes and key patterns in Cenozoic climate dynamics. Our findings could help to improve climate models and predictions of future climate change.

Трансформация системы стратегических коммуникаций предприятий легкой промышленности и индустрии моды

The fashion industry has to update collections extremely fast, which leads to resource depletion in the absence of demand. Moreover, environmentally-aware consumers tend to associate this accelerated production cycle with environmental pollution. As a result, the growing public interest in green materials and lean manufacturing increases the popularity of brands that are associated with sustainable business practices. The relevance of the topic is due to the fact that the strategic communications system is also a subject to qualitative changes brought about by new trends and patterns. If a fashion enterprise changes its principles, philosophy, ideology, and strategic priorities in the context of environmental transformations, customers should be made aware of these changes. Strategic communications and their transformations in the TFC industry remain largely understudied. The author identified the current working tools of the strategic communications system that could provide effective long-term development in the fashion industry. The research relied on the theory and methodology of strategizing developed by Professor V.L. Kvint, Dr.Sc.(Econ.), Foreign Member of the Russian Academy of Sciences. Such standard methods as analysis, synthesis, generalization, abstraction, and benchmarking made it possible to reveal the key strategic trends and patterns that shape the contemporary strategic principles of entrepreneurship in the TFC industry. The resulting updated system of strategic communications is effective in bringing across new values to fashion consumers.

Exploring the reasons for defaulting from childhood immunization: a qualitative study in Pakistan

BackgroundChildhood vaccination is widely recognized as the most effective means to prevent various diseases. However, a considerable amount of children still miss out on their vaccination schedules. Therefore, this study explores the reasons for defaulting from the expanded program on immunization in district Swat, Pakistan.MethodsA qualitative phenomenological approach was used. Data collection took place from March to September 2022. Thirty-six in-depth interviews were conducted with participants who had defaulter children. The collected qualitative data were analysed thematically to identify key patterns and themes related to the reasons for defaulting from childhood vaccination schedules.ResultsSix themes emerged, i.e., illness of the defaulter child at the scheduled time, perceived side effects of the vaccination, factors related to caregivers, myths and misconceptions, vaccinators attitudes and crowed vaccination centres, as well as poor immunization service arrangements. Four subthemes arose related to caregivers, such as lack of clear understanding about completion of vaccination, least priority for child’s vaccination, cultural restriction on mothers, and the loss of vaccination card.ConclusionAccording to the study’s findings, caregivers have their own perceptions regarding the non-completion of their children’s vaccination schedule. The childhood immunization defaulting arises from various factors including child illness, Adverse Events Following Immunization (AEFIs) concerns, misconceptions, improper injection techniques, and negative vaccinator attitudes. The vaccination completion rate may be increased if the concerns of the caregivers are appropriately addressed.

Exhaust Gas Temperature Prediction of Aero-Engine via Enhanced Scale-Aware Efficient Transformer

This research introduces the Enhanced Scale-Aware efficient Transformer (ESAE-Transformer), a novel and advanced model dedicated to predicting Exhaust Gas Temperature (EGT). The ESAE-Transformer merges the Multi-Head ProbSparse Attention mechanism with the established Transformer architecture, significantly optimizing computational efficiency and effectively discerning key temporal patterns. The incorporation of the Multi-Scale Feature Aggregation Module (MSFAM) further refines 2 s input and output timeframe. A detailed investigation into the feature dimensionality was undertaken, leading to an optimized configuration of the model, thereby improving its overall performance. The efficacy of the ESAE-Transformer was rigorously evaluated through an exhaustive ablation study, focusing on the contribution of each constituent module. The findings showcase a mean absolute prediction error of 3.47∘R, demonstrating strong alignment with real-world environmental scenarios and confirming the model’s accuracy and relevance. The ESAE-Transformer not only excels in predictive accuracy but also sheds light on the underlying physical processes, thus enhancing its practical application in real-world settings. The model stands out as a robust tool for critical parameter prediction in aero-engine systems, paving the way for future advancements in engine prognostics and diagnostics.

Insights from international environmental legislation and protocols for the global plastic treaty

Plastic pollution has emerged as a global challenge necessitating collective efforts to mitigate its adverse environmental consequences. International negotiations are currently underway to establish a global plastic treaty. Emphasizing the need for solution-orientated research, rather than focusing on further defining the problems of widespread environmental occurrence and ecological impacts, this paper extracts insights and draws key patterns that are relevant for these international negotiations. The analysis reveals that (i) environmental rather than human health concerns have been the predominant driving force behind previous regulations targeting pollutants, and (ii) the decision to ban or discontinue the use of harmful pollutants is primarily affected by the availability of viable substitutes. These two key findings are relevant to the discussions of the ongoing Intergovernmental Negotiating Committee (INC) on the global plastic treaty and underscore the recognition of environmental consequences associated with plastic pollution while emphasizing the need to enhance the knowledge base of potential human health risks. Leveraging the availability of substitutes can significantly contribute to the development and implementation of effective strategies aimed at reducing plastic usage and corresponding pollution.

Forest tree community ecology and plant–soil feedback: Theory and evidence

AbstractMounting evidence suggests that reciprocal interactions between plants and the soil microbiota can be a primary force that generates key macroscopic patterns of plant communities (coexistence, dominance, and succession) in forest ecosystems. The aim of this article is to review empirical and theoretical perspectives of plant–soil feedback research in the context of forest community ecology. I first use a simple theoretical model to get insights into an array of the dynamics generated by plant–soil feedback: negative plant–soil feedback maintains plant species diversity and reduces plant growth, while positive plant–soil feedback drives plant growth of certain species and hence their dominance. I then describe how ecologists have unveiled the enormously complex plant‐microbiota interaction (i.e., the soil conditioning experiment) and review the linkage of plant–soil feedback with three key plant community patterns: (i) dominance, (ii) spatial structure and (iii) succession. I highlight one belowground plant trait (mycorrhizal type) that can mediate these linkages: arbuscular mycorrhizal species tend to exhibit negative plant–soil feedback while ectomycorrhizal species tend to exhibit positive plant–soil feedback. Although mycorrhizal plant–soil feedback potentially explains the patterns of tree diversity from local to global scales, many questions remain. Future studies should expand plant–soil feedback theory to incorporate numerous other feedback mechanisms and test how mycorrhizal types mediate the net feedback effects that could propagate to shape large‐scale forest structures and dynamics.

BARAAN: ISLAMIC PHILOSOPHY THROUGH RELIGIOUS TRADITION OF EID-FITR IN BENGKALIS RIAU

This research explores the Islamic philosophy embedded in the cultural traditions of the Bengkalis people. The research was motivated by the need to understand the unique Islamic perspective of the Bengkalis people and how it affects their way of life. The research methodology used in this study is qualitative, with the data collection process conducted through observation, interviews, and document analysis. The participants in this study were members of the Bengkalis community and the data analysis process involved identifying key themes and patterns that emerged from the data collected. The study found that the cultural traditions of the Bengkalis community are deeply rooted in Islamic philosophy, which is reflected in their daily practices, beliefs and values. The community's strong adherence to Islamic principles has helped shape their way of life, as well as their social and economic structure. So the findings of this research are "Baraan" Research reveals that Eid-Fitr in Bengkalis, Riau, is a religious tradition that is an important part of Islamic philosophy. This tradition is seen as a reflection of the values of sincerity, solidarity and unity of Muslims in Bengkalis. Overall, the "Baraan" research provides a deep understanding of the relationship between religious tradition and Islamic philosophy in the community of Bengkalis, Riau

The Double-Edged Sword: Analyzing the Influence of Technology on English Language Learning in Kuwait Higher Education Institutions (HEIs)

This study explores the dynamic interplay between advanced technology and teaching English to non-native speakers within university contexts. Focused on insights from academic staff at Kuwait University, the research explores both the merits and challenges associated with integrating technology into language education. The literature review examines the evolution from traditional to modern teaching methods, emphasizing technology's role in creating engaging and personalized learning experiences. As a global lingua franca, English is a focal point, with technology-driven approaches reshaping language education for non-native speakers. The consequences of integrating advanced technology unfold nuancedly, showcasing both positive and negative outcomes. The study reveals that while technology enhances access to diverse learning resources and improves writing tools, it poses challenges such as distractions, dependence, and potential superficial learning. The research design involves a qualitative approach, employing semi-structured interviews with 11 academic staff members in Kuwaiti institutions. Thematic analysis is utilized to extract key patterns and themes from the gathered data, providing valuable insights into teacher perspectives on the consequences of technology integration. The findings highlight drawbacks, including concerns about the quality of online content, overreliance on technology, and potential isolation, along with obstacles faced by higher education institutions, such as cost considerations and faculty challenges. The study proposes strategic solutions, advocating for professional development, equitable access to technology, and a balanced approach that integrates traditional and technology-driven methods. In conclusion, this study underscores the importance of thoughtful and ethical technology integration in English language education. It advocates for a holistic approach, considering the quality of instruction, critical thinking development, and the need for a supportive culture of innovation. As universities navigate the complexities of technology, these insights offer guidance for creating inclusive and impactful language learning experiences for non-native speakers in the ever-evolving landscape of higher education.