Current Environment Research Articles

Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics.

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Legal principles of forest fire protection on radiation hazardous lands of Ukraine in modern conditions

The legal framework for protecting forests from wildfires on radiation hazardous lands in Ukraine, especially in the current environment, considering the new challenges and threats posed by both martial law and accelerated climate change, requires a thorough analysis of the current legislation in this area, clarification of legal gaps, and identification of the most priority areas for its improvement. The purpose of this study was to analyse the system of current legislation aimed at regulating the protection and defence of forests from fires, including on radiation-hazardous lands of Ukraine, and to assess the level of efficiency of legal regulation of these social relations and to evaluate them. The methodological principles in the context of the study were general and special methods of scientific cognition, including formal logical, comparative legal, formal legal, statistical, analysis and synthesis, and dialectical methods. The study substantiated the complex nature of the system of forest protection against fires on radiation-hazardous lands. The study analysed the risks and threats of forest fires on radiation-hazardous lands in Ukraine. It is stated that the state of fire safety on the lands of the forest fund that have been affected by radiation is the most threatening at the present stage. Generalisations were made containing a set of necessary measures aimed primarily at strengthening the due level of interaction between the relevant services in organising forest protection from fires on radiation-hazardous lands of Ukraine in modern conditions. The practical value of this study lies in the fact that, considering the scientific theory and a set of methods of scientific cognition, it provides a thorough analysis of Ukrainian legislation and clarifies the peculiarities of legal support for the protection of Ukrainian forests from fires on radiation-hazardous lands at the present stage, which helped to determine the real state of legal regulation of the relevant area and gaps in the organisation of its application, which should actualise the improvement of law-making and law enforcement practice in the area under study. The findings of this study can be used to update the legal support for the activities of public institutions implementing the state policy in the field of forest protection on lands subjected to radioactive contamination

Internationalization of Higher Education and Emerging National Rationales: Comparative Analysis of the Global North and South

AbstractThis paper provides a comparative analysis of national rationales to higher education internationalization in the global north and south countries using content analysis. The results reveal that the socio-economic rationales are dominant across most of the 27 sampled countries. However, they manifest differently across the global north and global south as countries interpret the benefits and effects of internationalization in line with their national priorities. These variations are being shaped by an increasingly complex, competitive, and multipolar higher education internationalization landscape with new global south actors acquiring agency despite the deepening global inequalities. As a result, political rationales are becoming an important driver to internationalization. The current geopolitical environment associated with global conflicts, health pandemics, and increased nationalistic, anti-immigrant, and anti-globalization sentiments is also adding more uncertainty and complexity. Due to increased concerns about this multipolar and self-centred internationalization, a few countries are starting to promote inclusive approaches to internationalization.

Management Modelsvis-À-Vis the Challenge of a VUCA Environment and Wicked Problems

A reductionist approach assumes the existence of a stable, simple and clear environment, characterized by certainty. Under this approach, the forward-looking social and technological changes need to be planned as progressive and incremental, since they can then be anticipated sufficiently ahead in time to understand them and include them in the agenda, so as to prevent their impacts and correct any deviations. But the current environment where companies manage their businesses is quite far from this reality. Instead, the environment is volatile, uncertain, complex and ambiguous (the four words that characterize a VUCA environment), giving rise to wicked problems which are difficult to manage. This context will force companies to change their structures , practices and beliefs and, consequently, their management style. The purpose of this paper is to describe such changes and offer a proposal to better deal with the environment.

The Interpersonal Hypersensitivity Formulation of Good Psychiatric Management as a Psychoeducational Intervention for Borderline Personality Disorder.

Interpersonal hypersensitivity (IHS) is a core organizing concept of Good Psychiatric Management, a generalist treatment for borderline personality disorder (BPD) that relies on basic tools most clinicians already employ yet is informed by an organized and evidence-based framework, developed for dissemination in various mental health care settings. We work in an inpatient psychiatric unit that specializes in the management of suicidal crises at the University Hospitals of Geneva, Switzerland. Because we see numerous patients with previously undiagnosed BPD during their first hospitalization, we have developed techniques and instruments to promote efficient and easy-to-implement psychoeducation. In this article, we propose a practical and user-friendly measure of IHS that is well-suited for use by multidisciplinary inpatient staff or outpatient nursing-based staff, the IHS Ruler, which is based on a visual analog scale. It is a pragmatic tool for preliminary psychoeducation for patients with BPD and their caregivers. Its ease of use and structured way of presenting the inner experience of these patients in relation to their current interpersonal environment allows caregivers to establish a framework for internal reflection and sharing, discuss the causes of current transactions, and illuminate larger patterns in the causes of the patient's crises. Ultimately, this process can help patients and the clinical staff supporting them anticipate future problems.

New Development Bank's role in the global financial architecture

AbstractThe New Development Bank (NDB) was established in 2015 by the grouping of Brazil, Russia, India, China, and South Africa (referred to as the BRICS). The establishment of the NDB was one of the outcomes of the economic and political dissatisfaction arising out of the growing disparity between the BRICS' development needs, their share of the world economy, and their representation in the established institutions of the global financial architecture. The paper examines the origins of NDB, the unique aspects of its governance structure, innovations in its operational model, and the challenges it currently faces. The paper concludes that 9 years after its establishment, NDB has completed the core foundational work required of a new multilateral development bank. It is undoubtedly an interesting experiment in the creation of a new international financial institution, and it has made a good and solid start. However, the current global environment is very different from the world of 9 years ago. If the NDB can navigate well the current challenges and if it can scale up significantly, then the NDB indeed has the potential to make a significant impact on the global architecture of development finance. Whether it does so, remains to be seen.

Advances in Speech Emotion Recognition and Analysis: A Review of Applied Machine Learning Methodologies

Abstract: The most important marketing tactics in the current environment is emotion detection based on individual’s interests, allowing extensive customization to cater to the varied needs of customers. For instance, contact centers may start playing music while a caller is on the line if they are agitated. A smart car that slows down when the driver is angry or scared is another illustration.The recognition of speech emotion has become a vital task in the field of computer science department . A very important aspect of human emotional state information is speech emotion that is the source of communication between human and computer interactions . The recognition of speech emotion is currently a very hot topic in the field of machine learning and deep learning and many systems have been build and are currently working on the recognition of these speech emotions using deep learning and neural networks algorithms. In this paper, various types of models and features like Mel-frequency Cepstral Coefficients (MFCC), Modulation spectral features (MSFs), Low-Level Descriptors(LLDs) for speech emotion recognition are categorized. Ultimately, the algorithms like recurrent neural network(RNN), support vector machine(SVM) used in different models are tabulated presenting their advantages and disadvantages along with their features and efficiency.

Harnessing collaborative learning automata to guide multi-objective optimization based inverse analysis for structural damage identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

دور القيادة التحويلية في تعزيز الالتزام والولاء للموظفين في القطاع الخاص في محافظة الرياض

This study aims to explore the role of transformational leadership in enhancing commitment and loyalty among employees in the private sector in Riyadh Province. Transformational leadership is considered a style of leadership that relies on building strong and sustainable relationships between leaders and followers, encouraging participation in decision-making, and fostering innovation and creativity. Riyadh Province, with its diverse array of companies and institutions across various sectors, provides an ideal environment for investigating this topic. The research methodology includes a review of literature related to transformational leadership and its impact on employee commitment and loyalty, as well as data collection through surveys distributed to a random group of employees in several private companies in Riyadh Province. The data were analyzed using advanced statistical methods to understand the relationship between transformational leadership variables and the level of commitment and loyalty among employees. The results of the study indicate that transformational leadership plays a crucial role in enhancing employee commitment and loyalty in the private sector in Riyadh Province. The study also shows that key factors contributing to the success of implementing transformational leadership include supportive organizational culture and strong managerial direction. Based on these findings, the study provides practical recommendations for leaders and managers in the private sector in Riyadh Province on how to enhance transformational leadership and use it effectively to achieve organizational goals and enhance employee satisfaction and loyalty. Thus, the study contributes to a deeper understanding of the role of transformational leadership in improving performance and enhancing commitment and loyalty among employees in the private sector in Riyadh Province, and provides a practical framework for achieving this in the current work environment.

Characteristics of research on green marketing. Theoretical study.

The article highlights how the idea of sustainability has become an integral part of the business economy, presenting more effective strategies that can be adopted within companies to gain increasingly competitive advantages linked to sustainability. The concept of green marketing, focused on promoting products and services with low environmental impact, is gaining increasing relevance in this context. The number of companies adopting sustainable practices is growing significantly, partly due to the increasing attention that states and international organizations are devoting to sustainability. The social benefits arising from the synergy between business activities and sustainability are recognized, prompting various entrepreneurial entities to adopt these perspectives. This trend involves companies from every sector and size, as they operate in a globalized market influenced by the surrounding environment. To achieve effective integration of sustainability, companies should adopt innovative approaches that not only address the complex market challenges but also create long-term value. This not only improves the relationship with stakeholders who share values and objectives but also reflects a commitment to responsible business management. Green marketing represents an essential tool in this context, promoting eco-friendly products and services, facilitating the communication of sustainable practices adopted by companies. This approach not only helps build a positive corporate image but can also positively influence consumer purchasing decisions, as they are increasingly oriented toward products and services that respect the environment. Furthermore, to tackle this complex challenge based on competitiveness, companies need to develop a robust Environmental, Social, and Governance (ESG) evaluation plan. This plan not only focuses on reducing environmental impact and responsible resource management but also contributes to enhancing corporate reputation, thus creating enduring value over time. The goal of the article is to analyse how the integration of green marketing and sustainability can generate competitive advantages and create long-term value for companies. By examining the current business environment and the increasing importance of sustainability in the corporate environment, the article aims to identify the most effective strategies to promote products and services with a low environmental impact and to transparently communicate the sustainable practices adopted. In addition, the article aims to highlight the social benefits of the synergy between business and sustainability, which are driving more and more companies to adopt these perspectives. Through the analysis of case studies and empirical data, an attempt will be made to demonstrate how the implementation of innovative approaches can not only address market challenges, but also improve stakeholder relations and enhance corporate reputation. Finally, the article aims to examine the importance of a sound environmental, social and governance (ESG) assessment plan in addressing competitive challenges, highlighting how such a plan can contribute not only to the reduction of environmental impacts, but also to the creation of lasting value through responsible business management.

Big Data Analytics: Analyzing the Significance of it in Light to Indian Banking Sector

Abstract: Banks are the engines that drive the financial sector, monetary markets, and economic expansion. Since the introduction of information technology (IT) in the 1980s, 1990s, and 2000s, the Indian banking sector has experienced a number of changes in terms of how IT is applied to various banking operations from different perspectives, such as cutting expenses, earning revenue, detection of fraud, security concerns, etc. These changes are still ongoing with the emergence of new trends like business intelligence and big data analytics. Banks are utilizing big data to their advantage. To obtain a general competitive edge, they push for innovations in data and analytics through the use of big data and data science. Due to the vast amount of data about transactions that banks collect, big data has the ability to completely change business operations and procedures. Big Data analytics is the answer to the current banking environment's challenges of growing competitiveness, fraud, and cyber security risks.

Optimizing Customer Relationships: A Case Study of CRM Practices at Puma Outlet in Ahmedabad city of Gujarat

Effective client Relationship Management (CRM) techniques are essential in the current competitive retail environment to maintain client loyalty and stimulate corporate expansion. This study aims to investigate and assess customer relationship management (CRM) techniques used in Puma shops. It seeks to provide insights into the impact of these tactics on customer relationships and the overall success of the organisation. The study uses a qualitative methodology, conducting in-depth interviews with branch managers in various geographical areas and market conditions. The findings indicate that common customer relationship management (CRM) tactics include the use of technology to handle data, personalised marketing efforts, and the implementation of loyalty programmes. The positives that have been identified include the efficient utilisation of customer data and the proactive interaction with customers. On the other hand, the limitations are related to the integration of CRM practices across all points of contact and the maintenance of data quality.This study makes theoretical contributions by connecting CRM theories with actual implementations, emphasising the changing role of technology and human interaction in enhancing CRM effectiveness. This study enhances the current CRM literature by offering in-depth understanding of a particular retail environment, opening up opportunities for further investigation into upcoming technologies and CRM tactics across other retail sectors.Ultimately, the results emphasise the crucial significance of CRM methods in cultivating client connections and promoting retail achievements in the digital age. Retail managers may use these observations to continually enhance their CRM strategies, while researchers are urged to explore more into the ever-changing environment of CRM to further enhance retail efficiency and consumer involvement.

A hydrogel-modified electrochemical biosensor for the rapid detection of ammonia‑nitrogen-resistant bacteria

Ammonia‑nitrogen wastewater is one of the main pollutants in the current environment. Rapid detection of microorganisms resistant to ammonia‑nitrogen provides a basis for bioremediation of ammonia‑nitrogen contaminated sites. This study uses electrochemical analysis for efficiently detecting of ammonia-resistant bacteria, utilizing a commercially available, low-cost screen-printed electrode (SPE) modified with agarose-based hydrogel (gel) or graphene oxide (GO). At the same time, the study employed electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) to monitor bacterial growth, revealing Escherichia coli (E. coli) inhibition upon ammonia‑nitrogen addition, while Raoultella terrigena (RN1) and Pseudomonas (RN2) exhibit tolerance. The method provides sensitivity results in <45 min, which is significantly faster than traditional methods. RN1 and RN2 exhibit promising ammonia‑nitrogen removal rates, reaching up to 81 % and 92 %, respectively. This study aimed to develop an effective electrochemical method for rapidly detecting the sensitivity of microorganisms to ammonia‑nitrogen. The method offers advantages such as high speed, efficiency, and cost-effectiveness, potentially providing valuable microbial resources for mitigating ammonia nitrogen wastewater pollution.

Research on Foreign Language Talent Cultivation Mode Based on the Concept of Language Security

Language security is an important part of national security, and in the current complex international environment, the issue of language security is becoming more and more prominent and has become an unignorable part of national security strategy. As the bridge and link of international communication, foreign language talents’ language skills and the level of national security awareness directly affect our country’s international image and the effect of international communication. Therefore, the establishment of a foreign language talent cultivation mode based on the concept of language security is not only an important way to improve the quality of foreign language education but also a realistic need to safeguard national security and promote international exchanges. Starting from the influence of the language security concept on foreign language talent cultivation, this paper analyzes the foreign language talent cultivation mode based on the language security concept, with a view to providing new ideas and methods for the development of foreign language education.

Application of form honeypot based on CSS style in ticket booking system

Since various means of transportation and entertainment activities are restricted by objective conditions, the number of tickets is always limited, so ticket scalpers continue to be a companion product to this day. In the current Internet environment, the web application of the ticketing system faces challenges from ticket-grabbing robots controlled by ticket dealers. The current security procedures have significantly increased the workload and time consumption of effective users. The question now is whether ticket-grabbing bots can be stopped without increasing the workload of legitimate users and being as unnoticed by users as possible. In response to this problem, this article proposes a ticket booking system model integrated with a form-based honeypot, which can achieve the function of deceiving robots without being noticed by ordinary users. This model provides a feasible method for implementing network applications that are both secure and efficient, ensuring that users have a more seamless and protected experience.

Tactical Intelligent Decision Modelling in Sports Competitions Based on Reinforcement Learning Algorithms

Tactical intelligence refers to the ability to gather, analyze, and apply information swiftly and effectively to achieve specific goals or objectives in dynamic and often challenging situations. It involves understanding the current environment, assessing available resources, and making informed decisions to gain a competitive advantage or mitigate risks. Tactical Intelligent Decision Modelling in Sports Competitions, grounded in Reinforcement Learning (RL) algorithms, represents a cutting-edge approach to enhancing strategic decision-making processes within athletic domains. This innovative methodology leverages RL's ability to learn optimal actions through trial and error, adapting strategies based on feedback received from the environment. By applying RL algorithms to sports competitions, teams can develop intelligent decision models that dynamically adjust tactics and strategies in response to changing game conditions and opponent behaviors. Such models enable teams to optimize their performance, exploit opponent weaknesses, and capitalize on opportunities during competitions. This paper introduces Predictive Weighted Big Data Reinforcement Learning (PWBDRL), an innovative approach aimed at optimizing decision-making processes and performance outcomes in sports competitions. Leveraging predictive analytics, big data techniques, and reinforcement learning, PWBDRL offers a comprehensive framework for athlete prediction and strategy optimization. The results show a remarkable increase in win rates, with the RL-based decision models achieving an average win rate of 80.5% compared to 65.2% with traditional methods. Additionally, we observe a substantial enhancement in average scores, with the RL-based models achieving an average score of 95.6 compared to 78.3 with baseline approaches. Moreover, the RL-based models exhibit superior adaptability, requiring fewer iterations to converge to optimal strategies, with an average convergence time of 200 episodes compared to 500 episodes for traditional methods.

Unveiling the Linguistic Landscape: Examining the Influence of Digital Communication in Social Media and Text Messaging on Language Development

Social media and SMS are examples of digital communication tools that have drastically altered how people communicate. As a result, linguistic standards and usage have rapidly evolved. This article looks at how language has changed as a result of digital communication and how new linguistic traits and conventions have emerged. It examines how the current linguistic environment has been shaped by the widespread use of acronyms, emojis, abbreviations, and internet slang. This article comes to the conclusion that creative linguistic adaptations and new forms of expression have been sparked by digital communication through a thorough analysis of the scholarly literature and real-world language use on digital platforms. There is also discussion of how these language shifts brought about by digital technology affect interpersonal communication, education, and literacy. The ultimate goal of this article is to show how social media and SMS have significantly influenced language evolution in the current digital era.

Integration of optimal power flow with combined heat and power dispatch of renewable wind energy based power system using chaotic driving training based optimization

Combined heat and power economic dispatch (CHPED) based optimal power flow (OPF) problem has been studied in this article using a new, practical approach based on chaotic driving training optimization (DTBO) (CDTBO). In the proposed technique (CDTBO), the chaotic based learning is integrated with DTBO to overcome the local optimal problem and inferior convergence speed of the existing algorithms. OPF is an important concern to retain the power system running effectively. In order to meet the demand for reasonably priced power generation with optimal power flow in transmission lines, the authors combined CHPED and OPF. Since fuel is changing daily in the current environment, using renewable energy sources to generate electricity economically is crucial. The renewable energy source like wind energy is integrated with thermal units for economic power generation with reducing the thermal fuel consumption of CHPED-based OPF system. The proposed technique implemented on CHPED based IEEE-30 bus system for renewable and without renewable energy sources with considering different cases. The suggested problem considering with valve point loading of thermal units, transmission losses and uncertainties of wind speed to address the non-linearity of the renewable-based CHPED-OPF system. Cost minimization, voltage deviation control, transmission losses minimization and stability index are the single objectives of the prospective system. Furthermore tested on multi-objective functions for simultaneously minimization of cost with emission and simultaneously minimization of active power loss with voltage profile. It is observed that the proposed CDTBO technique helps to reduce the cost by 2% and 12.8% for renewable based system as compared to non-renewable system for multi-objective function. The robustness of the proposed solution has been verified by implementing the statistical analysis on two systems with least variation of mean and optimal values of cost with the tolerance of less than 0.0035%. A comparison has been made with recent well known optimization techniques to address the superiority of the suggested CDTBO algorithm.

CRITERIA FOR DETERMINING THE COMPETITIVENESS OF HOSPITALITY ESTABLISHMENTS

Today, the tourism and hospitality industries are important social, economic, and cultural categories that serve as the basis for the development of economies in many countries. Ukraine is no exception. Although the full-scale invasion of Ukraine by the Russian Federation has left its mark on this sector of the economy, causing great losses, the situation has not changed globally and its development remains a priority today, especially in the context of Ukraine's vector towards European integration. This is what makes the chosen research topic relevant. Competition is a driving force for social and economic progress. In the current business environment in the market of hotel and tourist services, in order to maintain the competitiveness of a hospitality institution, it is necessary to implement a whole range of measures to form and consolidate competitive advantages. The competitiveness of a hospitality establishment must be sustainable not only in economic and environmental terms, but also in social, cultural and political terms. Thus, since the beginning of the full-scale invasion, a large number of hospitality businesses have suspended operations for security reasons, lack of demand, technical reasons, or as a result of damage or destruction from shelling. At the same time, despite the widespread understanding of the importance of defining it, there is no uniformity in the scientific literature in understanding the criteria by which it should be determined. In the article, the author makes an attempt to systematize the existing criteria for the competitiveness of hospitality establishments and identify those that are important for the development of hospitality establishments. Using such research methods as analysis, synthesis and the systematic method, the author has determined that such criteria should include the following indicators: pricing features, quality of services and amenities, online presence, human resources, effectiveness of marketing strategies used, and the ability to adapt and minimize risks. By analyzing the activities of the company and competitors in this niche, owners will be able to ensure a high level of competitiveness of their company.

Overcoming barriers to equality, diversity, inclusivity, and sense of belonging in healthcare education: the Underrepresented Groups’ Experiences in Osteopathic Training (UrGEnT) mixed methods study

BackgroundIndividuals from minority groups have historically faced social injustices. Those from underrepresented groups have been less likely to access both healthcare services and higher education. Little is known about the experiences of underrepresented students during their undergraduate studies in osteopathy in the UK. The aim of this project was to explore awareness of cultural diversity and beliefs about patients from underrepresented groups in current osteopathic educational environments and evaluate students’ preparedness to manage patients from diverse groups. The project also aimed to investigate the educational experiences of students from underrepresented backgrounds during their training and their opinions on changes that could support better levels of recruitment and achievement. The findings were discussed with stakeholders in interactive workshops with the aim to develop recommendations for action and change.MethodsA transformative action research paradigm informed this mixed methods project. It included: 1/ a survey of students from all seven osteopathic educational providers in the UK using the Multidimensional Cultural Humility Scale (MCHS); 2/ a series of focus groups with students from underrepresented groups (women, students with disabilities, students from minority ethnic backgrounds, and students identifying as LGBTQIA+); and 3/ a workshop forum to discuss findings.ResultsA total of 202 participants completed the MCHS and demographic questionnaire and seven focus groups were conducted. A model was developed to describe participants’ training experiences comprising two main themes: institutional contextual obstacles (with four sub-themes) and underrepresented students’ conceptual understanding of Equity, Diversity and Inclusion (EDI). Recommendations for change identified in the workshops were based on three topics: institutions, staff, and students.ConclusionOur findings confirm conclusions from other institutions that staff education is urgently needed to create and maintain equitable, inclusive environments in osteopathic educational institutions in the UK to support all students, particularly those from underrepresented groups. Institutional EDI processes and policies also need to be clarified or modified to ensure their usefulness, accessibility, and implementation.