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Values have long guided special education services and supports for students with extensive support needs; over the past four decades, those values have been backed by research evidence demonstrating the critical nature of values related to inclusive education, self-determination, and seeking strengths and assets. In this chapter, we investigate these values and their supporting research, documenting strengths and needs in extant research. We emphasize the need to continue to embrace and maintain these values while pursuing research that addresses research gaps while centering the priorities, perspectives, and preferences of people with extensive support needs.

In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.

Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.

A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.

This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.

It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.

Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.

Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.

Misunderstanding and harmful stereotyping have become commonplace amongst people in the United States and the Middle East/North Africa (MENA) region since 2001, if not earlier. If universities are the locus of transformative education, work remains towards remedying these issues.One non-profit organisation, “Natafaham (pseudonym, Arabic for « we understand each other”), works to undo this negativity student by student. It brings participants from the MENA and Europe/North America into dialogue via Zoom each week. The inter-cultural dialogue availed to participants is empowering to actors, including the dialogue facilitator. This narrative is an autoethnographic exploration of my experience as an intercultural dialogue facilitator. Yet reviewing contemporaneous notes and reflections revealed structural aspects of this programme that empower voices from the MENA region, while facilitating learning amongst participants on both sides of the Atlantic. Such aspects include the format and the location of the programme, its focus on individuals rather than institutions or groups, its mixed top-down and bottom-up approach, and the opportunities it avails for ascension to positions of authority. This narrative analyses these aspects through several lenses and academic traditions, including those of global citizenship, critical internationalisation, (reciprocal) global service learning, and socio-cultural frameworks of second language acquisition. The chapter urges that these aspects are recognised as key catalysts of (more) equal relationships between youth in the MENA region and the United States, which merit widespread replication. It concludes by envisioning a still more equal relationship predicated upon more equitable language usage.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

To ensure that students are well prepared to successfully analyze this case, they should be familiar with the following concepts, theories and principles:

▪ Stakeholder theory

▪ Concept of duty to consult and accommodate

▪ Concept of social license to operate (SLO)

▪ Concept of indigenous economic self-determination

▪ Indigenous world view

▪ Seventh generation principle

▪ Cree principles

▪ Dene principles

The information provided in this case was gathered by the authors through face-to-face interviews, phone interviews, e-mail exchanges and secondary research. Meadow Lake Tribal Council (MLTC) separates business operations from council operations through use of corporate entities (as shown in Exhibit 1 of the case). Meadow Lake Tribal Council II (MLTCII) is the corporate entity that oversees two companies referenced in the case: Mistik Management and NorSask Forest Products LP. Interviews were conducted with the General Manager at Mistik Management, Certification Coordinator at Mistik Management, Chief of Buffalo River Dene Nation, Chief of Waterhen Lake First Nation, MLTC Vice-Chief, Board Member and Advisor to MLTCII, President and CEO of MLTCII, MLTCII Business Development Consultant and a former consultant with MLTC, NorSask Forest Products and Mistik Management.

Mistik Management Ltd., a forestry management company co-owned by the nine First Nations of MLTC, was a leader in economic reconciliation in 2022. However, the company had dealt with significant challenges not long after it was established in 1989. Richard Gladue, former Chief of the one of MLTCs Member First Nations and a leader in economic development at MLTC, had been actively involved in establishing the organization. Gladue loved the life and vitality of the boreal forest in the Meadow Lake region and felt a sense of responsibility to take care of the forest and the land for generations to come. This responsibility was balanced with the acknowledgement that the forest also provided vast economic development, employment and wealth generation opportunities for MLTC and its Member First Nations.

In the early 1990s, MLTC and Mistik Management dealt with a year-long blockade by a group of protesters that included members of Canoe Lake Cree First Nation, one of the Member First Nations of MLTC. They had not been consulted on Mistik’s processes and policies, and the company’s clear-cut logging had affected their ability to continue their traditional way of life and practices on the land. After the incident, Mistik Management moved more quickly to invest in a co-management process that they were still refining and using in 2022 when consulting with Indigenous groups and communities.

A natural resource economy brings together Indigenous peoples, industry and government. In this case, students will learn about the important role that relationships play and how decisions are made when balancing complex legal, environmental and economic interests. Students will learn about the history of duty to consult and accommodate in Canada; conduct a stakeholder analysis and reflect on how decisions affect stakeholder interests; and make recommendations for meaningful Indigenous engagement strategies using the concept of social license and indigenous principles.

This case is suitable for use in undergraduate courses on indigenous business, ethical decision-making, public policy and/or natural resource development. There may also be applications in other fields of study, including anthropology, economics and political science.

If the case is used in an indigenous business course, it would be best positioned in the last third of the class, after topics such as duty to consult and accommodate, social license and meaningful engagement with indigenous communities have been covered. If used in an ethical decision-making course, it would be best used when discussing stakeholder theory and engaging in stakeholder analysis. If used in a public policy course, the case could be used to start a discussion around the duty to consult and accommodate indigenous communities in Canada. If used in a natural resource development course, the case would be best used as an example of indigenous economic development.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

Globally “non-urgent” health care services were ceased in response to the 2020 outbreak of COVID-19, until 2021, when restrictions were lifted. In the UK, this included speech and language therapy services. The implications of COVID-19 restrictions have not been explored. This study aimed to examine the impact of the UK’s COVID-19 response on speech and language therapy services.

An online survey of the practice of speech and language therapists (SLTs) in the UK was undertaken. This explored SLTs’ perceptions of the demand for their services at a time when COVID-19 restrictions had been lifted, compared with before the onset of the pandemic. The analysis was completed using descriptive statistics and content analysis.

Respondents were mostly employed by the UK’s National Health Service (NHS) or the private sector. Many participants reported that demands on their service had increased compared with before the onset of the pandemic. The need to address the backlog of cases arising from shutdowns was the main reason for this. Contributing factors included staffing issues and redeployment. Service users were consequently waiting longer for NHS therapy. Private therapy providers reported increased demand, which they directly attributed to these NHS challenges.

This presents the only focused account of the impact of the national response to COVID-19 on speech and language therapy services in the UK. It has been identified that services continue to face significant challenges, which indicate a two-tier system is emerging. Healthcare system leaders must work with service managers and clinicians to create solutions and prevent the system from being overwhelmed.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.