The article considers the concept of organizational projectivity as a central element of assessing the maturity of an innovative company in the field of project management. Organizational projectivity is defined as the ability of an innovative company to anticipate changes, adapt to them, and effectively implement projects under conditions of un-certainty. The key aspects of projectivity are analyzed in detail: strategic vision, flexibility and adaptability, project management culture, use of technology and data, and knowledge management. Methods are proposed that allow in-creasing the level of maturity of an innovative company for each of the criteria considered. An illustrative example is given. The scientific novelty of the study lies in the integrated approach to assessing the maturity of an innovative com-pany in the field of project management through the prism of organizational projectivity. Unlike traditional assessment models that focus on processes and methodologies, this work focuses on the ability of an innovative company to fore-cast, adapt and innovate. A structured model of organizational projectivity is substantiated, reflecting five key ele-ments: strategic vision, flexibility, project management culture, use of technology and knowledge management. This approach allows not only to assess the current level of maturity of an innovative company, but also to determine the directions for its further development. In addition, the work contributes to the theory of project management, expand-ing the understanding of the role of organizational culture and strategic thinking in the successful implementation of projects. The practical significance of the study lies in providing innovative companies with specific tools and recommen-dations to improve their maturity in the field of project management. Practical steps are proposed to develop organizational projectivity, such as the introduction of flexible methodologies, the creation of a culture of change, the use of modern technologies and knowledge management systems. In addition, the work can be useful for project managers and executives who seek to integrate project management into strategic planning and make it an integral part of organ-izational culture.

This paper explores how the concept of plurilingualism is positioned to act as an impetus for linguistic and cultural inclusion in human-rights-based language education. Drawing on frameworks foregrounding descriptors for plurilingualism and democratic citizenship, the paper employs discourse analysis and sorting techniques to identify and align strategies of linguistic and cultural inclusion found in multimodal plurilingual task artefacts collected from a multi-year, multi-site research partnership between a Canadian university and the Italian Ministry of Education. The findings reveal that the implementation of plurilingual tasks aligns with key elements of democratic, rights-based language education, including critical understanding of communication, openness to cultural otherness, cooperation skills, and the valuing of cultural diversity. The findings of this paper contribute to further understanding of the concept of plurilingualism and to empirically informed perspectives on pedagogies that support language rights as human rights in education.

The article discusses the possibilities of interdisciplinary collaboration between archaeology and cultural anthropology/ethnology. What seemed some decades ago unthinkable, due to the elusiveness or inaccuracy of oral tradition perceived from the archaeological side, has recently provided new perspectives for understanding space, the key concept that links both humanistic disciplines. The article shows some basic theoretical concepts, enabling interdisciplinary collaboration between the two disciplines. The key elements which connect the two disciplines are space, the oral tradition attached to it and collective memory. The traditional perception of space can offer a better understanding of some archaeological materials. The oral tradition embedded in the landscape can give us some understanding of the continuity of symbolic values of places, such as liminal spaces or elements of mythical landscapes.

This paper investigates the challenges faced by contemporary univer-sities and highlights the need for innovative educational strategies in response to social, cultural, and environmental changes. As the Inter-net shifts the role of educators from sole knowledge providers to facil-itators of student-centred learning, peer tutoring and peer feedback emerge as pivotal methods for enhancing academic success and per-sonal growth. Central to this discussion are two case studies from the University of Groningen's Masters of Didactics program in 2022-2023, which il-lustrates a practical application of these strategies. The paper also re-views theoretical foundations of these methods, drawing on construc-tivist learning theories and Zone of Proximal Development. Key ele-ments for successful implementation of the strategies discussed in the case studies include trained tutors, well-informed students, struc-tured sessions, personalized support and continuous feedback. These characteristics not only enhance the learning experience but also cul-tivate essential interpersonal skills. Our findings underscore the positive impact of integrating peer tu-toring and feedback on student engagement, collaboration, and aca-demic performance. This paper advocates for the widespread adoption of these pedagogical approaches in higher education, emphasizing their role in creating an inclusive and effective learning environment that prepares students for future academic and professional chal-lenges.

Early studies suggest medical cannabis (MC) has the potential to benefit people who suffer from chronic pain by offering a less addictive alternative to opioids; however, most investigators agree more research is indicated. Today, in 2023, cannabis remains a Schedule I drug and is an illegal substance in the United States under the Controlled Substances Act of 1970. Despite this designation, as of February 2022, 37 states, three territories, and the District of Columbia allowed using cannabis products to treat certain painful medical conditions. The contradictory status of federal and state legislation regarding cannabis use has resulted in delays and restrictions on relevant research. As a result, an inadequate foundation of knowledge exists needed to inform policy, program, and practice decisions concerning MC to treat pain. Implementing and controlling access to MC is influenced by overlapping individual, interpersonal, community, and organizational influences that all fall under the umbrella of federal and state policies. Increasingly, the legalization and expanded access to MC necessitates the integration of evidence, policy, and social-ecological reality. To adequately delineate these complex factors to anticipate and plan future interventions at multiple levels, we propose a social-ecological framework (SEF) for using MC to treat pain. This SEF assumes the transactional relationship between the individual and the environment and that no single factor can predict behavior or health outcomes. Our framework illustrates five dynamic levels of analysis that interact between dimensions. Key elements and intersections are discussed at the intrapersonal, interpersonal, institutional, community, and policy levels.

This paper reflects on four studies of integrated project delivery in which 80 expert IPD practitioners were interviewed. Taking an institutional theory perspective with a focus on the cultural- cognitive pillar, this paper discusses how people make sense of complex situations and how they interpret what is the right course of action to take. The paper explores how their cultural- cognitive skills assists them and identifies four key elements that helps explain the development of a unified- team best- for- project mindset.

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;20:1566-1574. © 2023 SETAC.

Across Western nations, ‘ageing in place’ policies rely on having a sufficient and skilled aged care workforce. In Australia, due to the impact of successive policy reforms, this workforce including the sector that provides community-based services has declined in number and skills. At the same time the need to upskill and sustain this workforce has intensified as the frailty and health needs of consumers have increased. This paper reports on an integrative literature review undertaken during 2021 to describe workforce needs and peer reviewed reports of programs instituted in aged care settings that aimed to address these needs. The review sought to examine programs implemented in both long-term and community care settings and to draw from these elements that may be utilised in future program design across the sector. It focussed primarily on workforce deficits in the community aged care sector and on the capacity of rurally-based services to meet and respond to growing consumer demand. The findings emphasise current workforce deficits while they also reveal a paucity of peer-reviewed reports of implemented programs across the sector as a whole. Nevertheless, the few programs examined in this review provide examples of the capacity and willingness of workers and providers to trial measures that aim to increase the recruitment, retention, skill and job-satisfaction of direct care workers. We propose that the key elements of the programs identified in this paper provide the foundation for the development of strategically designed programs that address particular workforce needs such as those shaped by rural contexts.

With the surge of data-driven analysis techniques, there is a rising demand for enhancing the exploration of large high-dimensional data by enabling interactions for the joint analysis of features (i.e., dimensions). Such a dual analysis of the feature space and data space is characterized by three components, 1) a view visualizing feature summaries, 2) a view that visualizes the data records, and 3) a bidirectional linking of both plots triggered by human interaction in one of both visualizations, e.g., Linking & Brushing. Dual analysis approaches span many domains, e.g., medicine, crime analysis, and biology. The proposed solutions encapsulate various techniques, such as feature selection or statistical analysis. However, each approach establishes a new definition of dual analysis. To address this gap, we systematically reviewed published dual analysis methods to investigate and formalize the key elements, such as the techniques used to visualize the feature space and data space, as well as the interaction between both spaces. From the information elicited during our review, we propose a unified theoretical framework for dual analysis, encompassing all existing approaches extending the field. We apply our proposed formalization describing the interactions between each component and relate them to the addressed tasks. Additionally, we categorize the existing approaches using our framework and derive future research directions to advance dual analysis by including state-of-the-art visual analysis techniques to improve data exploration.

Abstract: Recently memristors have emerged as a form of nonvolatile memory that is based on the principle of ion transport in solid electrolytes under the impact of an external electric field. It is perceived as one of the key elements to building next-generation computing systems owing to its peculiar resistive switching characteristics. The switching mechanism in a memristor is mainly governed by filamentary conduction. Further, it can be employed as a memory as well as a logic element, which makes it an ideal candidate for building innovative computer architecture. Moreover, it is capable of mimicking the characteristics of biological synapses, which makes it an ideal candidate for developing a Neuromorphic system. In this review to begin with the switching mechanism of the memristor, primarily focusing on filamentary conduction, is discussed. Few SPICE models of memristor are reviewed, and their critical comparison is performed, which are widely used to build computing systems. An in-depth study on the various crossbar memory architecture augmented with memristors is reviewed. Finally, the application of memristors in neuromorphic computing and hardware implementation of Artificial Neural Networks (ANN) employing memristors is discussed.

This practice paper reflects on the experience of delivering leadership development for the voluntary sector through open-access online learning. We outline key elements of learning design and explore the potential and challenges of widening access to leadership development through this form of learning. We note the importance of aligning the conceptualisation of the leadership approach to learning and the principles of open access. The paper ends by offering insights for leadership development practitioners.

Comprehensive resources exist on how to plan a systematic review and meta-analysis. The objective of this article is to provide guidance to authors preparing their systematic review protocol in the...

This systematic literature review (SLR) aimed to investigate the potential of digital online game-based learning (DOGBL) to enhance motivation in English as a foreign language (EFL). Online gaming has grown in popularity among students, opening up the possibility of using games as powerful instructional resources. Academic achievement depends on motivation, and this study, led by self-determination theory (SDT), explored how external rules, like rewards and recognition, could increase motivation in EFL utilizing DOGBL. The study used the SLR method, examining databases and choosing articles based on predetermined criteria. The chosen publications were examined in-depth, and a preferred reporting items for systematic reviews and meta-analyses (PRISMA) diagram was employed for analysis. For results, DOGBL could enhance teaching EFL by providing flexible and interesting learning environments. Key elements in motivating in DOGBL included game design, personalization, social engagement, curricular integration, and instructor assistance. As a promising method to improve EFL instruction, game-based learning, especially DOGBL, saw considerable developments between 2018 and 2023. Thus, these ground-breaking techniques transformed the way people learn English vocabulary and provided a fun and engaging way to learn the language. For educators and students, the potential for DOGBL to change EFL education is still exciting as technology develops.

As energy-intensive entities, data centers are associated with significant environmental impacts, making their sustainability a subject of growing interest in recent years. In this article, we revisit data center sustainability and propose a forward-looking vision for improving data center sustainability. We argue that data center sustainability encompasses more than just energy efficiency and must be evaluated and optimized through a multi-faceted approach. To this end, we first present an overview of the sustainability metrics from five aspects. After that, we demonstrate the sustainability status of the latest data centers utilizing publicly available data center sustainability ratings. Furthermore, we examine the evolution of data center sustainability standards in Singapore to highlight several trending features. Based on the analysis, we identify several key elements of sustainable data centers. We then propose the Cognitive Digital Twin (CDT) architecture, which incorporates a digital twin engine for system-wide simulation and a decision engine for optimal control to improve data center sustainability. A case study is performed to optimize the chiller plant efficiency of a production data center in Singapore. The results demonstrate that the CDT can improve chiller plant energy efficiency by 5%, indicating around 140 metric tons of annual carbon emission savings.

ABSTRACT Contemporary Islamophobia, while pervasive in the West, has now escalated in societies as distinct as China, India, Myanmar, and Israel in the post-9/11 era. Yet, Islamophobia is not something new, with roots from the centuries after Islam’s founding. This study argues that a global-historical framework is necessary to fully understand Islamophobia’s origins and impact. It extends previous global critical race and racism frameworks and their focus on whiteness to include an emphasis on the epistemological and structural foundations of global Islamophobia. Within these foundations, two key elements are forwarded as the basis for a guiding ontology of whiteness: (1) the Enlightenment-era epistemological transition from religious ways of knowing to knowledge based on controlled and controlling rationality; and (2) the institutions built by European conquest. Using this conceptual framework, the study traces a genealogy of Islamophobia to identify five key moments in its development and resurgence.

Human papillomavirus (HPV) vaccine introduction is anticipated in many countries in the coming years. This Perspective addresses the opportunities and challenges of introducing HPV vaccination in Pakistan. A substantial portion of the population within the high-risk age group necessitates the implementation of a robust vaccination strategy. Advocacy, community mobilization, and stakeholder engagement are the key elements for the successful implementation of the vaccination program. However, for long-term control strategies, a multifaceted approach is recommended. This approach should involve integrating HPV vaccination into the national immunization program, improving access to screening methods, and establishing comprehensive and cost-effective programs for preventing cervical cancer.

Key elements for achieving high impact and their relationship to the SDGs: Analysis of BCorp-certified companies in the primary sector

Current targets, which have been set at both the European and the international level, for reducing environmental impacts and moving towards a sustainable circular economy make energy efficiency and digitization key elements of all sectors of human activity. The authors proposed, developed, and tested a complex methodology for real-time statistical analysis and forecasting of the following main elements contributing to the energy and economic performance of an end user: energy performance indicators, power quality indices, and the potential to implement actions to improve these indicators, in an economically sustainable manner, for the end user. The proposed methodology is based on machine learning algorithms, and it has been tested on six different energy boundaries. It was thus proven that, by implementing an advanced energy management system (AEMS), end users can achieve significant energy savings and thus contribute to the transition towards environmental sustainability.

Cinematic Virtual Reality (CVR) is a style of narrative-based Virtual Reality (VR) experience built on filmed or computer-generated 360-degree videos. Since CVR is becoming more popular and widely accessible, researchers and practitioners have been trying to address challenges such as the conflict between the viewer’s freedom of choice and the creator’s control over where to look, or the risk of missing key story elements due to such freedom. As part of the solution, CVR creators employ attention-guiding cues, introduce viewer interaction, and combine these two techniques into all-encompassing CVR production frameworks. However, there are very few CVR projects that embrace the various differences in the backgrounds, preferences, and expectations of each individual viewer. Further to this, they do not consider the content creator/owners’ perspective when presenting and digitizing stories from the real world, especially when considering viewer’s connection to the cultural significance contained. In this article, a case study is presented to explore the use of adaptability to viewer situations and the coherence to Māori (the indigenous people of New Zealand) storytelling contexts in CVR experiences. In the case study, we began with co-design sessions with storytellers from Te Rau Aroha Marae (an active Māori cultural heritage site in the deep south of New Zealand), about appropriate features to collect from visitors to a virtual storytelling event , then co-built personas as representative tools. 360-degree videos of pūrākau (stories) were then captured and presented via an adaptable VR system. Evaluations were conducted with the storytellers to validate the system and to collect reflections and opinions on both the use of CVR in Māori storytelling and the cultural appropriateness of CVR with adaptability. We conclude this article with a discussion of possible improvements for future CVR frameworks.

Autonomous driving depends on reliable perception systems that involve various perception modules and advanced computer vision techniques. One crucial component of these systems is lane detection, which traditional methods often rely on basic features like color or edges that are sensitive to lighting and perspective changes. Recently, convolutional neural networks (CNNs), have revolutionized lane detection. Nevertheless, existing methods still have some limitations, such as the need for pixel-level labeling and computational inefficiency for real-time applications. To address these challenges, this work leverages PP-LiteSeg for real-time semantic segmentation. PP-LiteSegs key elements are its Simple Pyramid Pooling Module (SPPM), Unified Attention Fusion Module (UAFM), and Flexible and Lightweight Decoder (FLD), which optimize lane detection efficiency. The FLD flexibly adjusts computational costs between the encoder and decoder, balancing efficiency and accuracy. The UAFM enhances feature representations using attention mechanisms, increasing segmentation accuracy. The SPPM efficiently aggregates contextual information while reducing computational complexity. The comprehensive method for lane segmentation achieves competitive results on popular lane detection datasets. The proposed model can adapt to different computational capabilities and significantly enhances lane detection efficiency for real-time applications.