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Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.

The purpose of this paper is to examine how participants in diverse schools newly implement the Sanford Harmony social and emotional learning (SEL) program and perceive its benefits for students and overall school climate.

The current study employed a convergent parallel mixed-methods design with a sample of five elementary schools in the western USA. Measures included classroom observations, administrator interviews, teacher interviews and focus groups, student focus groups, and a teacher questionnaire.

Findings indicated expected variation in implementation across schools, although all participants reacted favorably to the program and, importantly, would recommend the program to others. Administrators, teachers and students all saw the value of the program, particularly in terms of student relationship building and improved school climate. Implementation challenges experienced by schools were consistent with research on diffusion of innovations.

The present study demonstrates the importance of effective professional development, continued support, collective decision making and intentional integration of the SEL program throughout a school to support robust implementation and ultimately achieve intended outcomes.

Researchers have yet to examine in-depth implementation of the Sanford Harmony program and how best to support scale-up and more intentional implementation in schools. As implementation fidelity is a key component of a program achieving intended outcomes, the findings from the present study contribute to the knowledge base of supporting SEL program implementation.

This article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.

A literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.

Findings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.

Given the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.

This article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.

The purpose of this study is to review evidence on the nature of effective leadership in interprofessional health and social care teams.

A critical review and thematic synthesis of research literature conducted using systematic methods to identify and construct a framework to explain the available evidence about leadership in interprofessional health and social care teams.

Twenty-eight papers were reviewed and contributed to the framework for interprofessional leadership. Twelve themes emerged from the literature, the themes were: facilitate shared leadership; transformation and change; personal qualities; goal alignment; creativity and innovation; communication; team-building; leadership clarity; direction setting; external liaison; skill mix and diversity; clinical and contextual expertise. The discussion includes some comparative analysis with theories and themes in team management and team leadership.

This research identifies some of the characteristics of effective leadership of interprofessional health and social care teams. By capturing and synthesising the literature, it is clear that effective interprofessional health and social care team leadership requires a unique blend of knowledge and skills that support innovation and improvement. Further research is required to deepen the understanding of the degree to which team leadership results in better outcomes for both patients and teams.

In the fall of 1966, a small and informal group of wives whose husbands were classified as Prisoner of War (POW) or Missing in Action (MIA) formed a small and informal group. By December 12, 1969, this group of women had gained such power, influence, and a multitude of disparate followers that twenty-six met with President and Mrs. Pat Nixon at the White House. In part, the POW/MIA story is about a small group of women taking a decisive role to change the United States POW/MIA policy, accentuate the plight of the prisoners, and demand humane treatment by Hanoi—all in a national and global arena.

Leadership education must evolve to keep pace with the growing recognition that effective leadership happens in a complex environment and is as much a systemic variable as a personal one. As part of a program review process, a graduate leadership program at a private Midwestern university conducted a qualitative review of 18 online graduate programs in leadership education. In the absence of a discipline or accrediting body to govern leadership degree programs, we utilized the integrating framework of complexity leadership theory (CLT), as well as two professional societies, to understand how the curricula and competencies of online graduate education align and diverge to meet the changing assumptions and challenges of leadership.

investigate and analyze the aspects of legitimation, theorization and trends for the evolution of research in information technology governance (ITG) in Brazil, according to researchers familiar with the matter.

By means of a qualitative and quantitative research of exploratory-descriptive approach, the Delphi method was applied using a questionnaire supported by content analysis.

ITG is an increasingly interdisciplinary research field, with significant help from other fields of knowledge, such as administration, computer science and engineering. The main means of ITG publication are periodicals (MISQ, JMIS, JISTEM RESI), scientific events (AMCIS, ECIS, HICSS, EnANPAD, CONTECSI) and researchers, such as Peter Weill and Edimara Mezzomo Luciano. Best practice models are the most significant theoretical frameworks, and the main trend of research are on emerging technologies such as cloud computing and Internet of things (IoT) in the context of ITG.

To the unavailability of some researchers to participate in the second phase of the Delphi research performed, as well as the non-completion of a third Delphi round. Likewise, the “Block B (open answer questions)” it was not contemplated in the second phase for a new collection of answers, which could partially change the results presented here.

The results show important insights for ITG researchers that can allow new researches about its applications, jointly reflecting on relevant aspects for the advancement of this research field.

There are several research contributions to broaden the discussion and the evolution of this new scientific field in Brazil and that can be grouped for each set of stakeholders: academia and related researchers; the practicing community of business managers and private and public organizations; the academic legitimizing bodies; the non-academic legitimating bodies and researchers from other areas of knowledge.

ITG is a concept that emerged as part of corporate governance (CG), which has evolved as an emerging theme and is expanding in the international academic arena. However, the current stage of legitimation, theorization and trends of ITG in the Brazilian researches are lacked greater understanding, in order to provide better targeting for new researches.

Dynamic advertising, including television and online video ads, demands new theory and tools developed to understand attention to moving stimuli. The purpose of this study is to empirically test the predictions of a new dynamic attention theory, Dynamic Human-Centred Communication Systems Theory, versus the predictions of salience theory.

An eye-tracking study used a sample of consumers to measure visual attention to potential areas of interest (AOIs) in a random selection of unfamiliar video ads. An eye-tracking software feature called intelligent bounding boxes (IBBs) was used to track attention to moving AOIs. AOIs were coded for the presence of static salience variables (size, brightness, colour and clutter) and dynamic attention theory dimensions (imminence, motivational relevance, task relevance and stability).

Static salience variables contributed 90% of explained variance in fixation and 57% in fixation duration. However, the data further supported the three-way interaction uniquely predicted by dynamic attention theory: between imminence (central vs peripheral), relevance (motivational or task relevant vs not) and stability (fleeting vs stable). The findings of this study indicate that viewers treat dynamic stimuli like real life, paying less attention to central, relevant and stable AOIs, which are available across time and space in the environment and so do not need to be memorised.

Despite the limitations of small samples of consumers and video ads, the results of this study demonstrate the potential of two relatively recent innovations, which have received limited emphasis in the marketing literature: dynamic attention theory and IBBs.

This study documents what does and does not attract attention to video advertising. What gets attention according to salience theory (e.g. central location) may not always get attention in dynamic advertising because of the effects of relevance and stability. To better understand how to execute video advertising to direct and retain attention to important AOIs, advertisers and advertising researchers are encouraged to use IBBs.

This study makes two original contributions: to marketing theory, by showing how dynamic attention theory can predict attention to video advertising better than salience theory, and to marketing research, showing the utility of tracking visual attention to moving objects in video advertising with IBBs, which appear underutilised in advertising research.