Specific Knowledge Research Articles

The knowledge, attitude and practice of cardiologists versus other specialists about the safety and efficacy of influenza vaccination in patients with cardiovascular diseases

Abstract Background Influenza vaccination has been shown to reduce the occurrence of cardiovascular events, both in the general population and especially in individuals with cardiovascular disease. However, the extent to which cardiologists and other physicians support and prescribe influenza vaccination for patients with cardiovascular diseases is not known. Purpose To explore cardiologists' and other specialists' opinions on the safety and efficacy of influenza vaccination in preventing cardiovascular events. Methods From September 2023 to February 2024, a survey was conducted among physicians of any specialty, following the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). The survey was available in 5 languages. Participants' opinions were assessed using Likert-type scales. Non-probabilistic convenience sampling was employed, and duplicated responses were prevented using the SurveyMonkey® platform that identifies duplicated IP addresses. Results A total of 2550 physicians from 44 countries answered the survey; the mean age was 46.1±13.1 years, 46.4% were women, and 17.1% were in training. Among respondents 43.6% were cardiologists. While 91.8% of participants considered the influenza vaccine to be very safe, and 90.6% believed that adverse effects of this intervention were rare, a significant proportion did not consider Influenza vaccine to be very beneficial in reducing acute myocardial infarction (54.4% for cardiologists vs 59.3% for other specialists, p=0.013) or stroke (62.2% for cardiologists vs 64.9% for other specialists, p=0.167). summarizes the participants’ opinions regarding the benefits and risks of influenza vaccination. Regarding potential barriers to achieving higher vaccination rates among patients with cardiovascular disease, cardiologists' opinions were similar to those of other specialists (Table 2). Patient beliefs and patients’ fear of vaccine-related adverse effects were identified as major barriers by both cardiologists and other specialists. Only 19.0% of participants reported having some type of checklist system to remind them to recommend the vaccine to their patients. While 73.0% of participants found this topic highly relevant to their daily clinical practice, with no differences between groups (p=0.178), a notable proportion, comprising 48.5% of cardiologists and 47.1% of other specialists, expressed the necessity for additional training to address the risk-benefit ratio of influenza vaccination with their patients (p=0.485). Conclusion Our data suggest that cardiologists and other specialists view the influenza vaccine as safe with a low rate of adverse effects, both in the general population and in individuals with cardiovascular disease. However, a significant proportion of them are unaware of the vaccination's benefit in reducing cardiovascular events. Additionally, about half of the surveyed professionals expressed a need for further education to discuss the benefits of vaccination with their patients.

Healthcare workers’ experience of screening older adults in emergency care settings: a qualitative descriptive study using the Theoretical Domains Framework

BackgroundIn emergency care settings, screening for disease or risk factors for poor health outcomes among older adults can identify those in need of specialist and early intervention. The aim of this study was to identify barriers and facilitators to implementing older person-centred screening in emergency care settings in the Mid-West of Ireland.MethodsThis study employed a qualitative descriptive design underpinned by the theoretical domains framework (TDF). This design informs implementation strategy by establishing a theoretical foundation for focused objectives. One on one semi-structured interviews were conducted with a purposive sample of healthcare workers (HCWs) to explore their screening experiences with older adults in emergency care settings. Information power guided sample size calculation. In data analysis, verbatim interview transcripts were deductively mapped to TDF constructs forming meta-themes that revealed specific barriers and facilitators to person-centred screening for older individuals. These findings will directly inform implementation strategies.ResultsThree themes were identified; Preconditions to Implementing Older Person-Centred Screening; Knowledge and Skills Required to Implement Older Person-centred Screening and Motivation to Deliver Older Person-Centred Screening. Overall, screening in emergency care settings is a complicated process which is ideally undertaken by knowledgeable and skilled practitioners with a keen awareness of team dynamics and environmental challenges in acute care settings. These practitioners serve as champions and sources of specialist knowledge and practice. Less experienced clinicians seek supervision and support to undertake screening competently and confidently. Education on frailty and aged related syndromes facilitates screening uptake. Recognition of the value of screening is a clear motivator and leadership is vital to sustain screening practices.ConclusionsScreening serves as an entry point for specialist intervention, necessitating a specialist multidisciplinary team (MDT) approach for effective implementation in emergency care settings. Strengthening screening practices for older adults who attend emergency care settings involves employing audit, supervision and tailored supports. Skilled and experienced practitioners play a key role in mentoring and supporting the broader MDT in screening engagement. Long-term and sustainable implementation relies on utilising existing managerial, practice development and educational resources to underpin screening practices. Communication between Emergency Department (ED) staff, the specialist team and wider geriatric team is vital to ensure a cohesive approach to delivering older person-centred care in the ED.

Virtual Children’s Hospital for Learning Pediatric Nursing

Abstract Background In the context of a funded Erasmus+ program, a platform of a Virtual Children’s Hospital for Learning Pediatric Nursing - VLPN is being developed. The education of nurses working with children, adolescents and families, needs to include specialized knowledge, skills, attitudes and behaviors that will empower them to provide optimal and high-quality care. The virtual platform enables the improvement of pediatric nursing competences of the nursing students through interactive and self-paced activities and content. Objectives 1. To develop an immersive and interactive virtual reality learning environment (VRLE), a virtual children’s hospital and new teaching and learning methods and practices, utilizing virtual reality and simulation in teaching. 2. To promote the international collaboration of students and lecturers through the VRLE Results The results are preliminary. 1. The VRLE includes educational materials developed to be integrated in the pediatric nursing studies, easy to access and use by the students and teachers with innovative self-pace learning material i.e. videos, 3D-models, interactive tests. Digital patients can react to the provided care with speech, movement, facial expressions and gestures, something that is not possible with the manikins in the Labs. 2. Nursing students and lecturers from different countries can participate in joint remote seminars or workshops in the VRLE, sharing and comparing their country and culture-specific differences and similarities in the nursing practices. VRLE and digital materials enables synchronous and asynchronous learning. Conclusions VRLE is highly conducive to clinical and procedure-focused training by enabling simulation. VR methods offer nursing students the opportunity to practice skills in a safe and risk-free environment in an immersive way. It can be accessed by multiple students, teachers or nurses at the same time from different locations in different countries. Key messages • New innovative VRLE enhances nursing students’ knowledge and skills that are needed when working with sick children and their families. • International collaboration, interaction and mobilization are enabled by using a virtual platform instead of traveling, thus strengthening the co-operation in European higher educational institutes.

INCREASING THE HUMAN RESOURCES POTENTIAL OF STATE AUDIT BODIES AS A BASIS FOR IMPROVING THE EFFICIENCY AUDIT MECHANISM

Recent economic and financial scandals worldwide, the growth of the shadow economy, the increase in funds concealed from the budget, the rise of corruption, and insufficient adherence to financial discipline create very serious problems. The development of an audit system that creates a transparent and comprehensive informational environment for the government and the public, and plays a key role in economic regulation, is aimed at addressing these serious issues and improving the economic and managerial environment. The purpose of the paper is to explore how increasing the human resources potential of state audit bodies serves as a basis for improving the efficiency audit mechanism. The improvement of the functioning of the state audit system and the enhancement of the knowledge and expertise of personnel and specialists working in this field are based on the critical need to assess and refine the existing system. At the current stage of development, improving the mechanisms of state audit and financial control, as well as monitoring the effective use of budget expenditures, has become a priority. In this context, the concept of state budget policy has undergone changes and is now focused on results-based management. To achieve these goals, new approaches to assessing economic efficiency are being developed, with the improvement of the efficiency audit mechanism being the main focus. The development of auditing institutions plays an important role in accelerating the country's socio-economic development. As a result of these institutions' activities, it becomes possible to identify new financial and economic resources necessary for economic growth. Increasing transparency in society and strengthening financial discipline in economic activities are also closely linked to the work of these institutions. The paper examines the issues of enhancing the knowledge and experience of personnel and specialists, who play a key role in the development of the audit institute.

Designing a Human Resource Empowerment Model for Pharmacists in Pharmacies in Tehran

Background: One of the most effective strategies to gain a competitive advantage in the current business environment is to enhance the efficiency of employees within organizations. The purpose of this research was to design a human resource empowerment model for pharmacists in pharmacies in Tehran. Methods: The research's statistical population includes two qualitative and quantitative components. In the qualitative part, 35 elite pharmacists from universities, industry, and the Ministry of Health were included, while the quantitative part involved a statistical sample of 220 individuals. For data analysis, the Grandad process of Kolmogorov-Smirnov statistical tests, independent one-sample t-test, exploratory factor analysis, confirmatory factor analysis, and structural equation modeling were used. SPSS 25 and AMOS 24 software were used to analyze the research data Results: The findings showed that in the final development model of empowering pharmacists and personnel in Tehran courts, causal factors include psychological characteristics and training. The core category includes cultural and moral competence, as well as professional and technical competence. Background factors include commitment and skill. Intervening factors include moral values. Strategies include efficiency and speed. The consequences include creativity, innovation, and social responsibility.Results: The findings showed that in the final development model of empowering pharmacists and personnel in Tehran courts, causal factors include psychological characteristics and training. The core category includes cultural and moral competence, as well as professional and technical competence. Background factors include commitment and skill. Intervening factors include moral values. Strategies include efficiency and speed. The consequences include creativity, innovation, and social responsibility. Conclusion: It can be concluded that continuous training workshops should be organized for pharmacists in Tehran pharmacies to enhance their specialized knowledge. Periodic in-service courses should be provided to these individuals based on their professional activities. The organization should consider social activities and social behaviors as focal points.

The Role of Digital Transformation in the Development of Forensic Science

Digital transformation plays a significant role in the implementation of forensic activities due to significant current expansion of the body of evidence based on study of combined computer information received in the course of legal proceedings. The key areas of forensic activity digital transformation are considered. It is shown that the sizes of special knowledge must obligatory cover a competent understanding of modern information technologies, their functionality and development dynamics as well as their effective use feasibility in forensic activities. The combination of systematic and integrated approaches representing various aspects of expert examination makes it possible to fully implement the principles of its objectivity, comprehensiveness and completeness as key principles of forensic activities. The need in setting up and implementation of strategic projects on improving forensic activities in the context of digital transformation determines the evolvement of digital transformation doctrine of forensic science as one of the theories of forensic expertology.

A socio-cognitive perspective of knowledge integration in digital innovation networks

Digital innovation is a complex process in which actors seek to create new value pathways by combining digital resources in a layered modular architecture. While IS scholarship has a rich tradition of research on developing and implementing digital artefacts within intra-organisational contexts, our understanding of knowledge integration across distributed innovation networks is nascent and under-theorised. This is an important area of research given the rising importance of digital innovation networks and the challenges faced in integrating specialised knowledge, especially given the greater diversity, speed, reach, and scope made possible by digital technologies. Drawing on in-depth case study findings from a health IoT project involving multiple organisations and disciplines, we explore how knowledge is integrated across boundaries during the initiation stage of a digital innovation network. Our findings point to boundaries related to the digital platform’s organising vision, resource allocation, delivery roadmap, technical architecture, and intellectual property, to name but a few challenges. We then reveal five socio-cognitive modes of knowledge integration which actors strategically enact to cross syntactic, semantic, and pragmatic boundaries: Signalling, Assembling, Contesting, Discounting, and Finalising. The choice of mode depends on the perceived knowledge status (‘what they know’) and social status (‘who they are’) of network actors, which highlight the salience of both social and cognitive dependencies for knowledge integration. We further discuss the contribution of design objects for overcoming differences and distinctions between specialist actors in a digital innovation network.

A qualitative study on the field experience of genetic counseling in Korea.

In Korea, genetic counseling services began with the opening of genetic clinics in the early 1990s; in recent years, demand for these services has increased. However, genetic counseling is not an officially recognized healthcare service under the Korean national health insurance system; further, its certification is not recognized as a medical qualification. To clarify the role and significance of genetic counselors, this study examined their field experiences. To this end, we conducted focus group interviews with 11 certified genetic counselors, six advanced practice nurses, and four regular nurses. The interviews were transcribed verbatim and examined using thematic analysis. We found that even though Korea did not recognize their roles, the participants met their responsibilities and primary duties. In addition, they faced challenges during counseling due to a lack of formal education in genetics and genomics. Moreover, they encountered dilemmas related to the legal and ethical aspects of decision support for family testing or prenatal diagnosis due to the complexity of rare genetic disorders. However, they attempted to acquire the specialized knowledge needed to support patients with rare genetic disorders and their families, gradually developing practical experience and specialized knowledge. Therefore, it is necessary to develop manuals, establish systems, and improve working environments to provide high-quality and specialized genetic counseling. Additionally, there is a need for national support, such as establishing set wages for genetic counselors, developing a national qualification certification system, and securing dedicated personnel.

Literati or Demolition Men? References to Thoth in New Kingdom Epigraphy from the Precinct of Senwosret III at Dahshur

Summary References to Thoth in New Kingdom epigraphy in the Middle Kingdom precinct of Senwosret III at Dahshur include two case studies: a literary dipinto and a depiction of an ibis. The fragmentary text might have contained a hymn to the god of writing, or a text resembling eulogy of the scribal profession. Alongside Kemyt, it attests to an emphasis on literacy and specialist knowledge. An image of Thoth articulated the allegiance to the patron of scribes. The New Kingdom writing and visual practices contribute to an understanding of the New Kingdom community involved in the use and destruction of the Middle Kingdom pyramid complex.

Rehabilitation of Pediatric Patients with Proctological Anomalies

More than 240 observations were analyzed. Patients are conditionally divided into three groups: 1) primary with a smooth postoperative course, A special group consists of patients with combined developmental defects. In most cases, these are so-called regional defects of the urinary tract, sacrococcygeal region. Individual attention should be paid to the issue of social adaptation and rehabilitation of children suffering from malformations of the colon and rectum. Rehabilitation of proctological patients of childhood is a complex medical and social problem that requires the integration of knowledge and actions of specialists from many services subordinate to various departments. The aim of this work: The purpose of this work is to evaluate the effectiveness of the rehabilitation of pediatric patients with proctological anomalies.

Reconstruction error based implicit regularization method and its engineering application to lung cancer diagnosis

The automatic diagnosis of lung cancer via artificial intelligence faces two hotspot issues: (1) insufficient data and (2) excessive redundant information, which make it difficult for convolutional neural networks (CNNs) to learn discriminative information of lung cancer. In this paper, we present the reconstruction error based implicit regularization method (REbIRM) that regularizes CNNs at the loss layer. During each training iteration, the reconstruction errors introduced by the two-stage discriminative auto-encoder are used to sharpen the generalization ability of deep CNNs by improving the decision boundary. In the application process, the trained deep CNN is used for completing computed tomography (CT) diagnostics. The main clinical benefit of our approach is that it is domain independent, requiring no specialized knowledge, and can therefore be applied to different types of datasets. To the best of our knowledge, this is the first attempt to implicitly regularize CNNs based on the reconstruction errors. Finally, experimental results on three CT image classification datasets show that REbIRM can achieve impressive results and that, in conjunction with Dropout, it obtains the state-of-the-art performance. REbIRM is also robust to the selection of hyper-parameters and only has the sublinear influence on the convergence of deep CNNs. Besides, empirical and theoretical evidence are provided to indicate that REbIRM prefers to converges in a constrained parameter space with flatter minima, which explains why it can generalize to new data. Finally, the nature of REbIRM is further explored through visualization techniques to analyze how it works in training deep CNNs.

Development of a Pomegranate Fruit Disease Detection and Classification Model using Deep Learning

Background: India’s economy heavily relies on agriculture, which provides a living for a significant portion of the nation’s population. Agriculture in India faces several challenges, including fruit diseases. Pomegranate cultivation is widespread across various states in India, with Maharashtra, Karnataka Andhra Pradesh, Gujarat and Tamil Nadu being major pomegranate-producing states. Fruit disease detection and classification play a significant part in refining crop yield: water scarcity, soil degradation, outdated farming techniques and the impact of climate change. Farmer suicides are a distressing issue, often linked to financial burdens, crop failures and debt. Manual disease detection methods are labor-intensive, time-consuming and prone to errors. Furthermore, understanding the data usually requires the knowledge of qualified specialists. These restrictions may make it more difficult to detect diseases promptly and increase the chance that the disease will spread across the flock, which could have dangerous results. Methods: In this paper, we use the PomeNetV2 Convolutional Neural Network (CNN) architecture and also examine 4 diseases of pomegranate fruit with names: Alternaria, Anthracnose, Bacterial Blight, Cercospora and Healthy. We used a proposed dataset of 5099 pomegranate fruit disease images. We compared the results of the proposed pomegranate fruit disease classification method with those of existing works. Result: Based on our experimental findings, the suggested framework outperforms all other state-of-the-art models with an accuracy of 99.02% for 75 epochs in identifying healthy and diseased pomegranate fruit.

Principals as Co-Advocates for Caregivers of Children With Disabilities: Possibilities and Realizations Beyond IDEA’s Collaborative Ideal

Although special education and its legal provisions under the Individuals with Disabilities Education Act (IDEA) were designed to support all children with disabilities, it has created a litigious and bureaucratic environment that further marginalizes disabled and labeled children of color and their families. Falling short of a collaborative ideal, school principals who can serve pivotal roles are often siloed from the rest of the school team, often lack special education knowledge and training beyond procedural matters, and can perpetuate inequities through their actions or inactions. We present a scenario illustrating the challenges and possibilities for school principals to promote equitable transformation through (a) an equitable, active leadership role, (b) embodying systemic equity commitments using intersectionality as praxis, (c) moving beyond school and district compliance, and (d) a co-advocacy role with families.

Automatic animal monitoring systems based on AutoML technologies

In contemporary agricultural contexts, the sector is experiencing active processes of automation, underscoring the need for effective tools to develop such automated systems. The utilization of automation tools enhances the efficiency of numerous processes, including those in the domain of animal monitoring. This article examines the application of the AutoML approach as a means for automating the process of generating deep learning models employed in automatic monitoring systems. The VGG19 architecture has been chosen as a testbed for demonstrating the capabilities of the developed technologies. This well-established architecture for deep learning models is designed for object recognition in images.The present study implements a technology for automated structural-parametric synthesis of VGG19 models and the optimization of their hyperparameters. Such an approach allows for the automated creation of models tailored to specific applied problems, even for users lacking specialized knowledge in deep learning.The system delineated in this work is developed on the AutoGenNet software platform, which embodies the No-Code development concept. This concept conceals complex aspects of model creation and training processes from users, significantly lowering the entry barrier for newcomers. Additionally, the AutoGenNet platform incorporates a mechanism for the automatic generation of software wrappers, facilitating efficient interaction with trained models.All aforementioned aspects have contributed to the effective implementation of the AutoML approach for automating the generation and training processes of the VGG19 model. Consequently, the processes associated with solving automatic monitoring tasks reliant on deep learning models have been significantly simplified and expedited.The developed system has been tested on the task of recognizing individual cows. Test results indicated that the system possesses a high degree of scalability and can be adapted for the automated generation of other object recognition models, thereby opening avenues for addressing a diverse array of applied challenges related to the monitoring of various animal species.

Große Transformation für eine Nachhaltige Raumentwicklung als Herausforderung für die raumbezogene Hochschullehre

Climatic and ecological changes across the globe represent a challenge for humanity that can only be solved through a great transformation, that is, a widespread shift toward sustainable spatial development. This means addressing transformation needs in all systems to recognize that civil society, economies and politics are all predetermined by planetary boundaries. This transformation demands that the fields of applied spatial science and spatial planning identify strategies and solutions. This paper examines the extent to which these topics are already being addressed by the university-level spatial studies programs currently training future planners. It develops and examines criteria for evaluating these programs using guideline-based interviews and literature research to perform detailed analysis of selected programs. The study demonstrates that not only specialist knowledge, but also personal and methodological skills are crucial to the success for far-reaching change processes and, ultimately, a society-wide paradigm shift. In some cases, these skills are already being addressed by individual spatial studies programs, especially planning programs. However, there remains a need to accelerate the cultivation of independent learning skills and collaboration in inter- and transdisciplinary teams. Accordingly, this paper proposes a differentiated view of teaching and learning formats in higher education and encourages deepening the focus of spatial studies programs on sustainability and transformation issues.

Optimized deep learning networks for accurate identification of cancer cells in bone marrow

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans to diagnose bone cancer. Manual methods are labor-intensive and may need specialized knowledge. As a result, creating an automated process for distinguishing between malignant and healthy bone is essential. Bones that have cancer have a different texture than bones in unaffected areas. Diagnosing hematological illnesses relies on correct labeling and categorizing nucleated cells in the bone marrow. However, timely diagnosis and treatment are hampered by pathologists' need to identify specimens, which can be sensitive and time-consuming manually. Humanity's ability to evaluate and identify these more complicated illnesses has significantly been bolstered by the development of artificial intelligence, particularly machine, and deep learning. Conversely, much research and development is needed to enhance cancer cell identification—and lower false alarm rates. We built a deep learning model for morphological analysis to solve this problem. This paper introduces a novel deep convolutional neural network architecture in which hybrid multi-objective and category-based optimization algorithms are used to optimize the hyperparameters adaptively. Using the processed cell pictures as input, the proposed model is then trained with an optimized attention-based multi-scale convolutional neural network to identify the kind of cancer cells in the bone marrow. Extensive experiments are run on publicly available datasets, with the results being measured and evaluated using a wide range of performance indicators. In contrast to deep learning models that have already been trained, the total accuracy of 99.7% was determined to be superior.

Efficiency of the method of forming special knowledge and skills in the process of physical training of cadets

The article theoretically substantiates, develops and experimentally tests the method of formation of special knowledge and skills of future officers in the process of physical education. It is determined that Military specialization has a different content of combat activity and, thus, different requirements for the training of future specialists, according to the specifics of the activity, the structure of work movements, and the involvement of the body's systems and functions.Analysis of the dynamics of psychophysiological preparation of future officers in the conditions of a pedagogical experiment showed the presence of reliable positive changes in the development of movement frequency, accuracy of reproduction of half and a quarter of muscle effort, accuracy of reproduction of short and long time intervals, accuracy of distance reproduction, speed of reaction to a moving object, speed of perception and processing of visual information, efficiency of psychomotor activity, mental stability, volume, distribution and switching of attention in young cadets. In female cadets, a significant increase is observed in the indicators of the frequency of movements, the accuracy of reproduction of half and a quarter of muscle efforts, the accuracy of reproduction of short and long time intervals, the strength of nervous processes, the speed of perception and processing of visual information, the efficiency of mental activity, mental stability, volume, distribution and switching of attention. In addition, it has been proven that the implementation of the method of formation of special knowledge and skills of future officers in the process of physical education significantly increased the effectiveness of professional training of cadets of military higher educational institutions.

The knowledge and skills needed for forensic social work in Australia: A Delphi study

Summary Forensic social work is the application of social work knowledge, skills, values and ethics within a legal and criminal justice context. Globally, social workers play an integral role in the criminal justice system but in many countries, including Australia, there is limited conception of the competencies needed for this specialist practice. Australia serves as an example of forensic social work regulated through a generalist social work competency framework, where specialist skills and knowledge are not distinctly outlined or assessed. The purpose of this study was to identify the knowledge and skills used by forensic social work practitioners in Australia. This study used a 3-round Delphi method with an expert panel of social workers working in forensic practice across Australia. It consisted of a 1-hour semi-structured individual interview followed by 2 rounds of online surveys. Findings Consensus was obtained for 30 skill and knowledge items for Australian forensic social work. The panel identified these competencies as specialist, meaning requiring further training beyond generalist proficiency. Of these, eight of the skill and knowledge items were seen as essential for graduates entering forensic social work. Applications The findings from this study contribute to an evidence-based model of forensic social work competency. In Australia, they can be used to consider potential gaps between current generalist mechanisms and specialist practice expectations. With further research, these findings can be used to inform professional standards for forensic social work in Australia and potentially internationally.

Intelligent manufacturing, auditor selection and audit quality

PurposeThe purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations.Design/methodology/approachThis research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020.Findings(1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods.Practical implicationsThis paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises.Originality/valueThis study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

Teacher: Where are You? About a Scenario for Permanent Teacher Training in Which the Teaching of Geometry is Invited to Think Professionally

In this article we share the story of a proposal for permanent training for mathematics teachers who are in charge of the training of students between 12 and 18 years old. We present a task and the fundamentals that lead us to develop it in this training scenario, for the collective construction of specialized knowledge of those who teach topics related to metric geometry and its relationship with optical illusions. We comment on the planning of the scenario and the results achieved from the perspective of the Mathematics Teacher's Specialized Knowledge Model (MTSK Model), which we relate to studies on the use of technologies in mathematics classrooms. We conclude with an analysis of the strengths and weaknesses, opportunities and threats that may arise in scenarios such as the one described for the permanent training of teachers considered teaching professionals.