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The citation of scientific papers is considered a simple and direct indicator of papers' impact. This paper predicts papers' citations through team‐related variables, team composition, and team structure. Team composition includes team size, male/female dominance, academia/industry collaboration, unique race number, and unique country number. Team structures are made up of team power level and team power hierarchy. Team members' previous citation number, H‐index, previous collaborators, career age, and previous paper numbers are a proxy of team power. We calculated the mean value and Gini coefficient to represent team power level (the collective team capability) and team power hierarchy (the vertical difference of power distribution within a team). Taking 1,675,035 CS teams in the DBLP dataset, we trained the XGBoost model to predict high/low citation. Our model has reached 0.71 in AUC and 70.45% in accuracy rate. Utilizing Explainable AI method SHAP to evaluate features' relative importance in predicting team citation categories, we found that team structure plays a more critical role than team composition in predicting team citation. High team power level, flat team power structure, diverse race background, large team, collaboration with industry, and male‐dominated teams can bring higher team citations. Our project can provide insights into how to form the best scientific teams and maximize team impact from team composition and team structure. [ABSTRACT FROM AUTHOR]

The number of digital solutions based on machine learning has increased in recent years. In many industrial sectors, they try to enhance automation in manual or repetitive tasks or provide decision support for complex problems. Data plays an essential role in the selection and implementation of ML algorithms, as it determines the quality of the training and the results. As data drive ML models, selecting the correct data with the suitable ML algorithm for a given use case is crucial but challenging. This paper reviews the application of machine learning in the embodiment design phase addressing the challenge. The work focuses on ML applications in conventional product development and non-conventional additive manufacturing processes. Based on the literature review, the required knowledge to implement the ML algorithms has been derived and presented in a systematic approach. This work highlights the importance of an initial analysis of the existing knowledge in the engineering and additive manufacturing processes in order to implement the proper ML algorithms. [ABSTRACT FROM AUTHOR]

The present work represents the state-of-art investigation for the effect of the dose deposited by gamma rays on Polyethylene terephthalate (PET) and its biaxially oriented film (BoPET) Samples. Set of Mylar biaxially oriented PET polymer films having a thickness of 10 um. Gamma rays irradiated the samples at different doses (100 to 900 kGy). There is a small signature of gamma-ray effect at absorption bands at 2983 cm–1, 2962 cm–1, and 2950 cm−1, which gives rise to radiation–possible effects. The possible effects may arise from energy deposition within the elements that make up these samples. The results show that chain secession in the PET sample is more likely to occur than in its mirror BoPET samples. The material's response from the macroscopic level to the microscopic level depends on the microscopic pattern of energy deposition. The molecular charge was interpreted based on the thrown light on the influence of molecular polarization on the physical nature of radiation interaction with matter. With respect to PET samples, its carboxyl ions have random distribution relative to the axis of the chain molecule in the amorphous phase. In contrast, BoPET samples have an ordered distribution of carboxyl dipoles in the radial direction. Indeed, the dipole of the BoPET is almost perpendicular to the polymer chain axis, leading to a reduction in energy deposition within the material. As a result, the material becomes more resistant to radiation. [ABSTRACT FROM AUTHOR]

An extremely large amount of user-generated content is produced by users worldwide every day with the rapid development of online social media. Content moderation has emerged to ensure the quality of posts on various social media platforms. This process typically demands collaboration between humans and AI because of the complementarity of the two agents in different facets. Wondering how AI can better assist humans to make final judgment in the "machine-in-the-loop" paradigm, we propose a lab experiment to explore the influence of different types of cues provided by AI through a nudging approach as well as time constraints on human moderators' performance. The proposed study contributes to the literature on the AI-assisted decision-making pattern, and helps social media platforms in creating an effective human-AI collaboration framework for content moderation. [ABSTRACT FROM AUTHOR]

The development and increasing use of artificial intelligence (AI), particularly in high-risk application areas, calls for attention to the governance of AI systems. Organizations and researchers have proposed AI ethics principles, but translating principles into practice-oriented frameworks has proven difficult. This paper develops meta-requirements for organizational AI governance frameworks to help translate ethical AI principles into practice and align operations with the forthcoming European AI Act. We adopt a design science research approach. We put forward research-based premises, then we report the design method employed in an industry-academia research project. Based on these, we present seven metarequirements for AI governance frameworks. The paper contributes to the IS research on AI governance by collating knowledge into meta-requirements and advancing a design approach to AI governance. The study underscores that governance frameworks need to incorporate the characteristics of AI, its contexts, and the different sources of requirements. [ABSTRACT FROM AUTHOR]

Teaching engineering students how to work in teams is necessary, important, and hard to do well. Minoritized students experience forms of marginalization from their teammates routinely, which affects their access to safe learning environments. Team evaluation tools like CATME can help instructors see where teaming problems are, but are often normed in ways that obscure the subtle if pervasive harassment of minoritized teammates. Instructors, particularly of large courses, need better ways to identify teams that are marginalizing minoritized team members. This paper introduces theory on microaggressions, selective incivility theory, and coded language to interpret data collected from a complex study site during the COVID-19 pandemic. The team collected data from classroom observations (moved virtual during COVID), interviews with instructors, interviews with students, interpretations of historical data collected through an online team evaluation tool called CATME, and a diary study where students documented their reflections on their marginalization by teammates. While data collection and analysis did not, of course, go as the research team had planned, it yielded insights into how frequently minoritized teammates experience marginalization, instructors' sense of their responsibility and skill for addressing such, marginalization, and students' sense of defeat in hoping for more equitable and supportive learning environments. The paper describes our data collection processes, analysis, and some choice insights drawn from this multi-year study at a large, research-extensive white university. [ABSTRACT FROM AUTHOR]

As organizations become increasingly globalized, understanding the impact of national culture on the successful usage and adoption of emerging technologies is crucial. National culture influences the strategies of organizations, for instance how the employees successfully adopt and use emerging technologies. While the effect of national culture has been widely observed in information systems, it is still challenging to measure the influence of national culture on the usage and adoption of emerging technologies. To contribute to the existing body of knowledge, we conducted a structured literature review on how previous work measured national culture to provide a starting point for further theory development. For instance, our findings emphasize the need to measure culture at an individual level. Finally, we developed a research agenda to provide a starting point for developing theories to measure the influence of national culture on emerging technologies. [ABSTRACT FROM AUTHOR]

The current study was conducted to study the therapeutic effect lemongrass leaves aqueous extract on some biochemical parameters of domestic male rabbits with experimentally induced arteriosclerosis by giving them a standard diet added to it with cholesterol powder at a concentration (1 g / kg diet). 40 male rabbits used in current work and distributed as follow (10 rabbits in each group): control group. The second group: male rabbits feeding on high cholesterol diet for 21 days. The third group: rabbits with atherosclerosis and then treated with (200 mg/kg/daily) aqueous extract for 30 days. The fourth group: rabbits with atherosclerosis and then treated with rosuvastatin at a concentration (1 mg / kg/ daily) for a period of 30 days. The results of the current study showed a significant (P<0.05) increase in the levels of TC, TG, LDL-C, VLDL-C, urea and creatinine levels and significant (P<0.05) decrease in the levels of total protein, albumin, globulin, glutathione and glutathione peroxide in the second group compared with control group. After treatment with aqueous extract of lemongrass (third group) and rosuvastatin (fourth group), the lipid profile, kidney function parameters and antioxidant enzymes show improvement compared with second group. [ABSTRACT FROM AUTHOR]

Internal audit is crucial to improve the effectiveness and efficiency of internal controls, governance, and risk management processes in organizations. For an internal audit organization, to benefit from the knowledge of its staff, it is vital to identify the knowledge that is needed to complete quality and efficient internal audits. Knowledge management is a system that is concerned with using to the best advantage knowledge and experience. In internal auditing, knowledge management is increasingly recognized as a tool to effectively manage not only the knowledge of individuals, but also the collective knowledge in the organization. Research on internal audit has appeared since the 1980s and brought many benefits to internal audit activities, but these studies have not explained how knowledge is created during an internal audit. To address the research gap, this study looks into how knowledge is managed in an internal audit process. The applied methodology is to conduct qualitative case study research by using in-depth interviews, observations, and documentary analysis in the internal audit field. Findings from empirical analysis of the case together with the literature review provide useful insights to construct a potential model of knowledge management in internal audit. During an internal audit process, there are three key elements including data, information, and knowledge that internal auditors need to consider. Data is a series of separate observations, measurements, or events in the audited company. Information is the organized data that has been arranged with relevance and purpose for better comprehension of the internal activities. The knowledge generated and applied by internal auditors can be thought of as a collection of specific and broad information sets and experience in similar audit situations. The process of knowledge management in internal audit involves four sub-processes: collecting data, analyzing data to get information, synthesizing information to create knowledge, and improving knowledge by putting knowledge into practice. The research findings imply that the process of internal auditing requires internal auditors to apply not only analysis capacities but also empirical experience in their work. In the internal audit, it requires collaboration from within the auditing organization and from the auditee's sources to enable a valuable outcome for all involved. [ABSTRACT FROM AUTHOR]

The purpose of this work in progress is to provide preliminary findings from efforts to develop a valid and reliable instrument to measure students' attitudes, beliefs, and intentions related to social justice in engineering contexts. As researchers continue to demonstrate the critical links between engineering topics and social justice and advocate for their integration into engineering curricula, it is important that engineering educators have tools to assess student growth and development in these areas as well. By measuring student perceptions of social justice and their relationship to it as engineers, we can help engineering educators and students more critically examine the sociotechnical nature of engineering and help better prepare students for the realities of modern engineering work. To address this need, we adapted the pre-existing, validated Social Justice Scale to develop an instrument designed to address the role of social justice specifically in engineering settings. We collected data via a survey of 251 first-year mechanical engineering students at a large, predominantly white, public university on the west coast. Using exploratory factor analysis, we examined the underlying constructs of the scale related to student attitudes, behaviors, subjective norms, and intentions concerning social justice in engineering. Preliminary findings suggest that the Engineering Social Justice Scale (ESJS) has the potential to assess different dimensions of student perceptions and development related to social justice in engineering, but that the scale might need to be modified to more appropriately fit in engineering-specific contexts. In this paper, we describe the development process for the ESJS and present preliminary validation measures from Exploratory Factor Analysis. In an effort to make the ESJS easier for instructors to implement and provide a more useful measure, we offer a revised version of the instrument for subsequent distribution and iterative statistical analysis. Based on our EFA, we discuss the different underlying factors present in student attitudes and behaviors related to social justice and compare those to existing theoretical models. Finally, we make recommendations for future iterations related to language and item construction and detail our plans to continue instrument development and validation. By providing a valid and reliable instrument for social justice in engineering, educators can more meaningfully assess critical student outcomes and begin to develop a shared language for discussing student learning outcomes related to social justice. [ABSTRACT FROM AUTHOR]

We are in the brink of the next disruptive technology in the automobile revolution. The autonomous vehicles will have the direct impact on our society and the way we move and live. The autonomy means "autos" (self) and "nomos (rule). The definition of autonomy is the ability of an individual to make a rational, uninfluenced decision. The autonomous vehicle must follow the principles of autonomy like humans, making fair decisions at all situations. To navigate to a given destination based on passenger provided instructions, autonomous vehicle must observe, understand, model, infer, and predict behavior of the surrounds like, weather, animals, debris, follow the traffic rules and signals, and the humans inside and outside the car and finally make a split-second decision. The social, economic, ethical, human behavior, urban and suburban landscape, insurance, legal and liability, and ethnographical effects are enormous. These aspects must be considered for the development of the autonomous vehicle. This paper would examine the challenges in developing autonomous vehicle. [ABSTRACT FROM AUTHOR]

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Blockchain is a technology that makes use of a set cryptographic primitives that allow it to store information by consensus of the nodes without using a trusted central party. Blockchain mechanisms also make the stored information unalterable, and allow it to be verified in a quick way. This technology allows us to relate intangibles like truth, consensus and security. This paper presents the development of a polygraph application that can work in social networks using the users of the social network previously registered in the application as the nodes of a blockchain. Using the Nash equilibrium and techniques of Artificial intelligence a mechanism of consensus is created that allows the nodes to register information in the ledger. Truth and accuracy is one of today's greatest problems in social media platforms and as such we develop and present an architecture to work in facebook as the first application of our blockchain. The architecture is ethical by design, inspired by the moral formalism of Immanuel Kant as truth, and lying, were central concerns to his philosophy. The principles of his ethics can be implemented into blockchain technology so we establish a technology which upholds truth as a formal duty between people, by detecting falsehoods spread on social media. This ethical coding would in principle enable society to protect the rationality and dignity of its citizens. This is a small step towards the possibility of greater ethics en-coded in the practices of our digital world, whilst we do discuss and recognise the many technical and conceptual complexities -- such as the nature of 'truth' and 'ethics' in itself, especially given Kant's hard-lined philosophy. However, Kant's universality of thinking aligns well with the logic of computing; therefore ethical formalism appears to be a suitable first step in the exploration of philosophically inspired truth judgements in blockchain technology. [ABSTRACT FROM AUTHOR]

: The operationalization of knowledge towards sustainability, climate changes issues, “overtourism”, development, communities’ attachment and “tourisation” are very important fields of study, since they may help to design and implement long-term policies in the tourism sector. This is recognized as a strategic sector, because of the global impact that tourism has on several economies and on sustainable development. Generational issues, climate change, global effects and big data have become very important issues in this industry. In order to reach the sustainable and smart tourism goals, it is necessary to design new policies to match theory and practices. The authors performed an extensive literature review of empirical research – regarding sustainable and smart tourism, community attachment, consumer preferences change and knowledge management – to grasp the tourism sector challenges and the current state of art of the literature. The results point out that research that involves, smart tourism, local communities and consumer preferences changes with the KM research is still scarce. [ABSTRACT FROM AUTHOR]

Our objective of this paper is to contribute to a better understanding of the meaning(s) and potential implications of AI related technologies and their use from an innovation management point of view. Starting with a brief survey of the history of AI, three exploratory lenses is then used to discuss AI in relation to innovation management. We have found implications of the intersection between AI and innovation management could be described along three dimensions; AI being, or being part of, the innovative outcome of the innovation process; AI being part of the innovation process; AI impacting, or being impacted by contextual structures. Together those three dimensions form a conceptual model that could be used to approach the encounter of AI and innovation management in greater detail. Let us stress however that while this brief review and those three perspectives provide some light on the interaction between A.I. and innovation management, further perspectives could and should be mobilized. [ABSTRACT FROM AUTHOR]

There is much contemporary concern about 'unfairness' in algorithmic systems. Public controversies have arisen over lack of transparency and accountability in the development and application of algorithmic systems, as well as their potential to produce outcomes that are systematically unfavourable to certain groups. As a result, a variety of fairness criteria and metrics have been proposed to guide the development of algorithmic systems. However, it is unclear whether and how wider society can be involved in deciding which of these different fairness criteria should be favoured. Our work addresses this question by drawing on Responsible Innovation (RI) and 'society in the loop' (STIL) approaches. These suggest that the development of 'fairer' algorithmic systems may be facilitated through responsive engagement with societal stakeholders. We conducted an exploratory study to determine whether it is possible to present a complex set of algorithms to lay stakeholders in a way that enables them to make informed decisions about them. We presented participants with two limited resource allocation scenarios and a set of algorithms; we then asked them to select which of the algorithms they most and least preferred for the allocation. We collected quantitative data recording participant selections and qualitative data capturing how participants explained and justified their selections. We found that participants were able to meaningfully interrogate the algorithms presented to them and displayed grounded understanding of the consequences of different selections. Whilst there was no overall consensus in either scenario, participants displayed patterns in their reasoning. They consistently treated their decisions as contingent on specific understandings of fairness and context, and different interpretations of these matters accounted for different preference selections. These insights and the approach itself can be incorporated into co design processes for contemporary algorithmic systems. [ABSTRACT FROM AUTHOR]

The studies in the area of knowledge management, directed to non-profit organizations are scarce, as opposed to what happens in the private and public sector. The growing importance of the third sector and its institutions, in establishing a more just and balanced society, combating asymmetries and placing itself on the side of the neediest, justifies the attention of the academic community, in order to establish and adopt best practices to carry out their missions. The choice of a case study of organizations such as the Portuguese fire brigades (FBs), unique in their action and identity, accompanies the need increasingly recognized by Portuguese society, in enabling these organizations of competencies for the best possible performance, in view of tragic events that have occurred in recent years in this country, particularly in the area of major fires. Research goal: placing the focus of the study on the sharing of tacit knowledge in these organizations and taking as a case study the Portuguese volunteer firefighter, we set as objectives the verification of the prevalence of tacit knowledge indicators within these organizations and the identification of barriers to this same sharing. Research methodology / design: a careful reading of the literature on sharing tacit knowledge allowed the identification of possible indicators and barriers to the sharing of this knowledge, which were later included in the script of interviews to eight commanders of fire brigades of the central region of Portugal, under the methodological technique snowball, for a qualitative study. Main findings: it was possible to conclude that these organizations tend not to share this type of knowledge, presenting barriers at the individual, organizational and technological level. Limitations / recommendations: as limitations of the research, it should be noted that the present research focuses exclusively on the sharing of tacit knowledge, not considering other forms of knowledge. As a case study, although with heterogeneous organizations, the same cannot be replicated to different realities. [ABSTRACT FROM AUTHOR]

Knowledge sharing (KS) is an integral part of knowledge management (KM) and can be simply expressed as the process of making knowledge available to others. The research reported in this paper discusses Chinese social networks where knowledge sharing (KS) occurs between IT Professionals in China. Social networks in this study are defined as a series of social interactions that form intimate and reciprocal relations and in which knowledge and information are exchanged. In China, where social networks (like Wechat, Weibo, Zhihu, Xiaomuchong, LinkedIn and ResearchGate) have become part of the relationship-building fabric of Chinese professional communities, knowledge is customarily shared in these social networks where it spreads in "viral" modes far beyond the initial sharing intention or objectives. This phenomena has been addressed in journalistic outlets and popular media (blogs), but has not been studied systematically by KM academics in China. This paper aims to address this gap and uses an inductive grounded theory approach to research the nature of the Chinese social networks where knowledge sharing routinely occurs as an integral part of the working practices of the software/IT industry in China. The research suggest that KS trough these social networks does not seem to be confined to the boundaries of the company, but also involves friends, web-based communities of practice (CoP), professional networks, social media networks and even sharing with competing organisations. Within these social networks different social circles co-exist: personal circles, professional circles, organisational circles, informal circles and web-based communities of practice. The study shows that, in modern China there is no clear boundary between these types of social circles and that due to the affordances of network applications, social media and Chinese cultural traits, practitioners share their experiences and knowledge with others for a number of reasons ranging from professional needs, organisational requirement and advertisement as well as because they have strong trust relationships with each other. [ABSTRACT FROM AUTHOR]

Despite the fact that the source of organizational knowledge creation is an individual member in an organization, many studies on knowledge creation have been discussed at the organizational level. Research on knowledge creation at the individual level has been approached mainly from the perspective of the institutional practice related to human resources or organizational mechanisms, and has not studied knowledge creation in terms of the leadership of the middle manager and various employee’s organizational behavior. This study empirically analyzed the relationship between developmental leadership, employee effectiveness (job satisfaction, need for achievement, quality of relationship with coworkers) and knowledge creation at the individual level through the structural equation model. As a result of the analysis, although there was a correlation between developmental leadership and individual knowledge creation, the level of knowledge creation was high when employee effectiveness was mediated between two variables. This result suggests that the organization needs to consider attitudinal, motivational, and relational aspects of the employee and provide training in developmental leadership for middle managers in order to promote individual employees’ knowledge creation. [ABSTRACT FROM AUTHOR]

Improving communication among healthcare providers is one of the critical components of safe and quality patient care. The study objective is to examine how occupation and training of health professionals in Riyadh, Saudi Arabia influence professionals’ perception of the role of electronic health records (EHRs) in improving communication between healthcare providers in primary healthcare centres. A survey-based study method employing a descriptive, cross-sectional design was used. Health professionals’ occupation and training were found to influence their perception of the role of the EHR in improving interprofessional communication. Physicians and professionals with training on EHRs had the highest rating for the system’s role in improving communication between healthcare professionals. All healthcare providers should embrace EHR systems in their practice to promote interprofessional communication and collaboration in the patient care process. [ABSTRACT FROM AUTHOR]

A numerical study has been performed to investigate turbulent forced convective flow of Al2O3-water nanofluid inside a wavy-walled pipe subjected to uniform wall heat flux. The two-dimensional Reynolds-Averaged Navier-Stokes (RANS) equations along with Shear Stress Transport (SST) turbulent model and Reynolds-Averaged energy equation in cylindrical coordinates are solved using finite element method. Numerical simulation is performed for either pure water or Al2O3-water nanofluid with constant solid volume fraction of φ = 2%, while the Kármán number is fixed at Reτ = 314. The implementation of wavy-walled surface over smooth-walled pipe can be considered as regular roughness, which ensures increased turbulence, whereas nanoparticles within base fluid improve thermal performance during turbulent transport mechanism. Therefore, their influences on mean velocity, mean temperature, Reynolds shear stress, radial heat flux, average Nusselt number and skin friction co-efficient are observed systematically. The results show that both the waviness of the pipe and the use of nanofluid potentially increase thermal performance for turbulent flow inside a heated pipe. [ABSTRACT FROM AUTHOR]

The use of v-groove in solar collector has a higher thermal efficiency in references. Dropping the working heat of photovoltaic panel was able to raise the electrical efficiency performance. Electrical and thermal efficiency were produced by photovoltaic thermal (PV/T) system concurrently. Mathematical modeling based on steady-state thermal analysis of PV/T system with v-groove was conducted. With matrix inversion method, the energy balance equations are explained by means of the investigative method. The comparison results show that in the PV/T system with the V-groove collector is higher temperature, thermal and electrical efficiency than other collectors. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present the result of a Systematic Literature Review SLR of models, methodologies, guidelines, analysis, strategies, practices and frameworks related to the implementation of Knowledge Codification Process. The study was conducted following the SLR approach, taking into account only scientific documents published between 2004 and 2013. The revision consisted of four phases: search process, inclusion and exclusion filter, quality assessment, and data extraction, each of which was intended to select the most suitable information to help answer the research questions; case studies were mainly considered for future applications in organizations. The results of each document were identified as well as its activities, roles, tools, variables and indicators. The findings did not explicitly show documents where the implementation of Knowledge Codification Process was specified. As a result, based on the revision of the literature, the different components were taken from alternative processes. The results show first general aspects, presenting the number of documents per industry, per outcome and per research method used, followed by the list of activities, roles, tools, variables and indicators organized by the number of documents and by the type of outcome found in the revision. The result of the SLR can be a starting point to create an implementation model of Knowledge Codification Process, as well as give the readers an overview of the state of Knowledge Codification Process and promote Knowledge Management community in future investigations. Based on the result of the systematic review, there are no previous studies related to the implementation of Knowledge Codification Process. [ABSTRACT FROM AUTHOR]

Knowledge sharing (KS) is an effective strategy in building up competitive advantages for all types of organisations, especially in knowledge intensive organisations such as Software (SW) development organisations. KS encompasses all the interactive activities related with transferring and disseminating knowledge between individuals and groups within the organisation. However, KS success is very closely related with individuals' awareness of the benefits of these interactive sharing activities. This awareness is clearly linked with the professional experience of the individuals and this, in turn, seems to determine individuals' willingness and ability to explicitly express and share their experiences, practices and personal tacit knowledge associated with the process of working practice. Nevertheless, and despite a number of theoretical propositions found in the literature, there is a clear lack of implementation strategies and models to explain the relationship between awareness and motivation in facilitating KS in world of practice. This issue of applicability of theoretical propositions is now recognised as one of the fundamental and key issues in KS. In order to explain the relationship between individuals' awareness and motivation for KS, the research reported in this paper not only identified possible relationships but also established areas of convergence. The findings of this research show that the motivation for KS, a time consuming and demanding activity, is indeed related to the awareness of managers and developers of benefits associated with their professional practice. Practitioners shared their experiences and tacit knowledge with others, partly because it was required by their companies and but also because they have a sound awareness of the need to share knowledge both inside and outside their organisations. Finally, the paper proposes a theory that can be of use to both academics and practitioners involved in knowledge intensive organisations. [ABSTRACT FROM AUTHOR]