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Digital transformation is a crucial strategy for enterprises to navigate the digital economy, leading to a growing number of organizations actively engaging in this process. However, the high failure rates in digital transformation initiatives have pushed both academia and industry to identify effective approaches. Key challenges include a lack of relevant knowledge and capabilities as well as the need for coordinated resource utilization. Knowledge is vital for developing new business models, selecting appropriate digital technologies, and strategizing their use; knowledge transfer is a central component of this transformation. To address these challenges, this study reviews the literature on knowledge transfer, dynamic capabilities, and digital transformation and proposes a theoretical model that connects these elements. Empirical research through questionnaire surveys and structural equation modeling reveals that knowledge transfer significantly enhances digital transformation and positively impacts enterprises' ability to perceive, capture, and reconstruct knowledge. These abilities also serve as partial mediators between knowledge transfers and digital transformations. This study innovatively integrates knowledge transfer and digital transformation into a unified model, thereby contributing to the theoretical exploration of digital transformation pathways. Moreover, it enhances the understanding of dynamic capabilities in this context, providing valuable insights and practical implications for Chinese enterprises aiming to improve their digital transformation efforts through effective knowledge transfer and cultivation of dynamic capabilities. [ABSTRACT FROM AUTHOR]

Aim/objective: Given an escalated interest in fostering environmental protection, scholars have associated green entrepreneurial behavior as a stimulating factor and the cornerstone of green entrepreneurial performance. Nevertheless, the underlying mechanism that nurtures university students' green entrepreneurial behavior is yet to be explored in the extant literature. Our study proposes the antecedent effects of institutional support and green knowledge transfer to enhance university students' green entrepreneurial behavior. Moreover, we also expand the boundary conditions of these relationships and suggest the mediating effect of university students' absorptive capacity and the moderating effect of environmental responsibility. Methodology: The study samples university graduates in Chinese universities (N = 434) by adopting a lagged research design spanning over three months. We assessed the proposed model through the multivariate analytical technique. Findings: The findings indicate that institutional support and green knowledge transfer significantly elevate university students' green entrepreneurial behavior. Further, these relationships are intervened considerably through absorptive capacity's mediating effect and environmental responsibility's moderating effect. Implications: By investigating the crucial roles of institutional support and green knowledge transfer in culminating university students' green entrepreneurial behavior, our study extends the boundary conditions of these relationships and investigates the hitherto unexplored moderated mediation model. [ABSTRACT FROM AUTHOR]

Knowledge transfer is the basis for R&D teams and enterprises to improve innovation performance, win market competition and seek sustainable development. In order to explore the path to promote knowledge transfer within the R&D team, this study considers the bounded rationality and risk preference of individuals, incorporates prospect theory into evolutionary game, constructs a perceived benefits matrix distinct from the traditional benefits matrix, and simulates the evolutionary game process. The results show that, R&D personnel's knowledge transfer decisions depend on the net income difference among strategies; only if perceived cost is less than the sum of perceived synergy benefit, perceived organization reward value, and perceived organization punishment value, can knowledge be fully shared and transferred within the R&D team. Moreover, R&D personnel's knowledge transfer decisions are interfered by the irrational psychological factors, including overconfidence, reflection, loss avoidance, and obsession with small probability events. The findings help R&D teams achieve breakthroughs in improving the efficiency of knowledge transfer, thereby enhancing the capacity of enterprises for collaborative innovation. [ABSTRACT FROM AUTHOR]

Ph-negative Myeloproliferative Neoplasm is a rare yet dangerous disease that can turn into more severe forms of disorders later on. Clinical diagnosis of the disease exists but often requires collecting multiple types of pathologies which can be tedious and time-consuming. Meanwhile, studies on deep learning-based research are rare and often need to rely on a small amount of pathological data due to the rarity of the disease. In addition, the existing research works do not address the data scarcity issue apart from using common techniques like data augmentation, which leaves room for performance improvement. To tackle the issue, the proposed research aims to utilize distilled knowledge learned from a larger dataset to boost the performance of a lightweight model trained on a small MPN dataset. Firstly, a 50-layer ResNet model is trained on a large lymph node image dataset of 3,27,680 images, followed by the trained knowledge being distilled to a small 4-layer CNN model. Afterward, the CNN model is initialized with the pre-trained weights to further train on a small MPN dataset of 300 images. Empirical analysis showcases that the CNN with distilled knowledge achieves 97% accuracy compared to 89.67% accuracy achieved by a clone CNN trained from scratch. The distilled knowledge transfer approach also proves to be more effective than more simple data scarcity handling approaches such as augmentation and manual feature extraction. Overall, the research affirms the effectiveness of transferring distilled knowledge to address the data scarcity issue and achieves better convergence when training on a Ph-Negative MPN image dataset with a lightweight model. [ABSTRACT FROM AUTHOR]

Aim/objectiveGiven an escalated interest in fostering environmental protection, scholars have associated green entrepreneurial behavior as a stimulating factor and the cornerstone of green entrepreneurial performance. Nevertheless, the underlying mechanism that nurtures university students' green entrepreneurial behavior is yet to be explored in the extant literature. Our study proposes the antecedent effects of institutional support and green knowledge transfer to enhance university students' green entrepreneurial behavior. Moreover, we also expand the boundary conditions of these relationships and suggest the mediating effect of university students' absorptive capacity and the moderating effect of environmental responsibility.MethodologyThe study samples university graduates in Chinese universities (N = 434) by adopting a lagged research design spanning over three months. We assessed the proposed model through the multivariate analytical technique.FindingsThe findings indicate that institutional support and green knowledge transfer significantly elevate university students' green entrepreneurial behavior. Further, these relationships are intervened considerably through absorptive capacity's mediating effect and environmental responsibility's moderating effect.ImplicationsBy investigating the crucial roles of institutional support and green knowledge transfer in culminating university students' green entrepreneurial behavior, our study extends the boundary conditions of these relationships and investigates the hitherto unexplored moderated mediation model.

As a core driving force of the most recent round of industrial transformation, artificial intelligence has triggered significant changes in the world economic structure, profoundly changed our life and way of thinking, and achieved an overall leap in social productivity. This paper aims to examine the effect of knowledge transfer performance on the artificial intelligence industry innovation network and the path artificial intelligence enterprises can take to promote sustainable development through knowledge transfer in the above context. First, we construct a theoretical hypothesis and conceptual model of the innovation network knowledge transfer mechanism within the artificial intelligence industry. Then, we collect data from questionnaires distributed to Chinese artificial intelligence enterprises that participate in the innovation network. Moreover, we empirically analyze the impact of innovation network characteristics, organizational distance, knowledge transfer characteristics, and knowledge receiver characteristics on knowledge transfer performance and verify the hypotheses proposed in the conceptual model. The results indicate that innovation network centrality and organizational culture distance have a significant effect on knowledge transfer performance, with influencing factors including network scale, implicit knowledge transfer, receiver's willingness to receive, and receiver's capacity to absorb knowledge. For sustainable knowledge transfer performance on promoting Chinese artificial intelligence enterprises innovation, this paper finally delivers valuable insights and suggestions. [ABSTRACT FROM AUTHOR]

BackgroundEffective knowledge transfer of eLearning objects can hasten the adoption and dissemination of technology in teaching and learning. However, challenges exist which hinder inter-organisational knowledge transfer, particularly across continents. The ACoRD project aimed to transfer knowledge on digital learning development from UK/EU (provider) to Malaysian (receiver) higher education institutions (HEIs). This study explores the challenges encountered during the knowledge transfer process and lessons learned.MethodsThis is a qualitative study involving both the knowledge providers and receivers in focus group discussions (n = 25). Four focus group discussions were conducted in the early (n = 2) and mid-phase (n = 2) of the project by trained qualitative researchers using a topic guide designed to explore experiences and activities representing knowledge transfer in multi-institutional and multi-cultural settings. The interviews were audio-recorded, transcribed verbatim, and checked. The transcripts were analysed using thematic analysis.ResultsFive main themes emerged from this qualitative study: mismatched expectations between providers and receivers; acquiring new knowledge beyond the professional "comfort zone"; challenges in cascading newly acquired knowledge to colleagues and management; individual and organisational cultural differences; and disruption of knowledge transfer during the COVID-19 pandemic.ConclusionThis study highlights the need to create a conducive platform to facilitate continuous, timely and bi-directional needs assessment and feedback; this should be done in the early phase of the knowledge transfer process. The challenges and strategies identified in this study could guide more effective knowledge transfer between organisations and countries.

To clarify the problems existing in the process of knowledge transfer of virtual teams, the team cooperation optimization model is combined with the technological innovation capability under the neural network (NN) model, and it is expected to provide a reference for the knowledge management and technological innovation of enterprises. This study first explores the organization, collaboration, and management of virtual teams from the perspective of knowledge transfer. In addition, based on NN, the research and development (R&D) and innovation capabilities of enterprises are studied, and an evaluation index system is constructed. In the stage of empirical analysis, this study selects Enterprise A for research and analyzes the status quo and existing problems of this company. Then, this study proposes a set of schemes conducive to virtual team collaboration and comprehensively uses management theory to evaluate the application effect. The team collaboration model based on knowledge transfer is applied to the operation and management of the enterprise, which significantly improves the collaboration between the various departments of the enterprise and the fluidity of resources. An enterprise R&D capability evaluation system based on a NN model can comprehensively evaluate various index data, thereby prompting its further strategic management and investment. The virtual team collaboration model combined with the R&D technological innovation under the NN model can objectively evaluate the capabilities of the enterprise, thereby improving the management efficiency and benefiting the long-term development of the enterprise.

Background: Although a lot of attention is paid to the flaws of balance training research in older adults, the low methodological quality and incomplete reporting of studies still limit the knowledge transfer between research and practice. These known shortcomings are considered also as barriers for creating recommendations for balance training in older adults. Despite the considerable efforts to improve the scientific quality of studies, such recommendations have not yet been formulated to date. Therefore, this scoping review aims (1) to analyze the literature that addresses balance training in older adults, (2) to identify and summarize gaps in the existing literature, and (3) to propose future research on this topic. Methods: We focused on studies that evaluated the effect of balance training on balance control in apparently healthy older adults over 60 years of age. Results: Out of 6910 potentially relevant studies, only 26 met the eligibility criteria. The identified shortcomings were as follows: missing a priori criteria for training session attendance and leisure-time physical activities, insufficiently described exercises and training load, and inappropriately chosen tests. Conclusions: Among the shortcomings of the balance training research, the insufficiently described balance training program and inappropriately chosen tests can be considered the most important. For this reason, even with an excellently designed experiment, it is almost impossible for practitioners to apply the results of such studies into practice. Therefore, researchers should pay more attention to possible users of the acquired knowledge, which is more than desirable in the case of exercise programs for older adults. [ABSTRACT FROM AUTHOR]

To clarify the problems existing in the process of knowledge transfer of virtual teams, the team cooperation optimization model is combined with the technological innovation capability under the neural network (NN) model, and it is expected to provide a reference for the knowledge management and technological innovation of enterprises. This study first explores the organization, collaboration, and management of virtual teams from the perspective of knowledge transfer. In addition, based on NN, the research and development (R&D) and innovation capabilities of enterprises are studied, and an evaluation index system is constructed. In the stage of empirical analysis, this study selects Enterprise A for research and analyzes the status quo and existing problems of this company. Then, this study proposes a set of schemes conducive to virtual team collaboration and comprehensively uses management theory to evaluate the application effect. The team collaboration model based on knowledge transfer is applied to the operation and management of the enterprise, which significantly improves the collaboration between the various departments of the enterprise and the fluidity of resources. An enterprise R&D capability evaluation system based on a NN model can comprehensively evaluate various index data, thereby prompting its further strategic management and investment. The virtual team collaboration model combined with the R&D technological innovation under the NN model can objectively evaluate the capabilities of the enterprise, thereby improving the management efficiency and benefiting the long-term development of the enterprise. [ABSTRACT FROM AUTHOR]

The distribution of silent comic illustrations can facilitate the communication and transfer of scientific recommendations about sustainable land management (SLM) to local communities in countries where many people are illiterate. However, since there are cross-cultural differences in "visual languages", visualization styles need to be carefully selected as well as locals' comprehension of the illustrated recommendation evaluated systematically. Three agricultural recommendations were chosen for comic-style illustrations, distributed to six communities in the Mahafaly region of southwestern Madagascar and evaluated using a three-step, interdependent approach. The silent comics illustrated (i) composting of manure and its application to improve soil fertility; (ii) cautious utilization of succulent silver thicket as supplementary forage; and (iii) sustainable harvesting practices of wild yam. Results revealed that general understandability strongly depended on the community that was surveyed and on the environmental subject that was illustrated. We found a strong relationship between the general understandability of comics and the divergence that exist in communities' socio-economic structure. Education level was an important factor that explained a better understanding of respondents for the comic illustrating compost production, but not for comics that illustrated sustainable usage of silver thicket and wild yam harvest. Willingness to follow the recommended practice was impaired when respondents valued no change to the improved technique compared to the common one. Effects of respondents' socio-economic characteristics on the implementation of the recommended practice could not be clarified within this study due to the small subset of data. Based on the evaluation of recurring comments made by respondents and interviewers, we conclude that comics can be a useful communication tool to increase locals' awareness and comprehension for SLM practices. This, however, requires that drawing details used to facilitate farmers' ability to adopt a point-of-view inside the comic story are used thoughtfully as they might interfere with the central message. [ABSTRACT FROM AUTHOR]

Persistent gaps in the availability of essential medicines have slowed the achievement of global health targets. Despite the supply chain knowledge and expertise that ministries of health might glean from other industries, limited empirical research has examined the process of knowledge transfer from other industries into global public health. We examined a partnership designed to improve the availability of medical supplies in Tanzania by transferring knowledge from The Coca-Cola system to Tanzania’s Medical Stores Department (MSD). We conducted a process evaluation including in-depth interviews with 70 participants between July 2011 and May 2014, corresponding to each phase of the partnership, with focus on challenges and strategies to address them, as well as benefits perceived by partners. Partners faced challenges in (1) identifying relevant knowledge to transfer, (2) translating operational solutions from Coca-Cola to MSD, and (3) maintaining momentum between project phases. Strategies to respond to these challenges emerged through real-time problem solving and included (1) leveraging the receptivity of MSD leadership, (2) engaging a boundary spanner to identify knowledge to transfer, (3) promoting local recognition of commonalities across industries, (4) engaging external technical experts to manage translation activities, (5) developing tools with visible benefits for MSD, (6) investing in local relationships, and (7) providing time and space for the partnership model to evolve. Benefits of the partnership perceived by MSD staff included enhanced collaboration and communication, more proactive orientations in managing operations, and greater attention to performance management. Benefits perceived by Coca-Cola staff included strengthened knowledge transfer capability and enhanced job satisfaction. Linking theoretical constructs with practical experiences from the field, we highlight the challenges, emergent strategies, and perceived benefits of a partnership across industry boundaries that may be useful to others seeking to promote the transfer of knowledge to improve global health. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the relationships among employees' usage intention pertaining to mobile information devices, focusing on subjective judgement, technology acceptance tendency, information sharing behavior and information transfer. A research model was established to verify several hypotheses. The research model based on integrated concepts of knowledge management and technology acceptance modeling. Participants were employees of enterprises in Taiwan, selected by combining snowball and convenience sampling. Data obtained from 779 e-surveys. Multiple-regression analysis was employed for hypothesis verification. The results indicate that perceived ease-of-use of mobile devices was affected by computer self-efficacy and computer playfulness directly; meanwhile, perceived ease-of-use directly affects perceived usefulness. In addition, perceived ease-of-use and perceived usefulness can predict information-sharing behavior in a positive manner, and impact knowledge transfer as well. Based on the research findings, it suggested that enterprises should utilize mobile information devices to create more contact with customers and enrich their service network. In addition, it is recommended that managers use mobile devices to transmit key information to their staff and that they use these devices for problem-solving and decision-making. Further, the staff’s skills pertaining to the operation of mobile information devices and to fully implement their features are reinforced in order to inspire the users' knowledge transfer. Enhancing the playfulness of the interface is also important. In general, it is useful to promote knowledge transfer behavior within an organization by motivating members to share information and ideas via mobile information devices. In addition, a well-designed interface can facilitate employees' use of these devices. [ABSTRACT FROM AUTHOR]

Audiovisual educational material has been used effectively as a knowledge translation strategy in patient education. Given the need to impact maternal mortality rates, 12 video clips related to maternal and neonatal health information were designed based on the results of a previous systematic review (SR). The content was formulated based on clinical practice guideline recommendations and validated following a formal consensus methodology. This study evaluated the effectiveness of knowledge transfer from the 12 video clips in terms of attention, emotional response, and recall by using neuroscience tools. In a randomized cross-over trial, 155 subjects (pregnant women, non-pregnant women, and men) received random sequences of 13 video clips, including a control video clip. Participants' attention levels were evaluated through eye tracking, their emotional reactions were monitored by electrodermal activity and pupillary diameter, and their recall was tested via a questionnaire. An analysis was performed to evaluate differences in the groups and between the video clips and the control clip using variance analysis models that considered period, sequence, and carry-over effects. Results revealed that fixation length was greater in women than in men, while the greatest emotional effects occurred in men. All three groups had good recall results, without any significant differences between them. Although the sequencing did influence attentional processes, no carry-over effect was demonstrated. However, a differential effect was noted among video clips in all three outcomes, that is, when adjusted for group, level of education, and having had children. The control clip generated less attention, emotional reaction, and recall than the experimental video clips. The video clips about maternal and neonatal health were shown to be effective in the transference and comprehension of information. Therefore, cognitive neuroscience techniques are useful in evaluating knowledge translation strategies through audiovisual formats.

The COVID-19 pandemic has highlighted the importance of local evidence ecosystems in which academia and practice in the Public Health Service (PHS) are interconnected. However, appropriate organizational structures and well-trained staff are lacking and evidence use in local public health decision-making has to be integrated into training programs in Germany. To address this issue, we developed a framework incorporating a toolbox to conceptualize training programs designed to qualify public health professionals for working at the interface between academia and practice. We conducted a scoping review of training programs, key-informant interviews with public health experts, and a multi-professional stakeholder workshop and triangulated their output. The resulting toolbox consists of four core elements, encompassing 15 parameters: (1) content-related aspects, (2) context-related aspects, (3) aspects relevant for determining the training format, and (4) aspects relevant for consolidation and further development. Guiding questions with examples supports the application of the toolbox. Additionally, we introduced a how-to-use guidance to streamline the creation of new training programs, fostering knowledge transfer at the academia-practice interface, equipping public health researchers and practitioners with relevant skills for needs-based PHS research. By promoting collaborative training development across institutions, our approach encourages cross-institutional cooperation, enhances evidence utilization, and enables efficient resource allocation. This collaborative effort in developing training programs within local evidence ecosystems not only strengthens the scientific and practical impact but also lays a foundation for implementing complex public health measures effectively at the local level. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify and characterize the actors involved in river restoration in Romania by untangling the complex networks that they are part of. Actors were considered nodes in a social network, tied by a common action or project. The nodes were characterized through the centrality metrics of a network. The network of actors in river restoration in Romania has a low density and high average path length and diameter for such a spare network, which suggests that knowledge transfer and collaboration are difficult. In the context of a highly centralized water governance system in Romania, the National Authority for Water exerts power and influence in river restoration as well. It has numerous partners, both disconnected and well connected in the network, therefore, it tends to be connected to everybody, as well as gets and diffuses knowledge. Yet, other actors are willing to get involved in river restoration in Romania. NGOs and research organizations have a central position in the network and play various roles (e.g., unconcerned influencers, gate-keepers, pulse-takers). As a recommendation for governing river restoration in Romania, we urge the creation of a national programme focused on river restoration, where the call for projects would be coordinated by the National Authority for Water and open to its territorial subordinates in agreement with stakeholders from various sectors and domains. [ABSTRACT FROM AUTHOR]

Credit card fraud is a significant problem that costs billions of dollars annually. Detecting fraudulent transactions is challenging due to the imbalance in class distribution, where the majority of transactions are legitimate. While pre-processing techniques such as oversampling of minority classes are commonly used to address this issue, they often generate unrealistic or overgeneralized samples. This paper proposes a method called autoencoder with probabilistic xgboost based on SMOTE and CGAN(AE-XGB-SMOTE-CGAN) for detecting credit card frauds.AE-XGB-SMOTE-CGAN is a novel method proposed for credit card fraud detection problems. The credit card fraud dataset comes from a real dataset anonymized by a bank and is highly imbalanced, with normal data far greater than fraud data. Autoencoder (AE) is used to extract relevant features from the dataset, enhancing the ability of feature representation learning, and are then fed into xgboost for classification according to the threshold. Additionally, in this study, we propose a novel approach that hybridizes Generative Adversarial Network (GAN) and Synthetic Minority Over-Sampling Technique (SMOTE) to tackle class imbalance problems. Our two-phase oversampling approach involves knowledge transfer and leverages the synergies of SMOTE and GAN. Specifically, GAN transforms the unrealistic or overgeneralized samples generated by SMOTE into realistic data distributions where there is not enough minority class data available for GAN to process effectively on its own. SMOTE is used to address class imbalance issues and CGAN is used to generate new, realistic data to supplement the original dataset. The AE-XGB-SMOTE-CGAN algorithm is also compared to other commonly used machine learning algorithms, such as KNN and Light GBM, and shows an overall improvement of 2% in terms of the ACC index compared to these algorithms. The AE-XGB-SMOTE-CGAN algorithm also outperforms KNN in terms of the MCC index by 30% when the threshold is set to 0.35. This indicates that the AE-XGB-SMOTE-CGAN algorithm has higher accuracy, true positive rate, true negative rate, and Matthew's correlation coefficient, making it a promising method for detecting credit card fraud. [ABSTRACT FROM AUTHOR]

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors. [ABSTRACT FROM AUTHOR]

Objectives: Scientific knowledge can help develop interventions that improve public health. The objectives of this review are (1) to describe the status of research on knowledge transfer strategies in the field of complex social interventions in public health and (2) to identify priorities for future research in this field. Method: A scoping study is an exploratory study. After searching databases of bibliographic references and specialized periodicals, we summarized the relevant studies using a predetermined assessment framework. In-depth analysis focused on the following items: types of knowledge transfer strategies, fields of public health, types of publics, types of utilization, and types of research specifications. Results: From the 1,374 references identified, we selected 26 studies. The strategies targeted mostly administrators of organizations and practitioners. The articles generally dealt with instrumental utilization and most often used qualitative methods. In general, the bias risk for the studies is high. Conclusion: Researchers need to consider the methodological challenges in this field of research in order to improve assessment of more complex knowledge transfer strategies (when they exist), not just diffusion/dissemination strategies and conceptual and persuasive utilization. [ABSTRACT FROM AUTHOR]

It has been suggested that technological variations associated with Still Bay assemblages of southern Africa have not been addressed adequately. Here we present a study developed to explore regional and temporal variations in Still Bay point-production strategies. We applied our approach in a regional context to compare the Still Bay point assemblages from Hollow Rock Shelter (Western Cape) and Umhlatuzana Rock Shelter (KwaZulu-Natal). Our interpretation of the point-production strategies implies inter-regional point-production conventions, but also highlights variability and intra-regional knapping strategies used for the production of Still Bay points. These strategies probably reflect flexibility in the organisation of knowledge-transfer systems at work during the later stages of the Middle Stone Age between about 80 ka and 70 ka in South Africa.

IntroductionHealth services research generates useful knowledge. Promotion of implementation of this knowledge in medical practice is essential. Prior to initiation of a major study on rural emergency departments (EDs), we deployed two knowledge transfer strategies designed to generate interest and engagement from potential knowledge users. The objective of this paper was to review: 1) a combined project launch and media press release strategy, and 2) a pre-study survey designed to survey potential knowledge users' opinions on the proposed study variables.Materials and methodsWe evaluated the impact of the project launch (presentation at two conferences hosted by key stakeholders) and media press release via a survey of participants/stakeholders and by calculating the number of media interview requests and reports generated. We used a pre-study survey to collect potential key stakeholder' opinions on the study variables.ResultsTwenty-one of Quebec's 26 rural EDs participated in the pre-study survey (81% participation rate). The press release about the study generated 51 press articles and 20 media request for interviews, and contributed to public awareness of a major rural research initiative. In the pre-study survey, thirteen participants (46%) mentioned prior knowledge of the research project. Results from the pre-study survey revealed that all of the potential study variables were considered to be relevant for inclusion in the research project. Respondents also proposed additional variables of interest, including factors promoting retention of human resources.ConclusionsThe present study demonstrated the potential utility of a two-pronged knowledge transfer strategy, including a combined formal launch and press release, and a pre-study survey designed to ensure that the included variables were of interest to participants and stakeholders.

We first propose a novel protocol to realize quantum cloning of an arbitrary unknown shared state with assistance offered by a state preparer. The initial phase of this protocol involves the utilization of quantum teleportation (QT), enabling the transfer of quantum information from an arbitrary number of senders to another arbitrary number of receivers through a maximally entangled GHZ-type state serving as a network channel, without centralizing the information at any specific location. In the second stage of this protocol, the state preparer performs a special single-qubit projective measurement and multiple Z-basis measurements and then communicates a number of classical bits corresponding to measurement results, the perfect copy or orthogonal-complementing copy of an unknown shared state can be produced at senders hands. Then, using a non-maximally entangled GHZ-type state instead of the aforementioned quantum channel, we extend the proposed protocol from three perspectives: projective measurement, positive operator-value measurement (POVM), and a single generalized Bell-state measurement. Our schemes can relay quantum information over a network without requiring fully trusted central or intermediate nodes, and none of participants can fully access the information. [ABSTRACT FROM AUTHOR]

A core feature of complex systems is that the interactions between elements in the present causally constrain their own futures, and the futures of other elements as the system evolves through time. To fully model all of these interactions (between elements, as well as ensembles of elements), it is possible to decompose the total information flowing from past to future into a set of non-overlapping temporal interactions that describe all the different modes by which information can be stored, transferred, or modified. To achieve this, I propose a novel information-theoretic measure of temporal dependency (Iτsx) based on the logic of local probability mass exclusions. This integrated information decomposition can reveal emergent and higher-order interactions within the dynamics of a system, as well as refining existing measures. To demonstrate the utility of this framework, I apply the decomposition to spontaneous spiking activity recorded from dissociated neural cultures of rat cerebral cortex to show how different modes of information processing are distributed over the system. Furthermore, being a localizable analysis, Iτsx can provide insight into the computational structure of single moments. I explore the time-resolved computational structure of neuronal avalanches and find that different types of information atoms have distinct profiles over the course of an avalanche, with the majority of non-trivial information dynamics happening before the first half of the cascade is completed. These analyses allow us to move beyond the historical focus on single measures of dependency such as information transfer or information integration, and explore a panoply of different relationships between elements (and groups of elements) in complex systems. [ABSTRACT FROM AUTHOR]

It is crucial to examine the impact between foreign direct investment (FDI) and net exports (NE) for unveiling international trade dynamics, and the economic development of different geographical regions. It yields sharp insights into how FDI inflows, driven by theories such as backward linkage, export platform, and knowledge transfer, enhance a host country's export capacity and contribute to economic growth. Moreover, studying the reciprocal linkages between FDI and NE helps recognise the aspects of domestic factors, such as productivity and the product life cycle, in attracting FDI and increasing export performance. Based on those theories, the study aims to ascertain the dynamic causality or correlation between FDI and NE across all regions with the utilisation of panel data gathered from 110 countries, considering the period from 2002 to 2020. The Wavelet coherence method is used to investigate the relationship between these variables across different frequencies and periods, followed by a Granger causality test. The findings demonstrated that FDI and NE have a significant relationship in most regions, with a bidirectional relationship between FDI and NE across all continents. The results could assist respective governments and policymakers in formulating policies related to FDI flows and offer insights into how a host country can attract more FDI and boost NE. [ABSTRACT FROM AUTHOR]

Audiovisual educational material has been used effectively as a knowledge translation strategy in patient education. Given the need to impact maternal mortality rates, 12 video clips related to maternal and neonatal health information were designed based on the results of a previous systematic review (SR). The content was formulated based on clinical practice guideline recommendations and validated following a formal consensus methodology. This study evaluated the effectiveness of knowledge transfer from the 12 video clips in terms of attention, emotional response, and recall by using neuroscience tools. In a randomized cross-over trial, 155 subjects (pregnant women, non-pregnant women, and men) received random sequences of 13 video clips, including a control video clip. Participants’ attention levels were evaluated through eye tracking, their emotional reactions were monitored by electrodermal activity and pupillary diameter, and their recall was tested via a questionnaire. An analysis was performed to evaluate differences in the groups and between the video clips and the control clip using variance analysis models that considered period, sequence, and carry-over effects. Results revealed that fixation length was greater in women than in men, while the greatest emotional effects occurred in men. All three groups had good recall results, without any significant differences between them. Although the sequencing did influence attentional processes, no carry-over effect was demonstrated. However, a differential effect was noted among video clips in all three outcomes, that is, when adjusted for group, level of education, and having had children. The control clip generated less attention, emotional reaction, and recall than the experimental video clips. The video clips about maternal and neonatal health were shown to be effective in the transference and comprehension of information. Therefore, cognitive neuroscience techniques are useful in evaluating knowledge translation strategies through audiovisual formats. [ABSTRACT FROM AUTHOR]

With the ease of gene sequencing and the technology available to study and manipulate non-model organisms, the extension of the methodological toolbox required to translate our understanding of model organisms to non-model organisms has become an urgent problem. For example, mining of large coral and their symbiont sequence data is a challenge, but also provides an opportunity for understanding functionality and evolution of these and other non-model organisms. Much more information than for any other eukaryotic species is available for humans, especially related to signal transduction and diseases. However, the coral cnidarian host and human have diverged over 700 million years ago and homologies between proteins in the two species are therefore often in the gray zone, or at least often undetectable with traditional BLAST searches. We introduce a two-stage approach to identifying putative coral homologues of human proteins. First, through remote homology detection using Hidden Markov Models, we identify candidate human homologues in the cnidarian genome. However, for many proteins, the human genome alone contains multiple family members with similar or even more divergence in sequence. In the second stage, therefore, we filter the remote homology results based on the functional and structural plausibility of each coral candidate, shortlisting the coral proteins likely to have conserved some of the functions of the human proteins. We demonstrate our approach with a pipeline for mapping membrane receptors in humans to membrane receptors in corals, with specific focus on the stony coral, P. damicornis. More than 1000 human membrane receptors mapped to 335 coral receptors, including 151 G protein coupled receptors (GPCRs). To validate specific sub-families, we chose opsin proteins, representative GPCRs that confer light sensitivity, and Toll-like receptors, representative non-GPCRs, which function in the immune response, and their ability to communicate with microorganisms. Through detailed structure-function analysis of their ligand-binding pockets and downstream signaling cascades, we selected those candidate remote homologues likely to carry out related functions in the corals. This pipeline may prove generally useful for other non-model organisms, such as to support the growing field of synthetic biology. [ABSTRACT FROM AUTHOR]

When lifting an object sequentially with the two hands, information about object weight can be transferred from one hand to the other. This information can be used to predictively scale fingertip forces and to form a perceptual estimation about the object's weight. This study investigated how weight information can be transferred between the two hands and how this depends on the used hand and handedness of the participant. Right- and left-handed participants lifted light and heavy objects with the right or left hand in a pseudorandomized order and estimated the object's weight. Results showed that predictive force scaling depended on the previously lifted object, with higher force rates if a previous object was heavy. This known effect of sensorimotor memory was mostly independent of the used hand and handedness, indicating that weight information could be transferred across hands for fingertip force scaling. Furthermore, a perceptual bias that depended on the previous lifted object was found, with lower weight estimations when the previous object was heavy compared to light. While this bias was found for both light and heavy objects in right-handers, it was only observed for light objects in left-handers. Notably, in contrast to the results on force scaling, this effect was not transferred across hands. These findings indicate that the transfer of weight information depends differently on the used hand and handedness for perceptual estimations and predictive force scaling. [ABSTRACT FROM AUTHOR]

In this study, we used unidirectional and bidirectional long short-term memory (LSTM) deep learning networks for Chinese news classification and characterized the effects of contextual information on text classification, achieving a high level of accuracy. A Chinese glossary was created using jieba—a word segmentation tool—stop-word removal, and word frequency analysis. Next, word2vec was used to map the processed words into word vectors, creating a convenient lookup table for word vectors that could be used as feature inputs for the LSTM model. A bidirectional LSTM (BiLSTM) network was used for feature extraction from word vectors to facilitate the transfer of information in both the backward and forward directions to the hidden layer. Subsequently, an LSTM network was used to perform feature integration on all the outputs of the BiLSTM network, with the output from the last layer of the LSTM being treated as the mapping of the text into a feature vector. The output feature vectors were then connected to a fully connected layer to construct a feature classifier using the integrated features, finally classifying the news articles. The hyperparameters of the model were optimized based on the loss between the true and predicted values using the adaptive moment estimation (Adam) optimizer. Additionally, multiple dropout layers were added to the model to reduce overfitting. As text classification models for Chinese news articles, the Bi-LSTM and unidirectional LSTM models obtained f1-scores of 94.15% and 93.16%, respectively, with the former outperforming the latter in terms of feature extraction. [ABSTRACT FROM AUTHOR]

Single image raindrop removal aims at recovering high-resolution images from degraded ones. However, existing methods primarily employ pixel-level supervision between image pairs to learn spatial features, thus ignoring the more discriminative frequency information. This drawback results in the loss of high-frequency structures and the generation of diverse artifacts in the restored image. To ameliorate this deficiency, we propose a novel frequency-oriented Hierarchical Fusion Network (HFNet) for raindrop image restoration. Specifically, to compensate for spatial representation deficiencies, we design a dynamic adaptive frequency loss (DAFL), which allows the model to adaptively handle the high-frequency components that are difficult to recover. To handle spatially diverse raindrops, we propose a hierarchical fusion network to efficiently learn both contextual information and spatial features. Meanwhile, a calibrated attention mechanism is proposed to facilitate the transfer of valuable information. Comparative experiments with existing methods indicate the advantages of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Foreign Direct Investment is theoretically expected to facilitate the transfer of knowledge from the home country to the host country, however, the empirical evidence on the subject is mixed. Some studies have shown that, on one hand, as competition grows, the incentive to innovate reduces with the decrease in monopoly rents (Schumpeterian effect). On the other hand, market competition can also boost investments in R&D activities incentivized by incremental profits (Escape-Competition effect). Therefore, this study aims to explore which of these two effects dominates in the selected group of countries. This study also identifies the moderators of the relationship between FDI stock and domestic innovation. It examines the role of absorptive capacity, quality of regulations, and property rights protection in the innovative activities of the host countries. Generalized Method of Moments is used to estimate the parameters of the multivariate regression equation. The analysis is based on panel data consisting of 49 countries over 14 years. The results show that FDI has a negative relationship with domestic innovation, indicating the presence of the Schumpeterian effect. The extensions of the main models show that FDI positively affects domestic innovation in countries with higher absorptive capacity, the superior quality of regulation, and stronger protection of property rights. This study shows that the positive relationship between FDI and domestic innovation is conditional on the ability to absorb knowledge and quality of governance in the recipient countries. [ABSTRACT FROM AUTHOR]

The use of head fixation has become routine in systems neuroscience. However, whether the behavior changes with head fixation, whether animals can learn aspects of a task while freely moving and transfer this knowledge to the head fixed condition, has not been examined in much detail. Here, we used a novel floating platform, the "Air-Track", which simulates free movement in a real-world environment to address the effect of head fixation and developed methods to accelerate training of behavioral tasks for head fixed mice. We trained mice in a Y maze two choice discrimination task. One group was trained while head fixed and compared to a separate group that was pre-trained while freely moving and then trained on the same task while head fixed. Pre-training significantly reduced the time needed to relearn the discrimination task while head fixed. Freely moving and head fixed mice displayed similar behavioral patterns, however, head fixation significantly slowed movement speed. The speed of movement in the head fixed mice depended on the weight of the platform. We conclude that home-cage pre-training improves learning performance of head fixed mice and that while head fixation obviously limits some aspects of movement, the patterns of behavior observed in head fixed and freely moving mice are similar. [ABSTRACT FROM AUTHOR]

Introduction: Health services research generates useful knowledge. Promotion of implementation of this knowledge in medical practice is essential. Prior to initiation of a major study on rural emergency departments (EDs), we deployed two knowledge transfer strategies designed to generate interest and engagement from potential knowledge users. The objective of this paper was to review: 1) a combined project launch and media press release strategy, and 2) a pre-study survey designed to survey potential knowledge users’ opinions on the proposed study variables. Materials and Methods: We evaluated the impact of the project launch (presentation at two conferences hosted by key stakeholders) and media press release via a survey of participants/stakeholders and by calculating the number of media interview requests and reports generated. We used a pre-study survey to collect potential key stakeholder’ opinions on the study variables. Results: Twenty-one of Quebec’s 26 rural EDs participated in the pre-study survey (81% participation rate). The press release about the study generated 51 press articles and 20 media request for interviews, and contributed to public awareness of a major rural research initiative. In the pre-study survey, thirteen participants (46%) mentioned prior knowledge of the research project. Results from the pre-study survey revealed that all of the potential study variables were considered to be relevant for inclusion in the research project. Respondents also proposed additional variables of interest, including factors promoting retention of human resources. Conclusions: The present study demonstrated the potential utility of a two-pronged knowledge transfer strategy, including a combined formal launch and press release, and a pre-study survey designed to ensure that the included variables were of interest to participants and stakeholders. [ABSTRACT FROM AUTHOR]

Background: The Global Digital Exemplar (GDE) Programme was designed to promote the digitisation of hospital services in England. Selected provider organisations that were reasonably digitally-mature were funded with the expectation that they would achieve internationally recognised levels of excellence and act as exemplars ('GDE sites') and share their learning with somewhat less digitally-mature Fast Follower (FF) sites. Aims: This paper explores how partnerships between GDE and FF sites have promoted knowledge sharing and learning between organisations. Methods: We conducted an independent qualitative longitudinal evaluation of the GDE Programme, collecting data across 36 provider organisations (including acute, mental health and speciality), 12 of which we studied as in-depth ethnographic case studies. We used a combination of semi-structured interviews with programme leads, vendors and national policy leads, non-participant observations of meetings and workshops, and analysed national and local documents. This allowed us to explore both how inter-organisational learning and knowledge sharing was planned, and how it played out in practice. Thematic qualitative analysis, combining findings from diverse data sources, was facilitated by NVivo 11 and drew on sociotechnical systems theory. Results: Formally established GDE and FF partnerships were perceived to enhance learning and accelerate adoption of technologies in most pairings. They were seen to be most successful where they had encouraged, and were supported by, informal knowledge networking, driven by the mutual benefits of information sharing. Informal networking was enhanced where the benefits were maximised (for example where paired sites had implemented the same technological system) and networking costs minimised (for example by geographical proximity, prior links and institutional alignment). Although the intervention anticipated uni-directional learning between exemplar sites and 'followers', in most cases we observed a two-way flow of information, with GDEs also learning from FFs, through informal networking which also extended to other health service providers outside the Programme. The efforts of the GDE Programme to establish a learning ecosystem has enhanced the profile of shared learning within the NHS. Conclusions: Inter-organisational partnerships have produced significant gains for both follower (FF) and exemplar (GDE) sites. Formal linkages were most effective where they had facilitated, and were supported by, informal networking. Informal networking was driven by the mutual benefits of information sharing and was optimised where sites were well aligned in terms of technology, geography and culture. Misalignments that created barriers to networking between organisations in a few cases were attributed to inappropriate choice of partners. Policy makers seeking to promote learning through centrally directed mechanisms need to create a framework that enables networking and informal knowledge transfer, allowing local organisations to develop bottom-up collaboration and exchanges, where they are productive, in an organic manner. [ABSTRACT FROM AUTHOR]

It has been suggested that technological variations associated with Still Bay assemblages of southern Africa have not been addressed adequately. Here we present a study developed to explore regional and temporal variations in Still Bay point-production strategies. We applied our approach in a regional context to compare the Still Bay point assemblages from Hollow Rock Shelter (Western Cape) and Umhlatuzana Rock Shelter (KwaZulu-Natal). Our interpretation of the point-production strategies implies inter-regional point-production conventions, but also highlights variability and intra-regional knapping strategies used for the production of Still Bay points. These strategies probably reflect flexibility in the organisation of knowledge-transfer systems at work during the later stages of the Middle Stone Age between about 80 ka and 70 ka in South Africa. [ABSTRACT FROM AUTHOR]

Network interpretation illuminates our understanding of the dynamic nature of cultural evolution. Guided by cultural evolution theory, this article explores how people collectively develop knowledge through knowledge collaboration network traits. Using network data from 910 artifacts (the WikiProject Aquarium Fishes articles) over 163 weeks, two studies were designed to understand how collaboration network traits drive population and artifact-level knowledge evolution. The first study examines the selection pressure imposed by10 network traits (against 11 content traits) on population-level evolutionary outcomes. While network traits are vital in identifying natural selection pressure, intriguingly, no significant difference was found between network traits and content traits, challenging a recent theory on network-driven evolution. The second study utilizes time series analysis to reveal that three network traits (embeddedness, connectivity, and redundancy) at a prior time predict future artifact development trajectory. This implies that people collectively explore various positions in a potential solution space, suggesting content exploration as a possible explanation of knowledge evolution. In summary, understanding the interplay between network traits and content exploration provides valuable insights into the mechanisms driving knowledge evolution and offers new avenues for future research. [ABSTRACT FROM AUTHOR]

Reservoir reconstruction, where parameter prediction plays a key role, constitutes an extremely important part in oil and gas reservoir exploration. With the mature development of artificial intelligence, parameter prediction methods are gradually shifting from previous petrophysical models to deep learning models, which bring about obvious improvements in terms of accuracy and efficiency. However, it is difficult to achieve large amount of data acquisition required for deep learning due to the cost of detection, technical difficulties, and the limitations of complex geological parameters. To address the data shortage problem, a transfer learning prediction model based on long short-term memory neural networks has been proposed, and the model structure has been determined by parameter search and optimization methods in this paper. The proposed approach transfers knowledge from historical data to enhance new well prediction by sharing some parameters in the neural network structure. Moreover, the practicality and effectiveness of this method was tested by comparison based on two block datasets. The results showed that this method could significantly improve the prediction accuracy of the reservoir parameters in the event of data shortage. [ABSTRACT FROM AUTHOR]

Purpose: To assess telementoring as a complementary tool for surgical training of a scleral fixation technique. Design: Randomized, controlled, two-arm, blinded clinical trial. Methods: Using a 3D visualization system, 132 participants were randomized in order of enrollment into traditional face-to-face mentoring (n = 66) and telementoring (n = 66). A single surgeon mentored all participants in the 2 groups. The procedure was performed in a model suitable for training in intraocular lens fixation SimulEYE® (INSEYET, WESTLAKE VILLAGE, CA, USA). In the telementoring group, the images captured on a local computer were sent to a second computer located in another room through a teleconferencing platform in real-time. Nine steps of the recorded procedure were evaluated and scored by two masked independent surgeons experienced in the technique. Main outcomes measures: The primary outcomes evaluated were the global score (the sum of each score on the rubric), surgical failure, and surgical time (in seconds). Results: Surgical success was achieved in 98.5% in the face-to-face group and in 95.5% in the telementoring group (p-value = 0.619). Minimal technical problems were reported in 8 procedures in the telementoring group (12%), without interfering with the surgical result, and completion of the procedure. Conclusions: Telementoring is an encouraging educational tool that can overcome geographical barriers to ease the transfer of abilities and knowledge. We lack evidence in terms of group differences for superiority comparing face-to-face and telementoring, in addition to presenting comparable results regarding surgical success and failure. More studies are needed to explore the impact of telementoring in other ophthalmological surgeries. Trial registration: The Federal University of São Paulo institution's Research Ethics Committee reviewed and approved this study protocol (approval number, 5.383.484). [ABSTRACT FROM AUTHOR]

The effective evaluation of the impact of a scholarly article is a significant endeavor; for this reason, it has garnered attention. From the perspective of knowledge flow, this paper extracted various knowledge flow patterns concealed in articles citation counts to describe the citation impact of the articles. First, the intensity characteristic of knowledge flow was investigated to distinguish the different citation vitality of articles. Second, the knowledge diffusion capacity was examined to differentiate the size of the scope of articles' influences on the academic environment. Finally, the knowledge transfer capacity was discussed to investigate the support degree of articles on the follow-up research. Experimental results show that articles got more citations recently have a higher knowledge flow intensity. The articles have various impacts on the academic environment and have different supporting effects on the follow-up research, representing the differences in their knowledge diffusion and knowledge transfer capabilities. Compared with the single quantitative index of citation frequency, these knowledge flow patterns can carefully explore the citation value of articles. By integrating the three knowledge flow patterns to examine the total citation impact of articles, we found that the articles exhibit distinct value of citation impact even if they were published in the same field, in the same year, and with similar citation frequencies. [ABSTRACT FROM AUTHOR]

Background: Frontline providers around the world deliver emergency care daily, often without prior dedicated training. In response to multiple country requests for open-access, basic emergency care training materials, the World Health Organization (WHO), in collaboration with the International Committee of the Red Cross (ICRC) and the International Federation for Emergency Medicine (IFEM), undertook development of a course for health care providers—Basic Emergency Care: Approach to the acutely ill and injured (BEC). As part of course development, pilots were performed in Uganda, the United Republic of Tanzania, and Zambia to evaluate course feasibility and appropriateness. Here we describe participant and facilitator feedback and pre- and post-course exam performance. Methods: A mixed methods research design incorporated pre- and post-course surveys as well as participant examination results to assess the feasibility and utility of the course, and knowledge transfer. Quantitative data were analyzed using Stata, and simple descriptive statistics were used to describe participant demographics. Survey data were coded and grouped by themes and analyzed using ATLAS.ti. Results: Post-course test scores showed significant improvement (p-value < 0.05) as compared to pre-course. Pre- and post-course questionnaires demonstrated significantly increased confidence in managing emergency conditions. Participant-reported course strengths included course appropriateness, structure, language level and delivery methods. Suggested changes included expanding the 4-day duration of the course. Conclusion: This pilot demonstrates that a low-fidelity, open-access course taught by local instructors can be successful in knowledge transfer. The BEC course was well-received and deemed context-relevant by pilot facilitators and participants in three East African countries. Further studies are needed to evaluate this course's impact on clinical practice and patient outcomes. [ABSTRACT FROM AUTHOR]

Effective tax rates (ETRs) estimated from the income statement data of multinational corporations (MNCs) are useful for comparing MNCs' corporate income taxation across countries. In this paper, we propose a new methodological approach to estimate ETRs as reliably and for as many countries as possible using Orbis' unconsolidated data for the 2011–2015 period. We focus on countries with at least 50 available companies, which results in a sample of 47, mostly European, countries. We estimate the ETR of a country as the ratio of corporate income tax to gross income for all affiliates of MNCs in that country, weighted by gross income. We propose four ETR estimations, including lower and upper bounds, which differ by gross income calculation. We find that ETRs substantially differ from statutory tax rates for some countries. For example, we show that despite similar statutory rates of 28% and 29%, MNCs in Luxembourg paid as little as 1–8% of gross income in taxes, while those in Norway paid as much as 46–67%. Despite being the best available, existing data is still imperfect. We therefore call for better data in the form of MNCs' unconsolidated, public country-by-country reporting data. [ABSTRACT FROM AUTHOR]

Introduction: Evidence-based practice (EBP) is the art of using up-to-date information for clinical decision-making. Healthcare professionals at all levels are expected to use the latest research evidence for quality care. In Ethiopia inclusive and nationally representative summarized evidence regarding the level of EBP among health professionals is scarce. Therefore, this systematic review and meta-analysis aimed to assess the pooled prevalence of EBP utilization and its determinants among Ethiopian health professionals. Method: A systematic review and meta-analysis were conducted using PRISMA guidelines. Comprehensive literature was searched in PubMed, Google Scholar, and African Online Journal databases. A weighted inverse variance random effect model was used to estimate pooled prevalence. Cochrane Q-test and I2 statistics were computed to assess heterogeneity among studies. Funnel plot and Eggers test were done to assess publication bias. Factors associated with EBP were identified using STATA v. 14. Result: Overall, 846 articles were retrieved and finally 23 articles were included in this review. The pooled prevalence of good EBP among health professionals was 52.60% (95%CI; 48.15%-57.05%). Knowledge about EBP (AOR = 2.38, 95% CI: (2.08–2.72)), attitude (AOR = 2.09, 95% CI: (1.67–2.60)), educational status (AOR = 3.12, 95% CI: (2.18–4.47)), work experience (AOR = 2.59, 95% CI: (1.48–4.22)), EBP training (AOR = 2.26, 95% CI: (1.87–2.74)), presence of standard guideline (AOR = 1.94, 95% CI: (1.51–2.50)), internet access (AOR = 1.80, 95% CI: (1.47–2.20)), presence of enough time (AOR = 2.01, 95% CI: (1.56–2.60)) and marital status (AOR = 1.73, 95% CI: (1.32–2.28)) were determinants of EBP. Conclusion: Around half of health professionals in Ethiopia have good EBP utilization which was low. Knowledge, attitude, educational status, work experience, EBP training, presence of standard guidelines, internet access, presence of enough time, and single marital status were positively associated with EBP. Therefore future interventions should focus on increasing their knowledge and changing their attitude through providing training and addressing organizational barriers like availing standard guidelines, accessing the internet, and minimizing professionals' workload that enables them to critically appraise and integrate the latest evidence for clinical decision-making to improve the quality of care. [ABSTRACT FROM AUTHOR]