The article is based on language model,through the cue word engineering and agent thinking method,automatic knowledge extraction,with China accounting standards support to complete the corresponding knowledge map cons...The article is based on language model,through the cue word engineering and agent thinking method,automatic knowledge extraction,with China accounting standards support to complete the corresponding knowledge map construction.Through the way of extracting the accounting entities and their connections in the pattern layer,the data layer is provided for the fine-tuning and optimization of the large model.Studies found that,through the reasonable application of language model,knowledge can be realized in massive financial data neural five effective extracted tuples,and complete accounting knowledge map construction.展开更多
For the history of medical culture in the world,the exchange and transmission of medical knowledge has formed an important part of mutual learning among different cultures,which has also increasingly shown unique acad...For the history of medical culture in the world,the exchange and transmission of medical knowledge has formed an important part of mutual learning among different cultures,which has also increasingly shown unique academic value in the study of knowledge history.Traditional Eastern medicine(such as Chinese medicine,Indian ayurvedic medicine,Persian medicine,Arabic medicine),and other medical systems in the ancient Western world(including Greek medicine and Roman medicine)have left precious literature/texts,cultural relics(for example,pills,preparations,medical instruments),folklore and legends,which truly record the process of learning,transplantation,fusion and succession after the encounter of different medical systems at least for the past two thousand years.展开更多
The integration of digital tools and effective knowledge management practices is critical for enhancing administrative efficiency and institutional continuity in higher education. This study investigates the relations...The integration of digital tools and effective knowledge management practices is critical for enhancing administrative efficiency and institutional continuity in higher education. This study investigates the relationships between knowledge modeling, institutional memory, leadership styles, technology, and administrative efficiency at the University of Cape Coast (UCC). The study sought to identify the challenges and opportunities in integrating digital tools into administrative processes and to provide actionable recommendations for improvement. A mixed-methods research design was employed, combining quantitative analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) with qualitative thematic analysis of interviews. The findings revealed key challenges, including resistance to change, fragmented knowledge repositories, and inadequate funding, alongside opportunities such as centralized knowledge systems, cost-effective open-source tools, and capacity-building initiatives. The study highlights the importance of strategic leadership, robust policies, and investments in digital infrastructure to enhance administrative practices. Policy implications include the need for clear digital transformation guidelines and leadership training to foster innovation and collaboration. Recommendations include investing in scalable digital tools, implementing comprehensive capacity-building programs, and promoting stakeholder engagement to drive successful digital integration. These insights provide a roadmap for UCC and similar institutions seeking to optimize administrative efficiency through digital transformation.展开更多
This study explores the epistemic imperative to decolonize African education systems by centering indigenous philosophies such as Ubuntu and introducing the Ubuntu Pedagogy as a pedagogical model.Ubuntu pedagogy trans...This study explores the epistemic imperative to decolonize African education systems by centering indigenous philosophies such as Ubuntu and introducing the Ubuntu Pedagogy as a pedagogical model.Ubuntu pedagogy transforms teacher-learner relationships,it provides a replicable model for relational learning,community partnerships,and reassert the dignity of indigenous epistemologies.The paper examines how language,knowledge production,and pedagogy can be restructured to reflect African epistemologies and educational sovereignty.This research also explores the relationship between mother tongue instruction and cognitive access to learning.Through a qualitative literature analysis of case studies and African scholarly discourse,this paper highlights the continued marginalization of indigenous knowledge systems and the need to embed culturally relevant teaching methodologies.The findings support the broader question of whether there exists an epistemological base for knowledge independence or production within African and Afro-Diasporic contexts,revealing culturally coherent frameworks of learning that resist colonial dominance and an exploration of reclaiming African indigenous knowledge systems for educational and cultural sovereignty.展开更多
Indigenous cultures prescribed a means of maximizing the benefits they produced and enjoyed in their relationship with each other and the environment-based on their understanding of the nature of existence and how to ...Indigenous cultures prescribed a means of maximizing the benefits they produced and enjoyed in their relationship with each other and the environment-based on their understanding of the nature of existence and how to live in harmony with the forces shaping the nature of existence.The emergence of civilization introduced the claim that rational abilities superseded indigenous knowledge.This was followed by positivism and the claim that knowledge passed through three stages:mythological,philosophical,and scientific.This impacted indigenous cultures in ways that reached a height when postcolonial development experts convinced national leaders that progress required adopting advances in science.A failure to modernize was regarded as holding back progress.With the development paradigm now regarded as inadequate for achieving its goals and with the rise of the sustainability discourse,there is appreciation for indigenous knowledge.This article describes an indigenous cultural knowledge system that reflects the insight and wisdom of the world’s most respected scientific and philosophical traditions.The beliefs of the Bodo people of Northeast India are used as an example of an indigenous worldview that portrays insight proven to have value that is comparable to the natural sciences,plus theories of natural law and political philosophy.展开更多
COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To ...COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To further the previous research,we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.展开更多
Since the foundation of the Western modern university in the eighteenth and nineteenth centuries,there has always been debate on the purpose and social or political utility of scientific knowledge.The question remains...Since the foundation of the Western modern university in the eighteenth and nineteenth centuries,there has always been debate on the purpose and social or political utility of scientific knowledge.The question remains as to what we consider as‘useful knowledge’to be(Flexner,1939;Gibbons et al.,1994).The purpose of this paper is to explore and propose an alternative conception of scientific knowledge usefulness,advocating for a balanced approach between direct and indirect utility of knowledge in higher education.To this end,the paper revisits Mill’s(1859)conception of epistemic utility as explained in his work On Liberty to present an idea of scientific knowledge usefulness which is utilitarian in a broader sense.Building on this foundation,the paper promotes a pluralistic conception of epistemic utility and suggests a typology by discerning between direct and indirect utility of knowledge.Overall,by revisiting Mill’s(1859)notion of utility,this paper aims to demonstrate that the notion of‘utility’is not only a function that serves the Idea of the University,but it is also linked to the notion of‘self-development’-Bildung.In that sense,one can make the case for a broader and more complex scientific utilitarianism.展开更多
Background: Blood transfusion (BT) is crucial to the provision of modern health care. However, blood is scarce and costly, and its use is associated with risks. Therefore, the medical professionals who handle it shoul...Background: Blood transfusion (BT) is crucial to the provision of modern health care. However, blood is scarce and costly, and its use is associated with risks. Therefore, the medical professionals who handle it should have adequate knowledge to ensure rational and safe utilization. The objective of the study was to determine the level of BT knowledge among junior medical doctors in Kenya. Methodology: A cross-sectional study was conducted among junior medical doctors working in Western Kenya. Data was collected using questionnaires from August 2021 to March 2022, and analysis was done by way of descriptive and inferential statistics. A p Results: A total of 150 medical doctors participated in the study. Males comprised 60% (n = 90), and the mean age of the participants was 29.9 (SD 3.6) with a range of 25 - 45 years. The mean knowledge score was 54.1% ± 16.4% and was associated with orientation (AOR = 3.157, 95% CI = 1.194 - 8.337). Conclusion: Blood transfusion knowledge among the doctors was suboptimal and was associated with pre-internship induction. There is a need for additional education in BT during all phases of medical training and practice, including orientation for medical interns.展开更多
Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algo...Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.展开更多
Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and ...Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.展开更多
BACKGROUND Breast cancer is one of the most prevalent causes of morbidity and mortality worldwide,presenting an increasing public health challenge,particularly in lowincome and middle-income countries.However,data on ...BACKGROUND Breast cancer is one of the most prevalent causes of morbidity and mortality worldwide,presenting an increasing public health challenge,particularly in lowincome and middle-income countries.However,data on the knowledge,attitudes,and preventive practices regarding breast cancer and the associated factors among females in Wollo,Ethiopia,remain limited.AIM To assess the impact of family history(FH)of breast disease on knowledge,attitudes,and breast cancer preventive practices among reproductive-age females.METHODS A community-based cross-sectional study was conducted in May and June 2022 in Northeast Ethiopia and involved 143 reproductive-age females with FH of breast diseases and 209 without such a history.We selected participants using the systematic random sampling technique.We analyzed the data using Statistical Package for Social Science version 25 software,and logistic regression analysis was employed to determine odds ratios for variable associations,with statistical significance set at P<0.05.RESULTS Among participants with FH of breast diseases,the levels of knowledge,attitudes,and preventive practices were found to be 83.9%[95%confidence interval(CI):77.9-89.9],49.0%(95%CI:40.8-57.1),and 74.1%(95%CI:66.9-81.3),respectively.In contrast,among those without FH of breast diseases,these levels were significantly decreased to 10.5%(95%CI:6.4-14.7),32.1%(95%CI:25.7-38.4),and 16.7%(95%CI:11.7-21.8),respectively.This study also indicated that knowledge,attitudes,and preventive practices related to breast cancer are significantly higher among participants with FH of breast diseases compared to those without HF breast diseases.CONCLUSION Educational status,monthly income,and community health insurance were identified as significant factors associated with the levels of knowledge,attitudes,and preventive practices regarding breast cancer among reproductive-age females.展开更多
Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challeng...Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.展开更多
In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shippi...In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.展开更多
Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and di...Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and differences of various surface features.Currently,topographic maps are mainly stored in raster and vector formats.Extraction of the spatio-temporal knowledge in the maps—such as spatial distribution patterns,feature relationships,and dynamic evolution—still primarily relies on manual interpretation.However,manual interpretation is time-consuming and laborious,especially for large-scale,long-term map knowledge extraction and application.With the development of artificial intelligence technology,it is possible to improve the automation level of map knowledge interpretation.Therefore,the present study proposes an automatic interpretation method for raster topographic map knowledge based on deep learning.To address the limitations of current data-driven intelligent technology in learning map spatial relations and cognitive logic,we establish a formal description of map knowledge by mapping the relationship between map knowledge and features,thereby ensuring interpretation accuracy.Subsequently,deep learning techniques are employed to extract map features automatically,and the spatio-temporal knowledge is constructed by combining formal descriptions of geographic feature knowledge.Validation experiments demonstrate that the proposed method effectively achieves automatic interpretation of spatio-temporal knowledge of geographic features in maps,with an accuracy exceeding 80%.The findings of the present study contribute to machine understanding of spatio-temporal differences in map knowledge and advances the intelligent interpretation and utilization of cartographic information.展开更多
Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate...Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.展开更多
In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant attention.Knowledge tracing(KT)plays a pivotal role in this field by pred...In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant attention.Knowledge tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional strategies.Traditional knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential data.However,these models may neglect crucial short-term dynamics and other relevant features.This paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)architecture.We proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature extractors.This architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key aspects.Empirical evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge states.These results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.展开更多
BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confid...BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.展开更多
Introduction: Breastfeeding is the best way to provide ideal nutrition for optimal infant growth and development. Objectives: The aim of our work was to assess the knowledge, attitudes and practices of mothers of chil...Introduction: Breastfeeding is the best way to provide ideal nutrition for optimal infant growth and development. Objectives: The aim of our work was to assess the knowledge, attitudes and practices of mothers of children aged 0 - 24 months on exclusive breastfeeding in the Central African Republic. Methods: This was a cross-sectional, descriptive and analytical study conducted from September 15 to October 15, 2024 among mothers of infants aged 0 to 24 months. Sociodemographic, obstetric and breastfeeding-related data were collected through individual interviews conducted during sensitizations on good feeding practices organized by the Tina Touadera Foundation. The chi2 test was used to test for relationships between variables, and the p significance level was set at 0.05. Results: The average age of the mothers surveyed was 27.67 years. 65.69% (n = 247) of mothers lived in urban areas and 55.85% (n = 210) were Muslim. 56.38% (n = 212) were living common-law and 34.04% (n = 128) were poor. Secondary-school mothers (44.42%, n = 167) and housewives (53.72%, n = 202) were in the majority. Exclusive breastfeeding (EBF) was correctly defined by 79.26% (n = 298) of mothers and actually practised in 24.20% (n = 91) of cases. The main source of information was a health professional in 75.36% (n = 304) of cases. Among the 285 mothers who practised mixed breastfeeding, lack of time (33.33%) was the main reason. They acknowledged having given water (100%), corn porridge (75.09%) and/or artificial milk (24.91%) before the first 6 months of life. The average time for introducing water was 2.2 months, and for porridge/formula 2.79 months. More than half the mothers (55.05%) said they did not know their infants’ weaning age. Factors positively influencing the use of EBF were age under 29, residence in an urban area, primiparity, having been informed about AME by a health professional, and being a housewife or shopkeeper (p Conclusion: Mothers’ level of knowledge was heterogeneous but insufficient overall. An effective system of information and education from pregnancy to the first six months of life is needed to promote breastfeeding.展开更多
Objective:This study aimed to explore undergraduates’knowledge,attitude,and practice/behavior of human papillomavirus(HPV)vaccination,as well as the essential influencing factors for vaccination decision-making.Metho...Objective:This study aimed to explore undergraduates’knowledge,attitude,and practice/behavior of human papillomavirus(HPV)vaccination,as well as the essential influencing factors for vaccination decision-making.Methods:Through cluster and convenience sampling,2000 undergraduates from the Nursing and Language department of a university in Shanghai were sent a self-designed questionnaire.Chi-square tests,independent sample t-test/ANOVE,and multiple linear regression were used to investigate participants’knowledge and attitude on HPV vaccination,as well as the factors that predicted potential action to receive and promote HPV vaccination in the future.Results:The mean HPV knowledge score was 5.027 out of 10.Health science students showed a significantly higher knowledge mean score than the non-health science students(P<0.000).There was a statistically difference in HPV vaccination attitude among undergraduates in different grades(P<0.05).Awareness of cervical cancer and worries about the risk of cervical cancer were the significant predictors of willingness to receive and promote HPV vaccination in the future.Conclusions:It would take time for a new health product to be aware,understood,accepted,and received.Education providing and information sharing are expected to break the dawn and make the procedure processed.展开更多
Objective:To assess knowledge and practice among nurses toward neonatal resuscitation in hospitals in Hebron.Methods:A cross-sectional study design was conducted among 151 nurses from Hebron.Data were collected using ...Objective:To assess knowledge and practice among nurses toward neonatal resuscitation in hospitals in Hebron.Methods:A cross-sectional study design was conducted among 151 nurses from Hebron.Data were collected using a self-administered questionnaire.Multiple logistic regression was conducted to test the associated factors with the dependent variables.Results:Only 9.3%of participants had a standardized level of knowledge,while 68.9%reported adequate skills for neonatal resuscitation.Factors associated with a standardized level of knowledge were age(p=0.001)and supportive supervision(p=0.007).Factors associated with the standardized practice level were the presence of hospital guidelines(p=0.028),previous training of nurses(p=0.011),and the presence of supportive supervision(p<0.001).Conclusions:The majority of emergency nurses in Hebron hospitals demonstrated a substandard level of knowledge of neonatal resuscitation.However,most of those nurses surprisingly reported a standardized practice level.The presence of hospital guidelines,training programs,or direct supervision for nurses are factors that can be considered to improve both knowledge and practice toward neonatal resuscitation among emergency nurses in Hebron.展开更多
文摘The article is based on language model,through the cue word engineering and agent thinking method,automatic knowledge extraction,with China accounting standards support to complete the corresponding knowledge map construction.Through the way of extracting the accounting entities and their connections in the pattern layer,the data layer is provided for the fine-tuning and optimization of the large model.Studies found that,through the reasonable application of language model,knowledge can be realized in massive financial data neural five effective extracted tuples,and complete accounting knowledge map construction.
文摘For the history of medical culture in the world,the exchange and transmission of medical knowledge has formed an important part of mutual learning among different cultures,which has also increasingly shown unique academic value in the study of knowledge history.Traditional Eastern medicine(such as Chinese medicine,Indian ayurvedic medicine,Persian medicine,Arabic medicine),and other medical systems in the ancient Western world(including Greek medicine and Roman medicine)have left precious literature/texts,cultural relics(for example,pills,preparations,medical instruments),folklore and legends,which truly record the process of learning,transplantation,fusion and succession after the encounter of different medical systems at least for the past two thousand years.
文摘The integration of digital tools and effective knowledge management practices is critical for enhancing administrative efficiency and institutional continuity in higher education. This study investigates the relationships between knowledge modeling, institutional memory, leadership styles, technology, and administrative efficiency at the University of Cape Coast (UCC). The study sought to identify the challenges and opportunities in integrating digital tools into administrative processes and to provide actionable recommendations for improvement. A mixed-methods research design was employed, combining quantitative analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) with qualitative thematic analysis of interviews. The findings revealed key challenges, including resistance to change, fragmented knowledge repositories, and inadequate funding, alongside opportunities such as centralized knowledge systems, cost-effective open-source tools, and capacity-building initiatives. The study highlights the importance of strategic leadership, robust policies, and investments in digital infrastructure to enhance administrative practices. Policy implications include the need for clear digital transformation guidelines and leadership training to foster innovation and collaboration. Recommendations include investing in scalable digital tools, implementing comprehensive capacity-building programs, and promoting stakeholder engagement to drive successful digital integration. These insights provide a roadmap for UCC and similar institutions seeking to optimize administrative efficiency through digital transformation.
文摘This study explores the epistemic imperative to decolonize African education systems by centering indigenous philosophies such as Ubuntu and introducing the Ubuntu Pedagogy as a pedagogical model.Ubuntu pedagogy transforms teacher-learner relationships,it provides a replicable model for relational learning,community partnerships,and reassert the dignity of indigenous epistemologies.The paper examines how language,knowledge production,and pedagogy can be restructured to reflect African epistemologies and educational sovereignty.This research also explores the relationship between mother tongue instruction and cognitive access to learning.Through a qualitative literature analysis of case studies and African scholarly discourse,this paper highlights the continued marginalization of indigenous knowledge systems and the need to embed culturally relevant teaching methodologies.The findings support the broader question of whether there exists an epistemological base for knowledge independence or production within African and Afro-Diasporic contexts,revealing culturally coherent frameworks of learning that resist colonial dominance and an exploration of reclaiming African indigenous knowledge systems for educational and cultural sovereignty.
文摘Indigenous cultures prescribed a means of maximizing the benefits they produced and enjoyed in their relationship with each other and the environment-based on their understanding of the nature of existence and how to live in harmony with the forces shaping the nature of existence.The emergence of civilization introduced the claim that rational abilities superseded indigenous knowledge.This was followed by positivism and the claim that knowledge passed through three stages:mythological,philosophical,and scientific.This impacted indigenous cultures in ways that reached a height when postcolonial development experts convinced national leaders that progress required adopting advances in science.A failure to modernize was regarded as holding back progress.With the development paradigm now regarded as inadequate for achieving its goals and with the rise of the sustainability discourse,there is appreciation for indigenous knowledge.This article describes an indigenous cultural knowledge system that reflects the insight and wisdom of the world’s most respected scientific and philosophical traditions.The beliefs of the Bodo people of Northeast India are used as an example of an indigenous worldview that portrays insight proven to have value that is comparable to the natural sciences,plus theories of natural law and political philosophy.
基金supported in part by the Natural Science Foundation of China(62303361)in part by the Hainan Provincial Natural Science Foundation of China(623QN266)+2 种基金the Fundamental Research Funds for the Central Universities(WUT:233110002)in part by the University-Industry Collaborative Education Program(231002531131826)in part by the National Key R&D Program of China(2018AAA0101502)
文摘COMPUTATIONAL knowledge vision[1]is emphasized as a novel perspective or field in this paper.It first proposes the visual hierarchy and its connection to knowledge,stating that knowledge is a justified true belief.To further the previous research,we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.
基金supported by a grant from the Onassis Foundation,a funding body based in Greece.
文摘Since the foundation of the Western modern university in the eighteenth and nineteenth centuries,there has always been debate on the purpose and social or political utility of scientific knowledge.The question remains as to what we consider as‘useful knowledge’to be(Flexner,1939;Gibbons et al.,1994).The purpose of this paper is to explore and propose an alternative conception of scientific knowledge usefulness,advocating for a balanced approach between direct and indirect utility of knowledge in higher education.To this end,the paper revisits Mill’s(1859)conception of epistemic utility as explained in his work On Liberty to present an idea of scientific knowledge usefulness which is utilitarian in a broader sense.Building on this foundation,the paper promotes a pluralistic conception of epistemic utility and suggests a typology by discerning between direct and indirect utility of knowledge.Overall,by revisiting Mill’s(1859)notion of utility,this paper aims to demonstrate that the notion of‘utility’is not only a function that serves the Idea of the University,but it is also linked to the notion of‘self-development’-Bildung.In that sense,one can make the case for a broader and more complex scientific utilitarianism.
文摘Background: Blood transfusion (BT) is crucial to the provision of modern health care. However, blood is scarce and costly, and its use is associated with risks. Therefore, the medical professionals who handle it should have adequate knowledge to ensure rational and safe utilization. The objective of the study was to determine the level of BT knowledge among junior medical doctors in Kenya. Methodology: A cross-sectional study was conducted among junior medical doctors working in Western Kenya. Data was collected using questionnaires from August 2021 to March 2022, and analysis was done by way of descriptive and inferential statistics. A p Results: A total of 150 medical doctors participated in the study. Males comprised 60% (n = 90), and the mean age of the participants was 29.9 (SD 3.6) with a range of 25 - 45 years. The mean knowledge score was 54.1% ± 16.4% and was associated with orientation (AOR = 3.157, 95% CI = 1.194 - 8.337). Conclusion: Blood transfusion knowledge among the doctors was suboptimal and was associated with pre-internship induction. There is a need for additional education in BT during all phases of medical training and practice, including orientation for medical interns.
文摘Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.
基金funded by Research Project,grant number BHQ090003000X03。
文摘Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.
文摘BACKGROUND Breast cancer is one of the most prevalent causes of morbidity and mortality worldwide,presenting an increasing public health challenge,particularly in lowincome and middle-income countries.However,data on the knowledge,attitudes,and preventive practices regarding breast cancer and the associated factors among females in Wollo,Ethiopia,remain limited.AIM To assess the impact of family history(FH)of breast disease on knowledge,attitudes,and breast cancer preventive practices among reproductive-age females.METHODS A community-based cross-sectional study was conducted in May and June 2022 in Northeast Ethiopia and involved 143 reproductive-age females with FH of breast diseases and 209 without such a history.We selected participants using the systematic random sampling technique.We analyzed the data using Statistical Package for Social Science version 25 software,and logistic regression analysis was employed to determine odds ratios for variable associations,with statistical significance set at P<0.05.RESULTS Among participants with FH of breast diseases,the levels of knowledge,attitudes,and preventive practices were found to be 83.9%[95%confidence interval(CI):77.9-89.9],49.0%(95%CI:40.8-57.1),and 74.1%(95%CI:66.9-81.3),respectively.In contrast,among those without FH of breast diseases,these levels were significantly decreased to 10.5%(95%CI:6.4-14.7),32.1%(95%CI:25.7-38.4),and 16.7%(95%CI:11.7-21.8),respectively.This study also indicated that knowledge,attitudes,and preventive practices related to breast cancer are significantly higher among participants with FH of breast diseases compared to those without HF breast diseases.CONCLUSION Educational status,monthly income,and community health insurance were identified as significant factors associated with the levels of knowledge,attitudes,and preventive practices regarding breast cancer among reproductive-age females.
基金supported by Natural Science Foundation of Sichuan,China(Grant No.:2024ZDZX0019).
文摘Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.
文摘In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.
基金Deep-time Digital Earth(DDE)Big Science Program(No.GJ-C03-SGF-2025-004)National Natural Science Foundation of China(No.42394063)Sichuan Science and Technology Program(No.2025ZNSFSC0325).
文摘Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and differences of various surface features.Currently,topographic maps are mainly stored in raster and vector formats.Extraction of the spatio-temporal knowledge in the maps—such as spatial distribution patterns,feature relationships,and dynamic evolution—still primarily relies on manual interpretation.However,manual interpretation is time-consuming and laborious,especially for large-scale,long-term map knowledge extraction and application.With the development of artificial intelligence technology,it is possible to improve the automation level of map knowledge interpretation.Therefore,the present study proposes an automatic interpretation method for raster topographic map knowledge based on deep learning.To address the limitations of current data-driven intelligent technology in learning map spatial relations and cognitive logic,we establish a formal description of map knowledge by mapping the relationship between map knowledge and features,thereby ensuring interpretation accuracy.Subsequently,deep learning techniques are employed to extract map features automatically,and the spatio-temporal knowledge is constructed by combining formal descriptions of geographic feature knowledge.Validation experiments demonstrate that the proposed method effectively achieves automatic interpretation of spatio-temporal knowledge of geographic features in maps,with an accuracy exceeding 80%.The findings of the present study contribute to machine understanding of spatio-temporal differences in map knowledge and advances the intelligent interpretation and utilization of cartographic information.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB0740000National Key Research and Development Program of China,No.2022YFB3904200,No.2022YFF0711601+1 种基金Key Project of Innovation LREIS,No.PI009National Natural Science Foundation of China,No.42471503。
文摘Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.
基金supported by National Natural Science Foundation of China(Nos.62266054 and 62166050)Key Program of Fundamental Research Project of Yunnan Science and Technology Plan(No.202201AS070021)+2 种基金Yunnan Fundamental Research Projects(No.202401AT070122)Yunnan International Joint Research and Development Center of China-Laos-Thailand Educational Digitalization(No.202203AP140006)Scientific Research Foundation of Yunnan Provincial Department of Education(No.2024Y159).
文摘In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant attention.Knowledge tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional strategies.Traditional knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential data.However,these models may neglect crucial short-term dynamics and other relevant features.This paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)architecture.We proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature extractors.This architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key aspects.Empirical evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge states.These results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.
文摘BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.
文摘Introduction: Breastfeeding is the best way to provide ideal nutrition for optimal infant growth and development. Objectives: The aim of our work was to assess the knowledge, attitudes and practices of mothers of children aged 0 - 24 months on exclusive breastfeeding in the Central African Republic. Methods: This was a cross-sectional, descriptive and analytical study conducted from September 15 to October 15, 2024 among mothers of infants aged 0 to 24 months. Sociodemographic, obstetric and breastfeeding-related data were collected through individual interviews conducted during sensitizations on good feeding practices organized by the Tina Touadera Foundation. The chi2 test was used to test for relationships between variables, and the p significance level was set at 0.05. Results: The average age of the mothers surveyed was 27.67 years. 65.69% (n = 247) of mothers lived in urban areas and 55.85% (n = 210) were Muslim. 56.38% (n = 212) were living common-law and 34.04% (n = 128) were poor. Secondary-school mothers (44.42%, n = 167) and housewives (53.72%, n = 202) were in the majority. Exclusive breastfeeding (EBF) was correctly defined by 79.26% (n = 298) of mothers and actually practised in 24.20% (n = 91) of cases. The main source of information was a health professional in 75.36% (n = 304) of cases. Among the 285 mothers who practised mixed breastfeeding, lack of time (33.33%) was the main reason. They acknowledged having given water (100%), corn porridge (75.09%) and/or artificial milk (24.91%) before the first 6 months of life. The average time for introducing water was 2.2 months, and for porridge/formula 2.79 months. More than half the mothers (55.05%) said they did not know their infants’ weaning age. Factors positively influencing the use of EBF were age under 29, residence in an urban area, primiparity, having been informed about AME by a health professional, and being a housewife or shopkeeper (p Conclusion: Mothers’ level of knowledge was heterogeneous but insufficient overall. An effective system of information and education from pregnancy to the first six months of life is needed to promote breastfeeding.
文摘Objective:This study aimed to explore undergraduates’knowledge,attitude,and practice/behavior of human papillomavirus(HPV)vaccination,as well as the essential influencing factors for vaccination decision-making.Methods:Through cluster and convenience sampling,2000 undergraduates from the Nursing and Language department of a university in Shanghai were sent a self-designed questionnaire.Chi-square tests,independent sample t-test/ANOVE,and multiple linear regression were used to investigate participants’knowledge and attitude on HPV vaccination,as well as the factors that predicted potential action to receive and promote HPV vaccination in the future.Results:The mean HPV knowledge score was 5.027 out of 10.Health science students showed a significantly higher knowledge mean score than the non-health science students(P<0.000).There was a statistically difference in HPV vaccination attitude among undergraduates in different grades(P<0.05).Awareness of cervical cancer and worries about the risk of cervical cancer were the significant predictors of willingness to receive and promote HPV vaccination in the future.Conclusions:It would take time for a new health product to be aware,understood,accepted,and received.Education providing and information sharing are expected to break the dawn and make the procedure processed.
文摘Objective:To assess knowledge and practice among nurses toward neonatal resuscitation in hospitals in Hebron.Methods:A cross-sectional study design was conducted among 151 nurses from Hebron.Data were collected using a self-administered questionnaire.Multiple logistic regression was conducted to test the associated factors with the dependent variables.Results:Only 9.3%of participants had a standardized level of knowledge,while 68.9%reported adequate skills for neonatal resuscitation.Factors associated with a standardized level of knowledge were age(p=0.001)and supportive supervision(p=0.007).Factors associated with the standardized practice level were the presence of hospital guidelines(p=0.028),previous training of nurses(p=0.011),and the presence of supportive supervision(p<0.001).Conclusions:The majority of emergency nurses in Hebron hospitals demonstrated a substandard level of knowledge of neonatal resuscitation.However,most of those nurses surprisingly reported a standardized practice level.The presence of hospital guidelines,training programs,or direct supervision for nurses are factors that can be considered to improve both knowledge and practice toward neonatal resuscitation among emergency nurses in Hebron.
