Related Knowledge Research Articles

Categorizing and defining the dominance and suppression into positive and negative conscious, subconscious and unconscious mind states

This study investigates biological interactions and social structures within psychological frameworks in different manifestations of dominance and suppression classifying into conscious, subconscious, and unconscious mind states by looking at empirical research and theoretical models. This paper then details their mechanisms and impacts on individual and group behavior by looking into intentional, semi-intentional, and non-intentional mechanisms, respectively. This study explores the role that dominance and suppression play in forming social and biological hierarchies as well as individual psychologies, in addition to outlining the traits and outcomes of each type. The results are intended to advance knowledge of power relations in various contexts and offer new perspectives on the advantages and disadvantages of dominance and suppression.

Health literacy and cognitive function in people with diabetic foot ulcer with focus on knowledge, attitude, and practice in relation to foot self-care

Health literacy and cognitive function in people with diabetic foot ulcer with focus on knowledge, attitude, and practice in relation to foot self-care

The practice of visual storytelling in STEM: Influence of creative thinking training on design students’ creative self-efficacy and motivation

This study investigated design students’ self-efficacy and motivation through a visual storytelling project in STEM. Forty-eight college design students participated in this study. The project-based learning method was adopted for both groups, while the test group received additional creative thinking training in the curriculum. Pre- and post-surveys and interviews were administered to obtain the students’ perspectives. Evaluation and analysis of the works were also implemented to reveal the learning outcomes. The results showed significant differences in the students’ creative self-efficacy and project performance. The test group's creative self-efficacy improved at the semester's end, while the control group mostly stayed at a similar level. Also, the test group with creative thinking training in the curriculum compared to the control group demonstrated significantly better project grades. Regarding motivation, both groups had similar levels of motivation in the pre and post-surveys. There was no significant difference between different instructional designs in terms of students’ motivation. Nevertheless, with fundamental visual storytelling training and practices in both groups, the high-performance works revealed more creative analogical expressions and related scientific knowledge, while the medium and low-performance works showed limited analogy or partially correct knowledge in STEM. Implications and suggestions are provided for curriculum design to enhance students’ creative self-efficacy and motivation in interdisciplinary learning.

Effects of the PRECEDE-PROCEDE Model on Self-Care Ability and Quality of Life Among Primipara During Puerperium.

Many parturients have poor self-care ability, strong dependence on others, and lack mother-infant related nursing skills and health care knowledge. Due to their lack of pregnancy experience, many primiparas lack the relevant skills and knowledge, which can affect maternal and infant health and maternal quality of life. The study aimed to investigate the effects of the PRECEDE-PROCEDE model on self-care ability and quality of life among primipara during puerperium. This quasi-clinical study selected eligible primaparas from those who gave birth at a Grade A hospital in Hengyang, China between April and July 2019. Eighty puerperium primiparas were divided into a control group receiving standard care and an intervention group following the PRECEDE-PROCEDE model. Comparison of self-care ability and quality of life scores was conducted between the two groups pre-intervention, at 3 weeks, and at 6 weeks postpartum. Statistical analysis using SPSS 18.0 included mean and standard deviation for measurement data, and frequency and constituent ratio for counting data. Tests such as t-test, Chi-squared test, rank-sum test, and repeated measure analysis of variance were applied. The control group's self-care ability scores were (150.8 ± 9.9), (150.9 ± 9.3), and (152.0 ± 10.2) before intervention, at 3 weeks postpartum, and at 6 weeks postpartum, respectively. For the intervention group, the corresponding scores were (151.1 ± 15.1), (157.8 ± 8.5), and (162.4 ± 7.2). Quality of life scores for the control group were (54.7 ± 8.6), (54.8 ± 7.7), and (55.1 ± 7.7) before intervention, at 3 weeks postpartum, and at 6 weeks postpartum, respectively. At the same time points, while the intervention group saw increases from (55.6 ± 7.6) to (59.2 ± 5.9) and (61.0 ± 5.3). There were statistically significant differences in the time effect and inter-group effect of the total score of self-care ability during puerperium, total score of quality of life, and the score of each dimension between the two groups (P < 0.05), and we also found an interaction effect between grouping and time factors (P < 0.05). After intervention, the incidence of common puerperium health problems except neonatal constipation and diarrhea in the intervention group was lower than that in the control group (P < 0.05). PRECEDE-PROCEDE model may improve self-care ability, reduce the occurrence of common health problems, and improve the quality of life of primiparas during puerperium.

Few-Shot Relation Extraction With Automatically Generated Prompts.

Relation extraction (RE) tends to struggle when the supervised training data is few and difficult to be collected. In this article, we elicit relational and factual knowledge from large pretrained language models (PLMs) for few-shot RE (FSRE) with prompting techniques. Concretely, we automatically generate a diverse set of natural language templates and modulate PLM's behavior through these prompts for FSRE. To mitigate the template bias which leads to unstableness of few-shot learning, we propose a simple yet effective template regularization network (TRN) to prevent deep networks from over-fitting uncertain templates and thus stabilize the FSRE models. TRN alleviates the template bias with three mechanisms: 1) an attention mechanism over mini-batch to weight each template; 2) a ranking regularization mechanism to regularize the attention weights and constrain the importance of uncertain templates; and 3) a template calibration module with two calibrating techniques to modify the uncertain templates in the lowest-ranked group. Experimental results on two benchmark datasets (i.e., FewRel and NYT) show that our model has robust superiority over strong competitors. For reproducibility, we will release our code and data upon the publication of this article.

Nature and Impact of Family Care in the Life of Elderly People: A Study in Dhaka City

Family care is an important issue that plays a significant role in the life of elderly people since the number of elderly people is increasing and the role of the families is also changing. The family structure reduces the number of caregivers in the family, and it has a crucial implication on the healthy life of older people. The objective of this study is to explore the nature and impact of family care in the life of elderly people in Dhaka city. This study is mainly qualitative in nature and the case study method was followed to understand the in-depth situation of family caregiving. Through a purposive sampling technique, 20 families were selected as cases from the Dhaka South City Corporation area. In-depth interviews were conducted to collect some qualitative data. The study findings indicated that the majority of elderly people get care from spouses and children to perform the basic activities necessary for daily life where women play a vital role. Family members provide both daily living and instrumental support to the elderly people. Moreover, this study found that lack of family attachment, busy urban life, professional stress, involvement of women in the labor market, migration of youth, individualism, limited formal and non-formal caregivers, lack of proper health and disease related information and knowledge, and apathetic attitude are the major challenges for getting adequate and effective elderly care. The findings suggest home-based and community-based care program is needed to support family caregivers and older people to stay in their homes and communities.

Research on Knowledge Sharing and Innovation Capacity Enhancement of Heterogeneous Research Institutes under the Construction of Knowledge Mapping

Abstract Enhancing research efficiency by managing related knowledge and forming standardized applications has always been an effort to optimize the work of off-site research institutes, and knowledge sharing is one of the most important methods in many practices. In this paper, the entity matching algorithm is used to identify and match the nodes in the knowledge graph, the connection algorithm is used to calculate and sort the data volume of each node, and all the nodes in the knowledge graph are connected in series. After introducing the update mechanism to establish the decentralized global knowledge graph, the knowledge graph has been integrated into the knowledge-sharing system to enable knowledge sharing between off-site research institutes. In this paper, the accuracy of the full-text search for knowledge graphs can reach 87%, which meets the demand for knowledge sharing. The speed of researchers’ research plan formulation in heterogeneous research institutes has been accelerated by 85.40%, and the efficiency of the research institutes has significantly improved. At the same time, the institute’s innovation ability also increased significantly, with a relative increase of 57.21% in the average number of patents filed annually. This paper provides a reference path for the realization of knowledge sharing among heterogeneous research institutes. It establishes a foundation for significant improvements in the efficiency and innovation ability of research institutes.

Cross-Anatomy Transfer Learning via Shape-Aware Adaptive Fine-Tuning for 3D Vessel Segmentation.

Deep learning methods have recently achieved remarkable performance in vessel segmentation applications, yet require numerous labor-intensive labeled data. To alleviate the requirement of manual annotation, transfer learning methods can potentially be used to acquire the related knowledge of tubular structures from public large-scale labeled vessel datasets for target vessel segmentation in other anatomic sites of the human body. However, the cross-anatomy domain shift is a challenging task due to the formidable discrepancy among various vessel structures in different anatomies, resulting in the limited performance of transfer learning. Therefore, we propose a cross-anatomy transfer learning framework for 3D vessel segmentation, which first generates a pre-trained model on a public hepatic vessel dataset and then adaptively fine-tunes our target segmentation network initialized from the model for segmentation of other anatomic vessels. In the framework, the adaptive fine-tuning strategy is presented to dynamically decide on the frozen or fine-tuned filters of the target network for each input sample with a proxy network. Moreover, we develop a Gaussian-based signed distance map that explicitly encodes vessel-specific shape context. The prediction of the map is added as an auxiliary task in the segmentation network to capture geometry-aware knowledge in the fine-tuning. We demonstrate the effectiveness of our method through extensive experiments on two small-scale datasets of coronary artery and brain vessel. The results indicate the proposed method effectively overcomes the discrepancy of cross-anatomy domain shift to achieve accurate vessel segmentation for these two datasets.

An Ontology-based Knowledge Modeling towards Eco-Design for Additive Manufacturing

Owing to the unique technological merits of additive manufacturing (AM), design for AM, particularly eco-design for AM, has been gaining attention in improving the sustainable performance of AM-fabricated (AMed) parts. The main challenge in harvesting potential sustainability benefits is how to capture the impact of design on sustainable performance. Though several existing studies adopted quantitative evaluation on AM sustainability and investigated the relationships between design information and sustainability information of AMed part, the sustainability information is still unavailable in the design phase. This hardly guides eco-design for AM in practice. To support the increasing industrial applications of AM, this paper illustrates related knowledge, that is, material-process-structure-ecoProperty (MPSeP) relationships to connect design and sustainability information in eco-design for AM. An ontology-based method is proposed to model the MPSeP relationships of the AMed part in a structured way. An example of an AMed hydraulic valve body was used to demonstrate the MPSeP modeling process. It is discussed that how the constructed model effectively assists AM designers through providing eco-design recommendation, and enables design software tools to perform sustainability analysis towards eco-design for AM.

Relation Knowledge Distillation by Auxiliary Learning for Object Detection.

Balancing the trade-off between accuracy and speed for obtaining higher performance without sacrificing the inference time is a challenging topic for object detection task. Knowledge distillation, which serves as a kind of model compression techniques, provides a potential and feasible way to handle above efficiency and effectiveness issue through transferring the dark knowledge from the sophisticated teacher detector to the simple student one. Despite demonstrating promising solutions to make harmonies between accuracy and speed, current knowledge distillation for object detection methods still suffer from two limitations. Firstly, most of the methods are inherited or refereed from the frameworks in image classification task, and deploy an implicit manner by imitating or constraining the features from the intermediate layers or the output predictions between the teacher and student models. While little consideration has been raised to the intrinsic relevance of the classification and localization predictions in object detection task. Besides, these methods fail to investigate the relationship between detection and distillation tasks in knowledge distillation pipeline, and they train the whole network by simply integrating losses from these two different tasks through hand-crafted designation parameters. For addressing the aforementioned issues, we propose a novel Relation Knowledge Distillation by Auxiliary Learning for Object Detection (ReAL) method in this paper. Specifically, we first design a prediction relation distillation module which makes the student model directly mimic the output predictions from the teacher one, and conduct self and mutual relation distillation losses to excavate the relation information between teacher and student models. Moreover, for better devolving into the relationship between different tasks in distillation pipeline, we introduce the auxiliary learning into knowledge distillation for object detection and develop a dynamic weight adaptation strategy. Through regarding detection task as primary task and treating distillation task as auxiliary task in auxiliary learning framework, we dynamically adjust and regularize the corresponding weights of the losses for these tasks during the training process. Experiments on MS COCO dataset are conducted using various detector combinations of teacher and student models and the results show that our proposed ReAL can achieve obvious improvement on different distillation model configurations, while performing favorably against state-of-the-arts.

Oral health related knowledge, attitude and behavior among group of mothers in relation to their primary school children's oral health: a cross-sectional study.

The etiology of oral diseases in children is complex and multifactorial. The oral health of children can be influenced by various factors, including parental knowledge, attitudes and behaviors, as well as socioeconomic status. The objective of this study was to assess, among mothers of children aged 6-12 years, (1) mothers' knowledge about their children's oral health, (2) mothers' attitude toward their children's oral health, and (3) mothers' dental behavior concerning their oral health and to evaluate their influence on their children's dental caries. This cross-sectional study involved three questionnaires to be filled in by mothers of primary school children in addition to an oral examination of their children to measure decayed, missing, filled teeth for primary (dmft) and permanenet (DMFT) dentitions. The mother-child pairs were recruited through multistage stratified random sampling of primary schools in Jeddah, Saudi Arabia. The questionnaire was comprised of four sections: 1-demographic characteristics and socioeconomic status 2-Hiroshima University Dental Behavioral Inventory (mothers' attitudes and behavior pertaining to their oral health) 3-mothers' knowledge regarding the oral health of their children 4-mothers' attitude toward their children oral health. A total of 1496 mother-child pairs completed the study. The mean values of dmft were 4.08 ± 3.47; DMFT was 1.82 ± 2.07; total dmft and DMFT were 5.65 ± 4.05. According to the questionnaire results, mothers in private schools had a more favorable attitude and behavior toward their oral health, as well as a more favorable knowledge and attitude toward their children's oral health. The multiple linear regression model revealed that children's dmft/DMFT scores were significantly related to mother education, mother questionnaire scores, and the Simplified Oral Hygiene Index. Children's oral health is significantly impacted by oral health-related knowledge, attitude and behaviors of their mothers in addition to income status and education level.

VGSG: Vision-Guided Semantic-Group Network for Text-based Person Search.

Text-based Person Search (TBPS) aims to retrieve images of target pedestrian indicated by textual descriptions. It is essential for TBPS to extract fine-grained local features and align them crossing modality. Existing methods utilize external tools or heavy cross-modal interaction to achieve explicit alignment of cross-modal fine-grained features, which is inefficient and time-consuming. In this work, we propose a Vision-Guided Semantic-Group Network (VGSG) for text-based person search to extract well-aligned fine-grained visual and textual features. In the proposed VGSG, we develop a Semantic-Group Textual Learning (SGTL) module and a Vision-guided Knowledge Transfer (VGKT) module to extract textual local features under the guidance of visual local clues. In SGTL, in order to obtain the local textual representation, we group textual features from the channel dimension based on the semantic cues of language expression, which encourages similar semantic patterns to be grouped implicitly without external tools. In VGKT, a vision-guided attention is employed to extract visual-related textual features, which are inherently aligned with visual cues and termed vision-guided textual features. Furthermore, we design a relational knowledge transfer, including a vision-language similarity transfer and a class probability transfer, to adaptively propagate information of the vision-guided textual features to semantic-group textual features. With the help of relational knowledge transfer, VGKT is capable of aligning semantic-group textual features with corresponding visual features without external tools and complex pairwise interaction. Experimental results on two challenging benchmarks demonstrate its superiority over state-of-the-art methods.

Exploratory Innovation in Family-Owned Firms: The Moderating Role of Digital Search

Family firm research agrees that family involvement in ownership gives rise to idiosyncratic innovation behaviors. However, whether family ownership fosters or hampers innovation is still debated because the distinction among the types of innovation outcomes has been often overlooked. To address this gap, we focus on exploratory innovation intensity as innovation outcome (i.e., the ratio between exploratory innovations and all the innovations developed by a firm) to improve our understanding of the family ownership-innovation relationship. Rooted in socioemotional wealth and social capital theories, our arguments posit that family ownership negatively influences exploratory innovation intensity. Recalling the literature on search and recombination, we further propose that this relationship is positively moderated when family-owned firms rely more heavily on digital, information and communication technologies (ICT) related knowledge components during the innovation process (i.e., on a digital search). A panel data analysis of 504 US public limited companies supports both our hypotheses. This article responds to calls for distinguishing exploitative and exploratory innovation outcomes in family firm research. Furthermore, it adds to the digital innovation research by studying the role of digital search as a contingency factor in the pursuit of exploratory innovations and, relatedly, contributes to the literature on search and recombination by underlying that the ICT domain is a relevant search space where to search knowledge to innovate.

Explicit Margin Equilibrium for Few-Shot Object Detection.

Under low data regimes, few-shot object detection (FSOD) transfers related knowledge from base classes with sufficient annotations to novel classes with limited samples in a two-step paradigm, including base training and balanced fine-tuning. In base training, the learned embedding space needs to be dispersed with large class margins to facilitate novel class accommodation and avoid feature aliasing while in balanced fine-tuning properly concentrating with small margins to represent novel classes precisely. Although obsession with the discrimination and representation dilemma has stimulated substantial progress, explorations for the equilibrium of class margins within the embedding space are still in full swing. In this study, we propose a class margin optimization scheme, termed explicit margin equilibrium (EME), by explicitly leveraging the quantified relationship between base and novel classes. EME first maximizes base-class margins to reserve adequate space to prepare for novel class adaptation. During fine-tuning, it quantifies the interclass semantic relationships by calculating the equilibrium coefficients based on the assumption that novel instances can be represented by linear combinations of base-class prototypes. EME finally reweights margin loss using equilibrium coefficients to adapt base knowledge for novel instance learning with the help of instance disturbance (ID) augmentation. As a plug-and-play module, EME can also be applied to few-shot classification. Consistent performance gains upon various baseline methods and benchmarks validate the generality and efficacy of EME. The code is available at github.com/Bohao-Lee/EME.

Decoupling REDD+ understanding of local stakeholders on the onset of materializing carbon credits from forests in Nepal

REDD+1 is an economic incentivizing mechanism aimed at reducing or offsetting of carbon emissions in forests, while realizing multiple benefits alongside climate action. Engaging local stakeholders is crucial for its sustainable implementation and benefit-sharing mechanism. This study focuses on the knowledge and understanding of local-level stakeholders about REDD+ and its associated attributes, revealing significant knowledge gaps between areas with and without REDD+ ​pilot activities. For this, we conducted the semi-structured questionnaire interviews (n ​= ​136), key informant interviews (n ​= ​27), and focus group discussions (n ​= ​4) with local-level REDD+ ​stakeholders (LLRS) comprising both inside and outside of pilot project districts in three provinces of Nepal, by adopting the concept of socio-ecological systems (SES). Data were analyzed using a generalized linear model (GLM) and visualized through Sankey diagrams. The results indicate a poor understanding (29%) of LLRS on the REDD+ ​process, its relationship with forests, concerns among stakeholders, and its potential significance. The perception of REDD+ ​knowledge, mechanisms, and benefits significantly (p ​< ​0.05) varied across study areas, age groups, genders, professional backgrounds, educational levels, ownership of private forests, and types of household energy sources used among respondents. Despite receiving readiness funds, stakeholders’ comprehension of the REDD+ ​process remains limited, indicating suboptimal policy implementation. Knowledge gaps were influenced by social background, voices and choices, and the fear of REDD+ ​disrupting traditional practices among the LLRS. The study emphasizes the need to redress the concerns of LLRS by considering their social backgrounds and traditional practices through informed and participatory decision-making, enhance communication, transparency, and inclusive forest governance. The findings show that current external support has not sufficiently enhanced capacity among LLRS, suggesting the need for sufficient and sustainable support through national policy and financing mechanisms. Further, the study identified extremely poor REDD+ ​-related knowledge dissemination within communities, exacerbating challenges in implementation and benefit-sharing mechanisms, revealing the simplification of its process is essential. The study advocates for revising REDD+ ​-related policies to optimize benefits, ensure smooth implementation, realize fair and equitable carbon credits from forests, and foster shared responsibility and ownership among all stakeholders in climate actions through improved forest governance.

Knowledge, Attitude, and Practice about Diabetes Mellitus and Its Implication on Oral Health among Diabetic Patients in Chengalpattu – A Cross-sectional Study

Abstract Background: Diabetes mellitus is considered to be a global epidemic. Currently india is considered to be the diabetic capital of the world. Despite the growing awareness of risk factors of diabetes mellitus and it’s management, only few are aware of the oral health implications of diabetes mellitus. Aims and Objective: With this background the study aims to assess the knowledge, attitude and practice about diabetes mellitus and its implication on oral health among diabetic patients. Materials and Methodology: This cross-sectional study was conducted among 100 participants, who met the inclusion criteria, visiting the outpatient department of karpaga vinayaga institute of medical science. A self-administered was distributed among the participants. The questionnaire consisted of 19 closed questions which were divided into 3 domains: The first domain is knowledge of risk factors includes 5 questions; the second domain is attitude of diabetes mellitus patients includes 5 questions; the third domain is oral health related knowledge included 9 questions. Statistical analysis was performed using spss. Chi-square test was used to compare association between males and females in P value of &lt;0.05 was considered to be significant. Results: The results displayed that the participants had adequate knowledge about risk factors of diabetes mellitus and they also showed positive attitudes towards the management of diabetes mellitus. However, their knowledge regarding oral health complications of diabetes mellitus was not so high. Conclusion: These results necessitate the implementation of various oral health and public health programs to increase people’s knowledge and awareness of diabetes-related oral health conditions.

Phenotypic characterization and genomic analysis of Limosilactobacillus fermentum phage

Limosilactobacillus (L.) fermentum is widely utilized for its beneficial properties, but lysogenic phages can integrate into its genome and can be induced to enter the lysis cycle under certain conditions, thus accomplishing lysis of host cells, resulting in severe economic losses. In this study, a lysogenic phage, LFP03, was induced from L. fermentum IMAU 32510 by UV irradiation for 70 s. The electron microscopy showed that this phage belonged to Caudoviricetes class. Its genome size was 39,556 bp with a GC content of 46.08%, which includes 20 functional proteins. Compared with other L. fermentum phages, the genome of phage LFP03 exhibited deletions, inversions and translocations. Biological analysis showed that its optimal multiplicity of infection was 0.1, with a burst size of 133.5 ± 4.9 PFU/infective cell. Phage LFP03 was sensitive to temperature and pH value, with a survival rate of 48.98% at 50 °C. It could be completely inactivated under pH 2. The adsorption ability of this phage was minimally affected by temperature and pH value, with adsorption rates reaching 80% under all treated conditions. Divalent cations could accelerate phage adsorption, while chloramphenicol expressed little influence. This study might expand the related knowledge of L. fermentum phages, and provide some theoretical basis for improving the stability of related products and establishing phage control measures.

Establishing a knowledge structure for yield prediction in cereal crops using unmanned aerial vehicles.

Recently, a rapid advancement in using unmanned aerial vehicles (UAVs) for yield prediction (YP) has led to many YP research findings. This study aims to visualize the intellectual background, research progress, knowledge structure, and main research frontiers of the entire YP domain for main cereal crops using VOSviewer and a comprehensive literature review. To develop visualization networks of UAVs related knowledge for YP of wheat, maize, rice, and soybean (WMRS) crops, the original research articles published between January 2001 and August 2023 were retrieved from the web of science core collection (WOSCC) database. Significant contributors have been observed to the growth of YP-related research, including the most active countries, prolific publications, productive writers and authors, the top contributing institutions, influential journals, papers, and keywords. Furthermore, the study observed the primary contributions of YP for WMRS crops using UAVs at the micro, meso, and macro levels and the degree of collaboration and information sources for YP. Moreover, the policy assistance from the People's Republic of China, the United States of America, Germany, and Australia considerably advances the knowledge of UAVs connected to YP of WMRS crops, revealed under investigation of grants and collaborating nations. Lastly, the findings of WMRS crops for YP are presented regarding the data type, algorithms, results, and study location. The remote sensing community can significantly benefit from this study by being able to discriminate between the most critical sub-domains of the YP literature for WMRS crops utilizing UAVs and to recommend new research frontiers for concentrating on the essential directions for subsequent studies.

The Significance of Modern Agreements Between Greece and Egypt as Secondary Readings: the echoes of Herodotus and Thucydides

Greece and Egypt, developed individually in two continents Europe and Africa, respectively, have maintained long beneficial relations since pre-historic times. The earliest evidence of Greek-Egyptian relations was uncovered from Minoan excavations that date back to 3000 BCE. Considering the literary sources available to examine the nature of contacts between Greece and Egypt, the Greek historians Herodotus and Thucydides from the 5th century BCE reveal evidently reliable information on the bilateral agreements that prevailed between the two nations. Historians relate stories on how these two nations significantly relied on times of need during the 5th century BCE war periods. While Egypt was the grain supplier for Greek city-states, specifically Athens, Athenians repaid Egypt by extending their military power to Egypt. Further, as history reveals, both nations maintained strong trade links. Fast-forwarding to modern diplomatic relations, Greece and Egypt have continued their relations with each other up to the 21st century, irrespective of the fact that the cultures of both nations have evolved with many developments and advances. This research paper explores the contemporary importance of the bilateral agreements between Greece and Egypt, drawing parallels with the historical narratives of Herodotus and Thucydides. The paper follows a historical method in analysing the narrative of history and an analytical approach in reading the modern agreements taken under discussion. The paper intends to analyse how modern agreements between these two nations reflect and reminiscence the historical interactions, emphasizing the political, economic, and cultural significance between these powerful nations in the Mediterranean basin. By examining the historical context, the paper aims to shed light on the enduring diplomatic and cultural ties between Greece and Egypt, offering valuable knowledge for international relations in the present and future.

Adoption of Digital Agro-Advisory Services Among Smallholder Farmers: Patterns of the Innovation-Decision Process

Various digital agricultural advisory services have been developed to effectively exchange agriculture related information, skill and knowledge with the farmers. However, innovation and readiness of such technology does not guarantee that it will be adopted by the farmers. This study focuses on understanding farmers’ adoption of digital agroand non-adoption. A mixed-method research was conducted with 50 farmers of Kageshwori Manohara Municipality of Bagmati province, Nepal, who were also the users of mobile-based agriculture application, innovation theory was used as an analytical lens for data interpretation. terms of their adoption decision i.e., passive rejecters, active rejecters as digital literacy, farmer’s agricultural needs, communication channel, farmer’s social network, socio-economic and household dynamics and technological cluster. The study further argues that such innovations need to incorporate information that not just aligns with the needs of any farmers but should also be based on the local context.