Background Knowledge Research Articles

Enabling Context-based AI in Chatbots for conveying Personalized Interdisciplinary Knowledge to Users

Adaptable chatbots have revolutionized user interactions by dynamically tailoring responses to users' knowledge and explainability preferences in interdisciplinary domains, such as AI in education and medicine. While strides have been made in model explainability, little attention has been paid to making models contextually aware and responsive to users' background knowledge. This study investigated interdisciplinary knowledge learning principles in a different domain, where the chatbot's contextual understanding is enhanced through dynamic knowledge graphs that capture users' past interactions to deliver up-to-date and relevant responses. By incorporating explainability features, chatbot responses become enriched, enabling users to understand the reasoning behind answers. This study proposed a model that showed superior chatbot performance and accurately addressed most queries, outperforming competitor chatbots DBpedia, ODC, and ODA. A 0.7 F-measure showcased its excellence, attributed to dynamic knowledge graphs and explainability checks. This study envisions a new era of conversational AI that not only meets user needs but also fosters a deeper understanding of AI decision-making, making it indispensable in delivering personalized, informed, and contextually aware interactions.

Effectiveness of Teaching and Demonstration in Improvement of Knowledge and Skill on CPR among School-going Adolescents: A Quasi-experimental Study

Background: Cardiopulmonary resuscitation (CPR) is one of the most evolving areas of saving actions that improve the survival rates following cardiac arrest and educating high school students can play a dynamic role in case of emergencies in society. Education of school students in CPR is a strategic goal for the improvement of bystander CPR in rural society. If adolescents were trained to perform CPR during school physical education hours, this may be a cost-effective approach to CPR training. This study is conducted to assess the effectiveness of health education in the improvement of knowledge of CPR among school-going adolescents. Aim: To assess the effect of a training program on students’ knowledge of CPR. Objective: (A) To determine the background knowledge of high school students about cardiac arrest and basic life support in adult victims of cardiac arrest. (B) To determine the association between knowledge of cardiopulmonary resuscitation and skills with selected demographic variables. Materials and methods: This is a quasi-experimental study conducted among adolescents aged 13–15 years attending schools in rural areas of South India. The study was conducted between Jan 2022 and Jan 2023. 680 students were included in this study. The universal sampling method was used to enumerate the participants to reduce the impact of the dropout rate. The data was collected using a pre-tested semi-structured questionnaire by interview method. Basic teaching of CPR for the participants included 2 hours of oral teaching using lecture method, question and answer discussion method as well as 2 hours of practical session using demonstration, practice on a manikin, provision of feedback and correction of errors. Results: A total of 680 participants were grouped into three categories according to their knowledge scores: (A) fair, (B) Moderate, and (C) Good scores obtained in pre-training observation and post-training observation. Initially, there were 666 (97.9%) in the fair category, most of them improved after training as seen in the post-training observation results, with 97 (14.3%) persons in the fair (A) category. There was not a single student in the good category of the score before intervention, which increased to 665 (45.6%) in the good category of knowledge. The mean score of pre-training is 2.55, and the post-training score is significantly increased to 9.5. Conclusion: An improvement is observed in knowledge of CPR post-training with planned teaching and demonstration. Hence, this method can be considered a logical solution for improving knowledge about CPR in cases of emergency life-saving skills in a particular group of society.

Assessment of Level of Awareness, Current State of Knowledge, and Skills on Endocrown Technique Among Senior Saudi Dental Students and Interns.

Background Awareness and knowledge about the endocrown technique contribute to the delivery of quality dental care and restorative long-term success. Dentists must be aware and knowledgeable about endocrowns as they offer a conservative approach, aid in maintaining tooth integrity, and have become a promising option in use recently. Aim This study evaluated the current state of knowledge, and the understanding of the endocrown technique as post-endodontic management among senior undergraduate dental students and interns who have studied the theoretical and laboratory procedures of endocrown as part of the curriculum. Materials and methods This cross-sectional investigation was conducted through an online questionnaire consisting of 21 questions in three parts. The first part consisted of demographic information; the second encompassed knowledge and attitude; and the third part evaluated skills regarding endocrown technique. A total of 164 voluntary dental students and dental intern questionnaires were evaluated.Factor analysis was used to identify the domains for knowledge and skill. Results In this study, the knowledge and skills of undergraduate dental students toward endocrowns were assessed. The reliability statistics showed favorable internal consistency (Cronbach's alpha values: 0.513 for knowledge and 0.729 for skill component 1). Significant correlations were noticed between knowledge component 1 and skill component 1 (r = 0.647, p < 0.001), knowledge component 1 and skill component 2 (r = 0.333, p < 0.001), and knowledge component 1 and skill component 3 (r = 0.260, p = 0.001). These findings emphasize the importance of evaluating students' understanding of endocrown. Significant differences were found among intern participants, fifth- and sixth-year dental students in component 1 of the knowledge (p-value<0.001), andall skills components. Conclusion Dental students have varying levels of knowledge and skills related to endocrown. Gaps in knowledge and skills have been detected, which dictates intervention actions, including curricular changes and training workshops.

Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas.

Ribosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq yields genome-wide insight into translational dynamics and post-transcriptional control of gene expression. Here, we provide details on the Ribo-seq method and the subsequent analysis with the unicellular model alga Chlamydomonas reinhardtii (Chlamydomonas) for generating high-resolution data covering more than 10 000 different transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5' and 3' sections of transcripts and characteristics of eukaryotic translation termination, which are fundamentally distinct for chloroplast translation. In chloroplasts, a heterogeneous RPF size distribution along the coding sequence indicates specific regulatory phases during protein synthesis. For example, local accumulation of small RPFs correlates with local slowdown of psbA translation, possibly uncovering an uncharacterized regulatory step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light-harvesting complex proteins, LHCs. By providing high-quality datasets for all subcellular genomes and attaching our data to the Chlamydomonas reference genome, we aim to make ribosome profiles easily accessible for the broad research community. The data can be browsed without advanced bioinformatic background knowledge for translation output levels of specific genes and their splice variants and for monitoring genome annotation.

Assessing the potential of ChatGPT for psychodynamic formulations in psychiatry: An exploratory study

Although there were several attempts to apply ChatGPT (Generative Pre-Trained Transformer) to medicine, little is known about therapeutic applications in psychiatry. In this exploratory study, we aimed to evaluate the characteristics and appropriateness of the psychodynamic formulations created by ChatGPT. Along with a case selected from the psychoanalytic literature, input prompts were designed to include different levels of background knowledge. These included naïve prompts, keywords created by ChatGPT, keywords created by psychiatrists, and psychodynamic concepts from the literature. The psychodynamic formulations generated from the different prompts were evaluated by five psychiatrists from different institutions. We next conducted further tests in which instructions on the use of different psychodynamic models were added to the input prompts. The models used were ego psychology, self-psychology, and object relations. The results from naïve prompts and psychodynamic concepts were rated as appropriate by most raters. The psychodynamic concept prompt output was rated the highest. Interrater agreement was statistically significant. The results from the tests using instructions in different psychoanalytic theories were also rated as appropriate by most raters. They included key elements of the psychodynamic formulation and suggested interpretations similar to the literature. These findings suggest potential of ChatGPT for use in psychiatry.

Knowledge and utilization of Traditional Birth Attendants by Women of Reproductive Age in Alanamu Community Ilorin, Northern Nigeria

INTRODUCTION The lack of access to skilled healthcare services during childbirth remains a major factor for high maternal mortality in developing countries, as traditional birth attendants (TBAs) continue to serve as the predominant providers of maternal health care in rural communities. This study explores the knowledge and utilization of TBAs by women of reproductive age in a rural community of Ilorin, kwara state Nigeria. METHODSThis study is a descriptive cross-sectional study which was conducted using a well-structured interviewer based questionnaire, administered to 212 women of reproductive age-group to collect data on their knowledge and utilization of the services of TBAs. Analysis was done using Statistical Product and Service Solutions (SPSS) software version 20. RESULTS One hundred and fifty three respondents (72.2%) had background knowledge of TBAs, 91 (40.8%) had visited a TBA at least once to carry out their deliveries, of which 73 (80.2%) of them had successful deliveries, while 18 (19.8%) had complications during their deliveries, and 7 (7.7%) were referred to health care facilities for expect management. The study showed statistical significance between the level of education of respondents and their patronage of TBAs with a p-value of 0.041, and showed no statistical significance with their level of income. CONCLUSION This study showed adequate knowledge and utilization of the services of TBAs by members of the community. The practice of TBAs has continued to thrive in rural communities; integrating their services with the standard healthcare system as well as continuous sensitization of rural communities on their roles and limitations would go a long way in reducing maternal morbidity and mortality associated with the use of poorly trained TBAs

Answering Binary Causal Questions Using Role-Oriented Concept Embedding

Answering binary causal questions is a challenging task, and it requires rich background knowledge to answer such questions. Extracting useful causal features from the background knowledge base and applying them effectively in a model is a crucial step to answering binary causal questions. The state-of-the-art approaches apply deep learning techniques to answer binary causal questions. In these approaches, candidate concepts are often embedded into vectors to model causal relationships among them. However, a concept may play the role of a cause in one question, but it could be an effect in another question. This aspect has not been extensively explored in existing approaches. Role-oriented causal concept embeddings are proposed in this paper to model causality between concepts. We also propose leveraging semantic concept similarity to extract causal information from concepts. Finally, we develop a deep learning framework to answer binary causal questions. Our approach yields accuracy that is comparable to or better than the benchmark approaches. <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Impact Statement</u> —Understanding causality is crucial for automatic question-answering systems, which are useful in extracting and distributing human knowledge. An automatic question-answering system with causal knowledge can be used to check whether there is causal relationship between two concepts. Existing approaches to answer binary causal questions often answer such questions with close to 55% accuracy due to the limited usage of causal and contextual features. The deep learning framework we propose in this paper uses a role-oriented concept embedding to address such issues. Our approach achieves better accuracy by up to 3.6%, compared to the state-of-the-art benchmark approaches. The proposed approach can be used in a variety of fields, including prescriptive analysis, event prediction, and any other area where entity relationships are essential. It could also be used to improve the retrieval of causality-related inquiries in web search engines.

Inconsistent Matters: A Knowledge-Guided Dual-Consistency Network for Multi-Modal Rumor Detection

Rumor spreaders are increasingly utilizing multimedia content to attract the attention and trust of news consumers. Though quite a few rumor detection models have exploited the multi-modal data, they seldom consider the inconsistent semantics between images and texts, and rarely spot the inconsistency among the post contents and background knowledge. In addition, they commonly assume the completeness of multiple modalities and thus are incapable of handling handle missing modalities in real-life scenarios. Motivated by the intuition that rumors in social media are more likely to have inconsistent semantics, a novel Knowledge-guided Dual-consistency Network is proposed to detect rumors with multimedia contents. It uses two consistency detection subnetworks to capture the inconsistency at the cross-modal level and the content-knowledge level simultaneously. It also enables robust multi-modal representation learning under different missing visual modality conditions, using a special token to discriminate between posts with visual modality and posts without visual modality. Extensive experiments on three public real-world multimedia datasets demonstrate that our framework can outperform the state-of-the-art baselines under both complete and incomplete modality conditions. Our codes are available at https://github.com/MengzSun/KDCN.

Die sozial-emotionalen Voraussetzungen im Fremdsprachenerwerb

Abstract In the field of second language acquisition, a lot of emphasis has been placed on factors such as input, age, linguistic background, and prior knowledge of the learner, and there has been ongoing examination and refinement of teaching methods and pedagogy. However, there is still an important factor that is not always considered in the learning process: socio-emotional prerequisites. These prerequisites refer to the non-linguistic factors that vary from person to person and can contribute to the complexity of the learning process. The social environment and emotional states of the learner can heavily influence the learning context, and it is no longer just a matter of considering the cognitive variables of an individual, but rather looking at the individual as a whole, which is formed by multiple variables. The group-specific learning atmosphere can also have greatly impact on the development of the learning process. All these factors raise the question of to what extent they influence the reception and production of a foreign language.

Abstract A127: Identification of therapeutic drug combinations targeting KRAS

Abstract KRAS is the most frequently mutated oncogene and increased development efforts targeting KRAS mutations have yielded recent FDA approvals of two KRAS G12C inhibitors. However, for some indications, there are other KRAS mutations more common than G12C. For Pancreatic ductal adenocarcinoma (comprising more than 90% of pancreatic cancer cases), 94% harbor KRAS mutations, where G12D mutations account for around 45% while G12C mutations are rare (1%). Hence, there is a need to develop methods to target a broader range of KRAS mutations. Beyond direct gene mutation, activation of oncogenic KRAS and downstream MAPK signaling through other genomic alterations may benefit from KRAS-specific therapeutic strategies, especially combination therapy. We have developed a platform, Optim.AI™, that rationally converges upon optimal drug combinations within a defined drug search space, without any prior knowledge of the background of the models.  In this study, we utilized the platform to identify efficacious drug combinations that contain a histone deacetylase 4/6 inhibitor, KYAN-001 in the context of KRAS mutations. 7 cell lines (6 prostate and pancreatic cancer with normal, epithelial THLE-2 cell line) were evaluated with Optim.AI. The cancer cells and THLE-2 were seeded into 384-well plates and treated with 155 different combinations consisting of indication-specific drugs the following day. Post-drug treatment cell viability was used for Optim.AI™ analysis, which maps experimental data points to a second-order quadratic function to predict and rank cancer cell killing efficacies for all other permutations of drug combinations. In androgen resistant prostate cancer, Optim.AI identified synergistic interaction between KYAN-001 and a MEK inhibitor. With MEK being downstream of the KRAS pathway, we wanted to evaluate the efficacy of this combination on pancreatic cancer. Interestingly, this combination was demonstrated to be top ranked against PANC-1 and AsPC-1 cell lines, both harboring G12D KRAS mutation, as compared to a cell line with wild-type KRAS, BxPC-3. This was further validated via half-maximal inhibitory curves (IC50), where synergism was also observed for the combination on AsPC-1, but not BxPC-3. KYAN-001 was also shown to exhibit monotherapy sensitivity against pancreatic cancer patient-derived organoids (PDOs), with a mean of 4 µM. This study has successfully demonstrated the ability of Optim.AI™ to identify novel, optimal drug combinations for both prostate and pancreatic cancers, without any prior background knowledge on these cell lines. With MEK being downstream of the KRAS pathway and 94% of those diagnosed with pancreatic cancer have KRAS mutations, the differential sensitivities of this combination across the cell lines presents the utility of the platform in precision medicine, especially for undruggable targets like KRAS. With promising and demonstrated monotherapy efficacy of KYAN-001 on PDOs, further experiments could be done to evaluate the clinical relevance of both KYAN-001 and MEK inhibition on other relevant ex vivo models. Citation Format: Masturah Mohd Abdul Rashid, Lisa Chow, Edward Kai-Hua Chow. Identification of therapeutic drug combinations targeting KRAS [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A127.

Vocational education’s growing focus on employability skills: A bibliometrics evaluation of current research

&lt;span lang="EN-US"&gt;The study aimed to investigate one of the search’s core issues, ‘employability skills’, and their relationship. It also attempted to recognize the valuable contributions of writers, journals, governments, and institutions worldwide in pursuing employability skills. The quantitative study of bibliographic content is known as bibliometric analysis. Furthermore, it provides a broad view of a study subject that may be subdivided into publications, authors, and journals. This study offers a bibliometric summary of recent research on employability skills. Data was taken from the Scopus database between 2003 and 2022 and examined using VOSviewer software, open refine, tableau public, and Microsoft Excel. The data from the Scopus database are 1,070 documents. Researchers observed that researchers mainly focus on employability skills, higher education, engineering education, curricula, employment, and vocational education. Education and Training journal is the most appropriate journal for contributions, followed by Higher Education, Skills, and Work-based Learning journal, and then the Higher Education Research and Development journal. This study informs researchers by providing insights into basic background knowledge about employability skills for visual and quantitative research. Therefore, this method can observe the research gap in employability skills and more in-depth academic discussions. The study demonstrates how employability skills research has arisen and progressed, as well as prospective future research agendas.&lt;/span&gt;

Mapping the knowledge of ecosystem service-based ecological risk assessment: scientometric analysis in CiteSpace, VOSviewer, and SciMAT

The ecosystem services approach offers a more ecologically relevant method to establish environmental conservation goals and implement ecological risk assessment (ERA). The emergence of bibliometrics has facilitated the development of new systematic review techniques. In this study, we utilised CiteSpace, VOSviewer, and SciMAT software, based on the Web of Science database, to qualitatively and quantitatively analyse the ecosystem service-based ecological risk assessment (ESRA) literature knowledge map spanning from 1994 to 2023. This article explored the field’s evolution from macro to micro perspectives, incorporating background information, current trends, and knowledge structure. The findings demonstrate that ESRA has progressed from an initial stage to a phase of global cooperation and policy applications. This transition between stages has been characterised by a shift from focusing on natural processes to understanding human impacts on ecosystems. Key themes identified include ecosystem services, landscape ERA, aquatic ERA and ecosystem health. The overall development of ERA can be observed as a progression through different periods, namely, the traditional era, regional era, and landscape era. Currently, landscape ERA methods based on changes in land use and land cover are widely employed. The study also revealed various challenges in the ESRA field, such as data availability, scale issues, and uncertainty. Future ESRA studies should consider holistic ecosystem services, interdisciplinary approaches, ecological models, and advanced technologies to address complexity. Using big data and informatisation for research offers new opportunities but requires integration and innovation. It is anticipated that ESRA holds promise for ecological sustainability and human wellbeing.

디지털 교과서를 활용한 초등 문학 교육 모델 연구: 초등 교사 전문가 심층면접을 중심으로

Digital textbooks in literature education focus on understanding, experiencing, and creating literature. This study analyzed their use in elementary schools, finding that they enhance material exploration, multimedia learning, and interactive literary learning, offering diverse educational experiences. They contribute to the acceptance and creation of literary works and foster literary attitudes, with a focus on both textbook content and learner engagement. The model incorporates interests and knowledge levels in forming literary attitudes and involves background knowledge, text analysis, and communication. It also supports work creation through tools and collaboration, and employs digital technologies like artificial intelligence to deepen the understanding and creation of literature.

Review on Pediatric Malignant Focal Liver Lesions with Imaging Evaluation: Part I

Malignant focal liver lesions (FLLs) are commonly reported in adults but rarely seen in the pediatric population. Due to the rarity, the understanding of these diseases is still very limited. In children, most malignant FLLs are congenital. It is very important to choose appropriate imaging examination concerning various factors. This paper will outline common pediatric malignant FLLs, including hepatoblastoma, hepatocellular carcinoma, and cholangiocarcinoma and discuss them against the background of the latest knowledge on comparable/similar tumors in adults. Medical imaging features are of vital importance for the non-invasive diagnosis and follow-up of treatment of FLLs in pediatric patients. The use of CEUS in pediatric patients for characterizing those FLLs that remain indeterminate on conventional B mode ultrasounds may be an effective option in the future and has great potential to be integrated into imaging algorithms without the risk of exposure to ionizing radiation.

Knowledge and Perceptions about Curative Therapies for Sickle Cell Disease and Hydroxyurea Among Caregivers and Patients at a Large Tertiary Care Center: A Survey Study

Background: Sickle Cell Disease (SCD) affects approximately 100,000 individuals in the United States. Patients require regular follow-up and monitoring to prevent serious complications. Even with rigorous monitoring, health outcomes can be poor due to pain-seeking stigma and other social determinants of health, namely racial, social, and economic disparities. According to the National Assessment of Health Literacy published in 2006, 36% of adults have limited health literacy in the United States. Among SCD populations, disease-specific knowledge can play a vital role in improving pain control and access to appropriate maintenance therapies. Aims:The purpose of this study is to investigate the knowledge and perceptions of patients with SCD and their caregivers attending The Valerie Fund Pediatric Hematology-Oncology Center at the Children's Hospital of New Jersey in Newark, NJ regarding their disease, complications, genetic impact, general anticipated course of treatment or natural history of disease. Hydroxyurea (HU) and curative therapies include bone marrow transplant (BMT) and gene therapy (GT). Methods: We surveyed 85 participants, accounting for 79 patients as some surveys were completed by each the patient and caregiver. Sixty-six (83.5%) participants were caregivers and 13 (16.5%) were children with sickle cell disease between 12- and 20-years-old. Most patients identified as black, African, or African American (76; 96.2%) with 2 (2.5%) Hispanic patients, and 1 (1.3%) white patient. Forty-three patients (54.4%) were female and 36 (45.6%) were male. The average age of the patients was 10.9 years with a standard deviation of 5.7 years. More than half of patients were HbSS genotype (51; 64.6%). Remaining genotypes were HbSC (21; 26.6%), HbS-β 0-thalassemia (5; 6.3%), and HbS-β +-thalassemia (2; 2.5%). Forty-six (58.2%) of patients had received HU and 33 (41.8%) had not. Results: When assessing background knowledge of sickle cell and heritable risk, most participants could correctly identify the patient's sickle cell genotype (74; 87.1%) and most caregivers could correctly identify their own genotype (49; 74.2%). However, many caregivers exhibited limited understanding of genetic risk with only 18 (27.2%) correctly identifying the one in four chance of having a subsequent child with SCD when both parents are carriers. The results revealed participants could not distinguish between treatment for SCD and sickle cell trait; few participants correctly identified that sickle cell trait is not an indication for treatment with HU (8; 10.1%), BMT (4; 5.1%) or GT (6; 7.6%). Baseline knowledge about BMT and GT was limited. Only 27 (34.1%) participants correctly identified that BMT is indicated for treating patients with HbSS or HbS-b 0-thalassemia, and only 9 (11.4%) participants correctly identified this treatment population for GT. BMT knowledge was slightly greater than GT knowledge, namely that 60.1% (48) correctly identified the benefits of BMT for SCD patients, including decreased pain, decreased need for pain medication, decreased length of hospital stay, and cure, and that either bone marrow, stem cells, or blood could be transplanted materials. Most patients did not correctly identify these benefits of GT (55; 70%), nor could they identify the source of blood or stem cells for GT (65; 82.3%). The ability to correctly identify the benefits of HU for sickle cell disease (48; 60.8%) was positively associated with the ability to correctly identify the benefits of BMT (p-value 0.0091) and GT (p-value 0.0438) using Fisher's exact test with 95% confidence interval. Conclusion: These results suggest that dedicated teaching about HU, a common treatment for SCD, can result in greater patient knowledge about newer and curative treatment options of bone marrow transplant and gene therapy. These findings underscore the necessity of implementation of comprehensive patient teaching that is inclusive of population education levels, literacy rates, health literacy rates, and other cultural and societal factors.

Attitudes and barriers to participation in window-of-opportunity trials reported by White and Asian/Asian British ethnicity patients who have undergone treatment for endometrial cancer

PurposeWindow-of-opportunity trials (WOT) are a study design that have been used to investigate drug activity in endometrial cancer (EC). Recruitment to cancer clinical trials by patients from ethnic minority groups is reported to be lower than for patients of White ethnicity.MethodsA verbal questionnaire was conducted with White and Asian/Asian British ethnicity patients who had undergone treatment for EC. Strategic purposeful sampling was used to recruit patients from diverse social/educational backgrounds. Questions explored: background knowledge of clinical research, WOT study design, and views on medications that might be investigated. Thematic analysis was used to explore motivations for WOT participation and perceived barriers.ResultsIn total, 21 patients were recruited to the study (15 White and 6 Asian/Asian British). Views on optimum time to receive trial information differed, preferences ranging from 'at the time of diagnosis' to 'a few days after diagnosis'. The choice of medication under investigation had a strong influence on potential willingness to participate, with greater interest reported in medications derived from vitamins or food supplements rather than hormone-based drugs. Potential barriers to participation included concern over potential side-effects and the emotional/physical burden of a cancer diagnosis prior to major surgery.DiscussionThis study provides important insights into patients’ views on WOT participation in EC and raises issues that need to be considered for future trial design and participant recruitment materials. The timing and format of study information and type of substance under investigation were factors influencing potential participation. Future studies should consider using multi-lingual visual information videos to address information needs, as this may encourage participation by ethnic minority patients.

GLPS: A Geohash-Based Location Privacy Protection Scheme.

With the development of mobile applications, location-based services (LBSs) have been incorporated into people's daily lives and created huge commercial revenues. However, when using these services, people also face the risk of personal privacy breaches due to the release of location and query content. Many existing location privacy protection schemes with centralized architectures assume that anonymous servers are secure and trustworthy. This assumption is difficult to guarantee in real applications. To solve the problem of relying on the security and trustworthiness of anonymous servers, we propose a Geohash-based location privacy protection scheme for snapshot queries. It is named GLPS. On the user side, GLPS uses Geohash encoding technology to convert the user's location coordinates into a string code representing a rectangular geographic area. GLPS uses the code as the privacy location to send check-ins and queries to the anonymous server and to avoid the anonymous server gaining the user's exact location. On the anonymous server side, the scheme takes advantage of Geohash codes' geospatial gridding capabilities and GL-Tree's effective location retrieval performance to generate a k-anonymous query set based on user-defined minimum and maximum hidden cells, making it harder for adversaries to pinpoint the user's location. We experimentally tested the performance of GLPS and compared it with three schemes: Casper, GCasper, and DLS. The experimental results and analyses demonstrate that GLPS has a good performance and privacy protection capability, which resolves the reliance on the security and trustworthiness of anonymous servers. It also resists attacks involving background knowledge, regional centers, homogenization, distribution density, and identity association.

Outline on Selected Teaching Strategies to Improving the Knowledge of B.Sc., Students in Physics

This research is designed to study about the Effectiveness of selected teaching strategies in improving the knowledge of B.Sc., Students in Physics. Physics is the very important area in Science. The main purpose of the study is to identify the problems faced by the under graduate Physics students and how it can be rectified to generate in their field of Physics. In Physics, teaching methods are different principles and methods that are used to instruct students in a learning environment. The methods used by a lecturer will depend on the skills or information the lecturer would like to convey to their students. Some of the most common teaching methods are memorization, class participation, recitation, and demonstration. While these teaching methods are widely used, every instructor has a specific teaching method. Lecturers must be flexible in their subjects and often adjust their style of teaching to accommodate their students. Efficient teaching methods are essential tools that can help students to achieve success in the classroom. In college level each student has a different personality and learning abilities. There are several factors that a teacher must consider when choosing a teaching method for their students. Some determining factors for selecting a teaching method include the student’s interest and background knowledge, as well as their environment and learning abilities.

Design and Validation of Structural Causal Model: A Focus on EGRA Dataset

Designing and validating structural causal model (SCM) correctness from a dataset whose background knowledge is obtained from a research process is not a common phenomenon. Studies have shown that in many critical areas, such as healthcare and education, researchers develop models from direct acyclic graphs (DAG), a component of an SCM, without testing them. This phenomenon is worrisome and is bound to cast a shadow on the inference estimates that may arise from such models. In this study, we have designed a novel application-based SCM for the first time using the background knowledge obtained from the Early Grade Reading Assessment (EGRA) program called the Strengthen Education in Northeast Nigeria (SENSE-EGRA), which is an educational intervention program of the American University of Nigeria (AUN), Yola, on the letter identification subtask. This project was sponsored by the United States Agency for International Development (USAID). We employed the conditional independence test (CIT) criteria for the validation of the SCM’s correctness, and the results show a near-perfect SCM.

Event causality identification via graph contrast-based knowledge augmented networks

Identifying causality between events is a crucial research task in natural language processing. However, existing methods either ignore background knowledge of events or do not consider interference of knowledge graph noise on event representations. In this paper, we propose a novel Graph Contrast-based Knowledge Augmented Network (GCKAN) for event causality identification task, which integrates comprehensive background knowledge of events from knowledge graphs and alleviates the knowledge graph noise problem. First, a descriptive knowledge augmentation module is proposed to aggregate one-hop neighbor information in knowledge graphs and learn meaningful descriptive knowledge of events. Then, a relational knowledge augmentation module is designed to encode multi-hop path information and learn latent reasoning knowledge between event pairs. In addition, trustworthiness-based and degree-based graph contrastive learning schemas are devised in the two modules respectively, which suppress knowledge graph noise during information aggregation and derive more robust knowledge-aware event representations. Extensive experiments on three public datasets demonstrate the consistent superiority of GCKAN over state-of-the-art knowledge-based techniques. Noise interference experiments and cross-topic adaptation experiments further verify the robustness and generalization of GCKAN.