Knowledge Base Research Articles

A comparative study of voice in Chinese English-major undergraduates’ timed and untimed argument writing

As a somewhat elusive and occlusive concept, voice can be a challenging and formidable hurdle for second language (L2) writers. One area that exemplifies this struggle is timed argument writing, where authors must position claims, ideas, and individual perspectives to an existing knowledge base and scholarly community under the confines of time. To enrich our understandings of voice construction in L2 English writers’ timed writing, we explored how 41 Chinese English-major undergraduates deployed authorial voice in two prompt-based argument writing tasks (timed versus untimed). We also sampled their self-reported knowledge, use, and understanding of voice through a survey-based instrument. To compare the quantity and quality of voice construction between the two samples, we measured 10 voice categories, three voice dimensions, and overall voice strength. Results showed that only two categories displayed statistically significant differences in terms of frequencies, but all three voice dimensions and overall voice strength scored significantly higher in untimed writing samples. Based on the results of our text analysis and survey, we further highlight the complexities of voice in L2 writing, provide evidence in support of existing voice rubrics, and make practical suggestions for teaching and assessing voice in writing.

Development and implementation of a guideline-based decision support system for etiological diagnosis of Sustained Monomorphic Ventricular Tachycardia (SMVT)

Abstract Background Guideline (GL)-based decision support systems (DSSs) play a significant role in supporting physicians in their decision-making processes by providing structured clinical guidance. While these systems have shown significant success in enhancing practitioner performance and patient outcomes in general practice, their application in the context of ventricular arrhythmias remains limited. Moreover, the clinical etiological diagnosis of ventricular arrhythmias presents various challenges for healthcare professionals, such as adherence to updated diagnostic criteria and understanding of complex arrhythmia mechanisms. Purpose In this study, we aim to design, implement, and evaluate a guideline-based decision support systems for etiological diagnosis of sustained monomorphic ventricular tachycardia (SMVT), which could potentially address critical challenges associated with the disease diagnosis and management. Methods To comprehensively capture the semantics embedded in clinical guidelines, we first developed a dedicated knowledge graph tailored to the clinical decision-making. This involved extracting entities and relationships pertinent to key decision procedures from ESC guidelines for ventricular arrhythmias, clinical textbooks or literatures. Subsequently, we translated instances within the knowledge graph into archetypes within openEHR, amplifying the interoperability of clinical information. To enhance the interpretability of the DSS, we established executable diagnostic and treatment processes to offer visual representation of clinical steps in diagnosis and treatment. Ultimately, we constructed a decision support engine to implement the GL-DSS, and its effectiveness was evaluated with anonymous real-world data. Results The proposed GL-DSS was found to be quite feasible and could provide etiological diagnosis for SMVT. The knowledge base for the constructed GL-DDS included more than 2000 entities and relations, which played a vital role in representing disease pathogenesis. The proposed system can map the clinical entities to a set of openEHR archetypes, thus mitigate the interoperability issues of the hospital information systems and CDSS data integration. Also, this module improved system usability and ensured that guidelines could be easily translated and updated into decision support tools. Real-word medical records from 20 patient were collected for model evaluation, the results showed that the GL-DSS covered most of the entities and relations between diseases and diagnostic evidence recorded in clinical texts and achieved a diagnosis accuracy of 80%. Conclusions The results demonstrated that our proposed GL-DSS could completely and accurately capture the diagnostic information under the concrete EHR data. Thus, the implement decision support system could have the potential to improve clinical decision-making, patient care, and outcomes in this specialized medical domain.

Future Finland – A nationwide Finnish multidisciplinary birth cohort initiative

Abstract Increasing evidence suggests that early-life conditions may have substantial consequences on individual health and wellbeing throughout the lifecycle. Development of complex social and health issues may be best understood through longitudinal studies that combine the perspectives of social and health sciences. Future Finland aims to collect a nationwide lifelong data resource that through collaborative multidisciplinary research will strengthen future population welfare. Future Finland will be based on index children born in Finland (43.000/year) during a specific time period. National registers and other administrative data sources will provide data for the age cohort (children), their parents and siblings, with special effort on data from more rarely used sources (e.g., electronic health records, school records). Subsets of cohort members will be recruited in early pregnancy (consent) to undergo deeper data collection through questionnaires, biological and environmental samples and measurements, and digital monitoring data (e.g., physical activity, citizens digital footprint). The Future Finland preparatory phase started in 2023 at the Finnish Institute for Health and Welfare (THL). The Future Finland design and focus areas are currently being planned based on identified information gaps and with consultations of experts from other birth cohort studies. Data collection is planned to start in 2025 by piloting and foreseen to expand to full-scale in 2027-2028. The Future Finland data resource will be made available for the entire research community as openly as possible, at the same time maintaining the highest possible data security standards to protect privacy now and in the future. Future Finland enables novel interdisciplinary research and intervention setups, which will strengthen the knowledge base for societal decision-making and promote the future population welfare. Future Finland is funded by the Finnish Cultural Foundation. Key messages • Future Finland initiative will collect a nationwide lifelong data resource enabling novel cross-disciplinary research designs to produce groundbreaking and impactful scientific results. • A larger-scale use of data enables novel interdisciplinary research and intervention setups strengthening the knowledge base for societal decision-making and promoting the future population welfare.

Digital health literacy and associated socio-demographic characteristics in the French population

Abstract Background With the development of digital devices in the health field, digital health literacy has become an important issue in promoting and protecting people’s health. Digital health literacy was measured in a representative sample of the French adult population in order to assess its level and to identify the socio-demographic characteristics of individuals with the lowest literacy levels. Comparisons with works carried out in other European countries as well as implications for the implementation of digital interventions will be discussed. Methods Digital health literacy was assed using the HLS19-DIGI-HI Instrument. This 8-item scale measuring the skills related to dealing with digital health information was introduced in the 2023 Health Barometer survey, conducted by the French national public health agency. The survey included French-speaking individuals living in France, aged 18-85, selected through randomly generated phone numbers. 3007 persons were interviewed using a computer assisted telephone interview. A continuous score and categories were calculated to determine the level of Digital Health Literacy. Their associations with sociodemographic characteristics were studied using univariate and multivariate analysis. Results 1902 persons declared they used internet to search information or advice on health on internet in the last 12 months and completed the Digital health literacy questionnaire. 61 % of these individuals have a low level of digital health literacy (29 % “inadequate” and 32% “problematic”). Multiple sociodemographic characteristics were associated with lower levels of literacy in univariate and multivariate analysis. Conclusions These results are useful to better understand and assess the digital health literacy of the population according to their socio-demographic characteristics. They will provide a knowledge base to implement web-based interventions for promoting targeted digital health interventions, according to targeted audiences. Key messages • This study in large random sample of the French population showed frequent difficulties to deal with online health information. • Multiple sociodemographic characteristics were associated with digital health literacy and can help to support implementation of targeted digital health interventions.

Mediating pathways between attention deficit hyperactivity disorder and type 2 diabetes mellitus: evidence from a two-step and multivariable Mendelian randomization study.

Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways. We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators. Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: -1.99%, 110.38%) of the ADHD-T2D association. These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.

Correlates of using behavioural sciences to design health promotion interventions and programs

Abstract Background The World Health Organization highlighted the need to better integrate behavioural science in the field of public health. Based on the theoretical domains framework, this study examined correlates of public health practitioners’ use of behavioural science principles to plan public health actions aim at promoting physical activity and healthy eating. Methods This study adopted a cross-sectional design. A convenience sample of 160 public health practitioners were recruited from different public health agencies (non-profit organizations, governmental and para-governmental agencies). They were asked to complete a survey questionnaire online and self-reported their use of behavioural science to plan health promotion interventions. Regression analyses were conducted to examine correlates of behaviour and behavioural intentions. All analyses were controlled for sex, number of years of experience in public health and the type of organization they work for. Results Skills (OR = 4.1, 95%CI: 1.3, 13.5) and intentions/goals (OR = 9.2, 95%CI: 2.3, 36.1) were the two domains significantly associated with the use of behavioural science. Perceived capacity to overcome the fact that none of their colleagues rely on behavioural sciences in their organization (OR = 7.2, 95%CI: 1.7, 30.3) was also associated with behaviour. Knowledge (OR = 8.6, 95%CI: 1.9, 39.1) and beliefs about consequences (OR = 4.0, 95%CI: 1.1, 14.7) were in turn associated with intentions/goals. Conclusions This unique study provides important insights for the development of future knowledge transfer activities aim at supporting positive attitudes and motivations toward the use of behavioural science as well as developing competencies and a normative use of behavioural science. The development of a strong knowledge basis would also need to be a core component of trainings to support the integration of behavioural science in public health to design physical active lifestyles and healthy eating interventions. Key messages • Increasing knowledge and skills in behavioural sciences is a key for a better integration in public health practices. • Changes in norms and attitudes toward the use of behavioural sciences will also support a better uptake.

On the Foundations of Conflict-Driven Solving for Hybrid MKNF Knowledge Bases

Abstract Hybrid MKNF Knowledge Bases (HMKNF-KBs) constitute a formalism for tightly integrated reasoning over closed-world rules and open-world ontologies. This approach allows for accurate modeling of real-world systems, which often rely on both categorical and normative reasoning. Conflict-driven solving is the leading approach for computationally hard problems, such as satisfiability (SAT) and answer set programming (ASP), in which MKNF is rooted. This paper investigates the theoretical underpinnings required for a conflict-driven solver of HMKNF-KBs. The approach defines a set of completion and loop formulas, whose satisfaction characterizes MKNF models. This forms the basis for a set of nogoods, which in turn can be used as the backbone for a conflict-driven solver.

The Influence of Graph Theory Approach in Preventing Cheating at Higher Learning Institution: A case of Institute of Accountancy Arusha

Academic dishonesty has been more common in recent years, both through self-reported and detected cases, which has brought significant attention to the issue of cheating in educational settings. Students often cheat for a variety of reasons, including lack of study time, unclear learning objectives, fear of failing, peer pressure, and parental pressure for academic success. Students who rely on plagiarizing answers miss the opportunity to build their skills and may face challenges in job requirements. The problem of cheating / copying the neighbor's works during the examination is particularly well known. With graph theory especially graph coloring, it is proposed to develop the students' sitting arrangement that can be the solution of cheating. An experimental case study focuses on three master's programs, three bachelor's degree programs, three diploma programs, and three certificate programs at the Institute of Accountancy Arusha. This is done when one room or a venue is assigned to two or more programs with different backgrounds depending on the size of the room. The result shows that using graph coloring has reduced the tendency of students to copy or ask questions from their neighbors in the examination room. Based on the assessment of graph theory's effectiveness in preventing cheating at the Institute of Accountancy Arusha, several recommendations can be made. First, the institution should invest in developing a comprehensive data collection system that captures relevant information such as seating arrangements, student interactions, and exam performance patterns. Collaboration with other institutions in implementing similar technologies could also create a shared knowledge base and lead to best practices in academic integrity. Finally, continuous monitoring and evaluation of this system should be conducted to refine its processes and adapt to new cheating technique.

Backdoor Attacks against Voice Recognition Systems: A Survey

Voice Recognition Systems (VRSs) employ deep learning for speech recognition and speaker recognition. They have been widely deployed in various real-world applications, from intelligent voice assistance to telephony surveillance and biometric authentication. However, prior research has revealed the vulnerability of VRSs to backdoor attacks, which pose a significant threat to the security and privacy of VRSs. Unfortunately, existing literature lacks a thorough review on this topic. This paper fills this research gap by conducting a comprehensive survey on backdoor attacks against VRSs. We first present an overview of VRSs and backdoor attacks, elucidating their basic knowledge. Then we propose a set of evaluation criteria to assess the performance of backdoor attack methods. Next, we present a comprehensive taxonomy of backdoor attacks against VRSs from different perspectives and analyze the characteristic of different categories. After that, we comprehensively review existing attack methods and analyze their pros and cons based on the proposed criteria. Furthermore, we review classic backdoor defense methods and generic audio defense techniques. Then we discuss the feasibility of deploying them on VRSs. Finally, we figure out several open issues and further suggest future research directions to motivate the research of VRSs security.

What can machine learning help with microstructure-informed materials modeling and design?

AbstractMachine learning (ML) techniques have been widely employed as effective tools in addressing various engineering challenges in recent years, particularly for the challenging task of microstructure-informed materials modeling. This work provides a comprehensive review of the current ML-assisted and data-driven advancements in this field, including microstructure characterization and reconstruction, multiscale simulation, correlations among process, microstructure, and properties, as well as microstructure optimization and inverse design. It outlines the achievements of existing research through best practices and suggests potential avenues for future investigations. Moreover, it prepares the readers with educative instructions of basic knowledge and an overview on ML, microstructure descriptors, and ML-assisted material modeling, lowering the interdisciplinary hurdles. It should help to stimulate and attract more research attention to the rapidly growing field of ML-based modeling and design of microstructured materials. Graphical abstract

Assessing the accuracy and reproducibility of ChatGPT for responding to patient inquiries about otosclerosis.

Patients increasingly use chatbots powered by artificial intelligence to seek information. However, there is a lack of reliable studies on the accuracy and reproducibility of the information provided by these models. Therefore, we conducted a study investigating the ChatGPT's responses to questions about otosclerosis. 96 otosclerosis-related questions were collected from internet searches and websites of professional institutions and societies. Questions are divided into four sub-categories. These questions were directed at the latest version of ChatGPT Plus, and these responses were assessed by two otorhinolaryngology surgeons. Accuracy was graded as correct, incomplete, mixed, and irrelevant. Reproducibility was evaluated by comparing the consistency of the two answers to each specific question. The overall accuracy and reproducibility rates of GPT-4o for correct answers were found to be 64.60% and 89.60%, respectively. The findings showed correct answers for accuracy and reproducibility for basic knowledge were 64.70% and 91.20%; for diagnosis & management, 64.0% and 92.0%; for medical & surgical treatment, 52.95% and 82.35%; and for operative risks & postoperative period, 75.0% and 90.0%, respectively. There were no significant differences found between the answers and groups in terms of accuracy and reproducibility (p = 0.073 and p = 0.752, respectively). GPT-4o achieved satisfactory accuracy results, except in the diagnosis & management and medical & surgical treatment categories. Reproducibility was generally high across all categories. With the audio and visual communication capabilities of GPT-4o, under the supervision of a medical professional, this model can be utilized to provide medical information and support for otosclerosis patients.

A comparative study of LLMs and NLP approaches for supporting business process analysis

ABSTRACT This paper compares two approaches to support Business Process Analysis (BPA) for the construction of a Business Process Knowledge Base (BPKB). The methodology is based on the BPA Canvas metamodel, which starts from the preliminary output of the business analysis (an interview). We focus on the extraction of key elements from the text to build the BPKBcore. We experiment with approaches based on Natural Language Processing (NLP) and Large Language Models (LLMs), using a running example to compare the outcomes with manual annotations. The experiment shows that the LLM-based approach yields better performance, especially with enriched prompts.

Path dependency, social capital and the geography of dirty inventions

ABSTRACT Dirty inventions are technologies inherently designed with features that pose significant risks to both human health and the environment. In this study, we focus on a particularly pernicious type of dirty invention within the chemical technological space: persistent organic pollutants (POPs). These chemicals are internationally recognised as among the most toxic and persistent, with properties that render them resistant to natural degradation. For the first time, we construct a comprehensive dataset of POP patents – those patents that incorporate at least one POP in their formulation – filed between 1990 and 2014. We then georeferenced these patents to analyse their distribution at both global and regional scales. Our analysis delves into the regional factors influencing the prevalence of POP inventions. They reveal a pronounced path dependency effect: regions with a more developed knowledge base in technologies relevant to POPs tend to have a higher volume of POP-related patents. However, this effect is mitigated by the presence of strong social capital within these regions.

A Review of the Conceptual Structure and Evolution of Digital Leadership Research in Education

With the advent of digital technologies that have rapidly changed the functioning of societies, digital leadership has also become a novel imperative for the effective functioning of organizations. As the backbone of societal development, educational institutions have not been exempt from the influence of these new trends, which has ignited a growing research interest in the digital leadership roles of school administrators. This study aims to map the conceptual and thematic evolution of this research on digital leadership in the education field to offer a better insight into the strategic themes that are sufficiently or insufficiently addressed; that is, to identify aspects that are clearly defined or left shrouded in shadow. This study employed science mapping methodology and used SciMAT software (version 1.1.04) to map the evolution of thematic strands across three periods of the field’s development. The analysis was conducted using metadata obtained from 174 articles that are indexed on WoS and Scopus. The results indicated that with a growing focus on technology or e-leadership, considering the developments in the world of computers and the internet, research into digital leadership has gained momentum in recent years, particularly following the COVID-19 pandemic. Digital leadership is regarded as a broader concept for application in investigating the knowledge, skills, competencies, and perspectives of school leaders to facilitate the healthy integration of digital technologies into education, school administration, and student learning. The field seems to require investigations into the many aspects of digitalization in education to build a more solid and insightful knowledge base to guide the effective practice of digital leadership in schools.

Combining Phototherapy and Gold-Based Nanomaterials: A Breakthrough in Basal Cell Carcinoma Treatment

Basal cell carcinoma (BCC) is the most common type of skin carcinoma worldwide. BCC development is the result of a complex interaction between environmental, phenotypic, and genetic factors. While conventional treatments such as surgery and topical therapies have demonstrated variable efficacy (some of them with limited efficacy), they are not free of adverse side effects, most of them debilitating. Thus, there is a notable gap in the literature regarding alternative and non-invasive therapeutic options. This review aims to address this gap, exploring the potential of photothermal therapy (PTT) combined with metallic nanoparticles, namely gold nanoparticles (AuNPs), as a minimally invasive treatment approach. Through a comprehensive review of the literature in the period from 2014 to 2024, using experimental investigations, this review seeks to elucidate the intricate interplay between genetic factors, environmental influences, and the tumor microenvironment in BCC disease progression, with PTT as a potential therapeutic strategy. Those studies confirmed an enhanced targeting of cancer cells and selective ablation of tumor tissue, using emerging technologies like PTT. A significant tumor reduction, often exceeding 50%, was observed, with some studies reporting complete elimination of the tumor. The main adverse effects noted were localized skin irritation and transient hyperpigmentation, but these were generally minimal and manageable, highlighting the promise of PTT as an effective treatment. Thus, by leveraging the unique properties of AuNPs to enhance the effectiveness of PTT, the targeting of cancer cells can more precisely occur, reducing collateral damage to healthy tissues. This approach not only aims to achieve better clinical results, but also contributes to the broader knowledge base in the field of BCC research. Continued research and clinical trials will be crucial in refining those techniques and validating their efficacy, ultimately paving the way for more effective and less invasive treatments for BCC.

COMMUNITY VIEWS ON PULMONARY TUBERCULOSIS: A STUDY OF KNOWLEDGE AND BEHAVIOR

Inadequate understanding of tuberculosis (TB) may impact patients' inclination to seek medical care and perpetuate the spread of the disease among the community. This study aimed to evaluate the understanding and perspective of individuals who appear to be in good health regarding pulmonary tuberculosis (PTB)). Objectives: To explore the knowledge and behavior of the population about pulmonary TB. Methods: The study was conducted using a cross-sectional design. A survey using a questionnaire was done on 165 randomly selected healthy individuals after obtaining verbal agreement from all participants. SPSS 23 was used to analyze the data. The chi-square test was applied to obtain the required results. Results: The findings indicated that the average age of the participants was 45.33 ± 1.49 years, ranging from 19 to 67 years. Out of the total, 42 individuals (25.46%) were females, while 123 individuals (74.54%) were males. Out of the respondents, 70 (42.42%) acknowledged that they were aware of the bacterial cause of TB. Eighty percent of individuals are aware that tuberculosis can be treated. The most prevalent symptom of tuberculosis (TB) was the presence of blood in the sputum, accounting for 101 cases (61.21%). In health institutions, contemporary pharmaceuticals were the favored treatment option, chosen in 70 cases (42.42%). Conclusion: The results suggest that communities possessed basic knowledge about the disease. However, it is essential to provide health education to change their traditional beliefs and views of the condition into factual knowledge.

Knowledge, Attitude and Practice of Nurses and Midwives towards Hepatitis B Infection and Control Measures in Alban Gaded Hospital, Khartoum, Sudan

Purpose: Infection with the hepatitis B virus (HBV) causes severe morbidity and death, burdening world health. Nurses and midwives, among other healthcare professionals, are more likely to contract the illness. Few studies have looked at the knowledge, attitude, and practices (KAP) of healthcare professionals in Sudan with regard to HBV infection, despite the fact that diverse components of KAP have an impact on health-related behaviors. This study's objective was to assess the knowledge, attitude, and practice (KAP) level of nurses and midwives concerning HBV viral infection in, Khartoum, Sudan.  Methods: In the Sudanese state of Khartoum, a public hospital (Alban Gaded Hospital) underwent a cross-sectional descriptive hospital-based study. To assess KAP's understanding of nurses and midwives about HBV infection. Self-administered questionnaires were used and approved by the supervisor for distribution to the population chosen for the study. The data was handed over to the Medical Director whom personally ensured the questionnaires were signed and filled by the Healthcare workers (HCWs) of the chosen criteria at the field. A member of group (23:B) took care of the supervision aside with the medical director, and made sure the data was collected as needed. The data at hand were subjected to statistical analysis using SPSS version 24.0 (Statistical Package for Social Sciences).  Results: 95 samples out of 99 were collected. According to participants’ knowledge: 67.95% have good knowledge about HBV, while 32.05% lack basic knowledge about it. The participants’ attitude towards HBV is above average showing 60.3% safe attitude. Lastly, the study shows excellent practice of the participants’ behavior towards HBV safety measures with a score of 92.3% safe practice. From the hospital, a total of 95 out of 99 nurses and midwives took part in the study. Two thirds of the respondents practiced safety, and the majority of respondents had a positive attitude about HBV preventative measures. More than half of the respondents (58.2%) had an average level of understanding. A minor but serious score of (12.6%) was noticed of the individuals, dealing with patients without wearing gloves. More over half of the nurses and midwives were not vaccinated against HBV; more than 50% of participants had incorrect ideas regarding the symptoms and route of HBV infection and all 95 participants voted (NO) for ever being infected by HBV.  Conclusion: In Alban Gaded hospital, the majority of the nurses and midwives were aware of HBV infection. But a sizeable majority of the participants lacked the necessary understanding of early immunization after birth. The study found a probability of high risk infection due to exposure under the poor level of HBV vaccine coverage rate. Moreover a clear point of limitation was noticed in Table 4 third question, where it asks whether you are or ever was infected by HBV. All the participants denied, showing a sense of partiality. Further occupational exposure prevention measures, training programs on HBV infection, including post-exposure prophylaxis, and increasing the vaccination rate of all HCWS are also strongly encouraged.

Exploration and Reflection on the Reform of the "Open Book Exam" in Organic Reactions for Drug Synthesis

Objective: In the era of big data, the traditional “memorization - repetition” learning method is inadequate for addressing the vast and ever - evolving knowledge in courses such as “Organic Reactions for Drug Synthesis”. This article aims to explore how to shift students from “memorization - repetition” to “understanding - application” through educational reform and changes in assessment mechanisms, enabling them to adapt to a rapidly changing knowledge system. Methods: The study analyzed examination data from 9 classes over three consecutive years to assess the impact of implementing “open - book exams” in the “Organic Reactions for Drug Synthesis” course. In the first and third years, a closed - book examination was employed, which is a traditional method that tests studentsʼ ability to recall and apply knowledge without external resources. The second year introduced an open - book examination, the exam allow students to consult materials, promoting a deeper understanding of concepts and the flexible application of knowledge to solve practical problems. Results: The analysis revealed that open - book exams positively influenced studentsʼ ability to understand and apply concepts, fostering greater learning autonomy and creativity. However, issues such as over - reliance on materials and insufficient mastery of basic knowledge were also identified. Conclusion: By examining the “successes” and “failures”, this article offers valuable insights for reforming assessment methods in courses like “Organic Reactions for Drug Synthesis”. Continuous exploration and practice can help educators develop teaching and assessment approaches better suited to the current era, ultimately enhancing studentsʼ comprehensive skills and innovative abilities.

“I Pink I Can” Breast Cancer Intervention Program: Its Effectiveness in Raising Knowledge among Junior High School Students of San Pablo City Integrated High School

As incidence rates rise from one in ten women to one in eight by 2023, breast cancer continues to be a serious worldwide health concern. Regardless of its rarity in men, this study included men in addition to women who frequently get breast cancer. Both sexes are affected by breast cancer, and its effects frequently get worse when discovered in advanced stages. This study highlights the importance of breast cancer education for people of all genders, in order to improve early detection and treatment outcomes. It aims to support the Sustainable Development Goal of "Good Health and Well-Being" by increasing Junior High Students' knowledge about breast cancer through an intervention program. Using a quasi- experimental design, 156 students' knowledge was assessed via a pre-test and post-test after exposure to leaflets, posters, and health teaching. A rigorously tested questionnaire focused on: breast cancer, signs and symptoms, risk factors, risk populations, and breast cancer screening showed that while students had basic knowledge initially, misconceptions were common. Post-intervention results demonstrated a significant increase in correct responses, indicating that the program effectively improved knowledge and corrected misconceptions. This underscores the value of targeted health education in promoting breast health and encouraging preventive measures.

Feasibility of Low-Code Development Platforms in Precision Agriculture: Opportunities, Challenges, and Future Directions

Low-Code Development Platforms (LCDPs) empower users to create and deploy custom software with little to no programming. These platforms streamline development, offering benefits like faster time-to-market, reduced technical barriers, and broader participation in software creation, even for those without traditional coding skills. This study explores the application of LCDPs in Precision Agriculture (PA) through a systematic literature review (SLR). By analyzing the general characteristics and challenges of LCDPs, alongside insights from existing PA research, we assess their feasibility and potential impact in agricultural contexts. Our findings suggest that LCDPs can enable farmers and agricultural professionals to create tailored applications for real-time monitoring, data analysis, and automation, enhancing farming efficiency. However, challenges such as scalability, extensibility, data security, and integration with complex IoT systems must be addressed to fully realize the benefits of LCDPs in PA. This study contributes to the growing knowledge base in agricultural technology, offering valuable insights for researchers, practitioners, and policymakers looking to leverage LCDPs for sustainable and efficient farming practices.