Case-Based Learning-Oriented Textbook: An Effort to Train Students’ Chemistry Problem Solving Skills

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Higher education plays a strategic role in developing the intellectual life of the nation and is part of the national education system. Chemistry learning should not only focus on mastering concepts but also on students’ ability to apply these concepts in real-world contexts through problem-solving skills to meet the challenges of the 21st century. This research aims to develop a case-based learning-oriented textbook that can train prospective teacher students’ chemistry problem-solving skills. This research method used Research and Development (R&D) as proposed by Borg and Gall, limited to the development stage. Data collection used non-test techniques, seeking validation from three subject matter and pedagogical experts. Quantitative descriptive statistics were used for data analysis. The validity test results showed that the case-based learning-oriented textbook was valid, with an Aiken validity index of 0.87 (high validity). Furthermore, the textbook can be used as a means to facilitate student learning activities in case-based learning to train prospective teacher students’ chemistry problem-solving skills, so that the function of this textbook can be maximized.

A Deep Feature Reliability-Based Framework for Offline Handwritten Signature Verification

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Offline handwritten signature verification is widely employed as a biometric authentication technique in financial, legal, and administrative applications. However, accurately distinguishing genuine signatures from skilled forgeries remains a challenging task because of natural intra-writer variations and the inconsistent discriminative capability of deep feature representations. This paper presents a Deep Feature Reliability-Based Framework for Offline Handwritten Signature Verification that enhances verification performance by identifying and utilizing stable writer-specific deep features. Initially, signature images are preprocessed and represented using 2048-dimensional deep features extracted from a pre-trained ResNet50 network. A feature reliability estimation scheme is then introduced to evaluate the statistical consistency of individual feature dimensions across genuine signatures of each writer. Based on the estimated reliability scores, the most reliable features are selected and incorporated into a weighted cosine similarity measure for signature verification. The proposed framework is evaluated on the CEDAR offline handwritten signature dataset using three training–testing splits of 25–75, 50–50, and 75–25. Experimental results demonstrate that the proposed method achieves its best performance with the 75–25 split, obtaining an accuracy of 77.61%, precision of 83.77%, recall of 68.48%, and an F1-score of 75.33%. The findings indicate that incorporating feature reliability into the verification process improves the robustness of deep feature representations and provides an effective framework for offline handwritten signature verification.

Linking Empirical Nickel Laterite Leaching Responses to Preliminary Economic Performance: Trade-Offs among Ni-Co Extraction, Acid Dosage, Fe Dissolution, and Residence Time

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This revised manuscript develops a transparent metallurgical-economic screening framework for atmospheric sulfuric acid leaching of a ferruginous nickel laterite ore. The objective is not to prove a universal kinetic mechanism or a final project-level feasibility estimate, but to evaluate how experimentally observed extraction responses translate into preliminary economic ranking under clearly stated assumptions. Duplicate leaching tests were performed at 95-100 °C using sulfuric acid dosages of 700-1000 kg H2SO4/t ore and residence times of 30-420 min. The tables report average values used for mass-balance and screening calculations; individual duplicate results are not shown in the main text, and formal significance claims are therefore avoided. Nickel and iron responses were modeled empirically as functions of acid dosage and residence time, while cobalt was included as a revenue component in selected base-case scenarios. The results show that the highest observed Ni extraction, 74.1% at 360 min and 1000 kg H2SO4/t ore, also produced the highest Fe dissolution, 65.8%, and a low Ni/Fe selectivity indicator. Under the base-case economic assumptions, the most attractive evaluated scenario was 420 min and 700 kg H2SO4/t ore, because the lower acid-addition cost and Fe penalty offset the lower Ni and Co extraction. Sensitivity analysis confirmed that this ranking is assumption-dependent and should be interpreted as a feasibility-screening result rather than a global economic optimum. Non-monotonic extraction behavior between 360 and 420 min is discussed cautiously as a possible combination of experimental dispersion, sampling effects, and secondary Ni retention associated with Fe(III) hydrolysis and sulfate-bearing phases. The revised framework provides a practical route for converting duplicated laboratory leaching tests into auditable, assumption-sensitive screening inputs for early-stage nickel laterite project evaluation.

Awareness on Intellectual Property Rights Among College Students, A Study with Special Reference to Kozhikode District

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Intellectual Property Rights (IPR) play a crucial role in protecting innovation, creativity, and intellectual assets. The present study examines the awareness of Intellectual Property Rights among college students. The objectives of the study are to assess the level of IPR awareness among college students and to examine differences in awareness based on gender and course of study. Both primary and secondary data were used for the study. Primary data were collected from 50 college students through a structured questionnaire using the purposive sampling method, while secondary data were gathered from books, journals, research articles, government reports, and WIPO publications. Responses were measured using a five-point scale. Descriptive statistics, One-Sample t-test, Independent Samples t-test, and One-Way ANOVA were employed for data analysis.

The results revealed that college students possess a significant level of awareness regarding Intellectual Property Rights. The Independent Samples t-test indicated no significant differences in IPR awareness between male and female students. However, the One-Way ANOVA revealed significant differences among students from different course categories in selected dimensions of IPR awareness. The study concludes that while the overall awareness of IPR among college students is satisfactory, variations exist across certain course categories. The findings emphasize the need for strengthening IPR education and awareness programmes in higher educational institutions.

Artificial Intelligence and Mechanical Engineering in Greek Vocational High Schools: Educational Perspectives and Institutional Barriers

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This scoping review investigates the potential and challenges of integrating Generative Artificial Intelligence (GenAI) into Vocational Education and Training, with a specific focus on the Mechanical Engineering sector of Greek Vocational High Schools (EPA.L.). The purpose of this study is to analyze how AI can transform the teaching of mechanical engineering courses, bridging the gap between theoretical knowledge and laboratory practice in the context of Industry 4.0. The methodology involved a literature review of 26 scientific sources (2016-2026), utilizing thematic analysis guided by theoretical frameworks such as the Technology Acceptance Model (TAM) and teacher self-efficacy. Key findings indicate that the use of specialized, knowledge-enhanced Large Language Models (LLMs) significantly improves the structural integrity and technical accuracy of instructional materials, effectively reducing teacher preparation time. However, despite a high perceived usefulness, the adoption of AI by educators in public schools is severely hindered by the lack of adequate laboratory infrastructure, the absence of discipline-specific training, and heightened AI anxiety regarding ethical risks. In conclusion, the transition to an AI-enhanced school laboratory necessitates immediate upgrades to equipment and a shift from general ICT training to targeted, specialty-specific professional development programs, ultimately empowering teachers to become designers of digital learning experiences.

Role of Artificial Intelligence oriented Tacit, Explicit and Reusable integrated Knowledge Management for the libraries in the 21st century

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Knowledge management will continue to evolve strategically and dynamically for libraries in the 21st century, driven by the knowledge economy and information technology. To understand the development of library knowledge, it is necessary to grasp the relationship between explicit, tacit, and relevant reusable integrated knowledge in an Artificial intelligence environment in today’s dynamic economy. This study examines relevant, explicit, tacit, and related reusable knowledge, the associated processes, and their practical implications for library operations, including efficiency and innovation in organization and learning.

By presenting knowledge management principles, the Nonaka SECI model incorporated with reusability concept of Harsh, and a conceptual framework for library science, this study examines a unified program for the practical application of explicit, tacit, and relevant reusable AI-empowered knowledge in the context of libraries in the educational sector. The role of artificial intelligence in the transformation of libraries regarding the design, collection, creation of meta-data, and dissemination of knowledge is also explored critically. The results presented, including the increased potential of libraries because of meaningfully reinforces reuse of knowledge, effectiveness of processes, and the remembrance of organisations, reveal huge aids for operators thus making libraries as smart centres of data.

Prevalence and Factors Associated with Neonatal Jaundice Among Term and Pre Term Infants at Amana Regional Referral Hospital in DAR ES Salaam, Tanzania

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Background: Neonatal jaundice among term and preterm infants in Tanzania is still a very common problem which has a negative effect on children growth and development. Kernicterus as a complication of extensive accumulation of unconjugated bilirubin can lead to mental retardation.  

Objective: The study focused on assessing prevalence and factors associated with neonatal jaundice among term and preterm infants at Amana Referral Hospital.

Materials And Methods: Cross section study conducted at Amana Regional Referral Hospital (ARRH) for assessing neonatal jaundice in both term and preterm infants. The sample of 120 children was taken.

The respondent mothers or care takers of infants with neonatal jaundice were structured interviewed based on questionnaire. Kramer’s rule as visual inspection of skin used to aid in collecting data.

Expected Results: This study is expected to provide valuable insight into prevalence and factors associated with neonatal jaundice among term and preterm infants admitted at ARRH. Findings will help understanding correlation between factors associated with neonatal jaundice and medical condition itself.

Effectiveness of the Rupiah Literacy Policy Through the www.cbprupiah.com Website in Mataram City, Indonesia

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This study aims to analyze the effectiveness of the Rupiah literacy policy implemented through the CBP Rupiah website www.cbprupiahntb.com in Mataram City and to identify the supporting and inhibiting factors affecting its implementation. The program is part of Bank Indonesia’s Love, Pride, and Understanding of Rupiah (CBP Rupiah) policy, which seeks to enhance public understanding of the functions, value, and role of the Rupiah as the national legal tender and a symbol of national sovereignty. This study employed a qualitative research approach. Data were collected through in-depth interviews, observations, and document analysis. Informants were selected purposively and included representatives of Bank Indonesia’s West Nusa Tenggara Regional Office, school principals, teachers, and students from elementary, junior high, and senior high schools in Mataram City. Data were analyzed using the Miles, Huberman, and Saldaña interactive model, consisting of data reduction, data display, and conclusion drawing. The findings indicate that the Rupiah literacy program delivered through the CBP Rupiah website is effective based on three policy effectiveness indicators: goal attainment, resource efficiency, and adaptability. The program successfully improved public knowledge, awareness, and positive attitudes toward the Rupiah through interactive educational methods and digital media utilization. Resource efficiency was reflected in the optimal use of human resources, educational facilities, and information technology without imposing significant additional burdens on schools. Adaptability was demonstrated through the use of digital platforms, the adjustment of learning methods to participants’ characteristics, and continuous program evaluation. Supporting factors included institutional support from Bank Indonesia, digital technology utilization, school support, student participation, and relevant educational materials. Inhibiting factors included limited website accessibility, inadequate digital literacy, time constraints, and intense information competition in the digital era.

Levelized Cost of Energy Analysis for Power Generation Technologies in Afghanistan: A Comparative Techno-Economic Assessment

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Afghanistan faces significant challenges in achieving reliable, affordable, and sustainable electricity supply while remaining heavily dependent on imported electricity. Despite possessing abundant renewable energy resources, including solar, wind, and hydropower, comprehensive economic assessments of electricity generation technologies under Afghan conditions remain limited. This study presents a comparative Levelized Cost of Energy (LCOE) analysis of six power generation technologies relevant to Afghanistan’s energy sector: Solar Photovoltaic (PV), Wind, Hydropower, Combined Cycle Gas Turbine (CCGT), Coal-Fired Power Plants, and Biomass. A discounted cash flow methodology is employed using technology-specific technical and economic parameters representative of Afghanistan. The analysis incorporates capital expenditure, operation and maintenance costs, fuel costs, capacity factors, plant lifetimes, and financing conditions. Sensitivity analysis is performed across a range of weighted average cost of capital (WACC) values from 5% to 18% to evaluate the impact of financing risk on generation costs. Results indicate that hydropower exhibits the lowest LCOE, followed by utility-scale solar PV and wind power. Renewable technologies demonstrate strong economic competitiveness while simultaneously achieving near-zero operational carbon emissions. The findings highlight the importance of low-cost financing and provide evidence-based guidance for future energy planning, investment prioritization, and sustainable electricity sector development in Afghanistan.

The Relationship between Reinforcement Aspects, Work Atmosphere, and Job Satisfaction with The Job Performance of Early Childhood Education Teachers

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The aspects of reinforcement, work atmosphere, and job satisfaction are important factors that can influence teacher performance in formal educational institutions. This study aims to test the significance of simultaneous and partial correlations between the aspects of reinforcement, work atmosphere, and job satisfaction with teacher performance. The population of this study was 4,759 early childhood education teachers in Surabaya, East Java Province, Indonesia who had a minimum of two years of service and were actively working until 2025. The research sample of 210 teachers was determined using a purposive random sampling technique. Data on the aspects of reinforcement, work atmosphere, and teacher job satisfaction were collected using a Likert scale questionnaire with five answer choices: Strongly Agree, Agree, Undecided, Disagree, and Strongly Disagree, which had met the item validity test and the Alpha Cronbach reliability test, while teacher performance data were collected using a teacher performance assessment rubric instrument that had been tested by experts. The research data were analyzed using parametric linear regression statistical techniques, resulting in the simultaneous positive correlation between the reinforcement, work atmosphere, and job satisfaction aspects with the performance of early childhood education teachers. Partially, the reinforcement aspect was significantly positively correlated with the performance of early childhood education teachers. The work atmosphere aspect was not significantly correlated with the performance of early childhood education teachers. The job satisfaction aspect was significantly positively correlated with the performance of early childhood education teachers. The findings of this study imply that it is important for leaders of early childhood education institutions to provide reinforcement to teachers and implement school management that can create teacher satisfaction in an effort to improve the quality of early childhood education to support the development of superior human resources with global competitiveness.