This paper aims to analyze the narratives that have emerged in the process of bureaucratic reform in Indonesia. The analysis is conducted using the Narrative Policy Framework at the mesa level. Using data from articles published in 6 credible national media about “bureaucratic reform” from 2010 to 2023. The collected data was classified according to the Narrative Policy Framework (NPF) elements in the article: Issue setting, the cause of the issue, plot, character (villain, victim, hero), and recommendations for solutions offered. There were 31 articles analyzed. The result showed that the main plot in the process of bureaucratic reform in Indonesia is based on the corrupt bureaucracy and the slow public service provided. The victims in the plot are the people who will access the services. The villains of the narrative are civil servants who do not improve the required competencies. The heroes of the narrative are several government institutions (Ministry of State Apparatus Utilization and Bureaucratic Reform, Commission of Corruption Eradication, and The Audit Board of The Republic of Indonesia) that are considered to expose the problem.

Electrospinning nanofiber membrane has the advantages of wide raw materials, large specific surface area, and high porosity. It is an ideal separator material for lithium-ion batteries. This paper first introduces two common electrospinning nanofiber diaphragms: polymer, polymer, and inorganic composite, and then focuses on the modification methods of composite modification, blending modification, and inorganic modification, as well as the methods of electrospinning nano modified polyolefin diaphragm. Finally, the development direction of the electrospinning lithium-ion battery separator has prospected.

Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.

Farm households in developing countries are often involved in a variety of livelihood income-generating activities to achieve basic needs and enhance food security. However, little attention has been given to investigating the effect of livelihood diversification strategies on the adoption of agricultural land management practices. This study explored the nexus between livelihood diversification and Agricultural Land Management (ALM) practices in the Southern Ethiopian Highlands. Data for this study were gathered through a structured questionnaire, interviews, and focus group discussions. A total of 423 sample respondents were selected by using multistage random sampling techniques. The data were analyzed using the Inverse Herfindahl Hirschman Diversity Index (IHHDI), the multinomial logit model (MNL), and the probit regression model. The findings of the study revealed that on-farm income activities are the most dominant livelihood income strategies (69.1%), followed by non-farm (21%) and off-farm (9.64%). The multinomial logit model analysis demonstrated that variables such as sex, education, family size, distance to market, land size, extension contact, membership in cooperatives, and household income were the major drivers of farmers income diversification activities (p<0.05). The results of the probit analysis indicated that income from crop production, daily labor work, rents from farmland, and farm assets have a positive and significant effect on households' decisions to implement ALM practices. In contrast, incomes from remittance and migrant sources have a negative but statistically significant impact on the adoption of ALM measures. The farm household sources of income-generating strategies substantially affected the adoption intensity of ALM measures. Income generated from the on-farm sector alone cannot be considered a core income-generating activity for households or a means of achieving food security. Therefore, land management policies and program implementations should consider farmers’ livelihood diversification and income-generating strategies. In addition, such interventions need to promote sustainable farming practices, enhance innovation, and related measures for the adoption of ALM measures to ensure land sustainability.