Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.

Problem: in recent years, new studies have been published on biological effects of strong static magnetic fields and on thermal effects of high-frequency electromagnetic fields as used in magnetic resonance imaging (MRI). Many of these studies have not yet been incorporated into current safety recommendations. Method: scientific publications from 2010 onwards on the biological effects of static and electromagnetic fields of MRI were searched and evaluated. Results: new studies confirm older work that has already described effects of static magnetic fields on sensory organs and the central nervous system accompanied by sensory perception. A new result is the direct effect of Lorentz forces on ionic currents in the semicircular canals of the vestibular organ. Recent studies on thermal effects of radiofrequency fields focused on the development of anatomically realistic body models and more accurate simulation of exposure scenarios. Recommendation for practice: strong static magnetic fields can cause unpleasant perceptions, especially dizziness. In addition, they can impair the performance of the medical personnel and thus potentially endanger patient safety. As a precaution, medical personnel should move slowly in the field gradient. High-frequency electromagnetic fields cause tissues and organs to heat up in patients. This must be taken into account in particular for patients with impaired thermoregulation as well as for pregnant women and newborns; exposure in these cases must be kept as low as possible.

This study aims to examine the pathways through which the user experience (UX) of ChatGPT, a representative of generative artificial intelligence, affects user loyalty. Additionally, it seeks to verify whether ChatGPT’s UX varies according to a user’s need for cognition (NFC). This research proposed and examined how ChatGPT’ UX affect user engagement and loyalty and used mediation analysis using PROCESS Macro Model 6 to test the impact of UX on web-based ChatGPT loyalty. Data were collected by an online marketing research company. 200 respondents were selected from a panel of individuals who had used ChatGPT within the previous month. Prior to the survey, the study objective was explained to the respondents, who were instructed to answer questions based on their experiences with ChatGPT during the previous month. The usefulness of ChatGPT was found to have a significant impact on interactivity, engagement, and intention to reuse. Second, it was revealed that evaluations of ChatGPT may vary according to users’ cognitive needs. Users with a high NFC, who seek to solve complex problems and pursue new experiences, perceived ChatGPT’s usefulness, interactivity, engagement, and reuse intentions more positively than those with a lower NFC. These results have several academic implications. First, this study validated the role of the UX in ChatGPT. Second, it validated the role of users’ need for cognition levels in their experience with ChatGPT.

This study empirically examines the complex relationship between materialism and economic motivation, proposing an inverted U-shaped relationship. The research analyzes three dimensions of materialism: happiness pursuit, social recognition, and uniqueness, and their impact on economic motivation. The findings suggest that materialism, when balanced, positively influences economic motivation without causing adverse effects. This relationship remains consistent across demographic characteristics and life satisfaction levels, challenging the traditional negative view of materialism. The implications of these findings extend to marketing strategies, policy design, and infrastructure development, offering actionable insights for real-world contexts. This research underscores the importance of balancing materialistic values to foster sustainable economic growth and well-being.

This paper conducts a comparative analysis of mentoring and metacognition in education, unveiling their intricate connections. Both concepts, though seemingly disparate, prove to be interdependent within the educational landscape. The analysis showcases the dynamic interplay between mentoring and metacognition, emphasizing their reciprocal influence. Metacognition, often perceived as self-awareness and introspection, is found to complement the relational and supportive nature of mentoring. Within this context, metacognitive education within mentoring emerges as a vital component. Practical recommendations are offered for effective metacognitive training, highlighting its role in enhancing cognitive and metacognitive skills. Moreover, the paper introduces the concept of a “mentoring scaffolding system.” This system emphasizes mentor-led gradual independence for mentees, facilitating their professional and personal growth. The necessity of fostering a metacognition culture in education is a central theme. Such a culture promotes improved performance and lifelong learning. The paper suggests integrating metacognition into curricula and empowering learners as essential steps toward achieving this culture. In conclusion, this paper advocates for the integration of metacognition into mentoring and education, fostering self-awareness, independence, and adaptability. These attributes are deemed crucial for individuals navigating the challenges of the information age.

Background: Multiple sclerosis is often a longitudinal disease continuum with an initial relapsing-remitting phase (RRMS) and later secondary progression (SPMS). Most currently approved therapies are not sufficiently effective in SPMS. Early detection of SPMS conversion is therefore critical for therapy selection. Important decision-making tools may include testing of partial cognitive performance and magnetic resonance imaging (MRI). Aim of the work: To demonstrate the importance of cognitive testing and MRI for the prediction and detection of SPMS conversion. Elaboration of strategies for follow-up and therapy management in practice, especially in outpatient care. Material and methods: Review based on an unsystematic literature search. Results: Standardized cognitive testing can be helpful for early SPMS diagnosis and facilitate progression assessment. Annual use of sensitive screening tests such as Symbol Digit Modalities Test (SDMT) and Brief Visual Memory Test-Revised (BVMT-R) or the Brief International Cognitive Assessment for MS (BICAMS) test battery is recommended. Persistent inflammatory activity on MRI in the first three years of disease and the presence of cortical lesions are predictive of SPMS conversion. Standardized MRI monitoring for features of progressive MS can support clinically and neurocognitively based suspicion of SPMS. Discussion: Interdisciplinary care of MS patients by clinically skilled neurologists, supported by neuropsychological testing and MRI, has a high value for SPMS prediction and diagnosis. The latter allows early conversion to appropriate therapies, as SPMS requires different interventions than RRMS. After drug switching, clinical, neuropsychological, and imaging vigilance allows stringent monitoring for neuroinflammatory and degenerative activity as well as treatment complications.