BiFeO₃-CoFe₂O₄ (BFO-CFO) vertically aligned nanocomposite (VAN) thin-film promises great potentials for next-generation electronic devices. Its strong magnetoelectric, antiferromagnetic-ferrimagnetic, and structural couplings occur via large interface area interactions across the vertical surface between BFO and CFO phases; this leads to emergent exotic fundamental physics rendering its potential applications for various electronics, such as magnetic sensor, data storages or memory devices, and energy harvesting devices. The distinctive photoactivity of both BFO and CFO phases in the BFO-CFO VAN system also can generate advanced applications as photovoltaic and photocatalytic devices. Furthermore, owing to small overpotential and excellent stability in alkaline media, BFO-CFO nanocomposites becomes the next electrode in electrocatalysis devices. The BFO-CFO VAN also have been exponentially developed having various type of thin-film architectures grown on various substrates. In this present article, we review the current status of the BFO-CFO VAN thin-film and discuss the fundamental understanding as well as the technology involved in developing this material. We also address the challenges that hinder the commercialization of this material and propose some plausible solutions to encourage BFO-CFO VAN-based electronic devices to reach their maturity level. Furthermore, the potential marketability of the BFO-CFO VAN materials and devices for future consumer products is also discussed.

Background and Objective Increases in outpatients seeking medical check-ups are expanding the number of health examination data records, which can be utilized for medical strategic planning and other purposes. However, because hospital visits by outpatients seeking medical check-ups are unpredictable, those patients often cannot receive optimal service due to limited facilities of hospitals. To resolve this problem, this study attempted to predict re-visit patterns of outpatients. Method Two-phase sequential pattern mining (SPM) and an association mining method were chosen to predict patient returns using sequential data. The data were grouped according to the outpatients’ personal information and evaluated by a discriminant analysis to check the significance of the grouping. Furthermore, SPM was employed to generate frequency patterns from each group and extract a general association pattern of return. Results Results of sequence patterns and association mining in this study provided valuable insights in terms of outpatients’ re-visit behaviors for regular medical check-ups. Cosine and Jaccard are two symmetric measures which were used in this study to indicate the degree of association between two variables. For instance, Jaccard values of variable abnormal blood pressure associated with an abnormal body-mass index (BMI) and/or abnormal blood sugar were respectively 47.5% and 100%, for the two-visit and three-visit behavior patterns. These results indicated that the corresponding pair of variables was more reliable when covering the three-visit behavior pattern than the two-visit behavior. Thus, appropriate preventive measures or suggestions for other medical treatments can be prepared for outpatients that have this pattern on their third visit. The higher degree of association implies that the corresponding behavior pattern might influence outpatients’ intentions to regularly seek medical check-ups concerning the risk of stroke. Furthermore, a radiology diagnosis (i.e., magnetic resonance imaging or neck vascular ultrasound) plays an important role in the association with a re-visit behavior pattern with respective 50% and 70% Cosine and Jaccard values in general behavior {f11}∧{f01}. These findings can serve as valuable information to increase the quality of medical services and marketing, by suggesting appropriate treatment for the subsequent visit after learning the behavior patterns. Conclusions The proposed method can provide valuable information related to outpatients’ re-visit behavior patterns based on hidden knowledge generated from sequential patterns and association mining results. For marketing purposes, medical practitioners can take behavior patterns studied in this paper into account to raise patients’ awareness of several possible medical conditions that might arise on subsequent visits and encourage them to take preventive measures or suggest other medical treatments.

The aim of this study was to investigate the potential of upcycling Expanded Polystyrene (EPS) waste collected from food packaging into a membrane for microalgae harvesting, in which membrane filtration often challenges fouling and pore blocking. The target species is Spirulina platensis, with Chlorella vulgaris as a comparison agent. The membrane was fabricated from used Styrofoam, which typically ends up as single-use food packaging waste. In this study, PVP was used as an additive at varying concentrations, from 2 wt.% to 8 wt.%. The experimental results indicated that despite varying PVP concentrations, all EPS waste membranes exhibited near-complete recovery of Spirulina platensis biomass extraction. Despite the similar harvesting efficiency, EPS/PVP-8 exhibited the largest flux of 970.5 LMH/Bar, which is twice the value of the pristine EPS waste membrane. All membranes were hydrophilic; however, hydrophobicity increased with PVP concentration. SEM micrographs revealed that PVP enlarged the membrane surface pores and improved connectivity within the membrane’s structure, ensuring efficient flow. The EPS waste membrane offers promising insights for sustainable materials and wastewater treatment. The upcycling of EPS waste into flat sheet membranes not only addresses the problem of Styrofoam waste accumulation but also paves the way to transform waste into valuable products.

Improving learning strategies through digital technology could contribute to educational enhancement. Concept mapping, as one example of prevailing learning strategies, has been known to be effective in supporting learning and teaching. Previous studies have demonstrated how concept maps could benefit learning. Despite the positive effects of concept maps and concept mapping on students’ learning performance, several studies have suggested that students struggled to enhance their understanding through concept map composition due to a lack of relevant understanding and prior knowledge of a particular learning topic. The role of the teacher as instructor remains important to exploit the potential of concept maps in their teaching and learning activities optimally. Thus, expect improvement in the students’ learning performance. This study reviewed how Kit-Build as a learning strategy could help students improve their understanding through the concept map recomposition activity. An in-lecture experiment with undergraduate students was conducted to experience several learning strategies as an activity to support their learning during the class. According to their acquaintances, the benefits and drawbacks of using Kit-Build and other strategies were investigated. The results suggested that Kit-Build concept map is the preferred learning strategy to support efficient and meaningful learning for students.