Polydiacetylene (PDA)-based colorimetric sensors offer a promising platform for rapid and visual detection, through a chromatic transition from blue to red. However, their broader applications are hindered by challenges in sensitivity, selectivity, and stability. This review comprehensively overviews functionalization strategies to overcome existing limitations, including chemical modification with reactive groups, conjugation with specific ligands or receptors, and integration with nanomaterials. Alternative approaches are also discussed. The interplay between base materials, deposition methods, and functionalization efficiencies is emphasized. Furthermore, this review addresses remaining challenges, proposes feasible solutions, and offers insights into future strategic directions for creating more advanced PDA-based colorimetric sensors. Polydiacetylene (PDA)-based colorimetric sensors have potential for rapid visual detection. However, their broader application remains limited by issues of sensitivity, selectivity, and stability. Here, the authors review functionalization strategies to overcome existing limitations, including chemical modification with reactive groups, conjugation with specific ligands or receptors, and integration with nanomaterials.
Abstract The integration of Southeast Asia’s power systems has positioned Sumatra as a strategic hub in Indonesia’s cross-border electricity development. As outlined in the 2025–2034 Electricity Supply Business Plan (RUPTL), the island is expected to receive approximately 15.1 GW of new generating capacity, accounting for around 21.7 percent of Indonesia’s planned national additions. However, realizing this potential requires navigating geographic, regulatory, and socio-political complexities. This study applies the Analytic Hierarchy Process (AHP) to evaluate Sumatra’s development potential in power grid systems across North, Central, and South Sumatra with the ASEAN Power Grid South Sub-System. Preliminary AHP results highlight Central Sumatra as the most strategic region by 2030, supported by access to a projected interconnection capacity exceeding 2,130 MW through Sumatra–Malaysia–Singapore transmission routes and growing investor interest in provinces such as Riau and Jambi. Meanwhile, North Sumatra demonstrates higher infrastructure readiness with a 99.81 percent electrification rate as of Q3 2024 and a significant renewable energy contribution projected at around 35 percent. These findings offer a structured multi-criteria basis for infrastructure prioritization, aligning national development goals while solving oversupply issues through regional interoperability within the ASEAN Power Grid framework.
The sustainability of community empowerment programs remains a challenge when corporate assistance is limited to a defined period. Programs need not only to generate benefits for communities but also to learn from each implementation process to continuously evolve in response to community needs. The Kuwatan Sadesa Program of PT Pupuk Kujang applies the Participatory Action Research (PAR) approach through a cycle of problem identification, planning, implementation, monitoring, evaluation, and reflection, with Triple Loop Learning (TLL) serving as a reflection framework to identify problems, determine follow-up actions, and develop the program in subsequent cycles. In farmer capacity-building activities, findings related to time constraints and inappropriate learning methods encouraged a shift from classroom-based training to hands-on learning in the field, which was subsequently developed into a learning module. In activities utilizing spices for health promotion, the learning process developed into the provision of nutritious food and subsequently into the Child Healthy School program based on local food, involving community health volunteers. These changes demonstrate that monitoring and evaluation findings can serve as a basis for developing activities that are more responsive to community needs. The cycle of implementation, monitoring, reflection, development, and re-implementation forms a continuous learning process. This process is formulated as a Sustainable Learning Model, in which program implementation experiences become a source of knowledge for continuously improving and developing community empowerment in subsequent cycles
Bio-based composites are a promising substitute for fossil-based plastics and aim to reduce their negative environmental impact. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) is a bio-based and biodegradable thermoplastic whose properties are comparable to those of commonly used plastics, such as polypropylene (PP) and polyethylene (PE). In this study, we propose different blends of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with bio-based fillers and additives, including wood fibres, poly(butylene-co-adipate terephthalate) grafted with either maleic anhydride or glycidyl methacrylate and calcium carbonate as an alternative to fossil-based plastics. Fourier transform infrared spectroscopy results showed that no significant new bonds were formed. The X-ray scattering data revealed that the presence of additives did not significantly influence the crystallinity of the composites. In terms of thermal stability, the formulation containing the poly(butylene-co- adipate terephthalate) grafted with glycidyl methacrylate demonstrated increased degradation temperature which was reduced by the presence of wood in the blends. Additionally, this formulation presented the highest melting temperature of 175.1 °C. Mechanical properties were decreased with the addition of wood fibres, in terms of tensile strength and elongation at break but increased in terms of Young modulus for all composites containing wood. The functionalisation of the wood with tannic acid and iron resulted in improved elongation at break (3.78 ± 0.14
The data presented here derives from the Sustainable Working Conditions in Academia survey (STAIRCASE) on researcher mental health. The survey addresses the ongoing mental health crisis in academia by providing comprehensive, multilevel data on researcher well-being and its structural determinants. We employed a cross-sectional between-participant study design to collect data from 4,296 researchers between September 15, 2023, and August 26, 2024. The sample, which primarily includes researchers based in European countries, has a mean age of 38.1 years (SD = 10.7) and consists of 63.7% female participants. Participants provided data on key mental health outcomes – including depression, anxiety, stress, burnout, and well-being – alongside detailed assessments of working conditions, leadership behavior, and organizational characteristics. The dataset facilitates a holistic, multilevel investigation of academic mental health beyond individual risk factors by including the individual, leadership, institutional, and national context. By enabling analyses across hierarchical levels this dataset provides the necessary evidence to identify systemic drivers of mental (ill) health and inform the development of effective, system-wide strategies for meaningful change in academic work environments.
