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Background Gestational diabetes mellitus (GDM) can increase the risk of adverse outcomes for both mothers and infants. Preventive interventions can effectively assist pregnant women suffering from GDM. At present, pregnant women are unaware of the importance of preventing GDM, and they possess a low level of self-management ability. Recently, mHealth technology has been used worldwide. Therefore, developing a mobile health app for GDM prevention could potentially help pregnant women reduce the risk of GDM. Objective To design and develop a mobile application, evaluate its acceptance, and understand the users’using experience and suggestions, thus providing a valid tool to assist pregnant women at risk of GDM in enhancing their self-management ability and preventing GDM. Methods An evidence-based GDM prevent app ( Better pregnancy ) was developed using user-centered design methods, following the health belief model, and incorporating GDM risk prediction. A convenient sampling method was employed from June to August 2022 to select 102 pregnant women at risk of GDM for the pilot study. After a week, the app's acceptability was evaluated using an application acceptance questionnaire, and we updated the app based on the feedback from the women. We used SPSS 26.0 for data analysis. Results The application offers various functionalities, including GDM risk prediction, health management plan, behavior management, health information, personalized guidance and consultation, peer support, family support, and other functions. In total, 102 pregnant women consented to participate in the study, achieving a retention rate of 98%; however, 2% ( n = 2) withdrew. The Better pregnancy app's average acceptability score is 4.07 out of 5. Additionally, participants offered several suggestions aimed at enhancing the application. Conclusions The Better pregnancy app developed in this study can serve as an auxiliary management tool for the prevention of GDM, providing a foundation for subsequent randomized controlled trials.

The integrated water systems (IWSs) concept involves managing water quantity and quality through dynamic interactions. This paper reviews the terrestrial water cycle, focusing on resilience and adaptive planning (AP) approaches within IWSs. We examine how integrating these approaches can improve IWS management and planning, addressing their inherent complexities. Using a performance-based resilience definition, we consider the system’s ability to absorb, recover from and adapt to adverse events. The AP focuses on flexible management pathways for uncertain future conditions. Although both resilience and AP aim to enhance water system performance and address uncertainties, they differ in their assessment and implementation approaches. We propose an Adaptive Resilience Planning (ARP) framework that merges both approaches. The ARP uses resilience metrics for performance assessment and incorporates AP’s methods for conceptualising uncertainties and optimising management portfolios. Implementing the ARP framework raises four research questions: (1) holistic characterisation of uncertainties and options in IWSs, (2) using resilience metrics for IWS adaptation, (3) balancing trade-offs among management goals through optimal portfolio selection and (4) monitoring portfolio performance and uncertainties for informed adaptation. The ARP framework offers a structured method for dynamic and adaptive resilience planning, enhancing IWS management’s responsiveness to evolving challenges.

In recent years, the biosensor research community has made rapid progress in the development of nanostructured materials capable of amplifying the interaction between light and biological matter. A common objective is to concentrate the electromagnetic energy associated with light into nanometer-scale volumes that, in many cases, can extend below the conventional Abbé diffraction limit. Dating back to the first application of surface plasmon resonance (SPR) for label-free detection of biomolecular interactions, resonant optical structures, including waveguides, ring resonators, and photonic crystals, have proven to be effective conduits for a wide range of optical enhancement effects that include enhanced excitation of photon emitters (such as quantum dots, organic dyes, and fluorescent proteins), enhanced extraction from photon emitters, enhanced optical absorption, and enhanced optical scattering (such as from Raman-scatterers and nanoparticles). The application of photonic metamaterials as a means for enhancing contrast in microscopy is a recent technological development. Through their ability to generate surface-localized and resonantly enhanced electromagnetic fields, photonic metamaterials are an effective surface for magnifying absorption, photon emission, and scattering associated with biological materials while an imaging system records spatial and temporal patterns. By replacing the conventional glass microscope slide with a photonic metamaterial, new forms of contrast and enhanced signal-to-noise are obtained for applications that include cancer diagnostics, infectious disease diagnostics, cell membrane imaging, biomolecular interaction analysis, and drug discovery. This paper will review the current state of the art in which photonic metamaterial surfaces are utilized in the context of microscopy.

Problems of water system integration occur when a model's boundaries are too narrow to capture interactions and feedbacks across the water cycle. We propose that integrated water systems models are required to overcome them, and are necessary to understand emergent system behaviour, to expand model boundaries, to evaluate interventions, and to ensure simulations reflect stakeholder goals. We present the Water Systems Integrated Modelling Framework (WSIMOD) software as one such approach and describe its theoretical basis, covering the node and arc nature of simulations, the integration framework that enables communication between model elements, and the model orchestration to customise interactions. We highlight data requirements for creating such a model and the potential for future development and refinement. WSIMOD offers a flexible and powerful approach to represent water systems, and we hope it will encourage further research and application into using model integration towards achieving sustainable and resilient water management. [ABSTRACT FROM AUTHOR]