Mapping the potential of groundwater is important for managing water resources in a way that will last, especially when the climate changes, land use changes, and water demand rise. This study examines the integration of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) methodologies, focusing on the Analytical Hierarchy Process (AHP), and illustrates their implementation in the Fork Fish Creek watershed, a humid Appalachian headwater basin in West Virginia, USA. Although GIS–AHP methodologies are extensively utilized in semi-arid areas, their efficacy in humid, structurally intricate mountainous environments is still inadequately investigated. Using expert-based AHP weighting and GIS-based weighted overlay analysis, six thematic parameters were combined: rainfall, geology and soil characteristics, slope, drainage density, land use and land cover (LULC), and lineament density. The appropriate AHP consistency ratio (<0.1) showed that the weights were reliable. The resulting groundwater potential map divided the watershed into three zones: Good (6.7%), Moderate (76.5%), and Low (16.8%). The prevalence of Moderate potential indicates the impact of fragmented topography and drainage configuration, which limit groundwater storage despite sufficient precipitation. Validation encompassed an evaluation of hydrogeomorphic consistency and an additional comparison with USGS monitoring-well depth data, so offering empirical corroboration for the Moderate-dominated distribution. The results show that groundwater potential patterns vary greatly from one place to the next. They also show how useful GIS–MCDA frameworks may be for assessing groundwater in humid, data-poor mountainous areas.
AI-based conversational agents are increasingly used for emotional support, companionship, and day-to-day coping. These systems can provide immediate reassurance, reduce distress in the moment, and offer a low-barrier channel for reflection. At the same time, concerns are growing that frequent reliance on AI companions may displace human relationships and narrow users’ exposure to the interpersonal friction that supports psychological growth. This narrative review synthesizes conceptual and empirical themes to explain how AI companion chatbot use may relate to loneliness and depressive symptoms across the lifespan. We propose a developmental framework distinguishing supportive pathways (e.g., perceived availability, emotion regulation scaffolding, and social activation) from risk pathways (e.g., social displacement, dependency, avoidance coping, and affirmation-biased feedback loops). A central contribution is a lifespan account of how positive-only or preference-aligned feedback may undermine constructive stress appraisal, frustration tolerance, resilience, and grit—capacities that are built through repeated experiences of manageable challenge, honest feedback, and relationship repair. We conclude with implications for practice, education, and design, emphasizing developmental tailoring, safeguards against over-reliance, and research priorities needed to clarify causal mechanisms and long-term outcomes.
The rural region of the municipality of Bananal (SP, Brazil) experiences recurrent flooding events associated with rising water levels in tributaries of the Bananal River, especially during periods of intense rainfall. This study aimed to compare the performance of different Digital Elevation Models (DEMs), one derived from NASA orbital data and another generated from drone-based aerophotogrammetric surveys, in identifying and mapping flood-prone areas. The objective was to assess whether drone field campaigns are essential for this type of analysis or whether orbital DEMs are sufficient for the hydrodynamic characterization of the area. Hydrodynamic models were developed using the software QGIS, HidroFlu—for watershed parametrization and inflow estimation, and MODCEL—for hydrodynamic simulation, with spatial resolutions of 10 m, 30 m, and 50 m, in order to analyze the impact of topographic detail on simulation results. Two approaches were tested for defining boundary conditions: one based on precipitation data with a 25-year return period, and another based on the Bananal River discharge estimated from the watershed. The results indicated that the model based on the drone-derived DEM, with 10 m resolution and boundary conditions defined by river discharge, showed the best performance in representing floodable areas. However, the findings also highlight that high-resolution DEMs entail higher operational costs, due to the need for field activities and greater computational capacity to run the simulations.
Stereolithography 3D printing technology is widely used in aerospace, automotive, medical, weapons, and other fields because of its high processing accuracy, low cost, simple operation, and flexible manufacturing. The photocuring 3D printing ceramic slurry is a key part of the photocuring 3D printing ceramic technology. The preparation techniques of photocurable 3D printing ceramic slurry mainly include the mechanical mixing method, sol-gel method, ultrasonic dispersion method, and in-situ polymerization method. This paper summarizes the preparation methods and research progress of photocuring 3D printing ceramic slurry, expounds the essence of photocuring and the composition and function of ceramic slurry, and analyzes the influence of various properties of photocuring 3D printing ceramic slurry on the properties of final products, such as rheological properties, solid content, curing thickness, and stability. Finally, the existing problems and future development potential of photocuring 3D printing ceramic slurry preparation technology are summarized.
Porous ceramic filters exhibit excellent prospects for application in the field of high-temperature flue gas filtration. In this study, the MgAl2O4 porous ceramics were prepared using α-Al2O3, MgO, and EDTA-MgNa2 as raw materials by the in-situ decomposition method. The effect of the introduction of EDTA-MgNa2 on phase composition and microstructure, as well as the correlation between the content of EDTA-MgNa2 and ceramic properties, was investigated using XRD, SEM, and EDS. The results revealed that the introduction of EDTA-MgNa2 formed pores, thereby improving gas permeability. Additionally, the addition of EDTA-MgNa2 was beneficial for the formation of a transitional liquid and promoted sintering, thereby slowing the decrease in compressive strength. The optimal specimen is the ceramic with 10 wt% EDTA-MgNa2, which exhibits a high porosity of 56.28%, a compressive strength of 10.93 MPa, and a high gas permeability coefficient (8.84 × 10−9 m2).
