Application of high-dimensional uniform manifold approximation and projection (UMAP) to cluster existing landfills on the basis of geographical and environmental features.

Due to extreme conditions, which are influenced by the location of landfills, the release of pollutants has been recently proven to be more severe in estuary landfills, as these landfill locations are affected by both sea-water and river-water interactions. To identify geographic and environmental features linked to the extreme conditions of certain landfills, a high-dimensional clustering method combining Uniform Manifold Approximation and Projection (UMAP) with the Louvain algorithm is proposed. A case study was conducted using 17 noteworthy features that transform to Landfill Suitability Index (LSI) applied to hundreds of landfill sites in Taiwan. This study clustered landfills into 10 clusters and identified several clusters with significant extreme locations, including estuary landfills (7.9 %), fault-water-body landfills (8.2 %), and densely-populated-water-body landfills (17.6 %). Furthermore, a critical discovery of endangered Platalea minor habitats near these estuary landfills was made. Additionally, this work identified "healthy" landfills (11.2 %) that are minimally affected by the considered features. These findings demonstrate the promising potential of our framework for managers to systematically improve landfill management strategies. Moreover, our framework was tested by incorporating rainfall and flooding features in relation to climate change scenarios. To address the demand for land release from occupied landfills in Taiwan, there is a pressing need to expedite the transition to a circular economy, and our framework can provide further assistance in this regard. This approach is promising, as it provides a new method to evaluate the environmental risks linked to landfills and also identifies potential opportunities related to landfill mining. Finally, this work was extended to include a case study in England, which has 19,801 landfills and a dataset containing 15 relevant landfill features; in this case study, our framework identified 110 landfill clusters, and several placed in extreme locations, demonstrating that our framework is flexible for use in other regions outside of Taiwan.

Using Smartphones to Locate Trapped Victims in Disasters.

Large and unaccounted numbers of victims in disasters, events, or fires are often trapped in buildings or debris, and must be located and rescued as soon as possible. This study transforms smartphones into indoor locating tools without extra modification or complicated program installation, considering smartphones are likely to be carried when disasters strike. The study creates a system that converts smartphones into a lifesaving tool for trapped victims and rescuers. This study employs the Bluetooth beacon in smartphones to send signals using its low power consumption feature. The signal could continue transmitting for rescuers to locate trapped victims for longer. Rescuers could use the Bluetooth function on a regular notebook computer to search such signals without any hardware implementation or modification, allowing them to locate and determine the position of many trapped victims simultaneously. Implementing this system will decrease the search and rescue team's need to enter unsafe areas and increase their rescue speed, a critical factor for the survival of trapped victims. Furthermore, when disasters strike, the smartphone calling function might not work, and the trapped victim might be too weak to call for help. Thus, autoreply messages from victims' smartphones could help them be located within a 2-m error, even if covered by fallen debris such as wood piles or tiles. This effort will increase the chance of finding trapped victims within the golden rescue hours and reduce the exposure time of search and rescue teams in unsafe environments.

A facile wet-chemistry approach to engineer an Au-based SERS substrate and enhance sensitivity down to ppb-level detection.

A two-dimensional flexible surface-enhanced Raman scattering (SERS) filter substrate provides an alternative strategy for the highly sensitive portable detection of various toxic molecules and biomaterials. Herein, we developed a solid-liquid interfacial reduction reaction to post-engineer a solid Au nanostructure surface on filter paper to improve the SERS effect. Among four reductants (ascorbic acid, l-dopamine, hydroquinone (HQ), and formaldehyde), HQ possessed a larger oxidation overpotential and facilitated homogeneous growth, forming small Au branch-structure nanoparticles from HAuCl4 solution. Due to the surface effect by exposing abundant -OH groups and intrinsic aromatic rings from TNA/HQ on nano-gold, the SERS effect on positively charged analytes near the plasmonic Au surface was enhanced, while forming a protective layer against severe water interruption. The resulting SERS substrate with branched nano-gold provided several SERS-enhanced sites, increased the enhancement by more than 6 times compared to original SERS sensing, and displayed a 1.4-7.4 × 105 analytical enhancement factor, which leads to a limit of detection down to several ppb. Less than 6% of deviation in the SERS intensity at different sensing sites was observed. We successfully improved the primary SERS substrate using a high overpotential reductant. Owing to its soft and flexible properties, the paper-based SERS substrate can be used conveniently in different sizes, pasting on curved materials, detecting additives in fish, and preventing the coffee-ring effect, showing high practicality and potential commercial value in the future.