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Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region's meteorological bureau's weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns. [ABSTRACT FROM AUTHOR]

Although salinity stress is one of the principal abiotic stresses affecting crop yield, a suitable concentration of NaCl has proven to be useful for increasing crop quality. This study used low salinity (34 mmol/L NaCl) and high salinity (85 mmol/L) to cultivate purple sweetpotato. Using transcriptomics and metabolomics to profile the pathway indicated that glycometabolism, secondary metabolite biosynthesis and the starch catabolic process were the significant pathways under the salinity stress. Further research showed that purple sweetpotato could regulate genes related to the regulation of the cellular Na+, K+, and other ions concentration in response to the low salinity tolerance, but loses this ability under high salinity. Meanwhile, under low salinity, the activity of antioxidant enzymes and their related gene expression are maintained at a high level. The low salinity influences the monosaccharide composition as well as the content and regulation of genes related to starch synthesis. Quality analysis showed that the low salinity could increase the starch content and influence the amylopectin biosynthesis. It suggested that low salinity promotes substance accumulation. High salinity could increase the anthocyanins biosynthesis and low salinity had a significant impact on phenolic acid and flavonol. Finally, the gene expression levels also prove the low salinity could change the composition and content level of the purple sweetpotato. This study showed that an appropriate concentration of NaCl can be used as an elicitor for application in purple sweetpotato planting. [ABSTRACT FROM AUTHOR]

A variety of chemical sensing materials and procedures for conveniently detecting mercuric ion (II) (Hg2+) have been extensively explored. The detection challenges for accomplishing a simple, fast, and low investment procedure at the ultrasensitive level are ongoing. Herein we report a quadrillionth level for detecting Hg2+ by the surface-enhanced Raman scattering (SERS) technique. There is an interaction of silver nanoparticles decorated on a zinc-oxide tetrapod structure and coated on FTO glass (Ag@ZnO-FTO) with an organic ligand. 4,4′-Dipyridyl (DPy) performed as being chemisorbed by Ag nanoparticles interacting with a pyridine ring to produce plasmonic hot spots for SERS. The morphology of the surface and porous structure of the tetrapod becomes the powerful platform for enhanced SERS performance of DPy detection. In the absence of the augmentative electrolyte, the enhancement factor for DPy is more than 107. The inhibiting of the aggregation between Ag and DPy was present following the appearance of Hg2+, demonstrated by the quenching of the SERS signal from the DPy molecules. The capability to reproduce and the selectivity of the sensing by DPy were both demonstrated. In addition, the applications for detecting Hg2+ in natural water and beverages were successfully detected. These results demonstrated the SERS sensors had the potential for detecting Hg2+ in practical use. [ABSTRACT FROM AUTHOR]