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To achieve the resource utilization of garden waste, in this study, we used garden waste as the main raw material and conducted static composting with high-temperature aerobic treatment and forced ventilation by adding appropriate external additives. Our results showed that during the composting process, the pH was weakly alkaline, and the electrical conductivity was between 1.42 and 1.50 mS/cm. The E4/E6 (an important indicator of the quality or degree of condensation and aromatization of humic acid) gradually decreased, and nitrogen, phosphorus, and potassium contents increased. The germination index gradually rose and ultimately exceeded 80%. Treatment (T2) with a final C/N ratio of 25:1 and the addition of 0.3% bacterial agent resulted in the highest nutrient content and the best degree of compost maturity. All indicators met the requirements of the Chinese "Technical Requirements for Urban Landscape Waste Resource Recycling and Deep Processing (GB/T 40199-2021)". When using a composite substrate of garden waste and other horticultural substrates for planting, a membership function was executed for comprehensive evaluation. The V (T2):V (peat):V (vermiculite):V (vermiculite) = 135:135:30:00 substrate treatment resulted in optimal lettuce growth and quality. In summary, combining the compost products of garden waste with traditional cultivation substrates at a specific ratio shows favorable applicative prospects. [ABSTRACT FROM AUTHOR]

We report the experimental discovery of intrinsic ferromagnetism in Cr2Ge2Te6 atomic layers by scanning magneto-optic Kerr microscopy. In this 2D van der Waals ferromagnet, unprecedented control of transition temperature is realized via small magnetic fields.

Most of the traditional indoor positioning technologies need to lay hardware equipment in advance, which is expensive and difficult to apply to part of the space where additional equipment cannot be laid. In order to reduce equipment cost as much as possible and reduce preparation work, this paper proposes an indoor positioning technology that integrates deep learning and feature point recognition. This technology uses mobile devices such as mobile phones to obtain realtime video streams, and uses a convolutional neural network-based marker recognizer to identify markers in each frame of the video stream, so as to obtain its rough position and complete rough positioning. At the same time, the feature points are identified for each frame of mage in the video stream, and matched with the feature points with location information in the constructed environment feature information database, and their positions are calculated to complete fine positioning. The technology proposed in this paper is based entirely on mage identification, without relying on the laying of hardware equipment, and can be better applied to secret spaces. This paper has completed the program deployment of the proposed indoor positioning technology on the Andriod mobile device terminal. The experiments show that the proposed indoor positioning technology has high accuracy and stability. [ABSTRACT FROM AUTHOR]