In this study, the influence of sewage sludge ash (SSA) waste particle contents on the mechanical properties and interlaminar fracture toughness for mode I and mode II delamination of S-glass fiber-reinforced epoxy composites was investigated. Composite laminate specimens for tensile, flexural double-cantilever beam (DCB), and end-notched fracture (ENF) tests were prepared and tested according to ASTM standards with 5, 10, 15, and 20 wt% SSA-filled S-glass/epoxy composites. Property improvement reasons were explained based on optical and scanning electron microscopy. The highest improvement in tensile and flexural strength was obtained with a 10 wt% content of SSA. The highest mode I and mode II interlaminar fracture toughness’s were obtained with 15 wt% content of SSA. The mode I and mode II interlaminar fracture toughness improved by 33% and 63.6%, respectively, compared to the composite without SSA.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.

The micro staring hyperspectral imager can simultaneously acquire two spatial and one spectral images, and only record the external orientation elements of the entire hyperspectral image rather than the external orientation elements of each frame of the image, which avoids the geometric instability during scanning, effectively solves the problem of large geometric deformation of the small line scanning hyperspectral imager, and is suitable for the small UAV load platform with unstable attitude. At present, most of the research focuses on the radio-metric correction method of line scan hyperspectral imager. The application time of staring hyperspectral imager is short, and there is no mature data processing re-search at home and abroad, which hinders the application of UAV micro staring hyperspectral imaging system. In this paper, the calibration method of the linearity and variability of the radiation response of the micro staring hyperspectral imager on the UAV is studied, and the effectiveness of this method is quantitatively evaluated. The results show that the hyperspectral image has obvious vignetting effect and strip phenomenon before the correction of radiation response variability. After the correction, the radiation response variation coefficient of pixels in different bands decreases significantly, and the vignetting effect and image strip decrease significantly. In this paper, a multi-target radiometric calibration method is proposed, and the accuracy of radiometric calibration is verified by comparing the calibrated hyperspectral image spectrum with the measured ground object spectrum of the ground spectrometer. The results show that the calibration results of the multi-target radiometric calibration method show better results, especially for the near-infrared band, and the difference with the surface reflectance measured by the spectrometer is small.

This paper aims to investigate the factors of competitive success and examine the relationship between Strategic Management Accounting, management accounting information systems and sustainability performance. This research was conducted with a quantitative approach. The survey involved 125 managers of 4- and 5-star hotels in Bali, Indonesia, a research sample of 154 managers was determined to be given a research questionnaire. Analysis of research data was carried out through Structural Equation Modeling. The results showed that strategic management accounting and Information Management Accounting System had a positive effect on sustainability performance. MAS information also mediates the relationship between strategic management accounting and sustainability performance which can involve a variety of factors. This study only focuses on competitive strategy and MAS information variables, so further research is needed on the sustainability performance of the hospitality industry. The positive relationship between strategic management accounting and social and environmental performance supports the argument that hotels use socio-environmental aspects for their strategic management accounting. Hotel managers also need government regulations and information related to social and environmental issues such as the Indonesian occupational health and safety management system and the Indonesia Green Hotel Award.

Language is fundamental to human communication, allowing individuals to express and exchange ideas, thoughts, and emotions. In early childhood, some children experience communication disorders that impede their ability to articulate words correctly, posing significant challenges to their learning and development. This issue is exacerbated in developing countries, where limited resources and a lack of technological tools hinder access to effective speech therapy. Traditional speech therapy remains vital, but the latest technological advancements have introduced robotic assistants to enhance therapy for communication disorders. Despite their potential, these technologies are often inaccessible in developing regions due to high production costs and a lack of sustainable manufacturing models. For these reasons, this paper presents “FONA,” a robotic assistant that employs rule-based expert systems to provide tactile, auditory, and visual stimuli. FONA supports children aged 3 to 6 in speech therapy by delivering exercises such as syllable production, word formation, and pictographic storytelling of various phonemes. Notably, FONA was successfully tested on children with cochlear implants, reducing the number of sessions required to produce isolated phonemes. The paper also introduces an innovative analysis of the Make To Order (MTO) manufacturing system for producing FONA in developing countries. This analysis explores two key perspectives: collaborative networks and entrepreneurship, offering a sustainable production model. In a pilot experiment, FONA significantly improved children’s attention spans, increasing the period by 17 min. Furthermore, the economic analysis demonstrates that producing FONA through collaborative networks can significantly reduce costs, making it more accessible to institutions in developing countries. The findings suggest that the project is viable for a five-year period, providing a sustainable and effective solution for addressing communication disorders in children.