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Alzheimer's diseases (AD) patients suffer from more serious bone loss than cognitively normal subjects at the same age. Type H blood vessels were tightly associated with bone homeostasis. However, few studies have concentrated on bone vascular alteration and its role in AD‐related bone loss. In this study, APP/PS1 mice (4‐ and 8‐month‐old) and age‐matched wild‐type mice were used to assess the bone vascular alteration and its role in AD‐related bone loss. Transmission electron microscopy, immunofluorescence staining and iGPS 1.0 software database were utilized to investigate the molecular mechanism. Mitochondrial division inhibitor (Mdivi‐1) and GSK‐3β inhibitor (LiCl) were used to rescue type H blood vessels injury and verify the molecular mechanism. Our results revealed that APP/PS1 mice exhibited more serious bone blood vessels injury and bone loss during ageing. The bone blood vessel injury, especially in type H blood vessels, was accompanied by impaired vascularized osteogenesis in APP/PS1 mice. Further exploration indicated that beta‐amyloid (Aβ) promoted the apoptosis of vascular endothelial cells (ECs) and resulted in type H blood vessels injury. Mechanistically, Aβ‐induced excessive mitochondrial fission was found to be essential for the apoptosis of ECs. GSK‐3β was identified as a key regulatory target of Aβ‐induced excessive mitochondrial fission and bone loss. The findings delineated that Aβ‐induced excessive mitochondrial fission drives type H blood vessels injury, leading to aggravate bone loss in APP/PS1 mice and GSK‐3β inhibitor emerges as a potential therapeutic strategy. [ABSTRACT FROM AUTHOR]

With the acceleration of the new generation of information technology innovation, the economy and society are showing important new features of digital transformation, and the digital transformation of the emergency management system, which is an important part of the economy and society and the concentrated expression of national governance capabilities, is on the agenda. This article follows the objective laws of technological industry transformation, based on the theoretical paradigm of technical and economic management, tries to portray the characteristics of modern emergency management systems, constructs a technical system and proposes a policy path to promote digital transformation of emergency management systems. Research shows that the current digital transformation technology system and technical capabilities are becoming more and more perfect, and the emergency management system needs digital transformation. It is facing the construction of an emergency management digital transformation technology system covering the three levels of technology, platform and management. It is an important task to promote the balanced development of the physical world and social systems, platform support and management decision-making, technological innovation and integrated applications. To this end, it is recommended that in the process of subsequent emergency management policy design and the formulation of the “14th Five-Year Plan”, it is necessary to strengthen the digital upgrade of emergency management infrastructure, consolidate the foundation of the digital platform for emergency management, and strengthen the integrated application of digital technology in emergency management practices.

Sentiment analysis refers to the use of computers to automatically analyze and determine the emotions that people want to express. It can play a significant role in human-computer interaction and criminal investigation and solving cases. The advancement of deep learning and traditional feature extraction algorithms provides conditions for the use of multiple modalities for sentiment analysis. Combining multiple modalities for sentiment analysis can make up for the instability and limitations of single-modal sentiment analysis, and can effectively improve accuracy. In recent years, researchers have used three modalities of facial expression information, text information, and voice information to perform sentiment analysis. This paper mainly summarizes the multi-modal sentiment analysis technology from these three modalities. Firstly, it briefly introduces the basic concepts and research status of multi-modal sentiment analysis. Secondly, it summarizes the commonly used multi-modal sentiment analysis datasets. It gives a brief description of the existing single-modal emotion analysis technology based on facial expression information, text information and voice information. Next, the modal fusion technology is introduced in detail, and the existing results of the multi-modal sentiment analysis technology are mainly described according to different modal fusion methods. Finally, it discusses the problems of multi-modal sentiment analysis and future development direction.

To understand the pipeline leakage characteristics of the large-scale main gas drainage system in coal mines and the multi-physical fields of the gas flow in pipeline, a three-dimensional numerical model is developed based on Ansys CFX and the process of gas drainage pipeline leakage is investigated.The influence of different leakage positions, different leakage intensities, and different negative pressures of the pumping station on the gas flow in the gas drainage pipeline is studied.The results show that the leakage intensity and the negative pressure are the important factors affecting the internal gas flow field in the gas drainage pipeline, and the leakage occurring near the pumping station of main gas drainage system is prone to be captured easily.The results of this paper are expected to provide technical support for the safety prevention and control of pipeline leakage accidents in the main gas drainage system and also suggestions for the optimization of the allocation of safety prevention and control resources.

Integrated multimodal imaging in theranostics nanomaterials offers extensive prospects for precise and noninvasive cancer treatment. Precisely controlling the structural evolution of plasmonic nanoparticles is crucial in the development of photothermal agents. However, previous successes have been limited to static assemblies and single‐component structures. Here, an activatable plasmonic theranostics system utilizing self‐assembled 1D silver‐coated gold nanochains (1D nanochains) is presented for precise tumor diagnosis and effective treatment. The absorbance of the adaptable core–shell chain structure can shift from visible to near‐infrared (NIR) regions due to the fusion between nearby Au@Ag nanoparticles induced by elevated H2O2 levels in the tumor microenvironment (TME), resulting in the creation of a novel 3D aggregates with strong NIR absorption. With a high photothermal conversion efficiency of 60.2% at 808 nm, nanochains utilizing the TME‐activated characteristics show remarkable qualities for photoacoustic imaging and significantly limit tumor growth in vivo. This study may pave the way for precise tumor diagnosis and treatment through customizable, optically tunable adaptive plasmonic nanostructures. [ABSTRACT FROM AUTHOR]