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Bullosis diabeticorum is a distinct, spontaneous, noninflammatory, blistering condition of acral skin that is unique to patients with diabetes mellitus, resulting in the infection, ulcer, gangrene and even amputation. This paper summarized the nursing practice of patient with bullosis diabeticorum combined with diabetic foot ulcer. Based on the comprehensive nursing evolution, an effective nursing plan consisting of wound care, pain control, psychological care and health education was established to improve the wound healing and patient’s quality of life during treatment. (糖尿病性大疱病是一种发生在糖尿病患者四肢远端的特异性皮肤损害。本文总结1例糖尿病性大疱合并足溃疡的护理经验。根据患者的评估情况, 在稳定血糖的基础上, 加强伤口护理、疼痛管理、心理护理、健康教育等护理措施, 促进水疱吸收, 加快足溃疡愈合, 改善患者生活质量。)

The images of coal mine underground belt transportation have the features of low illumination, unclear details, and background interference. The existing foreign object detection models for belt conveyors have problems such as low precision, poor flexibility, large computational complexity, and differences in optimization space. In order to solve the above problems, a foreign object detection method for belt conveyors based on generative adversarial nets (GAN) is proposed. The method preprocesses the video files of the tape transportation process, classifies them into normal and abnormal images. The method creats an experimental dataset to train the improved GANomaly model, and then uses the trained model to detect foreign objects in the belt conveyor. During the training phase, the image of the belt conveyor without foreign objects is used as input. In the testing phase, the image of the belt conveyor containing foreign objects is used as input. The reconstructed image obtained is subtracted from the original image of the input network to obtain the specific position of the foreign object. The lightweight improvement method of GANomaly model adds a depthwise separable convolution residual module to the GANomaly basic network model, and uses depthwise separable convolution to replace the convolution operation in the original backbone network. It greatly reduces the computational complexity of the model and reduces the redundant calculation of parameters, which can significantly improve the speed of foreign object detection. By merging multiple batch normalization (BN) layers, the convergence iteration speed of the model is accelerated, the generalization convergence capability of the model is improved, and gradient vanishing is effectively avoided. The experimental results show that the improved GANomaly model has improved the running speed by 6.27% compared to the traditional GANomaly model. The evaluation indicators F1 score, AUC, Recall, and mean average precision (mAP) have increased by 19.05%, 22.22%, 15.00%, and 17.14%, respectively.

Network slicing is an important technology in 5G networks. The existing research on mine 5G mainly focuses on system architecture and application scenarios, lacking specific implementation solutions for slicing technology. In order to solve the above problem, by analyzing the basic structure of mine 5G networks and the application requirements of intelligent mines, it is proposed to use the channelization function of FlexE to achieve resource allocation and business isolation in the transmission network. It constructs multiple on-demand customized dedicated logical networks on the same network infrastructure, namely network slicing. According to the current applications of mine information communication systems and intelligent mines, a method of mine 5G network basic slicing+transmission resource allocation based on bandwidth weight is proposed. The network is divided into five types of slicing: low delay service, large bandwidth service, industrial ring network service, specific service (unmanned cooperative control) and reserved service. Through further virtual private network (VPN) division method, differentiated bandwidth weight is designed to ensure sufficient transmission resources and avoid channel congestion. The specific 5G QoS identifiers (5QI) are defined based on the requirements of different services for latency and bandwidth. The mapping and isolation based on 5QI are obtained to provide the required service levels for various businesses. Under laboratory conditions, two indicators of business scheduling time and end-to-end delay are tested for mine 5G network systems. The results show that network slicing can achieve more efficient business scheduling than traditional best-effort service models. In high-load scenarios, the average scheduling time is reduced by 10.9%. Within the same business slice, the average end-to-end delay of the mine 5G network is 10.33 ms, providing necessary conditions for the implementation of unmanned collaborative control and other services.

In the traditional personnel re-recognition method in coal mine underground based on metric learning, because metric learning ignores the absolute distance between positive and negative samples, the gradient of the loss function disappears or disperses. This results in low recognition precision of underground personnel position information. In order to solve this problem, a personnel re-recognition method in coal mine underground based on improved metric learning is proposed. Firstly, a feature extraction method for underground personnel based on manual design features is adopted to manually process and extract features such as color space and texture space, enriching the feature dimensions. Secondly, Euclidean distance is used to calculate the similarity of high-dimensional features of personnel. Finally, an improved triple loss function is proposed. Adding adaptive weights to the traditional triple loss function increases the weight of effective samples. It solves the problem of gradient disappearance or dispersion caused by ignoring the absolute distance between positive and negative samples. The traditional recognition method is compared with the personnel re-recognition method in coal mine underground based on improved metric learning for cumulative matching feature curve verification and recognition rate verification. The results show the following points. ① The personnel re-recognition method in coal mine underground based on improved metric learning has a sample matching probability of 100% when the number of similar samples is around 50. ② The personnel re-recognition method in coal mine underground based on improved metric learning reduces the inference time of two different calibration size images by 44 ms and 68 ms, respectively, compared to traditional re-recognition methods. ③ The personnel re-recognition method in coal mine underground based on improved metric learning performs better after discarding the images of personnel heads and feet. It has a sample matching probability of 100% when the number of similar samples is around 42.

Emergency communication technologies and systems for mine post-disaster rescue scenarios generally use Wi-Fi as the relay and coverage solution. Due to the legal restrictions on continuous channel occupation time and the regulatory requirements for monitoring before access in unlicensed frequency bands, it is difficult to achieve extremely low latency. At the same time, multiple emergency communication devices in the same frequency band have co-frequency interference, which will affect the communication quality. 5G technology is oriented to public safety and Internet of Vehicles application scenarios, and defines Sidelink communication technology, which can realize low-latency and high-reliability direct communication between terminal devices. Aiming at the technical requirements of low-latency and high-reliability communication in mine emergency communication system, a mine emergency communication system architecture based on 5G Sidelink direct communication is proposed, and a mapping method between equipment identification and direct communication link time-frequency resource location is designed. The device transmits resource locations through pre-configured fronthaul links and backhaul links, and can communicate with adjacent front-end and back-end devices without establishing routing connections, and implement adjacent relays time-domain resources space division multiplexing by cyclically multiplexing and co-channel interference avoidance between devices. The method proposed in this paper can realize the relay networking mechanism without scheduling permission and simple routing and forwarding, realize the avoidance of co-channel interference under the space division multiplexing of transmission resources, and effectively improve the utilization efficiency of transmission resources. Under the conventional baseband parameters and networking configuration, the average air interface delay can reach 25 ms, which significantly reduces the transmission delay.

The mine Internet of things has the characteristics of large-scale and massive data transmission. These characteristics make the traditional network security and privacy protection methods unable to guarantee the traceability and reliability of key data. The main security risks of mine Internet of things are lack of data transmission traceability and credibility guarantee mechanism, lack of comprehensive signature verification guarantee mechanism of system equipment, and lack of security carrier deployment in system architecture. It is pointed out that blockchain technology can solve the above problems. The key technologies such as blockchain structure, encryption algorithm and consensus mechanism of mine Internet of things are introduced. This paper proposes a blockchain mechanism of mine Internet of things. The edge layer with edge computing power is added between the perception layer and the transmission layer of the mine Internet of things. The security carrier carrying the core functions of the blockchain is deployed. Thus the deployment architecture of the mine Internet of things blockchain is built. The data transmission process under the blockchain mechanism of the mine Internet of things is designed. The asymmetric encryption technology is adopted to ensure the security of data transmission. In the application layer of the Internet of things in mines, the data chain management platform is adopted to realize the functions of key data uplink, data traceability and distributed certificate storage. The blockchain mechanism of mine Internet of things can improve the information security guarantee capability and security level of mine Internet of things. The mechanism can make mine Internet of things to meet the expansion requirements in GB/T 22239-2019 Information security technology-Baseline for classified protection of cybersecurity, and reduce the demand for centralized operation and maintenance.

This paper analyses the development status and technical characteristics of intelligent and networked technologies for conventional ground automatic driving. This paper also analyses the coal mine environmental characteristics, such as no GNSS (global navigation satellite system) signal coverage, low roadway illumination, lots of obstructions and obstacles and ubiquitous coal dust. In the context of the above technical and environmental characteristics, this study puts forward the key technologies of automatic driving research in underground coal mine. The technologies include mobile high-precision positioning technology without GNSS, laser radar technology, underground obstacle detection technology based on millimeter wave radar, underground low illumination video real-time enhancement and characteristic matching technology, underground environment high-precision map technology, underground autonomous vehicle decision planning technology, underground autonomous vehicle control execution technology, underground 5G communication technology and C-V2X direct connection communication technology. It is pointed out that the application of automatic driving in underground coal mine has the advantages of significant demand for fewer people or no people, clear operation management subject, closed scene, fixed route, slow speed, controllable permeability, good 5G construction foundation, easy open interface, etc. The reference architecture of 'human-vehicle-roadway-cloud' coal mine underground network connected automatic driving system is constructed. The system includes underground automatic driving vehicle, roadway infrastructure, personnel, coal mine cloud/edge computing platform and coal mine automatic driving application service platform. This paper designs the coal mine automatic driving vehicle architecture, which includes perception positioning system, network connected collaborative system, vehicle-mounted operating system and vehicle basic components. This paper puts forward three stages of the evolution of the network connected automatic driving in underground coal mines. The first stage is remote control and automatic driving, which realizes the transfer of vehicle drivers from underground to ground. The second stage is the automatic driving of vehicles with emergency takeover boundary. The vehicles are mainly driven by automatic driving, and remote emergency takeover is used as a safety guarantee method. The third stage is 'human-vehicle-roadway-cloud' collaborative control, the underground autonomous vehicles operate safely, efficiently and autonomously to realize highly unmanned intelligent transportation.

Resolving complex three-dimensional (3D) subcellular dynamics noninvasively in live tissues demands imaging tools that balance spatiotemporal resolution, field-of-view and phototoxicity. Image scanning microscopy (ISM), as an advancement of confocal laser scanning microscopy, provides a 2-fold 3D resolution enhancement. Nevertheless, the relatively low imaging speed has been the major obstacle for ISM to be further employed in in vivo imaging of biological tissues. Our proposed solution, multi-confocal image scanning microscopy (MC-ISM), aims to overcome the limitations of existing techniques in terms of spatiotemporal resolution balancing by optimizing pinhole diameter and pitch, eliminating out-of-focus signals, and introducing a frame reduction reconstruction algorithm. The imaging speed is increased by 16 times compared with multifocal structured illumination microscopy. We further propose a single-galvo scan, akin to the Archimedes spiral in spinning disk confocal systems, to ensure a high-speed and high-accuracy scan without the galvanometer's inertial motion. Benefitting from its high photon efficiency, MC-ISM allows continuous imaging of mitochondria dynamics in live cells for 1000 frames without apparent phototoxicity, reaching an imaging depth of 175 μm. Noteworthy, MC-ISM enables the observation of the inner membrane structure of living mitochondria in Arabidopsis hypocotyl for the first time, demonstrating its outstanding performance. [ABSTRACT FROM AUTHOR]

Objective To evaluate the clinical effects of resin infiltration in treating molar-incisor hypomineralization. Methods Twelve patients (36 teeth) with mild molar-incisor mineralization imperfecta who met the inclusion criteria were selected and treated with penetrating resin. Before treatment (T0), at the one-week follow-up (T1) and at the six-month follow-up (T2), a Crystaleye spectrophotometer was used to take photos, and the color differences (ΔE) between the lesion area and the surrounding normal enamel area at different times were calculated and analyzed. The area of the lesion and the total area of the labial surface of affected teeth were calculated using Adobe Photoshop CS3 software. The corresponding area ratio (R) and treatment efficiency (SR) were obtained. The R value was used to judge the effectiveness of resin penetration in the treatment of molar and incisor mineralization imperfecta and to evaluate its aesthetic effect. The results were analyzed by repeated measures one-way ANOVA. Results The color difference of the lesion area vs sound adjacent enamel (ΔE) decreased significantly, and that of the lesion area decreased significantly after resin infiltration (P < 0.001). The success rate was approximately 86.02%, which means that the esthetic effect of resin infiltration in treating molar-incisor hypomineralization was remarkable. No important adverse events or side effects were observed. Conclusion The aesthetic effect of resin infiltration in the treatment of mild molar and incisor hypomineralization is good. This method is recommended for clinical use.

According to the demands of coal mine safety production, the safety management and control technology of key area in coal mine based on image recognition is studied. Machine learning algorithm and computer vision technology are used to analyze the data combined with personnel management data and equipment operation data. Through linkage analysis and data mining, the monitoring and control of underground personnel behavior and coal quantity can be realized, and a knowledge base for target risk pre-control can be formed, which is also verified by underground experiments. The experimental data show that the real-time analysis response time of the system platform is less than 2 s, and the recognition rate is more than 98%. The system can effectively realize the safety control of moving targets such as underground personnel and coal quantity.

Featured Application: This work can be applied to unmanned driving in mining environments, with a specific focus on enabling low-latency transmission of high-definition video from underground vehicles to the surface operators. In the development of intelligent mines, unmanned driving transportation has emerged as a key technology to reduce human involvement and enable unmanned operations. The operation of unmanned vehicles in mining environments relies on remote operation, which necessitates the low-latency transmission of high-definition video data across multiple channels for comprehensive monitoring and precise remote control. To address the challenges associated with unmanned driving in mines, we propose a comprehensive scheme that leverages the capabilities of 5G super uplink, edge collaborative computing, and advanced video transmission strategies. This approach utilizes dual-frequency bands, specifically 3.5 GHz and 2.1 GHz, within the 5G super uplink framework to establish an infrastructure designed for high-bandwidth and low-latency information transmission, crucial for real-time autonomous operations. To overcome limitations due to computational resources at terminal devices, our scheme incorporates task offloading and edge computing methodologies to effectively reduce latency and enhance decision-making speed for real-time autonomous activities. Additionally, to consolidate the benefits of low latency, we implement several video transmission strategies, such as optimized network usage, service-specific wireless channel identification, and dynamic frame allocation. An experimental evaluation demonstrates that our approach achieves an uplink peak rate of 418.5 Mbps with an average latency of 18.3 ms during the parallel transmission of seven channels of 4K video, meeting the stringent requirements for remote control of unmanned mining vehicles. [ABSTRACT FROM AUTHOR]

Summary: Soybean is a short‐day plant that typically flowers earlier when exposed to short‐day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome‐wide association studies (GWAS) using two re‐sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13‐3, which encodes a protein homologous to the pseudo‐response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13‐3 in the natural population, with haplotype H4 (qFT13‐3H4) being lost during domestication, while qFT13‐3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13‐3H1 were located in high‐latitude regions. Knockout of qFT13‐3 accelerated flowering and maturity time under long‐day conditions, indicating that qFT13‐3 functions as a flowering inhibitor. Our results also showed that qFT13‐3 directly downregulates the expression of GmELF3b‐2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13‐3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13‐3 can be utilized for the breeding of high‐yield cultivars with a short maturity time suitable for high latitudes. [ABSTRACT FROM AUTHOR]