Search

The automation of coal mine production processes has largely relied on artificial intelligence (AI) technology to analyze industrial data. However, AI models developed for single application scenarios prove inadequate for the complex environments in coal mining. Relying solely on distributed computing to process the input features of AI models has led to decreased application efficiency. To address these challenges, an automatic reasoning technology for AI models in coal mine industrial data was developed. The system architecture consisted of three layers: the data layer, the computation-driving layer, and the model reasoning layer. The data layer gathered and stored various types of monitoring data, supplying raw data to the computation-driving layer. The computation-driving layer converted this vast amount of raw data into input features for AI models tailored to coal mining applications. An automatic switching mechanism between two computational engines—based on the input feature values—intelligently selected either Spark-based distributed computing or Python-based local computing, depending on the data volume, thereby resolving the issues of slow processing speeds and high latency in large-scale data applications. In the model reasoning layer, the input features were fed into the AI models for reasoning. A collaborative reasoning mechanism, with multiple triggering methods—scheduled, manual, and feedback-triggered—was introduced to enhance the effectiveness of AI models in complex coal mining scenarios. The results demonstrate that this technology enables rapid calculation of input features for multiple AI models across different application scenarios, as well as fast, automatic, and collaborative reasoning.

A precise and fast digital twin mapping method for hydraulic support attitude in fully mechanized working face is proposed to address the problems of low precision, large time delay, and difficulty in balancing precision and time delay in implementing attitude mapping using digital twins. The study designs a digital twin system architecture for hydraulic support attitude, which includes physical perception layer, data layer, business logic layer, and presentation layer. At the business logic layer, by retaining the external shape of the high-precision model of the hydraulic support and merging key parts into lightweight structural components, a digital twin model of the hydraulic support attitude is established. It reduces rendering delay. By establishing a conversion relationship between the angle measured by the inclination sensor and the rotation angle of the digital twin model, consistent of virtual-real mapping of the digital twin model of the hydraulic support attitude and real entities of the hydraulic support is achieved, ensuring the precision of the hydraulic support attitude mapping. At the data layer, transmission intervals are divided from each data transmission link and parameter constraints are applied. Parameter programming is applied to optimize the data update interval of adjustable links, reducing resource waste and latency in the data transmission process of digital twin systems. A precise and fast digital twin mapping platform for hydraulic support attitude is built, and the time delay and precision of virtual real mapping for hydraulic support attitude are tested. The results show that this method has a lower time delay while ensuring the precision of hydraulic support attitude mapping.

The control of information is a defining feature of the information age, and the optical modulator likewise has a crucial role in optical networks. The transmission, processing, and storage of data have demanded low energy consumption and high speed for photonic systems, promoting the development of electro-optic modulators to all-optical modulators. Although these all-optical modulation methods eliminate the photoelectric conversion, the disadvantage of volatile materials requiring continuous power supply when processing and retaining data in new materials-based devices increase energy consumption. We propose a Ge2Sb2Te5 (GST) integrated all-optical, nonvolatile optical modulator for in-fiber operation. The pulse-induced GST phase transition changes the reflectivity of the fiber end face, and this difference affects the result of the interference, achieving a modulation of output light intensity in interference spectra. The experimental results reveal that the device has obtained 13 dB interference intensity contrast in the telecommunications bands, and its response to a pump pulse is around 100 ns. Furthermore, we demonstrated the operation of the device as a scalar multiplication unit and a logic operation unit. The signal can be transmitted, processed, and stored in the fiber without photoelectric conversion. With the benefits of the switching power consumption of less than 100 nJ and the nonvolatile nature of GST, the device will be more energy-efficient in synchronous processing and storing. This in-fiber operating modulator lays the foundation for developing all-optical devices and networks.

The deep integration of the coal industry and artificial intelligence (AI) is an important path for modern mines to achieve intelligent personnel reduction, cost reduction, and efficiency improvement. AI empowerment in the entire process and business application scenarios of the coal industry is a specific technical measure to achieve coal mine intelligence. In the context of the current development of intelligent coal mines, a basic paradigm for the evolution of primary intelligent coal mines to new generation intelligent coal mines has been proposed. The composition, functions, and technical connotations of primary intelligent coal mines and new generation intelligent coal mines have been compared and analyzed. It is pointed out the importance of AI empowerment technology for new generation intelligent coal mine and its two key applications and implementation: the coal mine industry mechanism AI model and the coal mine Industry internet platform. The paper summarizes the current research status of industrial mechanism AI models for complex operations such as coal mine geology, mining, excavation, and safety monitoring. The paper clarifies the rapid development trend of industrial mechanism AI analysis in intelligent coal mine construction. A new generation of intelligent coal mine multi-level cloud edge collaborative industrial Internet platform architecture is designed. Using industrial information software and hardware facilities such as group data center, mine data center, production system centralized control center, and combining the features of massive data cloud computing and small amount of data edge computing, a multi-level cloud edge collaborative mechanism of group cloud, mine cloud and link edge, scene edge is proposed. It is pointed out that further research directions in the future should continue to strengthen the development and software research of AI models for coal mining industry mechanisms. Gradually a knowledge software system empowered by AI throughout the entire process of coal mining will be formed. It is suggested to fully utilize the digital resources and information facilities of the coal mining industry Internet platform to gradually realize the AI technology support of the coal mining industry Internet platform.

Background Methods Results Conclusions The erector spinae plane block (ESPB) and quadratus lumborum block (QLB) are two novel interfascial plane block techniques with possible analgesic effects for both incisional and visceral pain. However, the results of the intercomparison of the two techniques for analgesia after abdominal surgery remain controversial.A systematic literature search was performed on five databases for randomized controlled trials comparing the analgesic efficacy of ESPB and QLB in abdominal surgery. The primary outcome was the 24 h postoperative intravenous IV morphine‐equivalent consumption. A meta‐analysis was performed using a random‐effects model, with subgroup analyses based on the types of surgery and approaches of QLB.The 24 h postoperative IV morphine‐equivalent consumption was lower in patients receiving ESPB than in those receiving QLB (MD –2.307 mg; 95% CI ‒4.577 to −0.038; p = 0.046; and I2 = 96.5%), though the reduction did not reach clinically meaningful difference. Static and dynamic pain at different postoperative time points, the time to first rescue analgesia, and the incidence of PONV showed no significant difference between the two groups. However, the QLB group demonstrated a significantly prolonged time in performing the block compared to the ESPB group (MD –2.985 min; 95% CI –4.608 to –1.363; p < 0.001; and I2 = 97.5%).Based on the available evidence from a systematic search of databases, the single‐shot ESPB exhibits similar analgesic effects as QLB in abdominal surgery. The incidence of PONV was similar between the two techniques, with no block‐related complications identified though QLB might be a more technically challenging approach than ESPB. [ABSTRACT FROM AUTHOR]

The characterization and analysis of rock types based on acoustic emission (AE) signals have long been focal points in earth science research. However, traditional analysis methods struggle to handle the influx of big data. While signal processing methods combined with deep learning have found widespread use in various process analyses and state identification, effective feature extraction using progressive fusion technology still faces challenges in the field of intelligent rock type identification. To address this issue, our study proposes a novel framework for rock type identification based on AE and introduces a new signal identification model called 3CTNet. This model integrates convolutional neural networks (CNNs) and Transformer encoder, intelligently identifying AE of different rock fractures by establishing dependencies between adjacent positions within the data and gradually extracting advanced features. Furthermore, we experimentally compare five oversampling methods, ultimately selecting the adaptive synthetic sampling method (ADASYN) to balance the dataset and enhance the model's robustness and generalization ability. Comparison of the internal structure of our model with a series of time series processing models demonstrates the effectiveness of the proposed model structure. Experimental results showcase the high identification accuracy of the intelligent rock type identification model based on 3CTNet, with an overall identification accuracy reaching 98.780%. Our proposed method lays a solid foundation for the efficient and accurate identification of formation rock types in geological exploration and oil and gas development endeavors. [ABSTRACT FROM AUTHOR]

Rock fracture acoustic emission (AE) signals are commonly used non-destructive testing data in geological exploration, resource exploitation, and engineering fields. However, these signals are often accompanied by noise interference caused by environmental factors. In this study, we propose an enhanced model for denoising rock fracture AE signals, called simplified fully convolutional denoising autoencoder (SFCDAE). This model is based on the denoising autoencoder principle in the field of deep learning neural networks. The SFCDAE model consists of only seven layers, with minimal preprocessing of data input. By comparing denoising performance evaluation indicators, higher peak signal-to-noise ratio (PSNR) and lower root mean square error (RMSE) were achieved. On average, PSNR increased by 5.575% and RMSE decreased by 22.225%. Using simulated environmental noise to validate the model, it was found that the model has good robustness and can remove artefacts from sudden noise. The practical application value of the LSTM classification model was validated using data containing real experimental noise, resulting in a higher classification accuracy of 80.083%. These results indicate that the proposed model has better denoising performance compared to existing intelligent models and has certain practical value. [ABSTRACT FROM AUTHOR]

With the changes in global climate, adverse weather events appear to be more frequent. The efficiency, reliability, and safety of transportation operations can be compromised by extreme weather conditions. It is critical to analyse the spatiotemporal effects of extreme weather on the operational efficiency of transportation operational efficiency for meeting people's travel and transport needs and formulating emergency management operation to prevent road congestion. It is also important to improve the resilience of transportation system. We compared the changes in transportation operational efficiency in Nanjing during normal weather on January 23 and snowstorm on January 25, 2018, using real-time travel data from Gaode Map. The results indicate that there are differences in the distribution of accessibility changes from different residential areas to the main city area in the morning peak. Overall, 90% of the accessibility change values are concentrated in -10 to 10 minutes, while 65% are concentrated in -5 to 5 minutes, and 70% of the rangeability of accessibility is concentrated in -20% to 20%. In a word, the travel in Nanjing in the snowstorm weather is basically normal. This observation is mainly due to the overnight snow removal and the reduction in the number of small car trips. In addition to the Xinjiekou area, the Hexi business district and the exit area of the cross-river tunnel should also be included in the key management areas for taking emergency management operation in the future., Author(s): Yangjin Chen (corresponding author) [1]; Yifan Qin [1] 1. Introduction Transport plays an important role in urban systems. However, extreme weather results in the reduction of operational efficiency, reliability, [...]

Reasonable construction of hierarchical electrode materials is verified as a promising way to improve the electrochemical performance due to the synergistic effect between unique components and constructions. Hence, a hierarchical nanostructure composed of tungsten oxide nanorods anchored on TiO2 nanowires coupled with a carbon layer (TiO2@WOx-C NWs) was synthesized as an electrode material by exploiting the self-assembly function of dopamine and carbonization. The inner one-dimensional TiO2 nanowires served as the stable substrate with WOx anchored on the surface of TiO2 NWs and the tightly coupled carbon nanosheets, which can not only facilitate electron transport but also provide more active sites for electrochemical reactions. As a result, benefitting from the synergistic effects between three functional components and the multi-dimensional hierarchical structures, the as-prepared TiO2@WOx-C NWs displayed excellent lithium storage performance with a specific capacity of 651.4 mA h g−1 after 500 cycles at 1.0 A g−1, which is superior to most Ti-based structures. The enhanced electrochemical performance is mainly attributed to the synergistic effect of the different dimensional structures, the high capacity of tungsten oxide and the surface coating of the conductive carbon material. This work provides a simple and effective approach to designing functional hierarchical structures for energy storage and conversion. [ABSTRACT FROM AUTHOR]

Purpose: Multiple regional nerve blocks proved no additional benefit in total laparoscopic hysterectomy in multimodal analgesia, as postoperative pain may mainly originate from the vaginal cuff. Theoretically, caudal block can relieve pain from the vaginal cuff by a sacral spinal nerve block. We aimed to verify whether a caudal block with ropivacaine and morphine can achieve an analgesic effect without additional adverse effects after a total laparoscopic hysterectomy.Patients and Methods: Forty-eight patients undergoing total laparoscopic hysterectomy were randomly allocated to receive preoperative caudal block with 20 mL of mixture including 0.25% ropivacaine and 2 mg morphine (caudal block group) or sham block (sham group). The primary outcome was the postoperative 24 h cumulative sufentanil consumption.Results: Median (IQR) sufentanil consumption in the first 24 postoperative hours of the caudal block group and the sham group was 0.00 (0.00 to 0.05) μg/kg vs 0.13 (0.04 to 0.21) μg/kg, respectively, p < 0.001. The majority of patients felt that visceral pain was more intense than incisional pain at 1, 6, 12, and 24 h post-surgery in the sham group (95.8% at 1 h, 95.8% at 6 h, 95.8% at 12 h, and 75% at 24 h post-surgery). Compared to the sham group, the caudal block reduced visceral pain scores at rest and during movement at 1 h (p < 0.001), 6 h (p < 0.001), 12 h (p < 0.001), and 24 h (p < 0.001) post-surgery. Intraoperative remifentanil consumption was significantly lower in the caudal block group than in the sham group (p = 0.004). There were no significant differences in other secondary outcomes between the two groups.Conclusion: A caudal block with ropivacaine and morphine could provide a satisfactory analgesic effect for 24 h postoperatively without additional adverse effects after total laparoscopic hysterectomy. [ABSTRACT FROM AUTHOR]

Background: Spodoptera frugiperda is an invasive, widespread agricultural pest in China. However, there have been no reports assessing feeding damage on wheat caused by S. frugiperda. To clarify the fitness and potential damage of S. frugiperda to wheat, this study analyzed the population parameters of S. frugiperda fed on wheat in a laboratory and simulated the potential damage in field conditions. Results: The population parameters of S. frugiperda were compared using life tables on wheat at the seedling and adult plant stages. The adult female longevity of S. frugiperda varied from 12.29 days on seedling plants to 16.60 days on adult plants. Egg production was significantly higher when fed on wheat at the seedling stage (646.34 eggs) than when fed on adult plants (495.86 eggs). On wheat at the seedling and adult plant stages, the mean generation times were 35.42 and 38.34 days, respectively, and the intrinsic rates of increase were 0.15 and 0.14, respectively. Spodoptera frugiperda completed development and increased its population in wheat at both plant growth stages. In the field, the effect of different larval densities on the 1000‐kernel weight of wheat was significantly different. An action threshold of 40 larvae per m2 was estimated, and the higher population densities caused a yield loss of 17.7%. Conclusion: Spodoptera frugiperda can complete its life cycle on wheat at different stages. Wheat can serve as an alternative host for S. frugiperda. If S. frugiperda reaches 320 larvae per m2 density during wheat growth, it will cause yield loss exceeding 17%. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Holotrichia parallela is an important plant pest. Comparative feeding experiments showed that the egg production, oviposition duration and survival rate of H. parallela beetles were significantly higher when they fed on elm leaves than when they fed on willow or purpus privet leaves. RNA sequencing was used to determine transcriptomic changes associated with oviposition. Comparative transcriptome analysis revealed that the beetles that fed on elm and willow had a total of 171 genes with differential expression. When the beetles fed on elm and purpus privet, 3568 genes had differential expression. The vitellogenesis, ovarian serine protease, odorant-binding proteins, acyl-CoA synthetase and follicle cell proteins were commonly upregulated genes in elm-fed beetles compared with those fed on willow/purpus privet leaves. The involvement of the follicle cell protein 3C gene in the regulation of oviposition was confirmed using RNA interference. The results provide insights into the molecular mechanisms underlying oviposition in H. parallela feeding on different host plants. This study also describes a method for identifying potentially effective genes for pest control. [ABSTRACT FROM AUTHOR]

We studied the dynamic behavior of a single semiflexible ring in linear chain matrix based on a coarse-grained model using the molecular dynamics simulation approach. We found that that ring chains' hollow centers are frequently filled with linear chains. However, as the rigidity of the linear chains increases, the linear chains arranged parallel to each other and the ring chain are temporary caged. As a result, the swing movement in the normal direction of the ring is significantly limited, and the relaxation time in the normal direction increases significantly. Our findings can help to understand the physical mechanism of the movement of the ring chain in ring–linear polymer blends at the microscopic level. [ABSTRACT FROM AUTHOR]

Mathematical modeling of mass transfer and absorption in the small intestine has been a challenging task. Systematic review and analysis of existing efforts indicate the need to pursue a reliable predictive model that is physically sound and computationally efficient. With the consideration of 3D intestinal inner wall structure, this work rigorously derives an absorption model that can be used as a source term in a 1D distributed model, conventionally called the diffusion–convection–reaction model. Moreover, computational fluid dynamics simulations are carried out to generate in silico experimental data for quantification of the mass‐transfer coefficient in the absorption model. This model facilitates a better understanding of the intricate influence of intestinal morphology and motility on mass transfer and absorption in the intestine. Rat duodenum featuring a villous structure and pendular movement is selected as an example to demonstrate the capability of this approach. [ABSTRACT FROM AUTHOR]

To solve the problem of secondary path mutation and external disturbance abrupt changes during helicopter maneuver flight, the previous research proposed a hybrid active vibration control law. To improve the engineering applicability, the original algorithm is ameliorated to the least mean square-input-output-based robust (LMS-IOBR) algorithm. The system model within the target frequency band can be identified through the input-output data to avoid constructing complex state observers. In addition, the output form of the feedback controller is constructed by an autoregressive moving average model with extra input, which is beneficial to improve operational efficiency. Numerical simulations demonstrate that compared with the original algorithm, controller real-time computation can be reduced by 52% with control effects guaranteed at the same time. Furthermore, to verify the effectiveness and adaptability of LMS-IOBR, multi-input multioutput vibration control experiments are carried out on a specially developed simple platform for simulating helicopter maneuver states. Comparative tests in various typical states are performed between the LMS-IOBR and the multichannel least mean square algorithm. Under the complex circumstances of simulating continuous subduction uplift, the peak response of closed-loop system attenuates by 80% and 70%, and the vibration of two points is reduced to 15% and 20%, respectively, within 3 s. The experimental results demonstrate that the proposed LMS-IOBR algorithm shows stronger transient adaptability and robustness against external disturbance excitation and secondary channel mutation in helicopter maneuver flight. [ABSTRACT FROM AUTHOR]

In this paper, two classes of high-order numerical schemes on the time discretization for the solutions of two-dimensional nonlinear Sobolev equations are analyzed. The two-level Newton linearized difference scheme had been established in the previous literature, in which the error estimates in L 2 -norm and H 1 -norm are obtained, but that in L ∞ -norm remains unsolved. The second difference scheme is established based on a three-level linearized difference technique in temporal direction. The numerical discretization in spatial dimension for both schemes utilizes the compact difference operator. We prove that the orders of convergence for both difference schemes in L ∞ -norm are O (τ 2 + h 1 4 + h 2 4) based on the energy argument, where τ denotes the temporal step size, h 1 and h 2 denote the spatial step sizes in x -direction and y -direction, respectively. The numerical tests further verify the theoretical results and demonstrate the efficiency of both difference schemes. [ABSTRACT FROM AUTHOR]