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Objective To investigate the efficacy and safety of cold snare polypectomy (CSP) in the treatment of gastric polyps with a diameter of 5-10 mm. Methods A total of 161 patients with 313 polyps who were found to have sessile gastric polyps with a diameter of 5-10 mm by gastroscopy and underwent gastric polypectomy in Laoshan Campus, The Affiliated Hospital of Qingdao University, from 2021 to 2022 were enrolled, and according to the surgical procedure for polypectomy, they were divided into CSP group with 88 patients (162 polyps) and hot snare polypectomy (HSP) group with 73 patients (151 polyps). The two groups were compared in terms of the complete resection rate and en bloc resection rate of gastric polyps, immediate bleeding rate, the rate of use of titanium clip during surgery, delayed bleeding rate, delayed gastric perforation rate, postoperative infection rate, and various inflammatory indicators after surgery. Results There were no significant differences between the two groups in the complete resection rate and en bloc resection rate of gastric polyps, immediate bleeding rate, delayed bleeding rate, delayed gastric perforation rate, and postoperative infection rate (P>0.05), and compared with the HSP group, the CSP group had a significantly lower rate of use of titanium clip (χ2=13.482,P

The wind power industry is increasing worldwide every year. Thus, obtaining timely and detailed information on wind farms’ number and spatial distribution is critical for quantitatively estimating wind energy utilization and for planning the construction of new wind farms. Therefore, this study proposes a method for quickly identifying wind farms in a large-scale area. Given that wind farms mainly comprise individual objects such as wind turbines and substations, we labeled sample images of wind turbines and substations on a global scale. Then, these sample images are used to train a target recognition model and an object classification model and detect the specific locations of wind turbines and substations in the study area. Additionally, we deeply analyzed the location features of the wind turbines and further improved the recognition accuracy based on these known features using geographic constraints. Based on the location information of wind turbines and substations, a clustering model organizes them effectively into complete wind farms. A comprehensive evaluation of the clustering model verifies its scientific validity and reliability. Specifically, this framework was systematically tested throughout Vietnam with remarkable results, using high-resolution historical images provided by Google Earth. Indeed, our framework achieved 90.45% recall and 95.73% accuracy for wind turbines and 81.37% recall and 78.96% accuracy for substations. Finally, we successfully obtained the spatial location and distribution of 15 completed wind farms, demonstrating that the proposed scheme can quickly and accurately identify wind power plants in a large-scale area, which supports wind power management and energy utilization planning.

Dyslipidemia may be related to the occurrence and development of colorectal tumors. Numerous studies have confirmed that dyslipidemia increases the risk of colorectal adenomas at present; however, the association of dyslipidemia with colorectal serrated lesions and colorectal cancer is still controversial, and there are few relevant reviews in China. This article comprehensively explores the correlation of dyslipidemia with colorectal serrated lesions and colorectal cancer, analyzes the possible causes of controversy, identifies the directions of subsequent researches, and discusses the role of dyslipidemia in the occurrence and progression of colorectal tumors. This article indicates that dyslipidemia is associated with colorectal serrated lesions and colorectal cancer. Dyslipidemia may be involved in the development of colorectal tumors through the interaction of multiple mechanisms such as insulin resistance, inflammatory factors, oxidative stress, high-fat diet and immunosuppression. The incidence of colorectal cancer is increasing yearly with a relatively slower natural course and more definite precancerous lesions. Therefore, the clarification of correlation between lipid indexes and colorectal tumors can facilitate early prevention and targeted screening of colorectal tumors and provide a reference for formulating targeted prevention strategies for colorectal cancer.

This paper builds a time series prediction model of recurrent neural networks based on time series electricity load forecasting. In this paper, the household electricity consumption record data of some residents in urban area S is taken as the research object, and the laws and characteristics of users’ electricity consumption behavior are analyzed in depth based on the real residential electricity consumption data. External factors such as temperature conditions, holidays, etc. The arithmetic cases are also analyzed using real load data sets. In the short-term continuous electricity data analysis, the smaller the time interval is, the closer its corresponding electricity consumption ratio is to 1. There is a negative correlation between long-term continuous electricity consumption. When the temperature is 30~35oC versus -5~0oC, electricity consumption rises significantly. Comparing and analyzing the time series decomposition-RNN with several models, the time series decomposition-RNN model has the highest fit at 10:00-12:00 and 12:00-14:00, and the result verifies the validity of the model proposed in this paper.

This paper summarizes the communication methods of local music culture elements in the Internet perspective, combines the feature extraction and melody recognition of local music culture elements with Internet technology, and analyzes the communication effects and WCI values of music publics in media communication. It briefly outlines integrating local music culture elements with piano performance education, models musical features and piano notes. It analyzes the development of piano performance and education from the perspectives of teachers and students using multi-dimensional evaluation rules. Taking the famous song “Two Fountains Reflecting the Moon” as the experimental material, we analyze the dissemination effect of the works of local music culture elements played by two instruments: erhu and piano. Compared with the other public numbers, the total number of likes of Folk Song China is the highest, which is 12,494 higher than that of the music research public number, and the music works containing local music culture elements are more resonant to the public. The mean value of the piano group is “2.67”, higher than that of the erhu group “2.13”, indicating that the piano version of local musical works is likelier to be liked on the Internet. This suggests that the piano version of local music works is more straightforward to spread in the Internet environment, and its influence is more significant.

Piano talent cultivation mostly focuses on repetitive training only, and lacks a clear cultivation program for theoretical knowledge and skill points. In this paper, we adopt the curriculum knowledge graph to extract the knowledge point subgraph of piano learning and provide an initialized knowledge graph structure for the learning path under the cultivation scheme. A multi-objective optimization model of the path containing constraints such as the difficulty and mastery of knowledge points is set, and the relevant parameters of the model are defined and calculated to establish a multi-optimization objective function. A solution method that uses constant differential error approximation is proposed as a means of approaching the Pareto optimal solution. To develop the LSPIA algorithm with reciprocal weights, the adjustment vectors are modified using a least squares asymptotic iterative approximation with minimum squares values. Following the discovery of the most suitable route, a teaching experiment was carried out. The results show that the posttest P-value of the total creative thinking score of the experimental and control classes is 0.022 less than 0.05, which indicates that there is a significant difference between the creative thinking of the students in the two classes in terms of affective characteristics. The experimental group achieved a mean score of 122.69 on the post-test, which was a significant improvement from the mean score on the pre-test. An innovative approach to cultivating piano playing talents involves optimizing learning paths.

Time series prediction has always been an important problem in the field of machine learning. Among them, power load forecasting plays a crucial role in identifying the behavior of photovoltaic power plants and regulating their control strategies. Traditional power load forecasting often has poor feature extraction performance for long time series. In this paper, a new deep learning framework Residual Stacked Temporal Long Short-Term Memory (RST-LSTM) is proposed, which combines wavelet decomposition and time convolutional memory network to solve the problem of feature extraction for long sequences. The network framework of RST-LSTM consists of two parts: one is a stacked time convolutional memory unit module for global and local feature extraction, and the other is a residual combination optimization module to reduce model redundancy. Finally, this paper demonstrates through various experimental indicators that RST-LSTM achieves significant performance improvements in both overall and local prediction accuracy compared to some state-of-the-art baseline methods. [ABSTRACT FROM AUTHOR]

Integrating real‐time electrical gas sensing and highly identifiable surface‐enhanced Raman spectroscopy (SERS) for volatile organic compounds (VOCs) monitoring holds significant potential for safeguarding public health and safety. However, this technique remains in the proof‐of‐concept stage because the performance and reproducibility of devices fall short of meeting the practical application requirements. This work addresses this challenge by employing vortex engineering on a bifunctional dual‐layer array of Ni‐doped SnO2 (Ni‐SnO2) bowl‐coated on Ni‐SnO2/Au/SiO2 and developing highly reproducible device fabrication. In the dual‐layer array, vortices generated in upper Ni‐SnO2 bowls slow down the VOC flow and direct its delivery to gaps between lower Ni‐SnO2/Au/SiO2 units that are critical to SERS and electrical sensing. Experimental results show that the vortex effect in the array enables a low limit of detection of 10 ppb with a response and recovery in seconds. The excellent practicality of the array has been demonstrated through a ca. 100 hours of quantitative dual‐monitoring of styrene in a spacious environment (~60 m3) with a 5‐meter distance between the leakage source and the array. This work advances dual‐monitoring sensors for practical applications and offers insights for designing gas‐sensing materials and devices. [ABSTRACT FROM AUTHOR]