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Abstract Objective To stratify patients with copy-number low (CNL) endometrial cancer (EC) by clinicopathological characteristics. Methods EC patients who underwent surgery between June 2018 and June 2022 at Peking University People’s Hospital were included and further classified according to TCGA molecular subtyping: POLE ultramutated, microsatellite instability high (MSI-H), CNL, and copy-number high (CNH). Clinicopathological characteristics and prognosis of CNL patients were retrospectively reviewed. The Cox proportional hazards regression model was applied to perform univariate and multivariate analysis, and independent risk factors were identified. Differentially expressed genes (DEGs) according to overall survival (OS) were screened based on the transcriptome of CNL cases from the TCGA program. Finally, a nomogram was established, with an accuracy analysis performed. Results (1) A total of 279 EC patients were included, of whom 168 (60.2%) were in the CNL group. A total of 21 patients had recurrence and 6 patients deceased, and no significant difference in recurrence-free survival (RFS) was exhibited among the four molecular subtypes (P = 0.104), but that in overall survival (OS) was statistically significant (P = 0.036). (2) CNL patients were divided into recurrence and non-recurrence groups, and significant differences (P

Bayesian networks are a class of probabilistic graphical models used to characterize the relationships between variables, and structure learning is a key step in Bayesian network modeling, which is the basis for network parameter learning and probabilistic inference. In this study, we introduce Bayesian networks and propose a model for tracking vocabulary knowledge based on BKT. In order to test the performance of the model, the vocabulary knowledge tracking model, including the Bayesian network model, is compared with other models by combining the learning structure algorithm and students’ learning characteristics, and the accuracy, recall, and mean square error of the model are explored to study the accuracy of the vocabulary knowledge tracking model in predicting students’ vocabulary mastery is close to 0.9, and the precision is in the interval of (0.5-0.6). In teaching, the model that predicts students’ mastery of English vocabulary in different datasets performs better than other models in practice.

The development of contemporary college English teaching methods and practice should respect the subjective will of college students; fully tap their wisdom and potential; constantly innovate college English teaching methods, teaching practice activities, classroom teaching, and teaching evaluation models; create a good teaching atmosphere; and establish the concept of developmental evaluation. Through the innovation of teaching methods, college students’ actual language communication ability is cultivated, the teaching objectives and teaching methods of college English reading are innovated, and interactive, body language, role play, situational teaching, communicative teaching, and other teaching methods are used. The College English teaching quality evaluation is a classical multiple attribute decision making (MADM). In this article, the triangular Pythagorean fuzzy sets (TPFSs) are introduced, and the MADM problem is investigated under TPFSs. Based on the traditional dual generalized weighted Bonferroni mean operator and power average operator, the triangular Pythagorean fuzzy dual generalized power Bonferroni mean (TPFDGPBM) operator is proposed. Accordingly, the TPFDGPBM operator is employed to construct the triangular Pythagorean fuzzy MADM method. Finally, a numerical example for College English teaching quality evaluation is constructed to verify the TPFDGPBM technique.

As one of the important way for constructing smart agriculture, unmanned farms are the most attractive in nowadays, and have been explored in many countries. Generally, data, knowledge and intelligent equipment are the core elements of unmanned farms. It deeply integrates modern information technologies such as the Internet of Things, big data, cloud computing, edge computing, and artificial intelligence with agriculture to realize agricultural production information perception, quantitative decision-making, intelligent control, precise input and personalized services. In the paper, the overall technical architecture of unmanned farms is introduced, and five kinds of key technologies of unmanned farms are proposed, which include information perception and intelligent decision-making technology, precision control technology and key equipment for agriculture, automatic driving technology in agriculture, unmanned operation agricultural equipment, management and remote controlling system for unmanned farms. Furthermore, the latest research progress of the above technologies both worldwide are analyzed. Based on which, critical scientific and technological issues to be solved for developing unmanned farms in China are proposed, include unstructured environment perception of farmland, automatic drive for agriculture machinery in complex and changeable farmland environment, autonomous task assignment and path planning of unmanned agricultural machinery, autonomous cooperative operation control of unmanned agricultural machinery group. Those technologies are challenging and absolutely, and would be the most competitive commanding height in the future. The maize unmanned farm constructed in the city of Gongzhuling, Jilin province, China, was also introduced in detail. The unmanned farms is mainly composed of information perception system, unmanned agricultural equipment, management and controlling system. The perception system obtains and provides the farmland information, maize growth, pest and disease information of the farm. The unmanned agricultural machineries could complete the whole process of the maize mechanization under unattended conditions. The management and controlling system includes the basic GIS, remote controlling subsystem, precision operation management subsystem and working display system for unmanned agricultural machineries. The application of the maize unmanned farm has improved maize production efficiency (the harvesting efficiency has been increased by 3－4 times) and reduced labors. Finally, the paper summarizes the important role of the unmanned farm technology were summarized in solving the problems such as reduction of labors, analyzes the opportunities and challenges of developing unmanned farms in China, and put forward the strategic goals and ideas of developing unmanned farm in China.

【Objective】 Winter wheat at anthesis stage is sensitive to water stress and in this paper, we elucidate how enzymatic activity, microbial community and diversity in its rhizosphere respond to change in water stress. 【Method】 The cultivar Jimai 22 was used as the model plant; we compared three water stresses: mild water stress (L), moderate water stress (M), and severe water stress (S), all occurring at the flowering stage. Sufficient irrigation was taken as the control (CK). In each treatment, we sampled the rhizosphere soil and then measured the enzymatic activities, microbial community and diversity in each sample using the Illumina high-throughput sequencing technology. 【Result】 Compared with CK, mild water stress increased and the severe water stress reduced the activity of sucrase, both at significant level, while the activity of the alkaline phosphatase remaining unchanged in the treatments. Water stress affected the diversity index of bacteria and fungi differently. Compared with CK, water stress reduced the Shannon index of bacteria significantly, while the Shannon index of fungi decreased significantly only under severe water stress. ACE, Chao1 and Simpson diversity indices of bacteria and fungi showed significant change only under severe water stress. It was found that water stress increased the relative abundance of Geobacter, Marseilla and Promicromonospora (P

It is important to quickly strengthen and repair earthquake-damaged buildings to restore the normal life after earthquake. Therefore, it is necessary to study the seismic performance of widely-used assembled buildings repaired with different approaches. In this paper, two different methods are designed to repair seismically damaged shear walls assembled with grouted sleeves. Based on different damage scenarios, the first method uses high-strength grout to replace damaged concrete, and the second method uses grout jacketing with reinforcement implantation and reinforcing mesh to enhance the damaged cross-section. The repaired walls are compared with the original walls on the damage mode, bearing capacity, ductility, energy dissipation capacity, and stiffness degradation. The test results verify that both repair methods can restore the load-bearing capacity of the assembled shear walls. Further, the seismic performance of the two repaired seismic-damaged shear walls with different axial pressure ratios is analyzed using finite element analysis. The seismic loss indices of the original assembled and the repaired shear walls are calculated using the Park-Ang two-parameter seismic damage model based on the results of the experimental studies and the finite element analysis.

Water resource shortage and unreasonable application of nitrogen (N) fertilizer have been problems in wheat production of northern China. However, the interaction effects of water regimes and N practices on wheat root growth, grain yield, soil water, and inorganic N changes as well as water-N use efficiency are still unclear under drip irrigation. A field experiment was conducted during the 2020–2021 and 2021–2022 winter wheat (Triticum aestivum) growing seasons. In this study, three irrigation schedules (i.e., irrigation was applied up to 80% [D1], 75% [D2], and 70% [D3] as soon as the soil water content decreased to 65%, 60% or 55% of field capacity) and two N practices (i.e., N applied at the base, jointing, booting stages were 90, 72, 48 kg ha−1 [N1], and the base, jointing, booting, filling stages were 90, 40, 40, 40 kg ha−1 [N2], respectively) were considered. The decease in irrigation water amount was offset by the increase in soil water consumption. In addition, N practices significantly interacted with irrigation on soil NO3−–N accumulation (2021–2022), NH4+–N accumulation, SPAD value (2020–2021), N content in stems and grains at maturity, and average root length and weight density at the flowering stage. Irrigation, rather than N practices, significantly affected grain yield, total N uptake, crop N transformations (NT), the contribution of NT to grain (NTPC), water and N productivity, in which, for the value of these two seasons, D2 increased total N uptake by 18.1% (p < 0.05), and NT by 39.4% (p < 0.05) under N1 as compared to D3. Additionally, the highest WUE and ANUE were found in D2 during 2021–2022. Heavy irrigation water amount caused high a LAI; further analysis proved that the LAI was the key factor affecting grain yield, and positively and significantly correlated to yield. However, no significant difference in the LAI between D1 and D2 was found. N1 was beneficial to prevent N leaching and increase water and N use efficiency, biomass, and N transformation amount. This study recommends that D2 + N1 might be a promising system for manipulating irrigation and fertilization practices under sub-surface drip irrigation systems to improve water and N use efficiency and grain yields in semi-arid regions. [ABSTRACT FROM AUTHOR]

The paper investigates the behavior of glass‐fiber reinforced polymer (GFRP) reinforced concrete columns with integrated steel spirals (hybrid reinforcement). Six concrete columns were tested under eccentric axial loading, resulting in failure due to bending. Columns with outer steel longitudinal bars experienced steel yielding at peak loads, while those with GFRP outer rebars failed due to concrete crushing. The results revealed that using GFRP as outer longitudinal bars led to peak loads 3–10% lower compared to columns with steel rebars. Inner confinement by steel spirals increased the load‐carrying capacity. Additionally, columns with inner tubular steel exhibited greater strength than those with steel spirals, indicating a slightly enhanced confinement effect. A finite element model was developed to analyze structural behavior, considering both material and geometric nonlinearity. The model's accuracy was validated by comparing predictions with test results. Parametric analysis from the nonlinear FE model showed that eccentricity significantly impacted column load‐carrying capacity. Increasing inner confinement area and the number of inner longitudinal bars improved structural stiffness and load‐carrying capacity. Furthermore, a simplified theoretical method was proposed. Comparison between experimental failure loads and theoretical predictions revealed differences within 20%, indicating satisfactory reliability of the proposed method. [ABSTRACT FROM AUTHOR]

The pseudorabies virus (PRV) gene encoding thymidine kinase (tk) is an important virulence-associated factor. Attenuation of PRV in susceptible animals is a frequent result of tk deletion. The aim of the study was to assess the pathogenicity of tk-deleted PRV in rats.

Summary This article focuses on a distributed optimization problem under an undirectd and connected network affected by DoS attacks. First, new event‐triggered mechanisms are developed to schedule the communication between agents. Then, an event‐based resilient distributed optimization algorithm that removes the requirement of continuous communication in the existing results is designed to achieve consensus optimization. Assisted by the design of regulator equations and the algebraic graph theory, it proves that the proposed algorithm is exponentially convergent. Moreover, Zeno behavior can be excluded by reductio ad absurdum. The simulation results validate that the proposed algorithm is effective. [ABSTRACT FROM AUTHOR]