Research on the Endogenous Problems of Rural Farmers’ Spiritual and Cultural Education

The author conducts research and analysis on the endogenous problems of rural farmers’ spiritual and cultural education and finds that: the current endogenous problems of rural farmers’ spiritual and cultural education in China are mainly manifested in the oldness of spiritual and cultural education concepts, the monotonousness of spiritual and cultural education content, the blurring of spiritual and cultural education forms, the simplicity of spiritual and cultural education methods, and the lag of spiritual and cultural education evaluation and etc. Meanwhile, the author proposes to build a scientific system of spiritual and cultural education policy, create a healthy and harmonious policy implementation atmosphere, and construct a full policy supervision system and some other policy suggestions

SWOT Analysis and Strategies of Constructing Rural Farmers’ Spiritual and Cultural Education System

Opportunities and challenges coexist in constructing rural farmers’ spiritual and cultural education system. Conducting SWOT analysis to analyze various factors from a holistic perspective will facilitate grasping advantages and opportunities, recognizing weaknesses and threats, and seeking a path suitable for local realities. Finally, the author proposes specific policy suggestions regarding awareness improvement, policy improvement, economic development and educational resource integration and so on

How Different Frames of Reference Interact: A Neural Network Model

It has been argued that people use multiple frames of reference (FORs) for representing and updating spatial relationships between objects in a complex environment. When there are conflicts among representations of multiple FORs, they compete to determine behavior. “Frame of Reference-based Map of Salience” theory (FORMS) suggests that FORs with high salience may be processed in priority. Here, we report a computational neural network model for a two-cannon task, which naturally involves multiple FORs with different levels of salience: intrinsic frame of reference (IFOR) and egocentric frame of reference (EFOR). The goal is to investigate the computational neural mechanisms underlying human spatial performance. Our simulation results fit earlier behavioral results well. The model suggests although multiple FORs may be initially represented independently, they interfere with each other by the inhibitory competition of neurons in the later process (in hidden layer) for conflict resolution. Moreover, salience may modulate the competition by prioritizing FORs with high salience levels. These results represent a connectionist support for the FORMS theory

A Model of Customer Lifetime Value Consider with Word-of-mouth Marketing Value

With the rapid development of IT technology and fierce competition of market, the customer relationship management(CRM) has gained its importance in the market. Companies have attached importance to acquiring and retaining the most profitable customers. So calculating customer’s value is a significant segment for every effective CRM. Many researches have been performed to calculate customer’s value based on customer lifetime value (LTV). But, these calculations can’t effectively include the whole customer value, especially for the word-of-mouth marketing value. This paper proposes a new LTV model which considers the customer’s past profit contribution, potential value and word-of-mouth marketing value, and gives a more reasonable LTV value in CRM for the company to make a decision

Geomechanical properties of hydrate-bearing strata and their applications

Natural gas hydrate is an alternative potential energy source that contributes to depressurizing the pressure of energy supply and environmental pollution in the future. Field hydrate production has a close association with geological risks. In this regard, accurate estimation of strength and deformation properties is crucial to risk prevention and control during hydrate development. However, the geomechanical properties of hydratebearing sediments and their applications remain unclear. Herein, this work provides a comprehensive summary of studies on the mechanical characteristics of hydrate-bearing sediments and their applications in field trials. It starts with the main research methods, including laboratory tests, constitutive modeling, and numerical simulations, followed by the effects of clay content, hydrate distribution, and morphology on mechanical properties. Besides, typical applications of geomechanical parameters are examined and discussed. Finally, the challenges and perspectives of mechanical studies on hydrate-bearing sediments are presented, which is favorable for the evaluation and control of geological risks during hydrate exploration and development.Document Type: PerspectiveCited as: Dong, L., Liu, X., Gong, B., Li, Y. Geomechanical properties of hydrate-bearing strata and their applications. Advances in Geo-Energy Research, 2024, 11(3): 161-167. https://doi.org/10.46690/ager.2024.03.0

TreeMAN: Tree-enhanced Multimodal Attention Network for ICD Coding

ICD coding is designed to assign the disease codes to electronic health records (EHRs) upon discharge, which is crucial for billing and clinical statistics. In an attempt to improve the effectiveness and efficiency of manual coding, many methods have been proposed to automatically predict ICD codes from clinical notes. However, most previous works ignore the decisive information contained in structured medical data in EHRs, which is hard to be captured from the noisy clinical notes. In this paper, we propose a Tree-enhanced Multimodal Attention Network (TreeMAN) to fuse tabular features and textual features into multimodal representations by enhancing the text representations with tree-based features via the attention mechanism. Tree-based features are constructed according to decision trees learned from structured multimodal medical data, which capture the decisive information about ICD coding. We can apply the same multi-label classifier from previous text models to the multimodal representations to predict ICD codes. Experiments on two MIMIC datasets show that our method outperforms prior state-of-the-art ICD coding approaches. The code is available at https://github.com/liu-zichen/TreeMAN

An investigation into methods for predicting material removal energy consumption in turning

The wide use of machining processes has imposed a large pressure on environment due to energy consumption and related carbon emissions. The total power required in machining include power consumed by the machine before it starts cutting and power consumed to remove material from workpiece. Accurate prediction of energy consumption in machining is the basis for energy reduction. This paper investigates the prediction accuracy of the material removal power in turning processes, which could vary a lot due to different methods used for prediction. Three methods, namely the specific energy based method, cutting force based method and exponential function based method are considered together with model coefficients obtained from literature and experiments. The methods have been applied to a cylindrical turning of three types of workpiece materials (carbon steel, aluminum and ductile iron). Methods with model coefficients obtained from experiments could achieve a higher prediction accuracy than those from literature, which can be explained by the inability of the coefficients from literature to match the specific machining conditions. When the coefficients are obtained from literature, the prediction accuracy is largely dependent on the sources of coefficients and there is no definitive dominance of one approach over another. With model coefficients from experiments, the cutting force based model achieves the best accuracy, followed by the exponential function based method and specific energy based method. Furthermore, the power prediction methods can be used in process design stage to support energy consumption reduction of a machining process

Contribution of recycled moisture to local precipitation in the inland Heihe River Basin

Recycled moisture contributed by continental evaporation and transpiration plays an important role in regulating the hydrological processes and atmospheric humidity budget in arid inland river basins. However, knowledge of moisture recycling within many large inland basins and the factors that control moisture recycling is generally lacking. Based on a three-component isotopic mixing model, we assessed the characteristics of moisture recycling in China’s semi-arid Heihe River Basin. During the active growing season, almost half of the precipitation in the upper reaches was provided by local moisture recycling, and the main contribution came from transpiration. In the middle reaches, almost half of the precipitation in the artificial oasis and the desert-oasis ecotone was also provided by local moisture recycling, and the transpiration fraction (fTr) and evaporation fraction (fEv) of the artificial oasis differed from those of the desert-oasis ecotone. In the lower reaches, less than 25% of the precipitation was provided by local moisture recycling. Mean fTr values were relatively low in the Gobi (15.0%) in the middle reaches and in the riparian forest at Ejina (25.6%) in the lower reaches. The positive correlations between fTr and both precipitation and relative humidity suggest that higher precipitation and relative humidity promote transpiration fraction, whereas higher vapor pressure deficit reduces transpiration fraction. The positive correlation between fEv and temperature and vapor pressure deficit, and the negative correlation between fEv and relative humidity indicate that higher temperature and vapor pressure deficit promotes evaporation fraction, whereas higher relative humidity reduces the evaporation fraction. Our results show that contributions of recycled moisture (especially transpiration) to local precipitation play an important role in regional water resource redistribution in the arid and semi-arid region of northwestern China