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[Objective Research on the influence mechanism of the five dimensions of farmers' livelihood capital on the intention and behavior of farmland transfer provides a scientific basis for promoting the rational transfer of farmland, improving the utilization efficiency of farmland, and promoting moderate scale management. [Methods] Based on the questionnaire data of 359 farmers from 3 towns and 12 villages in Qufu City, Shandong Province, binary Logistic regression was used for analysis. [Results] Physical capital and financial capital were 5% significantly correlated with transfer intention and transfer-in intention, natural capital was 5% significantly correlated with transfer-out intention, social capital was 10% significantly correlated with transfer-in behavior, and physical capital and social capital were 10% significantly correlated with transfer-out behavior. [Conclusion] The transfer intention of the surveyed area is relatively strong, and the proportion of farmland transfer is relatively high, but there is still a certain gap between the two. The influence of different dimensions of livelihood capital on circulation intention and behavior is not exactly the same. In order to promote the rational circulation of farmland, it is necessary to further improve the market mechanism of farmland circulation, strengthen the macro-control and intermediary functions of the government, and improve the livelihood capital of farmers. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Educational Studies (1673-1298) is the property of Journal of Educational Studies Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Taiwan Law Review is the property of Angle Publishing Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Human gaze behavior, as a non-verbal cue, plays a crucial role in revealing human intentions. Gaze target detection has attracted extensive attention from the machine vision community. However, existing gaze target detection methods usually focus on the texture information extraction of images, ignoring the importance of stereo depth information for gaze target detection, which makes it difficult to deal with scenes with complex texture. In this work, a novel gaze target detection network based on attention mechanism and depth prior is proposed, which adopts two-stage architecture (i.e., a gaze direction prediction stage and a saliency detection stage). In the gaze direction predication stage, a channel-spatial attention mechanism module is established to recalibrate texture features, and a head position encoding branch is designed to achieve texture and head position-aware enhanced high-representation features to accurately predict gaze. Furthermore, a strategy is proposed to introduce the depth representing the stereoscopic or distance information in the 3D scene as a prior into the saliency detection stage. At the same time, the channel-spatial attention mechanism is used to enhance the multi- scale texture features, and the advantages of depth geometric information and image texture information are fully utilized to improve the accuracy of gaze target detection. Experimental results show that the proposed model performs favorably against the state-of-the-art methods on GazeFollow and DLGaze datasets. [ABSTRACT FROM AUTHOR]

Copyright of New Architecture is the property of New Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Educational Research is the property of National Taiwan Normal University, Department of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Acquiring intentions before the start of lower limb movement imagery is the key issue in providing precise control strategies for the lower limb neurorehabilitation system. To this end, the feasibility of using electroencephalogram (EEG) signals prior to movement imagery to fully predict the movement imagery start‐stop intention and intention types of lower limb ambulation is investigated. The EEG signal is pre‑processed and the movement‑related cortical potential (MRCP) is extracted. 15 channels with significant discriminability are selected based on MRCP. The temporal convolutional network models are used to decode the movement imagery intention and intention types of lower limb ambulation from the selected MRCP channel features. The results show that the EEG channel signals selected by MRCP morphology are with significant separable differences in both start‐stop intention and intention types, verifying that using only pre‑movement imagery EEG signals is capable of fully prediction the movement imagery start‐stop intention and intention types of lower limb ambulation movement in humans. [ABSTRACT FROM AUTHOR]

Existing group recommendation models often have a monotonous approach when solving user representation, and only simple social relationships between users are utilized. This makes user representation inaccurate and most models do not consider the impact of user common intention and social interaction on group preferences. As a result, recommended items are not aligned with user needs. To address these issues, a new group recommendation model based on user common intention and social interaction (GR-UCISI) is proposed. Firstly, a user intention separation model that combines user- item interaction history with social interaction is constructed. Graph neural networks are utilized to collect user-item interaction and social interaction information, and to solve user intention and item representation. Secondly, by utilizing the social network random walk algorithm and the K - means clustering algorithm, users can be grouped. User group, user intention and group intention aggregation process are combined to obtain group common intention representation. Finally, group common intention representation and item representation are calculated to obtain the list of recommended items for the group. This method fully considers the impact of user individuality and commonality among group members on group preferences. It also utilizes social relationships to alleviate the problem of data sparsity and improve model performance. The experimental results show that compared with the model with the best recommendation effect of nine models, on the Gowalla dataset, the Precision and NDCG of the GR-UCISI model are increased by 3.01% and 5.26% respectively, on the Yelp-2018 dataset, the Precision and NDCG of the GR-UCISI model are increased by 2.96% and 1.12% respectively. [ABSTRACT FROM AUTHOR]

The reasons for Han Yu's demotion of Yangshan County have always been controversial. His comment on the palace market recorded in the two editions of Tang Books should be the cause of Han Yu's relegation. By analyzing the objective records and the subjective attitude of the characters, we can find that the people who prosecuted Han Yu are Wei Zhiyi, Wang Shuwen and other Yongzhen party members in the Dezong Dynasty, but not Li Shi as it was traditionally thought. Although Liu Zongyuan and Liu Yuxi had not the subjective intention to harm Han Yu, they were suspected of leaking the information to Wei Zhiyi and Wang Shuwen. Han Yu's resentment and accusation against Wei Zhiyi and Wang Shuwen's despicable behavior were also truthfully reflected in his later poems. [ABSTRACT FROM AUTHOR]

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Stroke high-risk population screening project is a national health project being vigorously promoted in China, but it is found that the participation rate of residents in it is low, which seriously affects the screening efficiency. Screening intention is an important predictor of screening behavior, however, there are few studies on the current status and influencing factors of the intention to screen for high-risk stroke among community residents. Objective To understand the current status of the intention to screen for high-risk stroke among community residents and explore the influencing factors. Methods A total of 648 residents of Guangdong Province were selected as survey respondents by using convenient sampling method from March to May 2022. Self-designed questionnaires (including General Data Questionnaire, Stroke High-Risk Screening Intention Scale, Stroke Health Knowledge Scale, Community Medical Service Trust Scale, Perceived Social Support Scale) were used to investigate the respondents. The scores of Stroke High-Risk Screening Intention Scale among residents with different characteristics were compared, and the factors affecting intention to screen for high-risk stroke among community residents were analyzed by multiple linear regression. Results A total of 600 valid questionnaires were collected with the recovery rate of 92.6%. The average total score of the Stroke High-Risk Screening Intention Scale among residents was (101.30±14.98), of which 352 (58.7%) residents had a high level of intention for screening, 248 (41.3%) residents had a middle or low level of intention for screening. There were significant differences in the scores of Stroke High-Risk Screening Intention Scale among residents by gender, residential status, hypertension, hyperlipidemia, smoking status, awareness of high-risk stroke screening, implementation of previous high-risk stroke screening in the community, acceptance of previous high-risk stroke screening, self-perceived lifetime risk of stroke and self-perceived risk of stroke within 1 year (P

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, an NEV purchase intention model featuring "external scenario-internal scenario-application behavior" is built on the basis of technology acceptance model and situational factors. A questionnaire survey combined with structural equation modeling is conducted to investigate the impacts of diversified policies concerning regulatory restrictions, support & improvement, technological enhancement and financial incentives on NEV consumers' purchase intention. Our research results show the financial incentives exert the greatest influence on consumers' purchase intention, followed by the technological enhancement and the regulatory restrictions. Policies concerning the support & improvement indirectly affect consumers' purchase intention by creating positive conforming-to-the-public mentality, but they have the least impact on consumers' purchase intention. From the perception perspective, the perceived value has a fairly large impact on consumers' purchase intention. [ABSTRACT FROM AUTHOR]

To address the problem of insufficient recommendation performance in session recommendation, this paper proposed a disentangled graph neural network model (GDST-GNN) using global graph diffusion and spatio-temporal awareness. Specifically, the model firstly constructed a global collaborative graph based on all sessions from a global perspective, and then employed graph diffusion as the message propagation paradigm for global representation learning of items to capture global information be- yond the current session. For the representation learning of the current session, this paper designed a disentangled spatio-temporal gated network modeling the complex transition pattern and temporal dependency pattern of items in the session, and then fused the learned global and local representations factor by factor. In addition, this paper employed a self-supervised task to achieve performance enhancement of the model. Finally, it generated session representations through attention networks to achieve accurate recommendation of items. Extensive experiments on four real-world datasets validate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traditional document clustering algorithms classify data by measuring the similarity between documents. But they can??t mine users' subjective intention of clustering results according to a small amount of supervision information given by users. With the development of the diversified application scenarios, the clustering results of the same dataset under the guidance of different users?? intentions may not be unique. How to obtain the clustering results following users' intentions is one of the problems in the current research. Besides, there is a small amount of supervision information given by users. How to learn the clustering intention of users to the greatest extent according to a small amount of supervision information is another problem. Therefore, a semi-supervised deep document clustering model with supplemented intention (SDDCS) is proposed. According to the supervision information given by the user, SDDCS constructs an intention matrix to mine the user's intention. The unknown elements in the intention matrix are supplemented according to the matrix factorization and supplement algorithm, so as to learn the users' intention to the greatest extent. The supplementary intention matrix is used to guide the document clustering process, and the user's intention is taken as one of the clustering bases. Finally, the clustering results in line with the user's intention are obtained. Experiments on four public document datasets show that the clustering performance of SDDCS is higher, and its effectiveness is proven.

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Copyright of Automotive Engineer (1674-6546) is the property of Auto Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of the Beijing Institute of Fashion Technology (Natural Science Edition) is the property of Beijing Institute of Fashion Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Nurse engagement and retention are critical issues affecting the quality of healthcare. Although the work environment is known to affect nursing performance and patient outcomes, little is known regarding the impact of this environment on nurse burnout and future work intention, especially in non-Western settings. Purpose: This study explored the extent to which Taiwanese nurses' perceptions of their practice environment mediates burnout levels and intention-to-stay. Methods: This descriptive, correlational study, conducted between September and December 2020, recruited nurses employed at a regional teaching hospital located in a relatively rural region in Taiwan. The participants completed standardized questionnaires, including a demographic information form, the 31-item Practice Environment Scale of the Nursing Work Index (PES-NWI), the 22-item Maslach Burnout Inventory (MBI-HSS), and the 6-item Intention-to-stay (ITS) scale. The mediating effect among the variables related to intention-to-stay was examined using Model 4 of the PROCESS macro and tested using the bootstrapping method (repeated 5,000 times) with a p value < .05. Results: The mean age of the 376 participants was 34.3 years (SD = 8.1). Nearly one-third (30.3%) scored > 27 on the emotional exhaustion subscale of the MBI-HSS, indicating they were "highly burned-out". Also, nearly one-third (30.6%) were uncertain about their intention to stay with their current employer. Burnout was associated with intention-to-stay (β = -.088, p < .001), and holding a positive perception toward their practice environment was shown to mediate the relationship between burnout and intention-to-stay (β = -.015; p < .001). Conclusions/Implications for Practice: Targeted interventions and technical support that promote a collaborative climate and psychological empowerment in clinical practice may alleviate burnout and intention-to-leave in nurses and improve workplace quality. [ABSTRACT FROM AUTHOR]

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Life Education is the property of Life Education Center, National Taiwan University & Taiwan Life Education Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Improvements in medical science and technology have increased the average number of years that older adults survive with impaired quality of life. Understanding behavioral intentions and related factors affecting advance decision (AD) decision-making can help medical professionals improve the decision-making ability of patients, allowing patients and their family members to make better medical decisions that reduce ineffective medical treatments, improve quality of life, and facilitate a good death. Purpose: This study was developed to explore behavioral intentions and related factors during the process of AD decision-making among community adults. Methods: A cross-sectional study design was used in this study. The knowledge, attitudes, and behavioral intentions regarding AD decisions, spiritual health, and social support were measured in a convenience sample using physical or internet-based questionnaires. Data were analyzed in SPSS 21.0 using descriptive and independent samples t-tests, one-way ANOVA, Pearson correlation, and multiple regression analysis. Results: Three hundred and seventy-seven community adults participated in this research (50.57 years old, SD = 13.39; 58.4% female). The average level of AD-related behavioral intention was found to be high, with high numbers of participants indicating that they would refuse endotracheal intubation (4.13, SD = 0.92), extracorporeal membrane oxygenation (4.09, SD = 0.95), extracorporeal heart massage (4.08, SD = 0.95), and defibrillation (4.08, SD = 0.98) if they were in a permanent vegetative state in the future. The important predictors of AD behavioral intention included gender, written expression of end-of-life medical decision-making, participation in the patient self-rights law and advance decision publicity lectures, having an advance decision attitude, and social support (R² = 40.1%, p < .001). Conclusion/ Implications for Practice: A high level of AD-related behavioral intention was found in the sample and several important factors that influence related behaviors were identified. These results provide an important reference for related public policymakers to increase the percentage of older patients participating in advance directive decision-making. [ABSTRACT FROM AUTHOR]

In order to spread green information more effectively, this paper used SOR model to analyze the influence mechanism of green information on clothing brand communication by taking green information presentation of clothing brand as stimulus variable, green cognition and green emotion as mediating variable, and green purchase intention as consumer behavior response. The empirical results show that information provision, relationship construction and behavior guidance have significant positive effects on consumers' green purchase intention. Green cognition plays a partial mediating role in the relationship between information provider, relationship construction and behavior guidance and green purchase intention. Green emotion partially mediates the relationship between behavioral guidance, green cognition and green purchase intention. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University (Science Edition) is the property of Journal of Zhejiang University (Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, some collaborative filtering recommendation models based on graph convolutional networks have been proposed. However, most models regard neighborhood weights as constants and do not distinguish the interaction between users and items, so they cannot obtain a satisfactory recommendation list for users. In order to get a more accurate embedded representation of users and items, this paper proposed a multi-intention-based graph convolution collaborative filtering recommendation algorithm MiGCCF. The algorithm decompose the interaction relationship, the interaction intention between the user and the item is analyzed in a fine-grained manner, and an attention mechanism is introduced to give the neighborhood a learnable attention weight in the process of message dissemination, and to mine the user’s preference for different interactive items. Experiments on Gowalla and Amazon-book show that compared with the benchmark algorithm, the HR@50 and NDCG@50 indicators of the two datasets are improved by 12.5% and 8.5%, respectively, with better performance. [ABSTRACT FROM AUTHOR]

With global warming and glacier melting, the strategic value of the Arctic passage has attracted more and more attention from the international community. The northeast route is close to the Sea of Japan and is an important national interest of Japan. In order to ensure the realization of national interests, Japan has formulated corresponding waterway policies. Japan's Arctic passage policy system consists of three parts: general policy, basic policy and specific policy. However, this policy system itself has logical contradictions which result from multiple factors such as power, economy and culture. The new trend of Japan's Arctic passage policy shows that Japan's demands for political powers in participating in Arctic affairs are becoming more and more obvious, its competition and alertness towards non-Arctic countries are more obvious, and its intention to control the Arctic strategic channel is clearer. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem that the networks based on metric learning do not consider the semantic constraints between the constructed prototypes in the few-shot intention detection（FSID) task, a few-shot intention detection model based on multi-view prototypical contrastive learning（MVPCL) was proposed. In this model, firstly, a multi-dimensional semantic component was constructed using the dynamic information of query instances and support sets to capture the high-level semantic information of support sets in the meta-task, and to understand the diverse expressions of discourse from a global perspective. Then, the semantic components were used to generate multi-view auxiliary prototypes, and the auxiliary prototypes were combined with contrastive learning to consider the constraints between category prototypes from multiple dimensions, which increased the differentiation between category prototypes and also avoided the over-reliance on a single prototype to a certain extent. Compared with prototypical network（PN), relation network（RN), hybrid attention-based prototypical network（HATT), hierarchical attention prototypical network（HAPN), and semantic matching and aggregation network（SMAN), the experimental results show that when the number of instances contained in each category in the support set is 1 and 5, the overall observation from the SNIPS and NLUE datasets shows that the intention detection accuracy of the MVPCL model is improved by at least 0.49% in FSID task, in the generalized few-shot intent detection（GFSID) task, the intent detection accuracy of the MVPCL model is improved by at least 0.39%. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Management & Business Research (2521-4306) is the property of Chinese Management Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traditional collaborative filtering methods largely model in a uniform way without considering the modeling relationships at the fine-grained level of interaction intent. This paper proposes a graph neural network collaborative filtering algorithm fused with interaction intention, named INTNGCF. Firstly, the potential intention is identified by decomposing edges into multiple potential spaces; Secondly, the interaction intention fusion layer is used to determine the importance of these potential intentions. Finally, a predicted user rating of the project is generated. Compared with seven baseline models on three real datasets, the results show that the proposed algorithm has certain performance advantages compared with other advanced recommendation models. [ABSTRACT FROM AUTHOR]

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to explore the influence and mechanism of advertising push methods on consumers′ clothing purchase intention under the new media environment, based on the theory of perceived value and S-O-R model, a model of the relationship between advertising push mode, perceived value and purchase intention was constructed, and relevant hypotheses were proposed. The hypotheses were verified by questionnaire survey and analysis. The results show that APP launch page ads, topic ads and other push methods have a positive impact on consumers′ purchase intention, while information flow ads, soft placement ads and other push methods have no significant impact on consumers′ purchase intention, and perceived value plays a mediating role. [ABSTRACT FROM AUTHOR]

Copyright of Taiwan Law Review is the property of Angle Publishing Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mountain sports tourism is very suitable for college students’ pursuit of health tourism. This paper takes university students in Yunnan province as an example, uses the questionnaire survey data, through the factor analysis method to analyze the main factors that affect the mountain sports tourism of university students. The results showed that the main influencing factors were the value of tourists, feasibility of tourism activities, influences of alternative destinations, tourists ’attitude, destination attraction and safety of tourists. Four enlightenments are obtained: strengthen destination construction and service quality, carry out mountain sports tourism publicity and strengthen information transmission, establish cooperation with the university to reduce the difficulty of activities, paying attention to professional knowledge and strengthening safety protection. [ABSTRACT FROM AUTHOR]