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Book ; Online: Transnational and Transdisciplinary Lessons of COVID 19 From the Perspective of Risk and Management

Baker, Julien S. / Gao, Yang / Cole, Alistair / Tran, Emilie / Yue, Xiao-Guang

2022

Keywords	Public health & preventive medicine ; COVID-19 ; coronavirus disease ; physiological effects ; psychological effects ; psychophysiological effects ; exercise ; physical activity ; n/a ; preventive behaviors ; physical activity (PA) ; fruit and vegetable consumption (FVC) ; depression ; loneliness ; older adults ; China ; behavioral response ; mental response ; pandemic ; social welfare ; trust ; transparency ; adult social care ; UK ; political trust ; social trust ; transnational ; transdisciplinary ; United States ; European Union ; Xi Jinping ; Donald Trump ; Joe Biden ; critical juncture ; health diplomacy ; facemasks ; racism
Language	0\|e
Size	1 electronic resource (132 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021621781
ISBN	9783036557045 ; 3036557040
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Impact of the number of cycles of platinum-based chemotherapy for early stage ovarian clear cell carcinoma on survival: a retrospective study.

Gao, Yang

BMC women's health

2023 Volume 23, Issue 1, Page(s) 262

Abstract: Background: Ovarian clear cell carcinoma (OCCC) is a unique subtype of ovarian epithelial ovarian cancer. The number of chemotherapy cycles for early-stage patients is still debated. This study aimed to evaluate whether at least 4 cycles of adjuvant ... ...

Abstract	Background: Ovarian clear cell carcinoma (OCCC) is a unique subtype of ovarian epithelial ovarian cancer. The number of chemotherapy cycles for early-stage patients is still debated. This study aimed to evaluate whether at least 4 cycles of adjuvant platinum-based chemotherapy have better prognostic value than 1-3 cycles in early-stage OCCC. Methods: We retrospectively retrieved data from 102 patients with stage I-IIA OCCC between 2008 and 2017. All patients underwent complete surgical staging followed by adjuvant platinum-based chemotherapy. Kaplan-Meier curves and Multivariate Cox analysis were performed to estimate 5-year overall survival (OS) and progression-free (PFS) according to the number of chemotherapy cycles. Results: Among stage I-IIA disease, twenty (19.6%) patients received 1-3 cycles, and eighty-two (80.4%) patients received at least 4 cycles of adjuvant chemotherapy. Univariate analysis revealed that the patients in 1-3cycles group had not significantly improved 5-year OS and PFS than those in the ≥ 4 cycles group (5-year OS: hazard ratio [HR] 1.21; 95% confidence interval [CI] 0.25- 5.78, p = 0.1), and 5-year PFS: HR 0.79; 95% CI 0.26- 2.34, p = 0.1). In the multivariate analysis, there was no impact of 1-3 versus ≥ 4 cycles of chemotherapy on 5-year OS (HR 1.21, 95% CI 0.25-3.89, p = 0.8) or 5-year PFS (HR 0.94, 95% CI 0.32-2.71, p = 0.9). The potential independent risk factors associated with 5-year OS and PFS included the surgery approach and FIGO stage. Conclusion: The number of cycles of platinum-based chemotherapy could not be associated with a survival benefit for patients with early-stage OCCC.
MeSH term(s)	Female ; Humans ; Ovarian Neoplasms/pathology ; Retrospective Studies ; Platinum/therapeutic use ; Neoplasm Staging ; Disease-Free Survival ; Carcinoma, Ovarian Epithelial/drug therapy ; Chemotherapy, Adjuvant ; Adenocarcinoma, Clear Cell/drug therapy ; Adenocarcinoma, Clear Cell/pathology
Chemical Substances	Platinum (49DFR088MY)
Language	English
Publishing date	2023-05-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2050444-5
ISSN	1472-6874 ; 1472-6874
ISSN (online)	1472-6874
ISSN	1472-6874
DOI	10.1186/s12905-023-02405-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Research on Music Content Recognition and Recommendation Technology Based on Deep Learning

Gao Yang

Security and Communication Networks, Vol

2022 Volume 2022

Abstract: With the development of information technology, various cloud music services are gradually emerging, which has fully changed and enriched people’s music life. How to propose the songs that consumers anticipate from the enormous song data is one of the ... ...

Abstract	With the development of information technology, various cloud music services are gradually emerging, which has fully changed and enriched people’s music life. How to propose the songs that consumers anticipate from the enormous song data is one of the key goals of the music recommendation system. This research aims to create a better music algorithm that incorporates user data for deep learning, a candidate matrix compression technique for suggestion improvement, accuracy, recall rate, and other metrics as evaluation criteria. In terms of recommendation methods, the music-music recommendation method based on predicting user behavior data and the recommendation method based on automatic tag generation are proposed. The music features obtained by audio processing are fully utilized, and the depth content information in music audio data is combined with other data for recommendation, which improves the tag quality and avoids the problem of low coverage. The results show that this model can extract the effective feature representation of songs in different classification criteria and achieve a good classification effect simultaneously.
Keywords	Technology (General) ; T1-995 ; Science (General) ; Q1-390
Subject code	780
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi-Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Follow-up water drive inefficient and ineffective cycle comprehensive management countermeasures

Gao Yang

E3S Web of Conferences, Vol 352, p

2022 Volume 01032

Abstract: When an oilfield is developed with a polymer drive, the injected polymer will play a role in improving the already formed dominant channel between oil and water wells, but after the polymer drive block is transferred to the subsequent water drive ... ...

Abstract	When an oilfield is developed with a polymer drive, the injected polymer will play a role in improving the already formed dominant channel between oil and water wells, but after the polymer drive block is transferred to the subsequent water drive development, an inefficient circulation field of injected water will be formed between oil and water wells again. This paper mainly applies dynamic and static data, combined with dynamic analysis and adjustment and optimization software of high water-bearing oilfield, to identifying the dominant channel of subsequent water drive, actively take comprehensive management countermeasures, reasonably control the injection and recovery rate, control inefficient and ineffective injection and recovery, so as to improve the effect of subsequent water drive development.
Keywords	advantageous access ; injection and extraction rate ; integrated tapping ; Environmental sciences ; GE1-350
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Unleashing the mechanism among environmental regulation, artificial intelligence, and global value chain leaps: a roadmap toward digital revolution and environmental sustainability.

Gao, Yang

Environmental science and pollution research international

2022 Volume 30, Issue 10, Page(s) 28107–28117

Abstract: Strengthening environmental regulation and adhering to the green as well as sustainable development of China's manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intelligence ...

Abstract	Strengthening environmental regulation and adhering to the green as well as sustainable development of China's manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intelligence becomes a new driving force for core competitiveness and value chain upgrading. Is there a link between environmental regulation, artificial intelligence, and the jump in global value chains? Does AI have a mediating effect? This paper draws the following conclusions through panel estimation: environmental regulation plays a positive role in global value chains, and artificial intelligence has improved the level of global value chains as well. Further analysis of the mediation effect of artificial intelligence finds that artificial intelligence replaces low-end labor, reduces labor costs for enterprises, and promotes the leap of the global value chain. The strengthening of environmental regulation has greatly improved the total factor productivity of enterprises, artificial intelligence has significantly improved production efficiency, and total factor productivity has shown a positive influence on the global value chain as well.
MeSH term(s)	Artificial Intelligence ; Industry ; Commerce ; Inventions ; Sustainable Development ; China ; Economic Development
Language	English
Publishing date	2022-11-17
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-022-23898-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Unleashing the mechanism among environmental regulation, artificial intelligence, and global value chain leaps: a roadmap toward digital revolution and environmental sustainability

Gao, Yang

Environ Sci Pollut Res. 2023 Feb., v. 30, no. 10 p.28107-28117

2023

Abstract: Strengthening environmental regulation and adhering to the green as well as sustainable development of China’s manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intelligence ...

Abstract	Strengthening environmental regulation and adhering to the green as well as sustainable development of China’s manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intelligence becomes a new driving force for core competitiveness and value chain upgrading. Is there a link between environmental regulation, artificial intelligence, and the jump in global value chains? Does AI have a mediating effect? This paper draws the following conclusions through panel estimation: environmental regulation plays a positive role in global value chains, and artificial intelligence has improved the level of global value chains as well. Further analysis of the mediation effect of artificial intelligence finds that artificial intelligence replaces low-end labor, reduces labor costs for enterprises, and promotes the leap of the global value chain. The strengthening of environmental regulation has greatly improved the total factor productivity of enterprises, artificial intelligence has significantly improved production efficiency, and total factor productivity has shown a positive influence on the global value chain as well.
Keywords	artificial intelligence ; environmental law ; industry ; labor ; supply chain ; sustainable development ; China
Language	English
Dates of publication	2023-02
Size	p. 28107-28117.
Publishing place	Springer Berlin Heidelberg
Document type	Article ; Online
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-022-23898-6
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Research on cross-modal emotion recognition based on multi-layer semantic fusion.

Xu, Zhijing / Gao, Yang

Mathematical biosciences and engineering : MBE

2024 Volume 21, Issue 2, Page(s) 2488–2514

Abstract: Multimodal emotion analysis involves the integration of information from various modalities to better understand human emotions. In this paper, we propose the Cross-modal Emotion Recognition based on multi-layer semantic fusion (CM-MSF) model, which aims ...

Abstract	Multimodal emotion analysis involves the integration of information from various modalities to better understand human emotions. In this paper, we propose the Cross-modal Emotion Recognition based on multi-layer semantic fusion (CM-MSF) model, which aims to leverage the complementarity of important information between modalities and extract advanced features in an adaptive manner. To achieve comprehensive and rich feature extraction from multimodal sources, considering different dimensions and depth levels, we design a parallel deep learning algorithm module that focuses on extracting features from individual modalities, ensuring cost-effective alignment of extracted features. Furthermore, a cascaded cross-modal encoder module based on Bidirectional Long Short-Term Memory (BILSTM) layer and Convolutional 1D (ConV1d) is introduced to facilitate inter-modal information complementation. This module enables the seamless integration of information across modalities, effectively addressing the challenges associated with signal heterogeneity. To facilitate flexible and adaptive information selection and delivery, we design the Mask-gated Fusion Networks (MGF-module), which combines masking technology with gating structures. This approach allows for precise control over the information flow of each modality through gating vectors, mitigating issues related to low recognition accuracy and emotional misjudgment caused by complex features and noisy redundant information. The CM-MSF model underwent evaluation using the widely recognized multimodal emotion recognition datasets CMU-MOSI and CMU-MOSEI. The experimental findings illustrate the exceptional performance of the model, with binary classification accuracies of 89.1% and 88.6%, as well as F1 scores of 87.9% and 88.1% on the CMU-MOSI and CMU-MOSEI datasets, respectively. These results unequivocally validate the effectiveness of our approach in accurately recognizing and classifying emotions.
MeSH term(s)	Humans ; Semantics ; Algorithms ; Emotions
Language	English
Publishing date	2024-03-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2024110
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: $\Lambda_{c}^{+}$ decays at BESIII

Gao, Yang

2022

Abstract: BESIII has made great progress in taking data which is the largest data samples near the $\Lambda_{c}^{+}\bar{\Lambda}_{c}^{-}$ threshold. We have measured the branching fraction of $\Lambda_{c}^{+}\to n\pi^{+}$ to be $(6.6\pm 1.2_{\mathrm{stat.}}\pm 0 ... ...

Abstract	BESIII has made great progress in taking data which is the largest data samples near the $\Lambda_{c}^{+}\bar{\Lambda}_{c}^{-}$ threshold. We have measured the branching fraction of $\Lambda_{c}^{+}\to n\pi^{+}$ to be $(6.6\pm 1.2_{\mathrm{stat.}}\pm 0.4_{\mathrm{syst.}})\times 10^{-4}$ with the statistical significance of 7.3 $\sigma$ firstly using $3.9\mathrm{fb}^{-1}$ $e^{+}e^{-}$ collision collected with BESIII detector at six center-of-mass energies between 4.612 and 4.699 GeV. With the result of the branching fraction of $\Lambda_{c}^{+}\to p\pi^{0}$ from Belle, the ratio of the branching fractions between $\Lambda_{c}^{+}\to n\pi^{+}$ and $\Lambda_{c}^{+}\to p\pi^{0}$ is measured to be larger than 7.2 at 90% confidence level. The branching fractions of $\Lambda_{c}^{+}\to \Lambda \pi^{+}$ and $\Lambda_{c}^{+}\to \Sigma^{0} \pi^{+}$ are measured to be $(1.31\pm 0.08_{\mathrm{stat.}}\pm 0.05_{\mathrm{syst.}})\times 10^{-2}$ and $(1.22\pm 0.08_{\mathrm{stat.}}\pm 0.07_{\mathrm{syst.}})\times 10^{-2}$, respectively, which are consistent with previous BESIII results. More results of $\Lambda_{c}^{+}$ decays will be published with better precision this year using $6.4\mathrm{fb}^{-1}$ $e^{+}e^{-}$ collision data samples between 4.600 and 4.946 GeV. Comment: 2 pages, 2 figures
Keywords	High Energy Physics - Experiment
Subject code	612
Publishing date	2022-07-27
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Recommendation Algorithm Combining Knowledge Graph and Short-Term Preferences

GAO Yang, LIU Yuan

Jisuanji kexue yu tansuo, Vol 15, Iss 6, Pp 1133-

2021 Volume 1144

Abstract: In recent years, attention has been paid to knowledge graph as auxiliary information to enhance recom-mendation increasedly. Since the goal of the knowledge graph learning task is to restore the relationship of the triples in the knowledge graph, rather ... ...

Abstract	In recent years, attention has been paid to knowledge graph as auxiliary information to enhance recom-mendation increasedly. Since the goal of the knowledge graph learning task is to restore the relationship of the triples in the knowledge graph, rather than to accomplish the recommendation task, it is difficult for the knowledge graph learning task to efficiently help the recommendation task improve the recommendation performance. In addition, user's interest is easily affected by short-term environment and mood. This paper proposes a recommendation model that is a multi-task feature learning approach for knowledge graph and short-term preferences enhanced recommendation (MKASR) in response to the above two points. Firstly, the RippleNet algorithm is used to extract the relationship pairs between the user and the knowledge graph entity, and then these relationship pairs are stored in the form of knowledge graph triples for participating in training. The bidirectional GRU (gate recurrent unit) network based on the attention mechanism is adopted from the user's recent interaction sequence of items to extract the user's short-term preferences. Secondly, this paper uses the multi-task learning method to train the knowledge graph learning module and the recommendation module. And the feature representation between user and item can be obtained. Finally, these feature representations and the short-term preferences of users are taken into account to make comprehensive recommendations to users. The experiments on real MovieLens-1M and Book-Crossing datasets demonstrate that the proposed model has improved performance compared with other recommendation algorithms in AUC, ACC, Precision and Recall evaluation indexes.
Keywords	recommender systems ; knowledge graph ; short-term preferences ; preference propagation ; multi-task learning ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	004
Language	Chinese
Publishing date	2021-06-01T00:00:00Z
Publisher	Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Nickel-Catalyzed Enantioselective Decarboxylative Acylation: Rapid, Modular Access to α-Amino Ketones.

Gao, Yang / Baran, Phil S

Angewandte Chemie (International ed. in English)

2023 Volume 62, Issue 50, Page(s) e202315203

Abstract: A new approach to the enantiocontrolled synthesis of α-amino ketone derivatives is disclosed by employing a decarboxylative acylation strategy. Thus, when an acyl chloride and an α-amido-containing redox-active ester are exposed to a nickel catalyst, ... ...

Abstract	A new approach to the enantiocontrolled synthesis of α-amino ketone derivatives is disclosed by employing a decarboxylative acylation strategy. Thus, when an acyl chloride and an α-amido-containing redox-active ester are exposed to a nickel catalyst, chiral ligand, and metal reductant, α-amido ketones are produced in good yield and high ee. The reaction exhibits broad substrate scope, can be easily scaled up, and is applied to dramatically simplify the synthesis of several known structures.
Language	English
Publishing date	2023-11-16
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2011836-3
ISSN	1521-3773 ; 1433-7851
ISSN (online)	1521-3773
ISSN	1433-7851
DOI	10.1002/anie.202315203
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