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Article ; Online: Contributing Factors to the Changes in Public and Private Transportation Mode Choice after the COVID-19 Outbreak in Urban Areas of China

Haiyan Liu / Jaeyoung Lee

Sustainability, Vol 15, Iss 5048, p

2023 Volume 5048

Abstract: The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify ... ...

Abstract	The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify contributing factors to the changes in public and private transportation mode choice behavior in China after COVID-19 based on an online questionnaire survey. In the survey, travel behaviors in three periods were studied: before the outbreak (before 27 December 2019), the peak (from 20 January to 17 March 2020), and after the peak (from 18 March to the date of the survey). A series of random-parameter bivariate Probit models was developed to quantify the relationship between individual characteristics and the changes in travel mode choice. The key findings indicated that individual sociodemographic characteristics (e.g., gender, age, ownership, occupation, residence) have significant effects on the changes in mode choice behavior. Other key findings included (1) a higher propensity to use a taxi after the peak compared to urban public transportation (i.e., bus and subway); (2) a significant impact of age on the switch from public transit to private car and two-wheelers; (3) more obvious changes in private car and public transportation modes in more developed cities. The findings from this study are expected to be useful for establishing partial and resilient policies and ensuring sustainable mobility and travel equality in the post-pandemic era.
Keywords	COVID-19 pandemic ; public transportation ; travel mode choice ; policy implications ; bivariate Probit model ; random-parameter approach ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	380
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Sensitivity analysis of disease-information coupling propagation dynamics model parameters.

Yang Yang / Haiyan Liu

PLoS ONE, Vol 17, Iss 3, p e

2022 Volume 0265273

Abstract: The disease-information coupling propagation dynamics model is a widely used model for studying the spread of infectious diseases in society, but the parameter settings and sensitivity are often overlooked, which leads to enlarged errors in the results. ... ...

Abstract	The disease-information coupling propagation dynamics model is a widely used model for studying the spread of infectious diseases in society, but the parameter settings and sensitivity are often overlooked, which leads to enlarged errors in the results. Exploring the influencing factors of the disease-information coupling propagation dynamics model and identifying the key parameters of the model will help us better understand its coupling mechanism and make accurate recommendations for controlling the spread of disease. In this paper, Sobol global sensitivity analysis algorithm is adopted to conduct global sensitivity analysis on 6 input parameters (different cross regional jump probabilities, information dissemination rate, information recovery rate, epidemic transmission rate, epidemic recovery rate, and the probability of taking preventive actions) of the disease-information coupling model with the same interaction radius and heterogeneous interaction radius. The results show that: (1) In the coupling model with the same interaction radius, the parameters that have the most obvious influence on the peak density of nodes in state AI and the information dissemination scale of the information are the information dissemination rate βI and the information recovery rate μI. In the coupling model of heterogeneous interaction radius, the parameters that have the most obvious impact on the peak density of nodes in the AI state of the information layer are: information spread rate βI, disease recovery rate μE, and the parameter that has a significant impact on the scale of information spread is the information spread rate βI and information recovery rate μI. (2) Under the same interaction radius and heterogeneous interaction radius, the parameters that have the most obvious influence on peak density of nodes in state SE and the disease transmission scale of the disease layer are the disease transmission rate βE, the disease recovery rate μE, and the probability of an individual moving across regions pjump.
Keywords	Medicine ; R ; Science ; Q
Subject code	612
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Modeling the Impact of Virtual Contact Network with Community Structure on the Epidemic Spreading

Jianlin Zhou / Haiyan Liu

Complexity, Vol

2022 Volume 2022

Abstract: The epidemic spreading is closely related to the spread of information, and it will coevolve with the information transmission. Considering that the network structure has a significant impact on network dynamics and the virtual contact networks have ... ...

Abstract	The epidemic spreading is closely related to the spread of information, and it will coevolve with the information transmission. Considering that the network structure has a significant impact on network dynamics and the virtual contact networks have obvious community structures in reality, in this article, we built a multiplex network, which contains a community structure to explore the interplay of the coupled spread dynamics. We first use a microscopic Markov chain approach to characterize the coupled disease-awareness dynamics and then analyze the effect of different factors on the coevolution of information dissemination and epidemic spreading based on the Monte Carlo simulation. The simulation results show that promoting the dissemination of information is indeed conducive to suppressing the spread of disease, but changing the process of disease transmission has no obvious effect on the information dissemination. The analysis also reveals that increasing the information transmission rate or decreasing the information recovery rate can promote the spread of information and inhibit the spread of diseases. In addition, taking preventive behaviors or decreasing the long-distance jump also helps slow the epidemic spreading.
Keywords	Electronic computers. Computer science ; QA75.5-76.95
Subject code	612
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: Research on customer lifetime value based on machine learning algorithms and customer relationship management analysis model

Yuechi Sun / Haiyan Liu / Yu Gao

Heliyon, Vol 9, Iss 2, Pp e13384- (2023)

2023

Abstract: Customer lifetime value is one of the most important tasks for enterprises to maintain customer relationships. However, due to the limitations of using a single data mining method, the measurement of customer lifetime value under the condition of ... ...

Abstract	Customer lifetime value is one of the most important tasks for enterprises to maintain customer relationships. However, due to the limitations of using a single data mining method, the measurement of customer lifetime value under the condition of noncontractual relationship has always been a research difficulty. This paper focuses on customer value measurement and customer segmentation based on customer lifecycle value theory, and carries out customer value measurement and customer segmentation research from the perspective of customer value, and constructs customer segmentation model. This paper first conducts feature engineering, such as data selection, data preprocessing, data transformation, and knowledge discovery, and then conducts customer value segmentation based on machine learning algorithms and customer relationship management analysis models and builds a customer value segmentation identification model under the condition of noncontractual relationship. Finally, empirical analysis is carried out with the real customer transaction data of the actual online shopping platform, which verifies the validity and applicability of the customer segmentation method and value calculation method proposed in this paper.
Keywords	Data mining ; Machine learning ; Customer lifetime value ; Customer segmentation ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	650 ; 670
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Role Knowledge Prompting for Document-Level Event Argument Extraction

Ruijuan Hu / Haiyan Liu / Huijuan Zhou

Applied Sciences, Vol 13, Iss 3041, p

2023 Volume 3041

Abstract: Document-level event argument extraction (DEAE) aims to identify the arguments corresponding to the roles of a given event type in a document. However, arguments scattering and arguments and roles overlapping make DEAE face great challenges. In this ... ...

Abstract	Document-level event argument extraction (DEAE) aims to identify the arguments corresponding to the roles of a given event type in a document. However, arguments scattering and arguments and roles overlapping make DEAE face great challenges. In this paper, we propose a novel DEAE model called Role Knowledge Prompting for Document-Level Event Argument Extraction (RKDE), which enhances the interaction between templates and roles through a role knowledge guidance mechanism to precisely prompt pretrained language models (PLMs) for argument extraction. Specifically, it not only facilitates PLMs to understand deep semantics but also generates all the arguments simultaneously. The experimental results show that our model achieved decent performance on two public DEAE datasets, with 3.2% and 1.4% F1 improvement on Arg-C, and to some extent, it addressed the overlapping arguments and roles.
Keywords	event argument extraction ; document-level ; prompting ; role knowledge ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	400
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Atosiban-induced acute pulmonary edema

Zuwei Yang / Wei Wu / Yi Yu / Haiyan Liu

Heliyon, Vol 9, Iss 5, Pp e15829- (2023)

A rare but severe complication of tocolysis

2023

Abstract: Background: Atosiban is commonly used to delay premature labor in pregnant women and is thought to have few side effects. Objectives: To report a case of acute pulmonary edema (APE) following administration of atosiban and conduct a systematic review to ... ...

Abstract	Background: Atosiban is commonly used to delay premature labor in pregnant women and is thought to have few side effects. Objectives: To report a case of acute pulmonary edema (APE) following administration of atosiban and conduct a systematic review to identify common characteristics and risk factors of atosiban-associated APE. Methods: Searches were performed in Pubmed, Embase, and Web of Science using the keyword “Atosiban” combined with the terms “Pulmonary edema” or “Dyspnea” or “Hypoxia” on 9th July 2022. Only case reports of atosiban-associated APE were included without language restrictions. Data were extracted from the reports, and median, range, and percentages were calculated as applicable. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal checklist for case reports. Results: Seven cases of atosiban-associated APE were included in the systematic review, including our case. APE occurred at a median gestational age of 32 + 6 weeks. Most patients were nulliparous (6/7, 85.7%) and were in multiple pregnancies (5/7, 71.4%). All patients were prescribed antenatal corticosteroids and tocolytics, with three (42.9%) receiving only atosiban and four (57.1%) receiving atosiban and other tocolytics. The median interval from starting atosiban administration to APE onset was about 40 h, and three patients (42.9%) showed symptoms 2–10 h after the end of atosiban treatment. Radiographic examinations (chest X-ray and/or computer tomography scan) confirmed APE in all patients and pleural effusion in four patients (57.1%). Five patients (71.4%) underwent emergency cesarean section, one patient (14.3%) with twin pregnancy had vaginal delivery with the help of suction cup and forceps, and another patient (14.3%) continued the pregnancy. All patients recovered well after administration of oxygen, diuresis, and other supportive therapy. Conclusion: Atosiban may cause acute pulmonary edema in patients with underlying risk factors. This complication remains rare, but caution during tocolytic ...
Keywords	Atosiban ; Acute pulmonary edema ; Pregnancy ; Preterm birth ; Tocolytics ; Hypoxia ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	610
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lentinan progress in inflammatory diseases and tumor diseases

Guangda Zhou / Haiyan Liu / Ying Yuan / Qian Wang / Lanping Wang / Jianghua Wu

European Journal of Medical Research, Vol 29, Iss 1, Pp 1-

2024 Volume 12

Abstract: Abstract Shiitake mushrooms are a fungal food that has been recorded in Chinese medicine to nourish the blood and qi. Lentinan (lLNT) is an active substance extracted from shiitake mushrooms with powerful antioxidant, anti-inflammatory, anti-tumor ... ...

Abstract	Abstract Shiitake mushrooms are a fungal food that has been recorded in Chinese medicine to nourish the blood and qi. Lentinan (lLNT) is an active substance extracted from shiitake mushrooms with powerful antioxidant, anti-inflammatory, anti-tumor functions. Inflammatory diseases and cancers are the leading causes of death worldwide, posing a serious threat to human life and health and posing enormous challenges to global health systems. There is still a lack of effective treatments for inflammatory diseases and cancer. LNT has been approved as an adjunct to chemotherapy in China and Japan. Studies have shown that LNT plays an important role in the treatment of inflammatory diseases as well as oncological diseases. Moreover, clinical experiments have confirmed that LNT combined with chemotherapy drugs has a significant effect in improving the prognosis of patients, enhancing their immune function and reducing the side effects of chemotherapy in lung cancer, colorectal cancer and gastric cancer. However, the relevant mechanism of action of the LNT signaling pathway in inflammatory diseases and cancer. Therefore, this article reviews the mechanism and clinical research of LNT in inflammatory diseases and tumor diseases in recent years.
Keywords	Lentinan ; Inflammatory diseases ; Tumor ; Cancer ; Medicine ; R
Subject code	610
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Influence of the Size of BN NSs on Silkworm Development and Tissue Microstructure

Vivian Andoh / Haiyan Liu / Liang Chen / Lin Ma / Keping Chen

Nanomaterials, Vol 13, Iss 1502, p

2023 Volume 1502

Abstract: Boron nitride nanosheets (BN NSs) have emerged as promising materials in a wide range of biomedical applications. Despite the extensive studies on these bio-nano interfacial systems, one critical concern is their toxicity, which is affected by a variety ... ...

Abstract	Boron nitride nanosheets (BN NSs) have emerged as promising materials in a wide range of biomedical applications. Despite the extensive studies on these bio-nano interfacial systems, one critical concern is their toxicity, which is affected by a variety of factors, including size. This study aimed at assessing the relationship between BN NSs size and toxicity. Two silkworm strains (qiufeng × baiyu and Nistari 7019) were used as model organisms to investigate the effect of different sizes of BN NSs (BN NSs-1, thickness of 41.5 nm and diameter of 270.7 nm; BN NSs-2, thickness of 48.2 nm and diameter of 562.2 nm) on silkworm mortality, growth, cocoon weight, and tissue microstructure. The findings show that exposure to BN NSs in this work has no lethal adverse effects on silkworm growth or tissue microstructure. BN NSs have a higher effect on the growth rate of qiufeng × baiyu compared to Nistari 7019, demonstrating that the same treatment does not favorably affect the Nistari 7019 strain, as there is no significant increase in cocoon weight. Overall, the study suggests that the sizes of BN NSs employed in this study are relatively safe and have less negative impact on silkworms. This offers significant insights into the effect of BN NSs size, a crucial factor to consider for their safe use in biomedical applications.
Keywords	boron nitride nanosheets ; size effect ; silkworm development ; tissue microstructure ; Chemistry ; QD1-999
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Establishment of the diagnostic and prognostic nomograms for pancreatic cancer with bone metastasis

Zongtai Liu / Haiyan Liu / Dalin Wang

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 15

Abstract: Abstract Bone metastasis (BM) is rare in patients with pancreatic cancer (PC), but often neglected at the initial diagnosis and treatment. Bone metastasis is associated with a worse prognosis. This study was aimed to perform a large data analysis to ... ...

Abstract	Abstract Bone metastasis (BM) is rare in patients with pancreatic cancer (PC), but often neglected at the initial diagnosis and treatment. Bone metastasis is associated with a worse prognosis. This study was aimed to perform a large data analysis to determine the predictors and prognostic factors of BM in PC patients and to develop two nomograms to quantify the risks of BM and the prognosis of PC patients with BM. In the present study, we reviewed and collected the data of patients who were diagnosed as PC from 2010 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses were used together to screen and validate the risk factors for BM in PC patients. The independent prognostic factors for PC patients with BM were identified by Cox regression analysis. Finally, two nomograms were established via calibration curves, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). This study included 16,474 PC patients from the SEER database, and 226 of them were diagnosed with BM. The risk factors of BM for PC patients covered age, grade, T stage, N stage, tumor size, and primary site. The independent prognostic factors for PC patients with BM included age, race, grade, surgery, and lung metastasis. The AUC of the diagnostic nomogram was 0.728 in the training set and 0.690 in the testing set. In the prognostic nomogram, the AUC values of 6/12/18 month were 0.781/0.833/0.849 in the training set and 0.738/0.781/0.772 in the testing set. The calibration curve and DCA furtherly indicated the satisfactory clinical consistency of the nomograms. These nomograms could be accurate and personalized tools to predict the incidence of BM in PC patients and the prognosis of PC patients with BM. The nomograms can help clinicians make more personalized and effective treatment choices.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Development and Validation of Nomograms to Assess Risk Factors and Overall Survival Prediction for Lung Metastasis in Young Patients with Osteosarcoma

Zongtai Liu / Guibin Li / Haiyan Liu / Jiabo Zhu / Dalin Wang

International Journal of Clinical Practice, Vol

A SEER-Based Study

2022 Volume 2022

Abstract: Background. To establish two nomograms to quantify the diagnostic factors of lung metastasis (LM) and their role in assessing prognosis in young patients with LM osteosarcoma. Methods. A total of 618 osteosarcoma young patients from 2010 to 2015 were ... ...

Abstract	Background. To establish two nomograms to quantify the diagnostic factors of lung metastasis (LM) and their role in assessing prognosis in young patients with LM osteosarcoma. Methods. A total of 618 osteosarcoma young patients from 2010 to 2015 were included from the Surveillance, Epidemiology, and End Results (SEER) database. Another 131 patients with osteosarcoma from local hospitals were also collected as an external validation set. Patients were randomized into training sets (n = 434) and validation sets (n = 184) with a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to identify the risk factor for LM and were used to construct the nomogram. Risk variables for the overall survival rate of patients with LM were evaluated by Cox regression. Another nomogram was also constructed to predict survival rates. The results were validated using bootstrap resampling and retrospective research on 131 osteosarcoma young patients from 2010 to 2019 at three local hospitals. Results. There were 114 (18.45%) patients diagnosed as LM at initial diagnosis. The multivariate logistic regression analysis suggested that T stage, N stage, and bone metastasis were independent risk factors for LM in newly diagnosed young osteosarcoma patients (P<0.001). The ROC analysis revealed that area under the curve (AUC) values were 0.751, 0.821, and 0.735 in the training set, internal validation set, and external validation set, respectively, indicating good predictive discrimination. The multivariate Cox proportional hazard regression analysis suggested that age, surgery, chemotherapy, primary site, and bone metastasis were prognostic factors for young osteosarcoma patients with LM. The time-dependent ROC curves showed that the AUCs for predicting 1-year, 2-year, and 3-year survival rates were 0.817, 0.792, and 0.815 in the training set and 0.772, 0.807, and 0.804 in the internal validation set, respectively. As for the external validation set, the AUCs for predicting 1-year, 2-year, and 3-year survival ...
Keywords	Medicine ; R
Subject code	610
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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