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Article ; Online: Improving healthcare workforce diversity.

Zou, Yang

Frontiers in health services

2023 Volume 3, Page(s) 1082261

Language	English
Publishing date	2023-02-13
Publishing country	Switzerland
Document type	Journal Article
ISSN	2813-0146
ISSN (online)	2813-0146
DOI	10.3389/frhs.2023.1082261
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Article ; Online: Bridging the mental health gap: unveiling and mitigating the hidden toll of workplace behaviors on diverse populations.

Zou, Yang

Frontiers in public health

2023 Volume 11, Page(s) 1308099

Abstract: This study investigates the critical issue of mental health disparities within diverse populations in modern workplaces, a concern that significantly affects both individuals and organizational structures. By focusing on how prevailing workplace ... ...

Abstract	This study investigates the critical issue of mental health disparities within diverse populations in modern workplaces, a concern that significantly affects both individuals and organizational structures. By focusing on how prevailing workplace behaviors, including implicit biases, microaggressions, and the scarcity of diversity in leadership, exacerbate these disparities, the research highlights the urgent need for attention and action in this area. The mental health gap-disparities in conditions and access to care among different workplace groups-emerges from systemic inequalities and stigmatization, deeply influencing employee productivity, creativity, collaboration, and retention. Our research underscores the disproportionate impact of this gap on diverse populations, characterized by varying ethnicity, gender, age, socio-economic status, and other unique identity attributes. The paper articulates the substantial economic repercussions for organizations, manifesting as reduced productivity, increased absenteeism, and higher turnover rates. Recommendations include the implementation of cultural competency training, promotion of inclusive leadership, investment in tailored mental health resources and fostering open dialog about mental health. These strategies are pivotal in creating an inclusive, resilient, and harmonious work environment. Our findings aim to catalyze a shift in organizational practices toward mental well-being, advocating for comprehensive strategies to bridge the mental health divide in workplaces, thereby enhancing overall organizational health and cohesion.
MeSH term(s)	Humans ; Mental Health ; Workplace
Language	English
Publishing date	2023-11-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1308099
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Article ; Online: The enhanced affinity of moderately hydrolyzed whey protein to EGCG promotes the isoelectric separation and unlocks the protective effects on polyphenols.

Ma, Zhiyuan / Zhao, Jiale / Zou, Yang / Mao, Xueying

Food chemistry

2024 Volume 450, Page(s) 138833

Abstract: The instability and discoloration of (-)-epigallocatechin-3-gallate (EGCG) constrain its application in functional dairy products. Concurrently, challenges persist in the separation and utilization of whey in the dairy industry. By harnessing the ... ...

Abstract	The instability and discoloration of (-)-epigallocatechin-3-gallate (EGCG) constrain its application in functional dairy products. Concurrently, challenges persist in the separation and utilization of whey in the dairy industry. By harnessing the interactions between polyphenols and whey proteins or their hydrolysates, this study proposed a method that involved limited enzymatic hydrolysis followed by the addition of EGCG and pH adjustment around the isoelectric point to obtain whey protein hydrolysates (WPH)-EGCG. Over 92 % of protein-EGCG complexes recovered from whey while ensuring the preservation of α-lactalbumin. The combination between EGCG and WPH depended on hydrogen bonding and hydrophobic interactions, significantly enhanced the thermal stability and storage stability of EGCG. Besides, the intestinal phase retention rate of EGCG in WPH-EGCG complex was significantly increased by 23.67 % compared to free EGCG. This work represents an exploratory endeavor in the improvement of EGCG stability and expanding the utilization approaches of whey.
Language	English
Publishing date	2024-02-21
Publishing country	England
Document type	Journal Article
ZDB-ID	243123-3
ISSN	1873-7072 ; 0308-8146
ISSN (online)	1873-7072
ISSN	0308-8146
DOI	10.1016/j.foodchem.2024.138833
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Thesis ; Online: Weakly Supervised Visual Understanding

Zou, Yang

2020

Abstract: Deep neural networks have led to remarkable progress in visual recognition. A key driving factor is the availability of abundant labeled data, enabling effective model training. However, the amount of labeled data is often limited by the high cost of ... ...

Abstract	Deep neural networks have led to remarkable progress in visual recognition. A key driving factor is the availability of abundant labeled data, enabling effective model training. However, the amount of labeled data is often limited by the high cost of manual annotation. The reliance on large-scale labeled data has become one of the key bottlenecks in creating intelligent systems. There exists data with weak annotations containing useful - yet not perfect - knowledge about the given tasks. Examples of weak annotations include possibly wrong labels, image-level rather than pixel-level labels for semantic segmentation, etc. Weak annotations are relatively cheap. If we could create powerful recognition systems by such supervision, the labeling cost can be vastly reduced. So can we enable machines to learn well with less supervision as humans? This thesis explores visual learning with weakly supervised data. Our core idea is to enable models to capture certain inductive biases or desired properties by leveraging the prior knowledge and the data regularities. We have rich prior knowledge about weakly supervised data - we should not place 100% confidence on potentially wrong labels, image-level labels indicate object presence, etc. Modeling such prior knowledge can regularize the solutions. Also the data has natural regularities - a horizontally flipped image mirrors the original one, various cats are more similar to each other than to a bike, etc. Such natural regularity in data also imposes regularity on the tasks and models - pixel-level classification of an image mirrors the prediction of the horizontally flipped input. We explore various forms of inductive biases in representation, predicting outputs and prior knowledge in labels. We show the effectiveness of our ideas on learning with various weak supervision for several important computer vision applications: image classification, semantic segmentation, object detection, person re-identification, and pose orientation estimation. We specifically focus on three types of weak supervision: incomplete supervision, where only a subset of training data is given with labels; inexact supervision, where the training data are given with only coarse-grained labels; and inaccurate supervision, where the given labels are not always correct.
Keywords	Artificial intelligence\|Information Technology\|Information science
Subject code	006
Language	ENG
Publishing date	2020-01-01 00:00:01.0
Publisher	Carnegie Mellon University
Publishing country	us
Document type	Thesis ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Impacts of farmer cooperative membership on household income and inequality: Evidence from a household survey in China

Zou, Yang / Wang, Qingbin

Agricultural and food economics. 2022 Dec., v. 10, no. 1

2022

Abstract: While joining farmer cooperatives has been identified as a way for farmers, especially small farmers, to overcome their limitations in the marketplace and increase their income, this paper presents an analytical framework for examining how farmer ... ...

Abstract	While joining farmer cooperatives has been identified as a way for farmers, especially small farmers, to overcome their limitations in the marketplace and increase their income, this paper presents an analytical framework for examining how farmer cooperative may increase farmer income in rural China, empirically assesses the impacts of such membership on household income, and examines how the membership may affect income inequality. Data from a large-scale survey of rural households in China are used to examine the impacts of farmer cooperative membership and other factors on household income through a multivariate regression analysis and to test whether the impacts are different across income groups through a quantile regression analysis. The propensity score matching technique is used to address potential self-selection bias problems in the dataset and quantile regression is used to examine the impact for different income quantiles or groups of farmers. The empirical results indicate that farmers participating in professional cooperatives, on average, earned significantly higher income than their counterparts, but the positive impact was not statistically significant for low-income quantiles. This finding suggests that encouraging the development of and participation in farmer cooperatives could increase the average income but may not contribute directly to the policy goal of reducing income inequality in rural China.
Keywords	data collection ; farm income ; farmers ; household income ; household surveys ; issues and policy ; markets ; regression analysis ; social inequality ; China
Language	English
Dates of publication	2022-12
Size	p. 17.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	2716609-0
ISSN	2193-7532
ISSN	2193-7532
DOI	10.1186/s40100-022-00222-x
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Remnant cholesterol can identify individuals at higher risk of metabolic syndrome in the general population.

Zou, Yang / Kuang, Maobin / Zhong, Yanjia / Jiang, Chunyuan

Scientific reports

2023 Volume 13, Issue 1, Page(s) 5957

Abstract: Remnant cholesterol (RC) is a highly atherogenic lipid. Previous studies have shown that RC was closely associated with many metabolism-related diseases. However, the relationship of RC with metabolic syndrome (MetS) remains unclear. This study's ... ...

Abstract	Remnant cholesterol (RC) is a highly atherogenic lipid. Previous studies have shown that RC was closely associated with many metabolism-related diseases. However, the relationship of RC with metabolic syndrome (MetS) remains unclear. This study's objective is to investigate the relationship of RC with MetS. A total of 60,799 adults who received health assessments were included in this study. RC was calculated by subtracting the directly measured values for low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) from total cholesterol (TC) and divided into 5 groups according to its quintile. MetS diagnosis according to National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) definitions. Application of receiver operating characteristic (ROC) curve analysis and multivariate logistic regression to assess the association of RC with MetS. In RC quintile groups, the prevalence of MetS was 0.84, 1.10, 1.92, 3.87 and 37.71%, respectively. Multivariate logical regression analysis showed that RC and MetS maintained a stable independent positive correlation between both sexes. An interaction test further showed that the MetS risk associated with RC was significantly higher in women than in men. Moreover, ROC analysis results showed that RC had high accuracy in identifying MetS, especially among young and middle-aged men [(area under the curve: AUC) < 30 years: 0.9572, 30-39 years: 0.9306, 40-49 years: 0.9067]. The current study provided the first evidence of a positive association between RC and MetS, and that this correlation was stronger in women than in man, which may be due to the relative deficiency of estrogen in women.
MeSH term(s)	Adult ; Male ; Middle Aged ; Humans ; Female ; Metabolic Syndrome/diagnosis ; Metabolic Syndrome/epidemiology ; Cholesterol ; Cholesterol, HDL ; Cholesterol, LDL ; ROC Curve ; Risk Factors
Chemical Substances	Cholesterol (97C5T2UQ7J) ; Cholesterol, HDL ; Cholesterol, LDL
Language	English
Publishing date	2023-04-12
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-33276-y
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Article: [Genetic analysis of a case of mild epilepsy due to variant of SCN9A gene].

Yin, Xunqiang / Niu, Yuping / Zou, Yang / Gao, Yuan

Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese journal of medical genetics

2023 Volume 40, Issue 3, Page(s) 344–348

Abstract: Objective: To explore the genetic etiology of a patient with epilepsy and provide genetic counseling.: Methods: A patient who had visited the Center for Reproductive Medicine of Shandong University on November 11, 2020 was selected as the study ... ...

Abstract	Objective: To explore the genetic etiology of a patient with epilepsy and provide genetic counseling. Methods: A patient who had visited the Center for Reproductive Medicine of Shandong University on November 11, 2020 was selected as the study subject, and her clinic information was collected. Candidate variant was identified through whole exome sequencing (WES), and Sanger sequencing was used for validation. Possible transcriptional changes caused by the variant was detected by reverse transcription-PCR and Sanger sequencing. Results: The patient was a 35-year-old female with no fever at the onset, loss of consciousness and abnormal firing in the temporal lobe, manifesting predominantly as convulsions and fainting. WES revealed that she had harbored a heterozygous c.2841+5G>A variant of the SCN9A gene, which was verified by Sanger sequencing. cDNA sequencing confirmed that 154 bases were inserted between exons 16 and 17 of the SCN9A gene, which probably produced a truncated protein and affected the normal function of the SCN9A protein. Based on the guidelines from the American College of Medical Genetics and Genomics, the c.2841+5G>A variant was classified as likely pathogenic (PVS1_Strong+PM2_Supporting). Conclusion: The c.2841+5G>A variant of the SCN9A gene probably underlay the epilepsy in this patient. Above finding has enriched the variant spectrum of the SCN9A gene and provided a basis for the prenatal diagnosis and preimplantation genetic testing for this patient.
MeSH term(s)	Humans ; Female ; Pregnancy ; Adult ; Epilepsy/genetics ; Seizures ; Exons ; DNA, Complementary ; Genetic Counseling ; NAV1.7 Voltage-Gated Sodium Channel
Chemical Substances	DNA, Complementary ; SCN9A protein, human ; NAV1.7 Voltage-Gated Sodium Channel
Language	Chinese
Publishing date	2023-03-01
Publishing country	China
Document type	Case Reports ; English Abstract ; Journal Article
ISSN	1003-9406
ISSN	1003-9406
DOI	10.3760/cma.j.cn511374-20211014-00814
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Article ; Online: Position-Wise Gated Res2Net-Based Convolutional Network with Selective Fusing for Sentiment Analysis.

Zhou, Jinfeng / Zeng, Xiaoqin / Zou, Yang / Zhu, Haoran

Entropy (Basel, Switzerland)

2023 Volume 25, Issue 5

Abstract: Sentiment analysis (SA) is an important task in natural language processing in which convolutional neural networks (CNNs) have been successfully applied. However, most existing CNNs can only extract predefined, fixed-scale sentiment features and cannot ... ...

Abstract	Sentiment analysis (SA) is an important task in natural language processing in which convolutional neural networks (CNNs) have been successfully applied. However, most existing CNNs can only extract predefined, fixed-scale sentiment features and cannot synthesize flexible, multi-scale sentiment features. Moreover, these models' convolutional and pooling layers gradually lose local detailed information. In this study, a new CNN model based on residual network technology and attention mechanisms is proposed. This model exploits more abundant multi-scale sentiment features and addresses the loss of locally detailed information to enhance the accuracy of sentiment classification. It is primarily composed of a position-wise gated Res2Net (PG-Res2Net) module and a selective fusing module. The PG-Res2Net module can adaptively learn multi-scale sentiment features over a large range using multi-way convolution, residual-like connections, and position-wise gates. The selective fusing module is developed to fully reuse and selectively fuse these features for prediction. The proposed model was evaluated using five baseline datasets. The experimental results demonstrate that the proposed model surpassed the other models in performance. In the best case, the model outperforms the other models by up to 1.2%. Ablation studies and visualizations further revealed the model's ability to extract and fuse multi-scale sentiment features.
Language	English
Publishing date	2023-04-30
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e25050740
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Article ; Online: Linking Cultural Tightness, Components of Norm Activation and COVID-19 Preventive Behaviors among University Students: Evidence from Beijing, China.

Zou, Yang / Liu, Xianwei / Yu, Miaomiao / Deng, Yichu

International journal of environmental research and public health

2023 Volume 20, Issue 6

Abstract: The ongoing COVID-19 pandemic has imposed greater challenges and more stringent requirements on higher education institutions (HEIs). However, limited empirical research has been devoted to identifying external and internal factors that may promote ... ...

Abstract	The ongoing COVID-19 pandemic has imposed greater challenges and more stringent requirements on higher education institutions (HEIs). However, limited empirical research has been devoted to identifying external and internal factors that may promote individual preventive behaviors during the COVID-19 pandemic within the higher education context. This study proposed and examined an extended norm activation model (NAM) concerning the relationships among cultural tightness, original NAM components, and COVID-19 preventive behaviors. An online survey was conducted with a sample of 3693 university students from 18 universities in Beijing, China. The results showed that cultural tightness was positively associated with respondents' COVID-19 preventive behaviors. Three original NAM variables, namely, awareness of consequences, the ascription of responsibility, and personal norms, played a chain mediating role in the relationship between cultural tightness and COVID-19 preventive behaviors. Theoretical and practical implications regarding the findings of this study and suggestions for future research are discussed.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Universities ; Pandemics/prevention & control ; Beijing/epidemiology ; Students ; China/epidemiology
Language	English
Publishing date	2023-03-10
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2175195-X
ISSN	1660-4601 ; 1661-7827
ISSN (online)	1660-4601
ISSN	1661-7827
DOI	10.3390/ijerph20064905
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Article ; Online: Auto-Encoding Generative Adversarial Networks towards Mode Collapse Reduction and Feature Representation Enhancement.

Zou, Yang / Wang, Yuxuan / Lu, Xiaoxiang

Entropy (Basel, Switzerland)

2023 Volume 25, Issue 12

Abstract: Generative Adversarial Nets (GANs) are a kind of transformative deep learning framework that has been frequently applied to a large variety of applications related to the processing of images, video, speech, and text. However, GANs still suffer from ... ...

Abstract	Generative Adversarial Nets (GANs) are a kind of transformative deep learning framework that has been frequently applied to a large variety of applications related to the processing of images, video, speech, and text. However, GANs still suffer from drawbacks such as mode collapse and training instability. To address these challenges, this paper proposes an Auto-Encoding GAN, which is composed of a set of generators, a discriminator, an encoder, and a decoder. The set of generators is responsible for learning diverse modes, and the discriminator is used to distinguish between real samples and generated ones. The encoder maps generated and real samples to the embedding space to encode distinguishable features, and the decoder determines from which generator the generated samples come and from which mode the real samples come. They are jointly optimized in training to enhance the feature representation. Moreover, a clustering algorithm is employed to perceive the distribution of real and generated samples, and an algorithm for cluster center matching is accordingly constructed to maintain the consistency of the distribution, thus preventing multiple generators from covering a certain mode. Extensive experiments are conducted on two classes of datasets, and the results visually and quantitatively demonstrate the preferable capability of the proposed model for reducing mode collapse and enhancing feature representation.
Language	English
Publishing date	2023-12-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e25121657
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