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Article ; Online: A Domain-Based, Adaptive, Multi-Scale, Inter-Subject Sleep Stage Classification Network

Zhiwei Zhang / Minfang Tang

Applied Sciences, Vol 13, Iss 3474, p

2023 Volume 3474

Abstract: Sleep stage classification is of great importance in sleep analysis, which provides information for the diagnosis and monitoring of sleep-related conditions. To accurately analyze sleep structure under comfortable conditions, many studies have applied ... ...

Abstract	Sleep stage classification is of great importance in sleep analysis, which provides information for the diagnosis and monitoring of sleep-related conditions. To accurately analyze sleep structure under comfortable conditions, many studies have applied deep learning to sleep staging based on single-lead electrocardiograms (ECGs). However, there is still great room for improvement in inter-subject classification. In this paper, we propose an end-to-end, multi-scale, subject-adaptive network that improves the performance of the model according to the model architecture, training method, and loss calculation. In our investigation, a multi-scale residual feature encoder extracted various details to support the feature extraction of single-lead ECGs in different situations. After taking the domain shift caused by individual differences and acquisition conditions into consideration, we introduced a domain-aligning layer to confuse the domain. Moreover, to enhance the performance of the model, the multi-class focal loss was used to reduce the negative impact of class imbalance on the learning of the model, and the loss of sequence prediction was added to the classification task to assist the model in judging sleep stages. The model was evaluated on the public test datasets SHHS2, SHHS1, and MESA, and we obtained mean accuracies (Kappa) of 0.849 (0.837), 0.827 (0.790), and 0.868 (0.840) for awake/light sleep/deep sleep/REM stage classification, which confirms that this is an improved solution compared to the baseline. The model also performed outstandingly in cross-dataset testing. Hence, this article makes valuable contributions toward improving the reliability of sleep staging.
Keywords	multi-scale inter-subject network ; sleep staging ; single-lead ECG ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
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: WD Repeat and HMG Box DNA Binding Protein 1

Zhiwei Zhang / Qing Zhu

International Journal of Molecular Sciences, Vol 24, Iss 12494, p

An Oncoprotein at the Hub of Tumorigenesis and a Novel Therapeutic Target

2023 Volume 12494

Abstract: WD repeat and HMG-box DNA binding protein 1 (WDHD1) is a highly conserved gene from yeast to humans. It actively participates in DNA replication, playing a crucial role in DNA damage repair and the cell cycle, contributing to centromere formation and ... ...

Abstract	WD repeat and HMG-box DNA binding protein 1 (WDHD1) is a highly conserved gene from yeast to humans. It actively participates in DNA replication, playing a crucial role in DNA damage repair and the cell cycle, contributing to centromere formation and sister chromosome segregation. Notably, several studies have implicated WDHD1 in the development and progression of diverse tumor types, including esophageal carcinoma, pulmonary carcinoma, and breast carcinoma. Additionally, the inhibitor of WDHD1 has been found to enhance radiation sensitivity, improve drug resistance, and significantly decrease tumor cell proliferation. This comprehensive review aims to provide an overview of the molecular structure, biological functions, and regulatory mechanisms of WDHD1 in tumors, thereby establishing a foundation for future investigations and potential clinical applications of WDHD1.
Keywords	WD repeat and HMG-box DNA binding protein 1 ; proliferation ; DNA damage ; tumorigenesis ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Language	English
Publishing date	2023-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A three-class carbon pool system for normalizing carbon mapping and accounting in coastal areas

Dahai Liu / Zhiwei Zhang / Zhenhang Liu / Yuan Chi

Ecological Indicators, Vol 158, Iss , Pp 111537- (2024)

2024

Abstract: Climate change is a key issue receiving increasing global attention. Coastal areas play an important role in mitigating climate change because of enormous potentials for carbon sequestration. Simulating and evaluating the carbon storage, increment, and ... ...

Abstract	Climate change is a key issue receiving increasing global attention. Coastal areas play an important role in mitigating climate change because of enormous potentials for carbon sequestration. Simulating and evaluating the carbon storage, increment, and value of coastal areas is of considerable importance in achieving carbon neutrality. In this study, the South Coast of Hangzhou Bay in China was selected as the study area. A three-class carbon pool system was established based on vegetation and soil and considering the coastline as the boundary for comprehensively revealing the carbon sink in coastal areas and accurately distinguishing the roles of different carbon pools. Then, the maps of carbon storage and increment were generated by integrating the field and remote sensing data through “from point to area” spatial simulations. An accounting list was developed for systematically summarizing, precisely quantifying, and visually displaying the carbon storage, increment, and value following the three-class carbon pools. Results indicated that the carbon sink showed a gradient change from sea to land. Salt marshes had low storage but high increment, whereas areas above the coastline had the opposite characteristics. The total carbon storage of vegetation and soil were 1417.94 Gg and 3359.07 Gg, respectively, and their carbon increments during 2011–2022 were 309.17 Gg/yr and 29.46 Gg/yr, respectively. The carbon storage per area of vegetation and soil were 27.66 Mg/ha and 53.09 Mg/ha, respectively, and their carbon increments during 2011–2022 were 6.03 Mg/(ha yr) and 0.47 Mg/(ha yr), respectively. As the main body of blue carbon, salt marshes have achieved distinctly higher increment than the adjacent areas above the coastline. The carbon increment per area of soil was lower than 1/5 of vegetation in salt marshes. Mudflats had low carbon increment but large storage because of the extensive area. Alien species had higher increment in terms of vegetation but similar one from the perspective of soil compared with ...
Keywords	Carbon pool ; Coastal areas ; Carbon sink ; Carbon mapping ; Carbon accounting ; South Coast of Hangzhou Bay ; Ecology ; QH540-549.5
Subject code	550 ; 333
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Learning from real world data about combinatorial treatment selection for COVID-19

Song Zhai / Zhiwei Zhang / Jiayu Liao / Xinping Cui

Frontiers in Artificial Intelligence, Vol

2023 Volume 6

Abstract: COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease ... ...

Abstract	COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease while considering patient and disease characteristics. This paper reports a case study of combinatorial treatment selection for COVID-19 based on real-world data from a large hospital in Southern China. In this observational study, 417 confirmed COVID-19 patients were treated with various combinations of drugs and followed for four weeks after discharge (or until death). Treatment failure is defined as death during hospitalization or recurrence of COVID-19 within four weeks of discharge. Using a virtual multiple matching method to adjust for confounding, we estimate and compare the failure rates of different combinatorial treatments, both in the whole study population and in subpopulations defined by baseline characteristics. Our analysis reveals that treatment effects are substantial and heterogeneous, and that the optimal combinatorial treatment may depend on baseline age, systolic blood pressure, and c-reactive protein level. Using these three variables to stratify the study population leads to a stratified treatment strategy that involves several different combinations of drugs (for patients in different strata). Our findings are exploratory and require further validation.
Keywords	G-computation ; virtual multiple matching ; subgroup analysis ; multiple comparisons with the best ; COVID-19 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	610
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Data-driven XGBoost model for maximum stress prediction of additive manufactured lattice structures

Zhiwei Zhang / Yuyan Zhang / Yintang Wen / Yaxue Ren

Complex & Intelligent Systems, Vol 9, Iss 5, Pp 5881-

2023 Volume 5892

Abstract: Abstract Lattice structures created using additive manufacturing technology inevitably produce inherent defects that seriously affect their mechanical properties. Predicting and analysing the effect of defects on the maximum stress is very important for ... ...

Abstract	Abstract Lattice structures created using additive manufacturing technology inevitably produce inherent defects that seriously affect their mechanical properties. Predicting and analysing the effect of defects on the maximum stress is very important for improving the lattice structure design and process. This study mainly used the finite element method to calculate the lattice structure constitutive equation. The increase in defect type and quantity leads to difficulty in modelling and reduces calculation accuracy. We established a data-driven extreme gradient enhancement (XGBoost) with hyperparameter optimization to predict the maximum stress of the lattice structure in additive manufacturing. We used four types of defect characteristics that affect the mechanical properties—the number of layers, thick-dominated struts (oversize), thin-dominated struts (undersizing), and bend-dominated struts (waviness)—as the input parameters of the model. The hyperparameters of the basic XGBoost model were optimised according to the diversity of the inherent defect characteristics of the lattice structure, while the parameters selected by experience were replaced using the Gaussian process method in Bayesian optimization to improve the model’s generalisation ability. The prediction datasets included the type and number of defects obtained via computer tomography and the calculation results of the finite element model with the corresponding defects implanted. The root mean square error and R-squared error of the maximum stress prediction were 17.40 and 0.82, respectively, indicating the effectiveness of the model proposed in this paper. Furthermore, we discussed the influence of the four types of defects on the maximum stress, among which the thick strut defect had the greatest influence.
Keywords	Additive manufacturing ; Lattice structure ; Inherent defects ; Maximum stress prediction ; XGBoost ; Electronic computers. Computer science ; QA75.5-76.95 ; Information technology ; T58.5-58.64
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Springer
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Carbon nanotube‐supported mixed‐valence Mn3O4 electrodes for high‐performance lithium‐oxygen batteries

Yuting Zhu / Jing Gao / Zhongxiao Wang / Rui Sun / Longwei Yin / Chengxiang Wang / Zhiwei Zhang

ChemPhysMater, Vol 3, Iss 1, Pp 94-

2024 Volume 102

Abstract: Lithium–oxygen batteries (LOBs) have extensive applications because of their ultra-high energy densities. However, the practical application of LOBs is limited by several factors, such as a high overpotential, poor cycle stability, and limited rate ... ...

Abstract	Lithium–oxygen batteries (LOBs) have extensive applications because of their ultra-high energy densities. However, the practical application of LOBs is limited by several factors, such as a high overpotential, poor cycle stability, and limited rate capacity. In this paper, we describe the successful uniform loading of Mn3O4 nanoparticles onto multi-walled carbon nanotubes (Mn3O4@CNT). CNTs form a conductive network and expose numerous catalytically active sites, and the one-dimensional porous structure provides a convenient channel for the transmission of Li+ and O2 in LOBs. The electronic conductivity and electrocatalytic activity of Mn3O4@CNT are significantly better than those of MnO@CNT because of the inherent driving force facilitating charge transfer between different valence metal ions. Therefore, the Mn3O4@CNT cathode obtains a low overpotential (0.76 V at a limited capacity of 1000 mAh g−1), high initial discharge capacity (16895 mAh g−1 at 200 mA g−1), and long cycle life (97 cycles at 200 mA g−1). This study provides evidence that transition metal oxides with mixed-valence states are suitable for application as efficient cathodes for LOBs.
Keywords	Mixed-valence states ; Carbon nanotube ; Electrode reaction kinetics ; Lithium–oxygen batteries ; Chemistry ; QD1-999 ; Physics ; QC1-999
Subject code	541
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	KeAi Communications Co., Ltd.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The relationship between education attainment and gout, and the mediating role of modifiable risk factors

Xin Huang / Xin Chen / Qixi Liu / Zhiwei Zhang / Juan Miao / Yuchan Lai / Jinqing Wu

Frontiers in Public Health, Vol

a Mendelian randomization study

2024 Volume 11

Abstract: ObjectiveTo investigate the causal relationship between educational attainment (EA) and gout, as well as the potential mediating effects of individual physical status (IPS) such as body mass index (BMI) and systolic blood pressure (SBP) and lifestyle ... ...

Abstract	ObjectiveTo investigate the causal relationship between educational attainment (EA) and gout, as well as the potential mediating effects of individual physical status (IPS) such as body mass index (BMI) and systolic blood pressure (SBP) and lifestyle habits (LH) including alcohol intake frequency (drinking), current tobacco smoking (smoking), and time spent watching television (TV).MethodsUtilizing two-sample Mendelian randomization (MR), we analyzed the causal effects of EA on gout risk, and of IPS (BMI and SBP) and LH (smoking, drinking, and TV time) on gout risk. Multivariable MR (MVMR) was employed to explore and quantify the mediating effects of IPS and LH on the causal relationship between EA and gout risk.ResultsAn elevation of educational attainment by one standard deviation (4.2 years) exhibited a protective effect against gout (odds ratio 0.724, 95% confidence interval 0.552–0.950; p = 0.020). We did not observe a causal relationship between smoking and gout, but BMI, SBP, drinking, and TV time were found to be causal risk factors for gout. Moreover, BMI, SBP, drinking, and TV time acted as mediating factors in the causal relationship between EA and gout risk, explaining 27.17, 14.83, 51.33, and 1.10% of the causal effects, respectively.ConclusionOur study indicates that having a genetically predicted higher level of EA may provide protection against gout. We found that this relationship is influenced by IPS factors such as BMI and SBP, as well as LH including drinking and TV time.
Keywords	education attainment ; gout ; mediation ; Mendelian randomization study ; causal relationship ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatiotemporal Evolution of Coordinated Development between Economic Resilience and Green Finance under the Background of Sustainable Development

Jin Zhang / Shuiping Zhang / Xin Huang / Zhiwei Zhang / Chengtuo Jin

Sustainability, Vol 15, Iss 9101, p

2023 Volume 9101

Abstract: The coupling and coordination between green finance (GF) and economic resilience (ER) are the foundation of sustainable economic development. This paper uses the panel data of 30 provinces (autonomous regions and municipalities) in mainland China from ... ...

Abstract	The coupling and coordination between green finance (GF) and economic resilience (ER) are the foundation of sustainable economic development. This paper uses the panel data of 30 provinces (autonomous regions and municipalities) in mainland China from 2011 to 2021 to calculate the comprehensive development level of the two systems by the entropy weight method. At the same time, we analyze the spatiotemporal evolution characteristics of the coupling coordination degree of the two systems by using the coupling coordination degree model, kernel density curve, spatial autocorrelation model, and Markov transition matrix. The results show that (1) the development level of ER increased steadily while that of GF fluctuated. The coupling coordination degree of the two systems shows an increasing trend. (2) The coupling coordination level of the two systems presents a spatial gradient pattern of “East > Middle > West”. (3) The level of coupling coordination has an obvious spatial correlation. (4) The coupling coordination level in our country remains stable in the future, and there is a possibility of transition to a higher level. The research of this paper provides valuable enlightenment for implementing a sustainable development strategy in China.
Keywords	green finance ; economic resilience ; coupling coordination ; time and space evolution ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	530
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Analysis of influence factors of target polarization characteristics

Zhiwei Zhang / Zhiyong Yang / Gengpeng Li / Dong Chen / Xiaowei Wang

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 11

Abstract: Abstract The target polarization characteristics reflect the important information about the medium material, surface texture, and structural characteristics of the target itself. In this paper, 9 kinds of samples with different materials, roughness, and ...

Abstract	Abstract The target polarization characteristics reflect the important information about the medium material, surface texture, and structural characteristics of the target itself. In this paper, 9 kinds of samples with different materials, roughness, and surface texture direction are selected to measure the polarization characteristics in an outdoor environment, and the influencing factors of the target polarization characteristics are analyzed, where the influence of the surface texture direction on the spatial distribution of the target polarization characteristics is emphatically analyzed. The results show that the target polarization characteristics are affected by many factors such as material, roughness, surface texture direction, and detection position, and the greater the angle between the surface texture direction and the principal plane, the more concentrated the target polarization characteristics are in and around the principal plane, which could provide a theoretical basis for comprehensively mastering the target polarization characteristics, improving the ability of target polarization detection and recognition, and enhancing the confidence of the target polarization modeling and simulation.
Keywords	Medicine ; R ; Science ; Q
Subject code	670
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Composed query image retrieval based on triangle area triple loss function and combining CNN with transformer

Zhiwei Zhang / Liejun Wang / Shuli Cheng

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

2022 Volume 12

Abstract: Abstract The existing typical combined query image retrieval methods adopt Euclidean distance as sample distance measurement method, and the model trained by triple loss function blindly pursues absolute distance between samples, resulting in ... ...

Abstract	Abstract The existing typical combined query image retrieval methods adopt Euclidean distance as sample distance measurement method, and the model trained by triple loss function blindly pursues absolute distance between samples, resulting in unsatisfactory image retrieval performance. Meanwhile, these methods singularly adopt Convolutional Neural Network (CNN) to extract reference image features. However, receptive field of convolution operation has the characteristics of locality, which is easy to cause the loss of edge feature information of reference images. In view of shortcomings of these methods, the following improvements are proposed in this paper: (1) We propose Triangle Area Triple Loss Function (TATLF), which adopts Triangle Area (TA) as measurement of sample distance. TA comprehensively considers the absolute distance and included angle between samples, so that the trained model has better retrieval performance; (2) We combine CNN with Transformer to simultaneously extract local and edge features of reference images, which can effectively reduce the loss of reference images information. Specifically, CNN is adopted to extract local feature information of reference images. Transformer is used to pay attention to the edge feature information of reference images. Extensive experiments on two public datasets, Fashion200k and MIT-States, confirm the excellent performance of our proposed method.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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