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Article ; Online: Mechanisms of Crystal Plasticization by Lattice Water.

Wang, Chenguang / Sun, Changquan Calvin

2022

Abstract: Purpose: Water of crystallization has been observed to increase plasticity, decrease crystal hardness, and improve powder compressibility and tabletability of organic crystals. This work is aimed at gaining a molecular level insight into this ... ...

Abstract	Purpose: Water of crystallization has been observed to increase plasticity, decrease crystal hardness, and improve powder compressibility and tabletability of organic crystals. This work is aimed at gaining a molecular level insight into this observation. Method: We systematically analyzed crystal structures of five stoichiometric hydrate systems, using several complementary techniques of analysis, including energy framework, water environment, overall packing change, hydrate stability, and slip plane identification. Results: The plasticizing effect by lattice water is always accompanied by an introduction of more facile slip planes, lower packing efficiency, and lower density in all hydrate systems examined in this work. Three distinct mechanisms include 1) changing the distribution of intermolecular interactions without significantly changing the packing of molecules to introduce more facile slip planes; 2) changing packing feature into a flat layered structure so that more facile slip planes are introduced; 3) reducing the interlayer interaction energies and increasing the anisotropy. Conclusion: Although the specific mechanisms for these five systems differ, all five hydrates are featured with more facile slip planes, lower packing efficiency, and lower density.
Language	English
Publishing date	2022-03-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	843063-9
ISSN	1573-904X ; 0724-8741 ; 0739-0742
ISSN (online)	1573-904X
ISSN	0724-8741 ; 0739-0742
DOI	10.1007/s11095-022-03221-1
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Article ; Online: A critical examination of three-point bending for determining Young's modulus.

Wang, Chenguang / Sun, Changquan Calvin

International journal of pharmaceutics

2022 Volume 629, Page(s) 122409

Abstract: The three point bending method is commonly used for determining Young's modulus, E. However, the literature E values of some common pharmaceutical excipients, determined by three point bending, exhibit orders of magnitude variability that cannot be fully ...

Abstract	The three point bending method is commonly used for determining Young's modulus, E. However, the literature E values of some common pharmaceutical excipients, determined by three point bending, exhibit orders of magnitude variability that cannot be fully explained by normal variations in material properties. To understand the root cause for the large variations, we assessed several potential experimental factors, including instrument stiffness, data analysis method, test speed, alignment between loading beam and specimen surface, and ratio of sample thickness to distance between two supports. Our results show that E value is sensitive to 1) deformation of instrument under force, 2) force-displacement data analysis method, 3) misalignment between loading beam and specimen surface, 4) flashing at the edge of a specimen, 5) accuracy of the true density. Finally, strategies to improve the accuracy of E determination by the three point bending method were recommended.
MeSH term(s)	Elastic Modulus ; Excipients ; Research Design
Chemical Substances	Excipients
Language	English
Publishing date	2022-11-15
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	428962-6
ISSN	1873-3476 ; 0378-5173
ISSN (online)	1873-3476
ISSN	0378-5173
DOI	10.1016/j.ijpharm.2022.122409
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Article ; Online: A dynamic prediction model of landslide displacement based on VMD-SSO-LSTM approach.

Wang, Haiying / Ao, Yang / Wang, Chenguang / Zhang, Yingzhi / Zhang, Xiaofeng

Scientific reports

2024 Volume 14, Issue 1, Page(s) 9203

Abstract: Addressing the limitations of existing landslide displacement prediction models in capturing the dynamic characteristics of data changes, this study introduces a novel dynamic displacement prediction model for landslides. The proposed method combines ... ...

Abstract	Addressing the limitations of existing landslide displacement prediction models in capturing the dynamic characteristics of data changes, this study introduces a novel dynamic displacement prediction model for landslides. The proposed method combines Variational Mode Decomposition (VMD) with Sparrow Search Optimization (SSO) and Long Short-Term Memory (LSTM) techniques to formulate a comprehensive VMD-SSO-LSTM model. Through the application of VMD, the method dissects cumulative displacement and rainfall data, thereby extracting distinct components such as trend, periodicity, and fluctuation components for displacement, as well as low-frequency and high-frequency components for rainfall. Furthermore, leveraging Gray Correlational Analysis, the interrelationships between the periodic component of displacement and the low-frequency component of rainfall, as well as the fluctuation component of displacement and the high-frequency component of rainfall, are established. Building upon this foundation, the SSO-LSTM model dynamically predicts the interrelated displacement components, synthesizing the predicted values of each component to generate real-time dynamic forecasts. Simulation results underscore the effectiveness of the proposed VMD-SSO-LSTM model, indicating root-mean-square error (RMSE) and mean absolute percentage error (MAPE) values of 1.2329 mm and 0.1624%, respectively, along with a goodness of fit (R
Language	English
Publishing date	2024-04-22
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/s41598-024-59517-2
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Article: Seamless MEMS-INS/Geomagnetic Navigation System Based on Deep-Learning Strong Tracking Square-Root Cubature Kalman Filter.

Zhao, Tianshang / Wang, Chenguang / Shen, Chong

Micromachines

2023 Volume 14, Issue 10

Abstract: To suppress inertial navigation system drift and improve the seamless navigation capability of microelectromechanical system-inertial navigation systems/geomagnetic navigation systems (MEMS-INS/MNS) in geomagnetically unlocked environments, this paper ... ...

Abstract	To suppress inertial navigation system drift and improve the seamless navigation capability of microelectromechanical system-inertial navigation systems/geomagnetic navigation systems (MEMS-INS/MNS) in geomagnetically unlocked environments, this paper proposes a hybrid seamless MEMS-INS/MNS strategy combining a strongly tracked square-root cubature Kalman filter with deep self-learning (DSL-STSRCKF). The proposed DSL-STSRCKF method consists of two innovative steps: (i) The relationship between the deep Kalman filter gain and the optimal estimation is established. In this paper, combining the two auxiliary methods of strong tracking filtering and square-root filtering based on singular value decomposition, the heading accuracy error of ST-SRCKF can reach 1.29°, which improves the heading accuracy by 90.10% and 9.20% compared to the traditional single INS and the traditional integrated navigation algorithm and greatly improves the robustness and computational efficiency. (ii) Providing deep self-learning capability for the ST-SRCKF by introducing a nonlinear autoregressive neural network (NARX) with exogenous inputs, which means that the heading accuracy can still reach 1.33° even during the MNS lockout period, and the heading accuracy can be improved by 89.80% compared with the single INS, realizing the continuous high-precision navigation estimation.
Language	English
Publishing date	2023-10-15
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2620864-7
ISSN	2072-666X
ISSN	2072-666X
DOI	10.3390/mi14101935
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Article ; Online: The role of retinal glial cells and related factors in macular edema.

Zhang, Qi / Qi, Shounan / You, Jiaxin / Wang, Chenguang

Biochemical and biophysical research communications

2023 Volume 695, Page(s) 149415

Abstract: Macular edema (ME) has emerged as a leading cause of visual impairment, representing a critical clinical manifestation and complication associated with many eye diseases. In the occurrence and development of ME, retinal glial cells like Müller cells and ... ...

Abstract	Macular edema (ME) has emerged as a leading cause of visual impairment, representing a critical clinical manifestation and complication associated with many eye diseases. In the occurrence and development of ME, retinal glial cells like Müller cells and microglial cells play vital roles. Moreover, growth factor and cytokines associated with them, such as vascular endothelial growth factor (VEGF), pigment epithelium-derived factor (PEDF), hypoxia-inducible factor-1α (HIF-1α), angiopoietin-like protein 4 (ANGPTL4), interleukin-6(IL-6), interleukin-8 (IL-8), monocyte chemoattractant protein-1 (MCP-1), prostaglandin, etc., also take part in the pathogenesis of ME. Changes in these cytokines can lead to retinal angiogenesis, increased vascular permeability, blood-retinal barrier (BRB) breakdown, and fluid leakage, further causing ME to occur or deteriorate. Research on the role of retinal glial cells and related cytokines in ME will provide new therapeutic directions and effective remedies. This article is a literature review on the role of Müller cells, microglial cells and related factors in ME pathogenesis.
MeSH term(s)	Humans ; Macular Edema ; Vascular Endothelial Growth Factor A/metabolism ; Retina/metabolism ; Neuroglia/metabolism ; Cytokines/metabolism
Chemical Substances	Vascular Endothelial Growth Factor A ; Cytokines
Language	English
Publishing date	2023-12-23
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	205723-2
ISSN	1090-2104 ; 0006-291X ; 0006-291X
ISSN (online)	1090-2104 ; 0006-291X
ISSN	0006-291X
DOI	10.1016/j.bbrc.2023.149415
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Article ; Online: Estimating causal effects in observational studies for survival data with a cure fraction using propensity score adjustment.

Wang, Ziwen / Wang, Chenguang / Wang, Xiaoguang

Biometrical journal. Biometrische Zeitschrift

2023 Volume 65, Issue 8, Page(s) e2100357

Abstract: In observational studies, covariates are often confounding factors for treatment assignment. Such covariates need to be adjusted to estimate the causal treatment effect. For observational studies with survival outcomes, it is usually more challenging to ... ...

Abstract	In observational studies, covariates are often confounding factors for treatment assignment. Such covariates need to be adjusted to estimate the causal treatment effect. For observational studies with survival outcomes, it is usually more challenging to adjust for the confounding covariates for causal effect estimation because of censoring. The challenge becomes even thornier when there exists a nonignorable cure fraction in the population. In this paper, we propose a causal effect estimation approach in observational studies for survival data with a cure fraction. We extend the absolute treatment effects on survival outcomes-including the restricted average causal effect and SPCE-to survival outcomes with cure fractions, and construct the corresponding causal effect estimators based on propensity score stratification. We prove the asymptotic properties of the proposed estimators and conduct simulation studies to evaluate their performances. As an illustration, the method is applied to a stomach cancer study.
MeSH term(s)	Propensity Score ; Computer Simulation
Language	English
Publishing date	2023-09-06
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	131640-0
ISSN	1521-4036 ; 0323-3847 ; 0006-3452
ISSN (online)	1521-4036
ISSN	0323-3847 ; 0006-3452
DOI	10.1002/bimj.202100357
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Article ; Online: Effects of straw mixed mulch length and coverage on infiltration, soil and water loss of Loess Plateau slopes

Wang, Chenguang / Zhang, Xiumei / Wang, Yangxiu / Ma, Bo

Land Degradation & Development. 2023 June, v. 34, no. 10 p.2931-2944

2023

Abstract: To study the influence of the wheat straw length and mulching on soil erosion under mixed mulch application, indoor simulation experiments were adopted to study the characteristics of infiltration, runoff and sediment yield changes under a rainfall ... ...

Abstract	To study the influence of the wheat straw length and mulching on soil erosion under mixed mulch application, indoor simulation experiments were adopted to study the characteristics of infiltration, runoff and sediment yield changes under a rainfall intensity of 90 mm hr⁻¹. The results indicated that the length, coverage and interaction imposed significant effects on these variables. With increasing coverage, the infiltration exhibits a trend of first increasing and then decreasing. The change trend of runoff and sediment is the opposite of the infiltration trend. When the length is less than or equal to 8–10 cm and the coverage is lower than 4.5 t hm⁻², the sum of the length and coverage multiplied by the length and coverage attains a power function relationship with the slope infiltration rate. When the length is greater than or equal to 8–10 cm and the coverage is lower than 4.5 t hm⁻², the sum of the length and coverage multiplied by the coverage divided by the length attains a power function relationship with slope infiltration rate. The reciprocal of these two variables attains a power function relationship with runoff and sediment yield. In this study, when the length ranged from 8–10 cm and the coverage was 3.5 t hm⁻², the average infiltration rate was the highest, and the cumulative runoff and sediment yield were the lowest. Mixed straw mulching can effectively increase infiltration and reduce runoff and sediment yield, which is of great significance for the sustainable development of agriculture and ecology on slope farms.
Keywords	ecology ; infiltration rate ; land degradation ; mulches ; rain intensity ; runoff ; sediment yield ; sediments ; soil ; soil erosion ; sustainable development ; wheat straw ; China
Language	English
Dates of publication	2023-06
Size	p. 2931-2944.
Publishing place	John Wiley & Sons, Ltd.
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	1319202-4
ISSN	1085-3278
ISSN	1085-3278
DOI	10.1002/ldr.4657
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Efficient Training of Multi-task Combinarotial Neural Solver with Multi-armed Bandits

Wang, Chenguang / Yu, Tianshu

2023

Abstract: Efficiently training a multi-task neural solver for various combinatorial optimization problems (COPs) has been less studied so far. In this paper, we propose a general and efficient training paradigm based on multi-armed bandits to deliver a unified ... ...

Abstract	Efficiently training a multi-task neural solver for various combinatorial optimization problems (COPs) has been less studied so far. In this paper, we propose a general and efficient training paradigm based on multi-armed bandits to deliver a unified combinarotial multi-task neural solver. To this end, we resort to the theoretical loss decomposition for multiple tasks under an encoder-decoder framework, which enables more efficient training via proper bandit task-sampling algorithms through an intra-task influence matrix. Our method achieves much higher overall performance with either limited training budgets or the same training epochs, compared to standard training schedules, which can be promising for advising efficient training of other multi-task large models. Additionally, the influence matrix can provide empirical evidence of some common practices in the area of learning to optimize, which in turn supports the validity of our approach.
Keywords	Computer Science - Machine Learning
Subject code	006 ; 004
Publishing date	2023-05-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River

Xue, Shaobo / Ma, Bo / Wang, Chenguang / Li, Zhanbin

Ecological Modelling. 2023 Oct., v. 484 p.110457-

2023

Abstract: Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices ... ...

Abstract	Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices and NPP changes in three major vegetation types (forest, grassland, and shrubland) in the upper and middle reaches of the Yellow River Basin using a random forest model. The results showed that landscape fragmentation increased, leading to higher landscape heterogeneity and edge effects. Patch shapes became more irregular, and spatial distribution became more dispersed. From 2000 to 2015, both vegetation types and NPP showed significant spatial heterogeneity in the study area. The number of patches (NP), largest patch index (LPI), and percent-like adjacency (PLADJ) metrics were used to determine the core landscape characteristics to assess the NPP changes in forest, shrubland, and grassland, respectively. This study provides a basis for understanding the relationships among landscape patterns, vegetation types, and NPP and serves as a reference for developing NPP predictive models in the Loess Plateau region.
Keywords	algorithms ; case studies ; climate change ; forests ; grasslands ; habitat fragmentation ; landscapes ; net primary productivity ; shrublands ; spatial variation ; watersheds ; China ; Yellow River ; Vegetation type ; NPP ; Landscape pattern index ; Random forest
Language	English
Dates of publication	2023-10
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	191971-4
ISSN	0304-3800
ISSN	0304-3800
DOI	10.1016/j.ecolmodel.2023.110457
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Meta-Path Constrained Random Walk Inference for Large-Scale Heterogeneous Information Networks

Wang, Chenguang

2019

Abstract: Heterogeneous information network (HIN) has shown its power of modeling real world data as a multi-typed entity-relation graph. Meta-path is the key contributor to this power since it enables inference by capturing the proximities between entities via ... ...

Abstract	Heterogeneous information network (HIN) has shown its power of modeling real world data as a multi-typed entity-relation graph. Meta-path is the key contributor to this power since it enables inference by capturing the proximities between entities via rich semantic links. Previous HIN studies ask users to provide either 1) the meta-path(s) directly or 2) biased examples to generate the meta-path(s). However, lots of HINs (e.g., YAGO2 and Freebase) have rich schema consisting of a sophisticated and large number of types of entities and relations. It is impractical for users to provide the meta-path(s) to support the large scale inference, and biased examples will result in incorrect meta-path based inference, thus limit the power of the meta-path. In this paper, we propose a meta-path constrained inference framework to further release the ability of the meta-path, by efficiently learning the HIN inference patterns via a carefully designed tree structure; and performing unbiased random walk inference with little user guidance. The experiment results on YAGO2 and DBLP datasets show the state-of-the-art performance of the meta-path constrained inference framework. Comment: 9 pages, 3 figures, 3 tables
Keywords	Computer Science - Social and Information Networks ; Computer Science - Machine Learning
Subject code	006
Publishing date	2019-12-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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