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Book ; Online: Enhanced Edge-Perceptual Guided Image Filtering

Li, Jinyu

2023

Abstract: Due to the powerful edge-preserving ability and low computational complexity, Guided image filter (GIF) and its improved versions has been widely applied in computer vision and image processing. However, all of them are suffered halo artifacts to some ... ...

Abstract	Due to the powerful edge-preserving ability and low computational complexity, Guided image filter (GIF) and its improved versions has been widely applied in computer vision and image processing. However, all of them are suffered halo artifacts to some degree, as the regularization parameter increase. In the case of inconsistent structure of guidance image and input image, edge-preserving ability degradation will also happen. In this paper, a novel guided image filter is proposed by integrating an explicit first-order edge-protect constraint and an explicit residual constraint which will improve the edge-preserving ability in both cases. To illustrate the efficiency of the proposed filter, the performances are shown in some typical applications, which are single image detail enhancement, multi-scale exposure fusion, hyper spectral images classification. Both theoretical analysis and experimental results prove that the powerful edge-preserving ability of the proposed filter.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics
Subject code	006
Publishing date	2023-10-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Insulin receptor alternative splicing in breast and prostate cancer.

Li, Jinyu / Huang, Gena

Cancer cell international

2024 Volume 24, Issue 1, Page(s) 62

Abstract: Cancer etiology represents an intricate, multifactorial orchestration where metabolically associated insulin-like growth factors (IGFs) and insulin foster cellular proliferation and growth throughout tumorigenesis. The insulin receptor (IR) exhibits two ... ...

Abstract	Cancer etiology represents an intricate, multifactorial orchestration where metabolically associated insulin-like growth factors (IGFs) and insulin foster cellular proliferation and growth throughout tumorigenesis. The insulin receptor (IR) exhibits two splice variants arising from alternative mRNA processing, namely IR-A, and IR-B, with remarkable distribution and biological effects disparities. This insightful review elucidates the structural intricacies, widespread distribution, and functional significance of IR-A and IR-B. Additionally, it explores the regulatory mechanisms governing alternative splicing processes, intricate signal transduction pathways, and the intricate association linking IR-A and IR-B splicing variants to breast and prostate cancer tumorigenesis. Breast cancer and prostate cancer are the most common malignant tumors with the highest incidence rates among women and men, respectively. These findings provide a promising theoretical framework for advancing preventive strategies, diagnostic modalities, and therapeutic interventions targeting breast and prostate cancer.
Language	English
Publishing date	2024-02-08
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2091573-1
ISSN	1475-2867
ISSN	1475-2867
DOI	10.1186/s12935-024-03252-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Environmental regulatory intensity, green finance and corporate green sustainable development performance.

Xu, Xinpeng / Wang, Shengxian / Li, Jinyu / Qiao, Tai

Heliyon

2024 Volume 10, Issue 9, Page(s) e30114

Abstract: In the "14th Five-Year Plan" period, the emphasis is made on green and low-carbon initiatives, which has become a defining feature of China's development, and it is of great significance to help enterprises realize green and sustainable development under ...

Abstract	In the "14th Five-Year Plan" period, the emphasis is made on green and low-carbon initiatives, which has become a defining feature of China's development, and it is of great significance to help enterprises realize green and sustainable development under the guidance of environmental regulation to achieve the goal of "dual-carbon". At first, this research analyzes the decision-making process between the government and enterprises under environmental regulation using the evolutionary game model. Moreover, using the TOPSIS method, this paper constructs the indicators of corporate green sustainable development performance, and empirically examines the impact of the intensity of environmental regulation on the green sustainable development performance of enterprises based on the data of Chinese A-share listed enterprises from 2010 to 2022. A noteworthy positive correlation between the intensity of environmental regulation and the sustainable green development performance of enterprises is unveiled by the results. Mechanism tests suggest that the intensity of environmental regulation has a positive impact on the green sustainable development performance of enterprises through enhancing green finance and green technological innovation. Moreover, this effect tends to be more pronounced for enterprises that are in the mature life cycle, with green executive team, and high media attention. The research presented in this study contributes to establishing a novel theoretical foundation for corporate sustainable development.
Language	English
Publishing date	2024-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e30114
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Recent Advances in End-to-End Automatic Speech Recognition

Li, Jinyu

2021

Abstract: Recently, the speech community is seeing a significant trend of moving from deep neural network based hybrid modeling to end-to-end (E2E) modeling for automatic speech recognition (ASR). While E2E models achieve the state-of-the-art results in most ... ...

Abstract	Recently, the speech community is seeing a significant trend of moving from deep neural network based hybrid modeling to end-to-end (E2E) modeling for automatic speech recognition (ASR). While E2E models achieve the state-of-the-art results in most benchmarks in terms of ASR accuracy, hybrid models are still used in a large proportion of commercial ASR systems at the current time. There are lots of practical factors that affect the production model deployment decision. Traditional hybrid models, being optimized for production for decades, are usually good at these factors. Without providing excellent solutions to all these factors, it is hard for E2E models to be widely commercialized. In this paper, we will overview the recent advances in E2E models, focusing on technologies addressing those challenges from the industry's perspective. Comment: invited paper submitted to APSIPA Transactions on Signal and Information Processing
Keywords	Electrical Engineering and Systems Science - Audio and Speech Processing ; Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Sound
Subject code	006
Publishing date	2021-11-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: TT3.1: a journey to protect chloroplasts upon heat stress.

Li, Jin-Yu / Liu, Jian-Xiang

Stress biology

2022 Volume 2, Issue 1, Page(s) 27

Abstract: Rice (Oryza sativa L.) is a staple crop that feeds over half the world's population. High temperature stress is a great threaten to sustainable agriculture and leads to yield loss and impaired grain quality in major crops. Rice is sensitive to heat ... ...

Abstract	Rice (Oryza sativa L.) is a staple crop that feeds over half the world's population. High temperature stress is a great threaten to sustainable agriculture and leads to yield loss and impaired grain quality in major crops. Rice is sensitive to heat stress at almost all the growth stages and the molecular mechanisms underlying responses to heat stress in rice is emerging. Through quantitative trait locus (QTL) mapping, a recent study conducted by Zhang et al. shows that one genetic locus Thermo-tolerance 3 (TT3) contains two genes that are required for thermotolerance in rice. The TT3.1-TT3.2 genetic module in rice links the plasma membrane to chloroplasts to protect chloroplasts from heat stress damage and increases grain yield under heat stress conditions. This breakthrough provides a promising strategy for future breeding of high temperature resilient crops.
Language	English
Publishing date	2022-07-12
Publishing country	Switzerland
Document type	Journal Article
ISSN	2731-0450
ISSN (online)	2731-0450
DOI	10.1007/s44154-022-00051-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Research on Two-Round Self-Balancing Robot SLAM Based on the Gmapping Algorithm.

Zhao, Jianwei / Li, Jinyu / Zhou, Jiaxin

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 5

Abstract: Aiming at the inconvenience of inspection and monitoring of coal mine pump room equipment in a narrow and complex environment, this paper proposes and designs a two-wheel self-balancing inspection robot based on laser SLAM. Using SolidWorks, the three- ... ...

Abstract	Aiming at the inconvenience of inspection and monitoring of coal mine pump room equipment in a narrow and complex environment, this paper proposes and designs a two-wheel self-balancing inspection robot based on laser SLAM. Using SolidWorks, the three-dimensional mechanical structure of the robot is designed, and the overall structure of the robot is analyzed by finite element statics. The kinematics model of the two-wheel self-balancing robot was established, and the multi-closed-loop PID controller was used to design the two-wheel self-balancing control algorithm of the robot. The 2D LiDAR-based Gmapping algorithm was used to locate the robot and construct the map. Through the self-balancing test and anti-jamming test, it is verified that the self-balancing algorithm designed in this paper has a certain anti-jamming ability and good robustness. By using Gazebo to build a simulation comparison experiment, it is verified that the selection of the particle number is of great significance for improving the map accuracy. The actual test results show that the constructed map has high accuracy.
Language	English
Publishing date	2023-02-23
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23052489
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Article ; Online: Probing microdomain Ca

Liu, Langzhou / Gao, Huayi / Li, Jinyu / Chen, Shangbin

Frontiers in network physiology

2023 Volume 3, Page(s) 1111306

Abstract: Astrocytic fine processes are the most minor structures of astrocytes but host much of the ... ...

Abstract	Astrocytic fine processes are the most minor structures of astrocytes but host much of the Ca
Language	English
Publishing date	2023-02-10
Publishing country	Switzerland
Document type	Journal Article
ISSN	2674-0109
ISSN (online)	2674-0109
DOI	10.3389/fnetp.2023.1111306
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Causations between obesity, diabetes, lifestyle factors and the risk of low back pain.

Liu, Yi / Tang, Gang / Li, Jinyu

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society

2023 Volume 33, Issue 2, Page(s) 525–532

Abstract: Background: Despite numerous observational studies, the causal relationship between obesity-measured by body mass index (BMI) and waist circumference (WC)-as well as type 2 diabetes (T2D), lifestyle habits, and susceptibility to low back pain (LBP) ... ...

Abstract	Background: Despite numerous observational studies, the causal relationship between obesity-measured by body mass index (BMI) and waist circumference (WC)-as well as type 2 diabetes (T2D), lifestyle habits, and susceptibility to low back pain (LBP) remains obscure. Methods: This investigation employed two-sample Mendelian randomization (MR) analysis to explore causality, using genetic variants linked to relevant factors from genome-wide association studies (GWASs). Specifically, we selected independent genetic variants related to BMI, WC, T2D, smoking, alcohol consumption, and coffee intake from established GWASs, all of which demonstrated genome-wide significance. The comparative data for LBP were derived from a GWAS involving European subjects, under the auspices of the renowned MRC-IEU (Medical Research Council Integrative Epidemiology Unit) consortium. Results: Elevated BMI and WC were associated with odds ratios of 1.002 (95% confidence interval [CI] = 1.001-1.004, p < 0.001) and 1.003 (95% CI = 1.002-1.004, p < 0.001) for LBP per standard deviation (SD) increase, respectively. Regarding smoking initiation and coffee consumption, the odds ratios stood at 1.002 (95% CI = 1.001-1.004, p = 0.001) and 1.004 (95% CI = 1.001-1.008, p = 0.034) for LBP, respectively. However, an augmented log odds ratio for T2D and each SD rise in alcohol consumption frequency revealed no significant causal impact on LBP risk. Conclusion: Our findings indicate a potential causal link between obesity, smoking, and coffee intake in the genesis of LBP, suggesting that mitigating these factors could contribute to LBP prevention.
MeSH term(s)	Humans ; Coffee/adverse effects ; Diabetes Mellitus, Type 2/etiology ; Diabetes Mellitus, Type 2/genetics ; Genome-Wide Association Study ; Life Style ; Low Back Pain/epidemiology ; Low Back Pain/etiology ; Obesity/epidemiology ; Mendelian Randomization Analysis
Chemical Substances	Coffee
Language	English
Publishing date	2023-12-20
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1115375-1
ISSN	1432-0932 ; 0940-6719
ISSN (online)	1432-0932
ISSN	0940-6719
DOI	10.1007/s00586-023-08069-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: ResidualTransformer

Wang, Yiming / Li, Jinyu

Residual Low-Rank Learning with Weight-Sharing for Transformer Layers

2023

Abstract: Memory constraint of always-on devices is one of the major concerns when deploying speech processing models on these devices. While larger models trained with sufficiently large amount of data generally perform better, making them fit in the device ... ...

Abstract	Memory constraint of always-on devices is one of the major concerns when deploying speech processing models on these devices. While larger models trained with sufficiently large amount of data generally perform better, making them fit in the device memory is a demanding challenge. In this paper, we aim to reduce model size by reparameterizing model weights across Transformer encoder layers and assuming a special weight composition and structure. More specifically, inspired by ResNet and the more recent LoRA work, we propose an approach named ResidualTransformer, where each weight matrix in a Transformer layer comprises 1) a shared full-rank component with its adjacent layers, and 2) a unique low-rank component to itself. The low-rank matrices only account for a small amount of model size increase. In addition, we add diagonal weight matrices to improve modeling capacity of the low-rank matrices. Experiments of our 10k-hour speech recognition and speech translation tasks show that the Transformer encoder size can be reduced by ~3X with very slight performance degradation. Comment: Accepted at IEEE ICASSP 2024. 5 pages, 1 figure
Keywords	Computer Science - Computation and Language ; Computer Science - Machine Learning ; Computer Science - Sound ; Electrical Engineering and Systems Science - Audio and Speech Processing
Publishing date	2023-10-03
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantitative analysis of spatiotemporal changes and driving forces of vegetation net primary productivity (NPP) in the Qimeng region of Inner Mongolia

Xue, Huazhu / Chen, Yunpeng / Dong, Guotao / Li, Jinyu

Ecological Indicators. 2023 Oct., v. 154 p.110610-

2023

Abstract: Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global ... ...

Abstract	Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global warming and human activities in Inner Mongolia. The net primary productivity (NPP) was used as an indicator to study the spatial and temporal changes in vegetation in the Qimeng Region (QR). The residual trend analysis method was used to analyze the relative contributions of climate variations (CV) and human activities (HA) to NPP changes across the QR, while their drivers were explored using a geographical detector approach to quantify the driving forces of NPP. The results show that (1) NPP exhibited a fluctuating growth trend from 2003 to 2020, with an overall growth rate of 2.91%/year. (2) Precipitation, GDP and population density were the dominant driving factors for the spatial distribution of NPP. The combined explanatory power of any two dominant factors exceeded the power of any dominant individual factor, and the interaction between climate and human factors had a significant effect on NPP. (3) The change in NPP was influenced by the combined effect of HA and CV, accounting for 37.69% of the total area, with the relative contribution of HA being 51.75%. Finally, the relative contribution of human activities was slightly higher than that of climate change, confirming the initial success of the Grain to Green Program as well as ecological conservation projects. This paper provides a scientific basis for the local government to carry out the conversion of cropland to forest.
Keywords	climate ; climate change ; cropland ; humans ; local government ; net primary productivity ; population density ; quantitative analysis ; vegetation ; China ; NPP ; Driving force ; Geographical detectors ; Inner Mongolia
Language	English
Dates of publication	2023-10
Publishing place	Elsevier Ltd
Document type	Article ; Online
ZDB-ID	2036774-0
ISSN	1872-7034 ; 1470-160X
ISSN (online)	1872-7034
ISSN	1470-160X
DOI	10.1016/j.ecolind.2023.110610
Database	NAL-Catalogue (AGRICOLA)

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