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Article ; Online: Does environmental information disclosure drive corporate sustainable growth? A new insight into U-shaped relationship

Jinsong Zhang / Mengmeng Wang

Frontiers in Ecology and Evolution, Vol

2023 Volume 11

Abstract: Due to the increasing rate of economic development and the increasingly serious problem of environmental degradation, environmental information disclosure has become an important basis for promoting carbon peaking and carbon neutrality, and an important ... ...

Abstract	Due to the increasing rate of economic development and the increasingly serious problem of environmental degradation, environmental information disclosure has become an important basis for promoting carbon peaking and carbon neutrality, and an important way for enterprises to carry out green governance to achieve sustainable development. This study uses empirical research methods to analyze the relationship between environmental information disclosure and corporate sustainable growth in the context of green governance using panel data of Chinese A-share listed companies in Shanghai and Shenzhen from 2012 to 2021. The empirical tests conclude that there is a U-shaped relationship between environmental information disclosure and corporate sustainable growth, which decreases and then increases, and the U-shaped relationship is transmitted through innovation inputs. The U-shaped relationship between environmental information disclosure and corporate sustainable growth is weakened by firm size and enhanced by equity incentives. In addition, further group analysis reveals that the above U-shaped relationship is more significant in non-state enterprises than in state-owned enterprises.
Keywords	green governance ; environmental information disclosure ; corporate sustainability ; innovation inputs ; U-shaped relationship ; Evolution ; QH359-425 ; Ecology ; QH540-549.5
Subject code	333 ; 339
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Citation Oriented AuthorRank for Scientific Publication Ranking

Jinsong Zhang / Xiaozhong Liu

Applied Sciences, Vol 12, Iss 4345, p

2022 Volume 4345

Abstract: It is now generally accepted that an article written by influential authors often deserves a higher ranking in information retrieval. However, it is a challenging task to determine an author’s relative influence since information about the author is, ... ...

Abstract	It is now generally accepted that an article written by influential authors often deserves a higher ranking in information retrieval. However, it is a challenging task to determine an author’s relative influence since information about the author is, much of the time, inaccessible. Actually, in scientific publications, the author is an important metadata item, which has been widely used in previous studies. In this paper, we bring an optimized AuthorRank, which is a topic-sensitive algorithm calculated by citation context, into citation analysis for testing whether and how topical AuthorRank can replace or enhance classical PageRank for publication ranking. For this purpose, we first propose a PageRank with Priors (PRP) algorithm to rank publications and authors. PRP is an optimized PageRank algorithm supervised by the Labeled Latent Dirichlet Allocation (Labeled-LDA) topic model with full-text information extraction. We then compared four methods of generating an AuthorRank score, looking, respectively, at the first author, the last author, the most famous author, and the “average” author (of a publication). Additionally, two combination methods (Linear and Cobb–Douglas) of AuthorRank and PRP were compared with several baselines. Finally, as shown in our evaluation results, the performance of AuthorRank combined with PRP is better ( p < 0.001) than other baselines for publication ranking.
Keywords	AuthorRank ; publication ranking ; PageRank with Priors ; citation context analysis ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	001
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: How to Improve the Corporate Sustainable Development?—The Importance of the Intellectual Capital and the Role of the Investor Confidence

Jinsong Zhang / Yiding Wang

Sustainability, Vol 14, Iss 3749, p

2022 Volume 3749

Abstract: In the era of the intelligent economy, to achieve business development, companies have shifted from focusing on physical resources to intangible resources and increasingly rely on investment in intangible assets. This phenomenon is a consensus. ... ...

Abstract	In the era of the intelligent economy, to achieve business development, companies have shifted from focusing on physical resources to intangible resources and increasingly rely on investment in intangible assets. This phenomenon is a consensus. Intellectual capital is a skill that is difficult for competitors to replicate and is the most significant intangible asset of modern firms. Research on intellectual capital mainly focuses on the impact of companies’ performance; however, this study focuses on the sustainable development effects of companies. Taking manufacturing companies from Chinese A-share listings from 2015 to 2020 as the sample space and adding innovation capital based on the traditional intellectual capital model, a two-way fixed-effects model was used to conduct empirical research on the relationship between companies’ intellectual capital and corporate sustainable development. Meanwhile, research was conducted to test whether investor confidence innovatively played an intermediary role. This study showed that intellectual capital was positively correlated with the sustainable development of companies and investor confidence. In general, investor confidence was a bridge that connected intellectual capital and sustainable development. The results provided an empirical basis for companies that can enhance their sustainable development capabilities through intellectual capital investment. Managers should focus on the development of activities that have a positive impact on companies’ intellectual capital, increase the investment of intellectual capital, and achieve high-quality, sustainable development.
Keywords	intellectual capital ; sustainable development ; investor confidence ; fixed effects model ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	650
Language	English
Publishing date	2022-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Application in Edge Detection of Medical Image Based on the Improved B-spline Wavelet Transform

Jinsong Zhang

International Journal Bioautomation, Vol 21, Iss 3, Pp 269-

2017 Volume 278

Abstract: The edge information of a medical image is the basis of the analysis and processing of that medical image. The medical image contains the muscle, blood vessels and other interference information, which is large but leads the edge detection to become very ...

Abstract	The edge information of a medical image is the basis of the analysis and processing of that medical image. The medical image contains the muscle, blood vessels and other interference information, which is large but leads the edge detection to become very difficult. So the research into an image edge detection algorithm has become one of the key technologies in image processing, and has important significance in the field of practical application. A new edge detection algorithm based on wavelet transform is proposed in this paper on the basis of regression analysis. Firstly, the signal is decomposed into approximate part and detailed part by the wavelet transform. Secondly, the wavelet coefficients of the detailed part are influenced by the threshold. Finally, the regression function of the signal is obtained by reconstructing wavelet coefficients. The experimental results show that the signal-noise ratio of the improved algorithm is clearly higher than the original, and it is helpful for improving the regression accuracy in terms of the wavelet transform. The algorithm can effectively remove noise, and the local feature of the signals is fully retained.
Keywords	Wavelet transform ; Medical image ; Edge detection ; B-spline ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2017-09-01T00:00:00Z
Publisher	Bulgarian Academy of Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Application in Edge Detection of Medical Image Based on the Improved B-spline Wavelet Transform

Jinsong Zhang

International Journal Bioautomation, Vol 21, Iss 3, Pp 269-

2017 Volume 278

Abstract	The edge information of a medical image is the basis of the analysis and processing of that medical image. The medical image contains the muscle, blood vessels and other interference information, which is large but leads the edge detection to become very difficult. So the research into an image edge detection algorithm has become one of the key technologies in image processing, and has important significance in the field of practical application. A new edge detection algorithm based on wavelet transform is proposed in this paper on the basis of regression analysis. Firstly, the signal is decomposed into approximate part and detailed part by the wavelet transform. Secondly, the wavelet coefficients of the detailed part are influenced by the threshold. Finally, the regression function of the signal is obtained by reconstructing wavelet coefficients. The experimental results show that the signal-noise ratio of the improved algorithm is clearly higher than the original, and it is helpful for improving the regression accuracy in terms of the wavelet transform. The algorithm can effectively remove noise, and the local feature of the signals is fully retained.
Keywords	Wavelet transform ; Medical image ; Edge detection ; B-spline ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2017-09-01T00:00:00Z
Publisher	Bulgarian Academy of Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Nonlinear model prediction of needle chlorophyll content of Picea koraiensis Nakai at different needle ages based on hyperspectral features

Yiheng Wang / Jinsong Zhang / Shu Diao / Liang Xue

Frontiers in Forests and Global Change, Vol

2023 Volume 6

Abstract: Pigment content is a critical assessment indicator in the study of plant physiological metabolism, stress resistance, ornamental characteristics, and forest health. Spectral imaging technology is widely used for rapid and non-destructive determination of ...

Abstract	Pigment content is a critical assessment indicator in the study of plant physiological metabolism, stress resistance, ornamental characteristics, and forest health. Spectral imaging technology is widely used for rapid and non-destructive determination of plant physicochemical parameters. To address the shortcomings of previous models of spectral reflectance prediction of chlorophyll content of needles only from the perspective of traditional algorithms and ignoring physical models, this research integrates variable complexity and refined classification of physical models to validate the increased accuracy of both the conventional partial least squares (PLS) method and the traditional neural network algorithm. The results of the conifer chlorophyll models of Picea koraiensis Nakai with different needle ages based on spectral reflectance and vegetation index parameters showed that the improved nonlinear state transition algorithm-backpropagation (STA-BP) neural network model approach (R2 of 0.73–0.89) and the nonlinear Stacking partial least squares (Stacking-PLS) model approach (R2 of 0. 67–0.85) is slightly more robust than the traditional algorithms nonlinear BP model (R2 of 0.63–0.82) and linear PLS model (R2 of 0.60–0.76). This finding suggests that the nonlinear fitting of chlorophyll content in needles of different needle ages in P. koraiensis Nakai surpasses the traditional linear model fitting methodology. Furthermore, the model fitting of chlorophyll content in conifers of different needle ages outperforms the mixed P. koraiensis Nakai model, suggesting that chlorophyll models using needle refinement classification help to improve model robustness. This study provides data and theoretical support for rapid and non-invasive characterization of physiological and biochemical properties of needles of different needle ages using spectral imaging techniques to predict growth and community structure productivity of forest trees in the coming years.
Keywords	STA-BP neural network ; stacking integration ; nonlinear fitting ; fine classification ; PLS model ; Forestry ; SD1-669.5 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on the Conventional Uniaxial Mechanical Properties and Micro-Mechanism of Sandstone under Dry–Wet Cycles

Jinsong Zhang / Shilong Peng / Yudi Yang

Journal of Composites Science, Vol 7, Iss 12, p

2023 Volume 494

Abstract: Dry–wet cycling has a significant impact on the mechanical properties of rocks, and a series of problems such as rock collapse can occur in rock masses under long-term dry–wet cycling. Based on this, some mechanical tests were carried out on sandstone ... ...

Abstract	Dry–wet cycling has a significant impact on the mechanical properties of rocks, and a series of problems such as rock collapse can occur in rock masses under long-term dry–wet cycling. Based on this, some mechanical tests were carried out on sandstone under different dry–wet cycles to analyze the evolution law of its physical and mechanical parameters. The results show that the internal connection of the mineral becomes looser, the drying quality of the sample decreases, and the water absorption quality increases gradually under different dry–wet cycles. The peak strength of the sample decreases first and then increases with increasing dry–wet cycles. The change trend of the elastic modulus and deformation modulus with the increase in dry–wet cycles are similar to the peak strength, which is mainly related to the change in the connection between particles. Furthermore, the specimens showed axial tensile failure under uniaxial action. With the increase in dry–wet cycles, the tensile crack on the surface of the specimen increased, and the fracture of the specimen became looser. The specimen exhibited block spalling when the number of dry–wet cycles was eight times.
Keywords	sandstone ; dry–wet cycles ; uniaxial strength ; deformation characteristics ; failure characteristics ; Technology ; T ; Science ; Q
Subject code	660
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: End-to-End Mispronunciation Detection and Diagnosis Using Transfer Learning

Linkai Peng / Yingming Gao / Rian Bao / Ya Li / Jinsong Zhang

Applied Sciences, Vol 13, Iss 6793, p

2023 Volume 6793

Abstract: As an indispensable module of computer-aided pronunciation training (CAPT) systems, mispronunciation detection and diagnosis (MDD) techniques have attracted a lot of attention from academia and industry over the past decade. To train robust MDD models, ... ...

Abstract	As an indispensable module of computer-aided pronunciation training (CAPT) systems, mispronunciation detection and diagnosis (MDD) techniques have attracted a lot of attention from academia and industry over the past decade. To train robust MDD models, this technique requires massive human-annotated speech recordings which are usually expensive and even hard to acquire. In this study, we propose to use transfer learning to tackle the problem of data scarcity from two aspects. First, from audio modality, we explore the use of the pretrained model wav2vec2.0 for MDD tasks by learning robust general acoustic representation. Second, from text modality, we explore transferring prior texts into MDD by learning associations between acoustic and textual modalities. We propose textual modulation gates that assign more importance to the relevant text information while suppressing irrelevant text information. Moreover, given the transcriptions, we propose an extra contrastive loss to reduce the difference of learning objectives between the phoneme recognition and MDD tasks. Conducting experiments on the L2-Arctic dataset showed that our wav2vec2.0 based models outperformed the conventional methods. The proposed textual modulation gate and contrastive loss further improved the F1-score by more than 2.88% and our best model achieved an F1-score of 61.75%.
Keywords	mispronunciation detection and diagnosis (MDD) ; computer-aided pronunciation training (CAPT) ; transfer learning ; pretrained model ; text modulation gate ; 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	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: SentenceLDA- and ConNetClus-Based Heterogeneous Academic Network Analysis for Publication Ranking

Jinsong Zhang / Bao Jin / Junyi Sha / Yan Chen / Yijin Zhang

Algorithms, Vol 15, Iss 159, p

2022 Volume 159

Abstract: Scientific papers published in journals or conferences, also considered academic publications, are the manifestation of scientific research achievements. Lots of scientific papers published in digital form bring new challenges for academic evaluation and ...

Abstract	Scientific papers published in journals or conferences, also considered academic publications, are the manifestation of scientific research achievements. Lots of scientific papers published in digital form bring new challenges for academic evaluation and information retrieval. Therefore, research on the ranking method of scientific papers is significant for the management and evaluation of academic resources. In this paper, we first identify internal and external factors for evaluating scientific papers and propose a publication ranking method based on an analysis of a heterogeneous academic network. We use four types of metadata (i.e., author, venue (journal or conference), topic, and title) as vertexes for creating the network; in there, the topics are trained by the SentenceLDA algorithm with the metadata of the abstract. We then use the Gibbs sampling method to create a heterogeneous academic network and apply the ConNetClus algorithm to calculate the probability value of publication ranking. To evaluate the significance of the method proposed in this paper, we compare the ranking results with BM25, PageRank, etc., and homogeneous networks in MAP and NDCG. As shown in our evaluation results, the performance of the method we propose in this paper is better than other baselines for ranking publications.
Keywords	heterogeneous academic network ; publication ranking ; SentenceLDA ; ConNetClus ; Industrial engineering. Management engineering ; T55.4-60.8 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	001
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Parameter Measurement of Live Animals Based on the Mirror of Multiview Point Cloud

Jinsong Zhang / Yue Qin / Li Wang

Computational Intelligence and Neuroscience, Vol

2021 Volume 2021

Abstract: Scale and standardization are essential to the prosperity of the breeding industry. During large-scale, standardized breeding, the selective breeding of good livestock breeds hinges on the accurate measurement of body parameters for live animals. However, ...

Abstract	Scale and standardization are essential to the prosperity of the breeding industry. During large-scale, standardized breeding, the selective breeding of good livestock breeds hinges on the accurate measurement of body parameters for live animals. However, the complex shooting environment brings several urgent problems, such as the missing of many local data in the point cloud and the difficulty in the automatic acquisition of body data. To solve these problems, this paper proposes a method for parameter measurement of live animals based on the mirror of multiview point cloud. Firstly, the acquisition and stitching principles were given for the multiview point cloud data on body parameters of live animals. Next, the authors presented a way to make up for the data missing areas in the point cloud. Finally, this paper acquires the body mirror data of live animals and scientifically calculates the body parameters. The proposed measurement method was proved effective through experiments.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
Subject code	630
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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