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Article ; Online: Study of ischemic progression in different intestinal tissue layers during acute intestinal ischemia using swept-source optical coherence tomography angiography.

Tian, Yu / Zhang, Mingshuo / Man, Hongbo / Wu, Chunnan / Wang, Yimin / Kong, Linghui / Liu, Jian

2024 Volume 17, Issue 4, Page(s) e202300382

Abstract: In acute intestinal ischemia, the progression of ischemia varies across different layers of intestinal tissue. We established a mouse model and used swept-source optical coherence tomography (OCT) to observe the intestinal ischemic process longitudinally ...

Abstract	In acute intestinal ischemia, the progression of ischemia varies across different layers of intestinal tissue. We established a mouse model and used swept-source optical coherence tomography (OCT) to observe the intestinal ischemic process longitudinally in different tissue layers. Employing a method that combines asymmetric gradient filtering with adaptive weighting, we eliminated the vessel trailing phenomenon in OCT angiograms, reducing the confounding effects of superficial vessels on the imaging of deeper vasculature. We quantitatively assessed changes in vascular perfusion density (VPD), vessel length, and vessel average diameter across various intestinal layers. Our results showed a significant reduction in VPD in all layers during ischemia. The mucosa layer experienced the most significant impact, primarily due to disrupted capillary blood flow, followed by the submucosa layer, where vascular constriction or decreased velocity was the primary factor.
MeSH term(s)	Animals ; Mice ; Tomography, Optical Coherence/methods ; Angiography/methods ; Capillaries ; Intestines/diagnostic imaging ; Ischemia/diagnostic imaging
Language	English
Publishing date	2024-01-21
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2390063-5
ISSN	1864-0648 ; 1864-063X
ISSN (online)	1864-0648
ISSN	1864-063X
DOI	10.1002/jbio.202300382
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Article ; Online: Integrated analysis revealing the role of TET3-mediated MUC13 promoter hypomethylation in hepatocellular carcinogenesis.

Kong, Ruijiao / Zhang, Hui / Jia, Yin / Man, Qiuhong / Liu, Shanrong

Epigenomics

2023 Volume 14, Issue 24, Page(s) 1579–1591

Abstract: Aim: ...

Abstract	Aim:
MeSH term(s)	Humans ; Carcinoma, Hepatocellular/pathology ; Liver Neoplasms/pathology ; Cell Line, Tumor ; DNA Methylation ; Cell Transformation, Neoplastic/genetics ; Neoplastic Stem Cells/metabolism ; Mucins/genetics ; Mucins/metabolism ; Dioxygenases/genetics
Chemical Substances	MUC13 protein, human ; Mucins ; TET3 protein, human (EC 1.-) ; Dioxygenases (EC 1.13.11.-)
Language	English
Publishing date	2023-03-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2537199-X
ISSN	1750-192X ; 1750-1911
ISSN (online)	1750-192X
ISSN	1750-1911
DOI	10.2217/epi-2022-0395
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Article ; Online: Coordination Environment Engineering to Regulate the Adsorption Strength of Intermediates in Single Atom Catalysts for High-performance CO

Wang, Maohuai / Kong, Lingyan / Lu, Xiaoqing / Wu, Chi-Man Lawrence

Small (Weinheim an der Bergstrasse, Germany)

2024 , Page(s) e2310339

Abstract: The modulation of the coordination environment of single atom catalysts (SACs) plays a vital role in promoting ... ...

Abstract	The modulation of the coordination environment of single atom catalysts (SACs) plays a vital role in promoting CO
Language	English
Publishing date	2024-01-31
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2168935-0
ISSN	1613-6829 ; 1613-6810
ISSN (online)	1613-6829
ISSN	1613-6810
DOI	10.1002/smll.202310339
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Article ; Online: Distilling Privileged Knowledge for Anomalous Event Detection From Weakly Labeled Videos.

Liu, Tianshan / Lam, Kin-Man / Kong, Jun

IEEE transactions on neural networks and learning systems

2023 Volume PP

Abstract: Weakly supervised video anomaly detection (WS-VAD) aims to identify the snippets involving anomalous events in long untrimmed videos, with solely video-level binary labels. A typical paradigm among the existing WS-VAD methods is to employ multiple ... ...

Abstract	Weakly supervised video anomaly detection (WS-VAD) aims to identify the snippets involving anomalous events in long untrimmed videos, with solely video-level binary labels. A typical paradigm among the existing WS-VAD methods is to employ multiple modalities as inputs, e.g., RGB, optical flow, and audio, as they can provide sufficient discriminative clues that are robust to the diverse, complicated real-world scenes. However, such a pipeline has high reliance on the availability of multiple modalities and is computationally expensive and storage demanding in processing long sequences, which limits its use in some applications. To address this dilemma, we propose a privileged knowledge distillation (KD) framework dedicated to the WS-VAD task, which can maintain the benefits of exploiting additional modalities, while avoiding the need for using multimodal data in the inference phase. We argue that the performance of the privileged KD framework mainly depends on two factors: 1) the effectiveness of the multimodal teacher network and 2) the completeness of the useful information transfer. To obtain a reliable teacher network, we propose a cross-modal interactive learning strategy and an anomaly normal discrimination loss, which target learning task-specific cross-modal features and encourage the separability of anomalous and normal representations, respectively. Furthermore, we design both representation-and logits-level distillation loss functions, which force the unimodal student network to distill abundant privileged knowledge from the well-trained multimodal teacher network, in a snippet-to-video fashion. Extensive experimental results on three public benchmarks demonstrate that the proposed privileged KD framework can train a lightweight yet effective detector, for localizing anomaly events under the supervision of video-level annotations.
Language	English
Publishing date	2023-04-10
Publishing country	United States
Document type	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2023.3263966
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Article ; Online: Retraction Note: METTL13 is downregulated in bladder carcinoma and suppresses cell proliferation, migration and invasion.

Zhang, Zhe / Zhang, Guojun / Kong, Chuize / Zhan, Bo / Dong, Xiao / Man, Xiaojun

Scientific reports

2023 Volume 13, Issue 1, Page(s) 11916

Language	English
Publishing date	2023-07-24
Publishing country	England
Document type	Retraction of Publication
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-39010-y
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Article ; Online: High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models.

Man, Xingwei / Liu, Rui / Zhang, Yu / Yu, Weiqiang / Kong, Fanhao / Liu, Li / Luo, Yan / Feng, Tao

Environmental research

2024 Volume 251, Issue Pt 1, Page(s) 118609

Abstract: Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of ground ...

Abstract	Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of ground observations, there is a pressing need for high-precision models to simulate ground-level ozone to assess surface ozone pollution. In this study, we have compared several widely utilized ensemble learning and deep learning methods for ground-level ozone simulation. Furthermore, we have thoroughly contrasted the temporal and spatial generalization performances of the ensemble learning and deep learning models. The 3-Dimensional Convolutional Neural Network (3-D CNN) model has emerged as the optimal choice for evaluating the daily maximum 8-h average ozone in Yunnan Province. The model has good performance: a spatial resolution of 0.05° × 0.05° and strong predictive power, as indicated by a Coefficient of Determination (R
Language	English
Publishing date	2024-03-03
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2024.118609
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Article ; Online: Active Compliance Smart Control Strategy of Hybrid Mechanism for Bonnet Polishing.

Li, Ze / Cheung, Chi Fai / Lam, Kin Man / Lun, Daniel Pak Kong

Sensors (Basel, Switzerland)

2024 Volume 24, Issue 2

Abstract: Compliance control strategies have been utilised for the ultraprecision polishing process for many years. Most researchers execute active compliance control strategies by employing impedance control law on a robot development platform. However, these ... ...

Abstract	Compliance control strategies have been utilised for the ultraprecision polishing process for many years. Most researchers execute active compliance control strategies by employing impedance control law on a robot development platform. However, these methods are limited by the load capacity, positioning accuracy, and repeatability of polishing mechanisms. Moreover, a sophisticated actuator mounted at the end of the end-effector of robots is difficult to maintain in the polishing scenario. In contrast, a hybrid mechanism for polishing that possesses the advantages of serial and parallel mechanisms can mitigate the above problems, especially when an active compliance control strategy is employed. In this research, a high-frequency-impedance robust force control strategy is proposed. It outputs a position adjustment value directly according to a contact pressure adjustment value. An open architecture control system with customised software is developed to respond to external interrupts during the polishing procedure, implementing the active compliance control strategy on a hybrid mechanism. Through this method, the hybrid mechanism can adapt to the external environment with a given contact pressure automatically instead of relying on estimating the environment stiffness. Experimental results show that the proposed strategy adapts the unknown freeform surface without overshooting and improves the surface quality. The average surface roughness value decreases from 0.057 um to 0.027 um.
Language	English
Publishing date	2024-01-10
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/s24020421
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Article: Serum Ferritin in Geriatric Individuals in the Shanghai Region: Distribution, Correlations, and Reference Intervals.

Wang, Ying / Yu, Xueying / Fan, Jiahui / Huang, Man / Fu, Yan / Zhang, Hui / Kong, Ruijiao / Man, Qiuhong

Clinical laboratory

2023 Volume 69, Issue 8

Abstract: Background: Serum ferritin levels have a clinical application in diagnosing diseases. However, the clinical standard levels and distribution characteristics of serum ferritin based on reference intervals (RIs) in the geriatric Han Chinese population in ... ...

Abstract	Background: Serum ferritin levels have a clinical application in diagnosing diseases. However, the clinical standard levels and distribution characteristics of serum ferritin based on reference intervals (RIs) in the geriatric Han Chinese population in the East China region have not previously been well reported. This work aimed to investigate the correlation between serum ferritin levels and 14 metabolic markers, analyse the distribution of serum ferritin, and establish serum ferritin RIs for geriatric (> 60 years) individuals in Shanghai. Methods: Four hundred and sixty-nine healthy Chinese Han subjects (age, 61 - 95 years; median, 71 years) were recruited from the Health Examination Center of Shanghai Fourth People's Hospital in 2021. Serum ferritin was measured on a Roche Cobas 8000 e602, and 14 biochemical parameters were measured on a Siemens Atellica CH-930 to analyse distributions and correlations and to establish serum ferritin RIs for the elderly population in Shanghai. Results: Serum ferritin levels were significantly different between genders (p = 0.06). The established RIs for serum ferritin were 24.44 - 627.09 ng/mL and 48.18 - 554.88 ng/mL in males and females, respectively. Correlation analyses revealed that ferritin levels were correlated with 7 parameters, including body mass index (BMI, p = 0.02), gamma-glutamyl transferase (GGT, p < 0.01), alanine aminotransferase (ALT, p < 0.01), triglycerides (TGs, p < 0.01), high-density lipoprotein (HDL, p < 0.01), total protein (TP, p < 0.01) and prealbumin (PAB, p < 0.01). When the participants were further divided by BMI, aspartate aminotransferase (AST) was an additional variable that was positively correlated only in the overweight/obese group (p = 0.04), while globulin (GLO) was an additional variable that was positively correlated only in the other group (p < 0.01). Conclusions: Nutrition and metabolism may play a great role in the regulation of serum ferritin levels in geriatric individuals in vivo. The RIs established for serum ferritin may provide precise references for further studies on ferritin-related disease in geriatric individuals.
MeSH term(s)	Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; China ; Ferritins/blood ; Obesity ; Reference Values ; Triglycerides ; East Asian People
Chemical Substances	Ferritins (9007-73-2) ; Triglycerides
Language	English
Publishing date	2023-08-07
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1307629-2
ISSN	1433-6510 ; 0941-2131
ISSN	1433-6510 ; 0941-2131
DOI	10.7754/Clin.Lab.2023.221223
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Article ; Online: AMENet is a monocular depth estimation network designed for automatic stereoscopic display.

Wu, Tianzhao / Xia, Zhongyi / Zhou, Man / Kong, Ling Bing / Chen, Zengyuan

Scientific reports

2024 Volume 14, Issue 1, Page(s) 5868

Abstract: Monocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge. In this paper, we propose a depth estimation network for autostereoscopic ... ...

Abstract	Monocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge. In this paper, we propose a depth estimation network for autostereoscopic displays, which aims at improving the accuracy of monocular depth estimation by fusing Vision Transformer (ViT) and Convolutional Neural Network (CNN). Our approach feeds the input image as a sequence of visual features into the ViT module and utilizes its global perception capability to extract high-level semantic features of the image. The relationship between the losses is quantified by adding a weight correction module to improve robustness of the model. Experimental evaluation results on several public datasets show that AMENet exhibits higher accuracy and robustness than existing methods in different scenarios and complex conditions. In addition, a detailed experimental analysis was conducted to verify the effectiveness and stability of our method. The accuracy improvement on the KITTI dataset compared to the baseline method is 4.4%. In summary, AMENet is a promising depth estimation method with sufficient high robustness and accuracy for monocular depth estimation tasks.
Language	English
Publishing date	2024-03-11
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/s41598-024-56095-1
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Article ; Online: Holistic-Guided Disentangled Learning With Cross-Video Semantics Mining for Concurrent First-Person and Third-Person Activity Recognition.

Liu, Tianshan / Zhao, Rui / Jia, Wenqi / Lam, Kin-Man / Kong, Jun

IEEE transactions on neural networks and learning systems

2024 Volume 35, Issue 4, Page(s) 5211–5225

Abstract: The popularity of wearable devices has increased the demands for the research on first-person activity recognition. However, most of the current first-person activity datasets are built based on the assumption that only the human-object interaction (HOI) ...

Abstract	The popularity of wearable devices has increased the demands for the research on first-person activity recognition. However, most of the current first-person activity datasets are built based on the assumption that only the human-object interaction (HOI) activities, performed by the camera-wearer, are captured in the field of view. Since humans live in complicated scenarios, in addition to the first-person activities, it is likely that third-person activities performed by other people also appear. Analyzing and recognizing these two types of activities simultaneously occurring in a scene is important for the camera-wearer to understand the surrounding environments. To facilitate the research on concurrent first- and third-person activity recognition (CFT-AR), we first created a new activity dataset, namely PolyU concurrent first- and third-person (CFT) Daily, which exhibits distinct properties and challenges, compared with previous activity datasets. Since temporal asynchronism and appearance gap usually exist between the first- and third-person activities, it is crucial to learn robust representations from all the activity-related spatio-temporal positions. Thus, we explore both holistic scene-level and local instance-level (person-level) features to provide comprehensive and discriminative patterns for recognizing both first- and third-person activities. On the one hand, the holistic scene-level features are extracted by a 3-D convolutional neural network, which is trained to mine shared and sample-unique semantics between video pairs, via two well-designed attention-based modules and a self-knowledge distillation (SKD) strategy. On the other hand, we further leverage the extracted holistic features to guide the learning of instance-level features in a disentangled fashion, which aims to discover both spatially conspicuous patterns and temporally varied, yet critical, cues. Experimental results on the PolyU CFT Daily dataset validate that our method achieves the state-of-the-art performance.
MeSH term(s)	Humans ; Neural Networks, Computer ; Semantics ; Human Activities ; Cues
Language	English
Publishing date	2024-04-04
Publishing country	United States
Document type	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2022.3202835
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