作者机构：
[Tang, Dan; Xiang, Xing; Yi, Linfeng] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Inst Microbiol & Infect Dis,Dept Clin Lab Med, Hengyang, Hunan, Peoples R China.;[Tang, Huifang; Huang, Hong; Tang, Dan; Xiang, Xing; Yi, Linfeng; Tang, HF] Clin Res Ctr Myocardial Injury Hunan Prov, Hengyang, Hunan, Peoples R China.;[Tang, Huifang; Huang, Hong; Tang, Dan; Xiang, Xing; Yi, Linfeng; Tang, HF] Univ South China, Affiliated Hosp 1, Inst Cardiovasc Dis, Hengyang Med Sch, Hengyang, Hunan, Peoples R China.;[Tang, Huifang; Huang, Hong; Tang, Dan; Xiang, Xing; Yi, Linfeng; Tang, HF] Univ South China, Hunan Prov Key Lab Multiom & Artificial Intelligen, Hengyang, Hunan, Peoples R China.;[Xiao, Chungang] Hunan Univ Med Gen Hosp, Dept Orthoped, Huaihua, Hunan, Peoples R China.
通讯机构：
[Huang, H ; Tang, HF] C;Clin Res Ctr Myocardial Injury Hunan Prov, Hengyang, Hunan, Peoples R China.;Univ South China, Affiliated Hosp 1, Inst Cardiovasc Dis, Hengyang Med Sch, Hengyang, Hunan, Peoples R China.;Univ South China, Hunan Prov Key Lab Multiom & Artificial Intelligen, Hengyang, Hunan, Peoples R China.;Univ South China, Hunan Prov Key Lab Multiom & Artificial Intelligen, Hengyang 421001, Hunan, Peoples R China.
关键词：
Titin;heart failure;lactylation;sarcomeric structure and function;α-MHC
摘要：
Lactylation of alpha-myosin heavy chain (alpha-MHC) has recently been reported to preserve sarcomeric structure and function and attenuate the development of heart failure. Specifically, lactylation enhanced the interaction of alpha-MHC with the sarcomeric protein Titin, thereby maintaining normal sarcomeric structure and myocardial contractile function. Furthermore, the administration of lactate or inhibition of lactate efflux potentially treats heart failure by restoring lactylation of alpha-MHC and the interaction of alpha-MHC with Titin. This finding highlights the significant role of alpha-MHC lactylation in myocardial diseases and presents a new therapeutic target for the treatment of heart failure.
作者机构：
[Liu, Fuchun; Liu, Zeyong; Chen, Xujian; Liu, FC] South China Univ Technol, Sch Automat Sci & Engn, Guangzhou, Peoples R China.;[Huang, Zewen] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
会议名称：
35th Chinese Control and Decision Conference (CCDC)
会议时间：
MAY 20-22, 2023
会议地点：
Yichang, PEOPLES R CHINA
会议主办单位：
[Liu, Fuchun;Chen, Xujian;Liu, Zeyong] South China Univ Technol, Sch Automat Sci & Engn, Guangzhou, Peoples R China.^[Huang, Zewen] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
会议论文集名称：
Chinese Control and Decision Conference
关键词：
LiDAR point cloud;Multi-scale contextual feature;Semantic segmentation
摘要：
Semantic segmentation of point clouds scanned by LiDAR is one of the means for robots to perceive the environment autonomously. Aiming at the sparse and unstructured characteristics of LiDAR point clouds, we use the spherical projection formula to project LiDAR point clouds to a dense range image. A 2D convolutional neural network based on the encoder-decoder structure is used to perform semantic segmentation on the range image. After segmentation on the range image, we re-project the semantic result of the range image to the LiDAR point clouds using a kNN method. To extract the context features of the range image, we design a multi-scale contextual feature extraction module based on the feature pyramid network, so the encoder-decoder network can better obtain the semantic features of the range image. The experimental results show that the mIoU of the proposed model is 55.2% and 45.0% in SemanticKITTI and SemanticPOSS, which is 3.0% and 16.1% higher than that of the RangeNet++ network, respectively.
作者机构：
[Isa, Mohd Hafizal Mohd; Isa, MHM; He, Danqiu; He, DQ] Univ Sains Malaysia, Sch Housing Bldg & Planning, George Town 11800, Malaysia.;[He, Danqiu] Univ South China, Solux Coll Architecture & Design, Hengyang 421001, Peoples R China.
会议名称：
6th International Conference on Architecture and Civil Engineering (ICACE)
会议时间：
AUG 18, 2022
会议地点：
Kuala Lumpur, MALAYSIA
会议主办单位：
[He, Danqiu;Isa, Mohd Hafizal Mohd] Univ Sains Malaysia, Sch Housing Bldg & Planning, George Town 11800, Malaysia.^[He, Danqiu] Univ South China, Solux Coll Architecture & Design, Hengyang 421001, Peoples R China.
会议论文集名称：
Lecture Notes in Civil Engineering
关键词：
MPCM;Building wall;Energy saving;Sustainable development
摘要：
Many researchers have confirmed that applying phase change material (PCM) thermal energy storage technology to building walls can effectively solve the problem of building energy consumption, but there are still many shortcomings. For example, leakage is easy to occur in the process of material compounding. Therefore, this problem can be solved by using microcapsule technology. With the use of microencapsulated phase change material (MPCM) and building materials composites, PCM is encapsulated in microcapsules, which can effectively solve problems such as leakage, so that PCM can be fully used in building walls. This paper reviews the basic characteristics, preparation technology, and thermal properties of MPCM and focuses on the application of MPCM in walls after compounding with several building materials. The influence of this composite material on building energysaving was explored, hoping to provide more ideas for the sustainable development of future buildings.
摘要：
The task of Knowledge Graph Completion (KGC) entails inferring missing relations and facts in a partially specified graph to discover new knowledge. However, the discrepancy in the targets between the training and inference phases might lead to in-depth bias and in-breadth bias during inference, potentially resulting in incorrect outcomes. In this work, we conduct a comprehensive analysis of these biases to determine their extent of impact. To mitigate these biases, we propose a novel debiasing framework called Causal Inference-based Debiasing Framework for KGC (CIDF) by formulating a causal graph and utilizing it for causal analysis of KGC tasks. The framework incorporates In-Depth Bias Mitigation to diminish the bias on feature representations by measuring the bias during inference, and In-Breadth Bias Mitigation to increase the distinguishability between feature representations by introducing a novel loss function. We evaluate the effectiveness of our proposed method on four benchmark datasets - WN18RR, FB15k-237, Wikidata5M-Trans, and Wikidata5M-Ind, achieving improvements of 2.5%, 0.9%, 3.2%, and 1.5% on Hit@1 respectively. Our results demonstrate that CIDF leads to significant improvements on these datasets, with more substantial gains observed in the biased settings on WN18RR achieving a 3.4% improvement in Hit@1.
作者机构：
[Chen, Kai; Zhang, Yi; Ni, Bingbing; Zhang, Wenjun; Huang, Xiaoyang] Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China.;[Li, Teng] Anhui Univ, Hefei, Peoples R China.;[Ni, Bingbing] USC SJTU Inst Cultural & Creat Ind, Shanghai, Peoples R China.
会议名称：
IEEE/CVF International Conference on Computer Vision (ICCV)
会议时间：
OCT 02-06, 2023
会议地点：
Paris, FRANCE
会议主办单位：
[Huang, Xiaoyang;Zhang, Yi;Chen, Kai;Zhang, Wenjun;Ni, Bingbing] Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China.^[Li, Teng] Anhui Univ, Hefei, Peoples R China.^[Ni, Bingbing] USC SJTU Inst Cultural & Creat Ind, Shanghai, Peoples R China.
会议论文集名称：
IEEE International Conference on Computer Vision
摘要：
Shape primitives decomposition has been an important and long-standing task in 3D shape analysis. Prior arts heavily rely on 3D point clouds or voxel data for shape primitives extraction, which are less practical in real-world scenarios. This paper proposes to learn shape primitives from multi-view images by introducing implicit surface rendering. It is challenging since implicit shapes have a high degree of freedom, which violates the simplicity property of shape primitives. In this work, a novel regularization term named Implicit Convexity Regularization (ICR) imposed on implicit primitive learning is proposed to tackle this problem. We start with the convexity definition of general 3D shapes, and then derive the equivalent expression for implicit shapes represented by signed distance functions ( SDFs). Further, instead of directly constraining the output SDF values which cause unstable optimization, we alternatively impose constraint on second order directional derivatives on line segments inside the shapes, which proves to be a tighter condition for 3D convexity. Implicit primitives constrained by the proposed ICR are combined into a whole object via softmax-weighted-sum operation over all primitive SDFs. Experiments on synthetic and real-world datasets show that our method is able to decompose objects into simple and reasonable shape primitives without the need of segmentation labels or 3D data. Code and data is publicly available in https:// github.com/ seanywang0408/ICR.
期刊：
Journal of Building Engineering,2023年72:106503 ISSN：2352-7102
通讯作者：
Xie, D
作者机构：
[Zhang, Zixuan; Xie, D; Xie, Dong; Zhou, Lifeng; Wang, Lize] Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.;[Zhang, Zixuan; Xie, Dong; Zhou, Lifeng; Wang, Lize] Natl & Local Joint Engn Res Ctr Airborne Pollutant, Hengyang 421001, Peoples R China.
通讯机构：
[Xie, D ] U;Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.
关键词：
Building energy prediction;Bi-directional gated recurrent unit;Convolution neural network;Attention mechanism;Residual connection
摘要：
Accurate building energy consumption prediction is crucial to the rational planning of building energy systems. The energy consumption of buildings is influenced by various elements and is characterized by non-linearity and non-stationarity. To fully tap the time series characteristics of building energy consumption and heighten the model's prediction accuracy, this paper proposes a hybrid neural network prediction model combining attention mechanism, Bidirectional Gate Recurrent Unit (BiGRU), Convolutional Neural Networks (CNN), and the residual connection. The model uses BiGRU to train the extracted feature vectors by CNN on a two-way cycle. The attention mechanism highlights the key information extracted, and the residual connection is used to learn the features fully. Taking the energy consumption data of an office building in Guangzhou, China, as the object of study, the results indicate that the proposed model shows a stronger prediction accuracy than the commonly used model with an R2 of 90.74% and a CV-RMSE of 19.24%. Compared with the other five common models, the RMSE, MAPE, and MAE of the proposed model achieve lower error rates. Besides, the length 24 of the sliding window exceeds other lengths in the established model. The prediction accuracy of the established model in working hours outperforms the non-working hours of the office building. Building energy consumption prediction in the same season is better than that in the whole year.
期刊：
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS,2023年117(2, Supplement):e479-e480 ISSN：0360-3016
通讯作者：
Q. Ni
作者机构：
[Ni, Q.] Cent South Univ, Hunan Canc Hosp, Affiliated Canc Hosp, Dept Radiat Oncol,Xiangya Sch Med, Changsha, Peoples R China.;[Ni, Q.] Univ South China, Sch Nucl Sci & Technol, Hengyang, Peoples R China.
通讯机构：
[Q. Ni] D;Department of Radiation Oncology, Hunan Cancer Hospital, Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China<&wdkj&>School of Nuclear Science and Technology, University of South China, Hengyang, China
会议名称：
65th ANNUAL MEETING OF THE AMERICAN-SOCIETY-FOR-RADIATION-ONCOLOGY (ASTRO)
会议时间：
OCT 01-04, 2023
会议地点：
San Diego, CA
摘要：
To establish the different machine learning classification predict models of gamma pass rates for specific dosimetric verification of pelvic intensity modulated radiotherapy plan which based on the radiomic features and to explore the best prediction model.
Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 196 pelvic intensity-modulated radiotherapy plans was carried. Prediction models were established by extracting radiomic features data. Four machine learning algorithms, random forest, support vector machine, adaptive boosting and gradient boosting decision trees, were used to calculate the AUC value, sensitivity and specificity respectively. The classification performance of the four prediction models were evaluated.
The sensitivity and specificity of the random forest, support vector machine, adaptive boosting, and gradient boosting decision trees models were 0.93,0.85,0.93,0.96, and 0.38,0.69,0.46, and 0.46, respectively. The AUC values for the random forest model and the adaptive boosting model were 0.81 and 0.82, respectively, and the AUC values for the support vector machine and gradient boosting decision tree models were 0.87.
Machine learning methods based on radiomics can be used to establish a prediction model of gamma pass rate for specific dosimetric verification of pelvic intensity modulated radiotherapy. The classification performance of support vector machine model and gradient boosting decision trees model is better than that of random forest model and adaptive boosting model. The prediction model for a specific site is helpful to improve the performance of the model.
摘要：
Sr-doped LaMnO3, as one of the most successful cathodes for solid oxide fuel cells (SOFCs), can effectively function at high temperatures. However, its cathode kinetics considerably decreases with decreasing temperature, rendering it unsuitable for SOFCs operating at intermediate temperatures. In this study, La0.5Sr0.5MnO3-delta(LSM) is coated with TiO2 to create the LSM + TiO2 cathode. TiO2 is shown to modify the electronic structure at the LSM/TiO2 interface, allowing for charge accumulation for the O atoms at the interface. The activated O atoms enhance the formation of oxygen vacancies, which benefit the oxygen diffusion ability. Using LSM + TiO2 as a cathode for proton-conducting SOFCs (H-SOFCs) operating at intermediate temperatures, the corresponding fuel cell demonstrated enhanced cell output performance compared with cells employing solely LSM or TiO2 cathodes, exhibiting the synergistic effect of combining LSM and TiO2. Additionally, the LSM + TiO2 cells achieved a power output of 1118 mWcm(-2) at 700 degrees C, the highest yet reported value for H-SOFCs with LSM cathodes. LSM + TiO2 was demonstrated to be stable against CO2 and steam, allowing for steady functioning of the cell under working conditions, thereby resolving the problem of LSM's poor performance in H-SOFCs while retaining remarkable stability.
作者机构：
[Liu, Yong] Univ South China, Coll Elect Engn, Hengyang 421001, Peoples R China.;[Hu, Ji-wen; Xie, Ya-qian; Liu, Yong] Univ South China, Coll Math & Phys, Hengyang 421001, Peoples R China.
会议名称：
Conference on Biophysical-Society-of-GuangDong-Province-Academic-Forum - Precise Photons and Life Health (PPLH)
会议时间：
DEC 09-11, 2022
会议地点：
Guangzhou, PEOPLES R CHINA
会议主办单位：
[Liu, Yong] Univ South China, Coll Elect Engn, Hengyang 421001, Peoples R China.^[Liu, Yong;Hu, Ji-wen;Xie, Ya-qian] Univ South China, Coll Math & Phys, Hengyang 421001, Peoples R China.
会议论文集名称：
Proceedings of SPIE
关键词：
Atherosclerosis;Electromagnetic wave;Ablation of heat;Finite element method
摘要：
The purpose of this study is to explore the thermal damage of microwave to atherosclerotic plaques in order to achieve the purpose of treating atherosclerosis. In this paper, a fluid-solid-heat coupling model of thermal ablation of atherosclerotic plaque is established (The coupling model of blood-plaque-electromagnetic wave is studied in this paper, in which the thermal ablation of atherosclerotic plaque means that the electromagnetic wave is used to generate heat, and the temperature of atherosclerotic plaque tissue rises. If the cells in it reach the threshold of death temperature, they will be killed, so as to achieve the purpose of thermal ablation.). The electromagnetic field and bio-thermal equation are solved and analyzed by finite element method. By calculating the temperature and thermal damage distribution of microwave on atherosclerotic plaque, the effect of microwave on thermal ablation of atherosclerotic plaque was evaluated. The results show that the thermal damage degree of atherosclerotic plaque is positively correlated with electromagnetic wave frequency, electromagnetic wave power and heating time. The model shows that electromagnetic wave hyperthermia may provide a new therapeutic mode for thermal ablation of atherosclerotic plaques.
作者机构：
[Liu, Jing; Hu, Bin; Gong, Han; Yang, Chaoying; Liang, Long] Cent South Univ, Mol Biol Res Ctr, Hunan Prov Key Lab Basic & Appl Hematol, Dept Hematol,Xiangya Hosp 2,Sch Life Sci, Changsha, Peoples R China.;[Nie, Ling] Cent South Univ, Xiangya Hosp, Dept Hematol, Changsha, Peoples R China.;[Zhang, Ji] Univ South China, Dept Clin Lab Med, Inst Microbiol & Infect Dis, Affiliated Hosp 1,Hengyang Med Sch, Hengyang, Peoples R China.;[Narla, Mohandas] New York Blood Ctr, Res Lab Red Cell Physiol, New York, NY USA.;[Sheng, Yue] Cent South Univ, Xiangya Hosp 2, Dept Hematol, Changsha, Peoples R China.
会议名称：
65th Annual Meeting of the American-Society-of-Hematology (ASH)
会议时间：
DEC 09-12, 2023
会议地点：
San Diego, CA
摘要：
Lysine succinylation has emerged as a recently discovered protein modification that significantly impacts the chemical environment and exhibits diverse functions in various biological processes. However, the specific role of lysine succinylation in erythropoiesis has not been fully elucidated. In this study, we investigated the levels of six common acylations (acetylation, crotonylation, succinylation, propionylation, butyrylation, and malonylation) in human erythroid cells. Interestingly, we observed a prominent accumulation of lysine succinylation during human erythroid differentiation, suggesting its potential importance in this process. To explore the functional significance of succinylation, we inhibited succinylation in human erythroid progenitor cell line by disrupting the expression of the key succinyltransferases and desuccinylases. The results revealed that succinylation inhibition led to suppressed cell proliferation, increased apoptosis, and disrupted differentiation, indicating the essential role of succinylation in erythropoiesis. Furthermore, integrative proteome and succinylome analysis identifies 939 quantifiable proteins with 2,871 Ksu sites. Notably, we observed inconsistencies between alterations in protein levels and succinylation levels, suggesting that the role of succinylation in proteins' function regulation. These succinylated proteins are widely distributed in various cellular compartments and involved in multiple cell processes, indicating that succinylation is a prevalent modification in erythropoiesis. Mechanically, we identified CYCS as a key target of succinylation during erythropoiesis, emphasizing its essential role in this process. Specially, we implicated KAT2A-mediated histone succinylation in chromatin remodeling, further highlighting the regulatory significance of lysine succinylation in erythropoiesis at the epigenetic level. Collectively, our comprehensive investigation of the succinylation landscape during erythropoiesis provides valuable insights into its regulatory role and offer potential implications for erythroid-related diseases and therapeutic strategies.
会议名称：
11th International Conference on Bioinformatics and Computational Biology (ICBCB)
会议时间：
APR 21-23, 2023
会议地点：
Hangzhou, PEOPLES R CHINA
会议主办单位：
[Xu, Rong;Luo, Lingyun;Liu, Zhiming;Ouyang, Chunping;Wan, Yaping] Univ South China, Sch Comp, Hengyang, Peoples R China.
关键词：
drug-drug interaction;prediction;deep learning;graph contrastive learning;adverse drug events
摘要：
Adverse drug-drug interactions (DDIs) may occur when drugs are combined to treat complex or comorbid diseases, which can result in adverse drug events, injury, and even death. Therefore, accurate prediction of potential DDI events is critical. Recently, automated computational methods such as deep learning are widely used for DDI events prediction. However, most of these methods only consider single information about the drug or rely on a large amount of label data, which easily leads to insufficient robustness and generalization ability. Accordingly, we proposed a novel end-to-end graph contrastive learning model for predicting multi-relational DDI events (CLDDI). It comprehensively considers the rich biomedical information of the Knowledge Graph (KG) and the structural information of the drug network. Specifically, we first generate two graph views by randomly corrupting the original KG, and compute a contrastive loss to maximize the agreement of node representation in these two views. Then we extract the drug embeddings obtained by contrastive learning and aggregate their neighbor information in the multi-relational DDI network. Finally, we combine the contrastive and supervised loss to learn the feature representation of nodes in an end-to-end fashion. Extensive experiments on real datasets show that the performance of CLDDI is competitive with the best baselines. Experimental results on sparse datasets further demonstrate that CLDDI has strong generalization performance and robustness.
会议名称：
22nd International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2021)
会议时间：
DEC 17-19, 2021
会议地点：
Sun Yat Sen Univ, Guangzhou, PEOPLES R CHINA
会议主办单位：
Sun Yat Sen Univ
会议论文集名称：
Lecture Notes in Computer Science
关键词：
Communication distance;Data locality;Executor allocation;Spark
摘要：
Data locality is a key factor influencing the performance of Spark systems. As the execution container of tasks, the executors started on which nodes can directly affect the locality level achieved by the tasks. This paper tries to improve the data locality by executor allocation in reduce stage for Spark framework. Firstly, we calculate the network distance matrix of executors and formulate an optimal executor allocation problem to minimize the total communication distance. Then, an approximation algorithm is proposed and the approximate factor is proved to be 2. Finally, we evaluate the performance of our algorithm in a practical Spark cluster by using several representative benchmarks: sort, pageRank and LDA. Experimental results show that the proposed algorithm can help to improve the data locality and application/job performance obviously.
会议名称：
12th International Conference on Position Sensitive Detectors
会议时间：
SEP 12-17, 2021
会议地点：
Birmingham, ENGLAND
会议主办单位：
[Pritchard, J. L.;Velthuis, J. J.;Beck, L.;Li, Y.;De Sio, C.;Ballisat, L.;Duan, J.;Shi, Y.;Hugtenburg, R. P.] Univ Bristol, Sch Phys, Bristol BS8 1TL, Avon, England.^[Velthuis, J. J.;Hugtenburg, R. P.] Swansea Univ Med Sch, Dept Med Phys, Swansea SA2 8QA, W Glam, Wales.^[Velthuis, J. J.] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.^[Hugtenburg, R. P.] Swansea Bay Univ Hlth Board, Dept Med Phys & Clin Engn, Swansea SA2 8QA, W Glam, Wales.
关键词：
Radiotherapy concepts;Solid state detectors;X-ray detectors;Image reconstruction in medical imaging
摘要：
A multileaf collimator (MLC) is an integral component in modern radiotherapy machines as it dynamically shapes the photon field used for patient treatment. Currently, the MLC leaves which collimate the treatment field are mechanically calibrated to ±1 mm every 3 months and during pre-treatment calibration are calibrated to the mechanically set leaf positions. Leaf drift can occur between calibration dates and hence exceed the ±1 mm tolerance. Pre-treatment verification, increases LINAC usage time so is seldom performed for each individual patient treatment, but instead for an acceptable sample of patients and/or treatment fractions. Independent real-time treatment verification is therefore desirable. We are developing a large area CMOS MAPS upstream of the patient to monitor MLC leaf positions for real-time treatment verification. CMOS MAPS are radiation hard for photon and electron irradiation, have high readout speeds and low attenuation which makes them an ideal upstream radiation detector for radiotherapy. Previously, we reported on leaf position reconstruction for single leaves using the Lassena, a 12 × 14 cm2, three side buttable MAPS suitable for clinical deployment. Sobel operator based methods were used for edge reconstruction. It was shown that the correspondence between reconstructed and set leaf position was excellent and resolutions ranged between 60.6 ± 8 and 109 ± 12 μm for a single central leaf with leaf extensions ranging from 1 to 35 mm using 0.3 sec of treatment beam time at 400 MU/min. Here, we report on leaf edge reconstruction using updated methods for complex leaf configurations, as occur in clinical use. Results show that leaf positions can be reconstructed with resolutions of 62 ± 6 μm for single leaves and 86 ± 16 μm for adjacent leaves at the isocenter using 0.15 sec at 400 MU/min of treatment beam. These resolutions are significantly better than current calibration standards.
