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1. Secure and Efficient General Matrix Multiplication On Cloud Using Homomorphic Encryption

Author

Gao, Yang, Quan, Gang, Homsi, Soamar, Wen, Wujie, and Wang, Liqiang

Subjects
Computer Science - Cryptography and Security
Abstract

Despite the cloud enormous technical and financial advantages, security and privacy have always been the primary concern for adopting cloud computing facility, especially for government agencies and commercial sectors with high-security requirements. Homomorphic Encryption (HE) has recently emerged as an effective tool in assuring privacy and security for sensitive applications by allowing computing on encrypted data. One major obstacle to employing HE-based computation, however, is its excessive computational cost, which is multiple magnitudes higher than its counterpart based on the plaintext. In this paper, we study the problem of how to reduce the HE-based computational cost for general Matrix Multiplication (MM), i.e., a fundamental building block for numerous practical applications, by taking advantage of the Single Instruction Multiple Data (SIMD) operation supported by HE schemes. Specifically, we develop a novel element-wise algorithm for general matrix multiplication, based on which we propose two HE-based General Matrix Multiplication (HEGMM) algorithms to reduce the HE computation cost. Our experimental results show that our algorithms can significantly outperform the state-of-the-art approaches of HE-based matrix multiplication., Comment: 10 pages, 7 figures. 4 tables

Published
2024

2. CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference

Author

Ran, Ran, Xu, Nuo, Wang, Wei, Quan, Gang, Yin, Jieming, and Wen, Wujie

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Recently cloud-based graph convolutional network (GCN) has demonstrated great success and potential in many privacy-sensitive applications such as personal healthcare and financial systems. Despite its high inference accuracy and performance on cloud, maintaining data privacy in GCN inference, which is of paramount importance to these practical applications, remains largely unexplored. In this paper, we take an initial attempt towards this and develop $\textit{CryptoGCN}$--a homomorphic encryption (HE) based GCN inference framework. A key to the success of our approach is to reduce the tremendous computational overhead for HE operations, which can be orders of magnitude higher than its counterparts in the plaintext space. To this end, we develop an approach that can effectively take advantage of the sparsity of matrix operations in GCN inference to significantly reduce the computational overhead. Specifically, we propose a novel AMA data formatting method and associated spatial convolution methods, which can exploit the complex graph structure and perform efficient matrix-matrix multiplication in HE computation and thus greatly reduce the HE operations. We also develop a co-optimization framework that can explore the trade offs among the accuracy, security level, and computational overhead by judicious pruning and polynomial approximation of activation module in GCNs. Based on the NTU-XVIEW skeleton joint dataset, i.e., the largest dataset evaluated homomorphically by far as we are aware of, our experimental results demonstrate that $\textit{CryptoGCN}$ outperforms state-of-the-art solutions in terms of the latency and number of homomorphic operations, i.e., achieving as much as a 3.10$\times$ speedup on latency and reduces the total Homomorphic Operation Count by 77.4\% with a small accuracy loss of 1-1.5$\%$., Comment: Accepted in Conference on Neural Information Processing Systems (NeurIPS 2022)

Published
2022

7. Neural Kalman Filtering for Speech Enhancement

Author

Xue, Wei, Quan, Gang, Zhang, Chao, Ding, Guohong, He, Xiaodong, and Zhou, Bowen

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
Abstract

Statistical signal processing based speech enhancement methods adopt expert knowledge to design the statistical models and linear filters, which is complementary to the deep neural network (DNN) based methods which are data-driven. In this paper, by using expert knowledge from statistical signal processing for network design and optimization, we extend the conventional Kalman filtering (KF) to the supervised learning scheme, and propose the neural Kalman filtering (NKF) for speech enhancement. Two intermediate clean speech estimates are first produced from recurrent neural networks (RNN) and linear Wiener filtering (WF) separately and are then linearly combined by a learned NKF gain to yield the NKF output. Supervised joint training is applied to NKF to learn to automatically trade-off between the instantaneous linear estimation made by the WF and the long-term non-linear estimation made by the RNN. The NKF method can be seen as using expert knowledge from WF to regularize the RNN estimations to improve its generalization ability to the noise conditions unseen in the training. Experiments in different noisy conditions show that the proposed method outperforms the baseline methods both in terms of objective evaluation metrics and automatic speech recognition (ASR) word error rates (WERs)., Comment: Submitted to ICASSP2021

Published
2020

8. DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

Author

Liu, Zihao, Liu, Tao, Wen, Wujie, Jiang, Lei, Xu, Jie, Wang, Yanzhi, and Quan, Gang

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Computer Science - Performance
Abstract

As one of most fascinating machine learning techniques, deep neural network (DNN) has demonstrated excellent performance in various intelligent tasks such as image classification. DNN achieves such performance, to a large extent, by performing expensive training over huge volumes of training data. To reduce the data storage and transfer overhead in smart resource-limited Internet-of-Thing (IoT) systems, effective data compression is a "must-have" feature before transferring real-time produced dataset for training or classification. While there have been many well-known image compression approaches (such as JPEG), we for the first time find that a human-visual based image compression approach such as JPEG compression is not an optimized solution for DNN systems, especially with high compression ratios. To this end, we develop an image compression framework tailored for DNN applications, named "DeepN-JPEG", to embrace the nature of deep cascaded information process mechanism of DNN architecture. Extensive experiments, based on "ImageNet" dataset with various state-of-the-art DNNs, show that "DeepN-JPEG" can achieve ~3.5x higher compression rate over the popular JPEG solution while maintaining the same accuracy level for image recognition, demonstrating its great potential of storage and power efficiency in DNN-based smart IoT system design., Comment: 55th Design Automation Conference (DAC2018)

Published
2018

9. PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning

Author

Liu, Tao, Jiang, Lei, Jin, Yier, Quan, Gang, and Wen, Wujie

Subjects
Computer Science - Neural and Evolutionary Computing, Quantitative Biology - Neurons and Cognition
Abstract

One of the most exciting advancements in AI over the last decade is the wide adoption of ANNs, such as DNN and CNN, in many real-world applications. However, the underlying massive amounts of computation and storage requirement greatly challenge their applicability in resource-limited platforms like the drone, mobile phone, and IoT devices etc. The third generation of neural network model--Spiking Neural Network (SNN), inspired by the working mechanism and efficiency of human brain, has emerged as a promising solution for achieving more impressive computing and power efficiency within light-weighted devices (e.g. single chip). However, the relevant research activities have been narrowly carried out on conventional rate-based spiking system designs for fulfilling the practical cognitive tasks, underestimating SNN's energy efficiency, throughput, and system flexibility. Although the time-based SNN can be more attractive conceptually, its potentials are not unleashed in realistic applications due to lack of efficient coding and practical learning schemes. In this work, a Precise-Time-Dependent Single Spike Neuromorphic Architecture, namely "PT-Spike", is developed to bridge this gap. Three constituent hardware-favorable techniques: precise single-spike temporal encoding, efficient supervised temporal learning, and fast asymmetric decoding are proposed accordingly to boost the energy efficiency and data processing capability of the time-based SNN at a more compact neural network model size when executing real cognitive tasks. Simulation results show that "PT-Spike" demonstrates significant improvements in network size, processing efficiency and power consumption with marginal classification accuracy degradation when compared with the rate-based SNN and ANN under the similar network configuration., Comment: 23rd Asia and South Pacific Design Automation Conference (ASP-DAC 2018)

Published
2018

10. MT-Spike: A Multilayer Time-based Spiking Neuromorphic Architecture with Temporal Error Backpropagation

Author

Liu, Tao, Liu, Zihao, Lin, Fuhong, Jin, Yier, Quan, Gang, and Wen, Wujie

Subjects
Computer Science - Neural and Evolutionary Computing, Quantitative Biology - Neurons and Cognition
Abstract

Modern deep learning enabled artificial neural networks, such as Deep Neural Network (DNN) and Convolutional Neural Network (CNN), have achieved a series of breaking records on a broad spectrum of recognition applications. However, the enormous computation and storage requirements associated with such deep and complex neural network models greatly challenge their implementations on resource-limited platforms. Time-based spiking neural network has recently emerged as a promising solution in Neuromorphic Computing System designs for achieving remarkable computing and power efficiency within a single chip. However, the relevant research activities have been narrowly concentrated on the biological plausibility and theoretical learning approaches, causing inefficient neural processing and impracticable multilayer extension thus significantly limitations on speed and accuracy when handling the realistic cognitive tasks. In this work, a practical multilayer time-based spiking neuromorphic architecture, namely "MT-Spike", is developed to fill this gap. With the proposed practical time-coding scheme, average delay response model, temporal error backpropagation algorithm, and heuristic loss function, "MT-Spike" achieves more efficient neural processing through flexible neural model size reduction while offering very competitive classification accuracy for realistic recognition tasks. Simulation results well validated that the algorithmic power of deep multi-layer learning can be seamlessly merged with the efficiency of time-based spiking neuromorphic architecture, demonstrating great potentials of "MT-Spike" in resource and power constrained embedded platforms., Comment: 36th International Conference On Computer Aided Design (ICCAD 2017)

Published
2018

11. Structural-visual functional relationships detected by optical coherence tomography in varying age-cohorts’ patients with optic neuritis

Author

Wei Shi, Hong-Tao Zhang, Hua-Xin Zuo, Si-Yuan Li, Pan-Pan Zheng, Quan-Gang Xu, Si-Yu Cai, Shi-Hui Wei, Li Li, and Chun-Xia Peng

Subjects
optic neuritis, age-cohort, final visual acuity, structural impairment, linear correlations, Ophthalmology, RE1-994
Abstract

AIM: To assess the relationships of final best-corrected visual acuity (BCVA) and the optic nerve structural loss in varying age-cohorts of optic neuritis (ON) patients. METHODS: This is a retrospective, cross-sectional study. Totally 130 ON subjects (200 eyes) without ON onset within 6mo were included, who underwent BCVA assessment, peripapillary retinal nerve fibre layer (pRNFL) and macular segmented layers evaluation by optical coherence tomography (OCT). RESULTS: For the 0-18y cohort, the final BCVA (logMAR) was significantly better and less frequent recurrences than adult cohorts (P=0.000). The final BCVA (logMAR) in all age-cohorts of the ON patients had negative and linear correlations to the pRNFL thicknesses and macular retinal ganglion cell layer (mRGCL) volumes, when the pRNFL thicknesses were reduced to the thresholds of 57.2-67.5 µm or 0.691-0.737 mm3 in mRGCL volumes, respectively, with the strongest interdependence in the 19-40y cohort. The ON patients from varying age cohorts would be threatened by blindness when their pRNFL thicknesses dropped 36.7-48.3 µm or the mRGCL volumes dropped to 0.495-0.613 mm3. CONCLUSION: The paediatric ON has best prognosis and young adult ON exhibits perfectly linear correlations of final vision and structural loss. The pRNFL and the mRGCL could be potential structural markers to predict the vision prognosis for varying-age ON patients.

Published
2022
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13. Leber’s hereditary optic neuropathy companied with multiple-related diseases

Author

Ming-ming Sun, Huan-fen Zhou, Qiao Sun, Hong-en Li, Hong-juan Liu, Hong-lu Song, Mo Yang, Da Teng, Shi-hui Wei, and Quan-gang Xu

Subjects
Leber’s hereditary optic neuropathy, optic neuritis, aquaporin-4 antibody, myelin oligodendrocyte glycoprotein antibody, multiple sclerosis, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

ObjectiveTo elucidate the clinical, radiologic characteristics of Leber’s hereditary optic neuropathy (LHON) associated with the other diseases.Materials and methodsClinical data were retrospectively collected from hospitalized patients with LHON associated with the other diseases at the Neuro-Ophthalmology Department at the Chinese People’s Liberation Army General Hospital (PLAGH) from December 2014 to October 2018.ResultsA total of 13 patients, 24 eyes (10 men and 3 women; mean age, 30.69 ± 12.76 years) with LHON mitochondrial DNA (mtDNA) mutations, were included in the cohort. 14502(5)11778(4)11778 &11696(1)12811(1)11696(1)3460(1). One patient was positive for aquaporin-4 antibody (AQP4-Ab), and two were positive for myelin oligodendrocyte glycoprotein antibody (MOG-Ab). Three patients were associated with idiopathic optic neuritis (ON). Two patients were with compression optic neuropathy. Three patients were with the central nervous system (CNS) diseases. One patient was with proliferative diabetic retinopathy (PDR) and one with idiopathic orbital inflammatory syndrome (IOIS). At the onset, visual acuity (VA) in eighteen eyes was below 0.1, one eye was 0.5, five eyes were above 0.5, while VA in sixteen eyes was below a 0.1 outcome, three eyes experienced moderate vision loss. MRI images showed T2 lesions and enhancement in nine patients who received corticosteroids treatment; additional immune modulators treatment was performed on two patients. None of the patients had relapse during the follow-up time.ConclusionLeber’s hereditary optic neuropathy can be accompanied with multiple-related diseases, especially different subtypes of ON, which were also exhibited with IOIS and compression optic neuropathy for the first time in this cohort. This condition may be a distinct entity with an unusual clinical and therapeutic profile.

Published
2022
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15. Mitochondrial Mutations in Ethambutol-Induced Optic Neuropathy

Author

Xiao-Hui Zhang, Yue Xie, Quan-Gang Xu, Kai Cao, Ke Xu, Zi-Bing Jin, Yang Li, and Shi-Hui Wei

Subjects
ethambutol, optic neuropathy, OPA1, mitochondrial DNA, mutation, Biology (General), QH301-705.5
Abstract

Background: Ethambutol-induced optic neuropathy (EON) is a well-recognized ocular complication in patients who take ethambutol as a tuberculosis treatment. The aim of the current study was to investigate the presence of mitochondrial mutations, including OPA1 and Leber’s hereditary optic neuropathy (LHON)-mitochondrial DNA (mtDNA), in patients with EON and to determine their effect on clinical features of these patients.Methods: All 47 patients underwent clinical evaluations, including best-corrected visual acuity, fundus examination, and color fundus photography; 37 patients were then followed up over time. Molecular screening methods, including PCR-based sequencing of the OPA1 gene and LHON-mtDNA mutations, together with targeted exome sequencing, were used to detect mutations.Results: We detected 15 OPA1 mutations in 18 patients and two LHON-mtDNA mutations in four patients, for an overall mutation detection rate of 46.8%. The mean presentation age was significantly younger in the patients with the mitochondrial mutations (27.5 years) than in those without mutations (48 years). Fundus examination revealed a greater prevalence of optic disc hyperemia in the patients with mutations (70.5%) than without mutations (48%). Half of the patients with mutations and 91% of the patients without mutations had improved vision. After adjusting for confounders, the logistic regression revealed that the patients with optic disc pallor on the first visit (p = 0.004) or the patients with the mitochondrial mutations (p < 0.001) had a poorer vision prognosis.Conclusion: Our results indicated that carriers with OPA1 mutations might be more vulnerable for the toxicity of EMB to develop EON.

Published
2021
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16. Cognitive Function of Children and Adolescents with Attention Deficit Hyperactivity Disorder and Learning Difficulties: A Developmental Perspective

Author

Fang Huang, Li Sun, Ying Qian, Lu Liu, Quan-Gang Ma, Li Yang, Jia Cheng, Qing-Jiu Cao, Yi Su, Qian Gao, Zhao-Min Wu, Hai-Mei Li, Qiu-Jin Qian, and Yu-Feng Wang

Subjects
Attention Deficit Hyperactivity Disorder, Children and Adolescents, Cognitive Function, Developmental Trajectory, Learning Difficulties, Medicine
Abstract

Background: The cognitive function of children with either attention deficit hyperactivity disorder (ADHD) or learning disabilities (LDs) is known to be impaired. However, little is known about the cognitive function of children with comorbid ADHD and LD. The present study aimed to explore the cognitive function of children and adolescents with ADHD and learning difficulties in comparison with children with ADHD and healthy controls in different age groups in a large Chinese sample. Methods: Totally, 1043 participants with ADHD and learning difficulties (the ADHD + learning difficulties group), 870 with pure ADHD (the pure ADHD group), and 496 healthy controls were recruited. To investigate the difference in cognitive impairment using a developmental approach, all participants were divided into three age groups (6–8, 9–11, and 12–14 years old). Measurements were the Chinese-Wechsler Intelligence Scale for Children, the Stroop Color-Word Test, the Trail-Making Test, and the Behavior Rating Inventory of Executive Function-Parents (BRIEF). Multivariate analysis of variance was used. Results: The results showed that after controlling for the effect of ADHD symptoms, the ADHD + learning difficulties group was still significantly worse than the pure ADHD group, which was, in turn, worse than the control group on full intelligence quotient (98.66 ± 13.87 vs. 105.17 ± 14.36 vs. 112.93 ± 13.87, P < 0.001). The same relationship was also evident for shift function (shifting time of the Trail-Making Test, 122.50 [62.00, 194.25] s vs. 122.00 [73.00, 201.50] s vs. 66.00 [45.00, 108.00] s, P< 0.001) and everyday life executive function (BRIEF total score, 145.71 ± 19.35 vs. 138.96 ± 18.00 vs. 122.71 ± 20.45, P < 0.001) after controlling for the effect of the severity of ADHD symptoms, intelligence quotient, age, and gender. As for the age groups, the differences among groups became nonsignificant in the 12–14 years old group for inhibition (meaning interference of the Stroop Color-Word Test, 18.00 [13.00, 25.00] s vs. 17.00 [15.00, 26.00] s vs. 17.00 [10.50, 20.00] s , P = 0.704) and shift function (shifting time of the Trail-Making Test, 62.00 [43.00, 97.00] s vs. 53.00 [38.00, 81.00] s vs. 101.00 [88.00, 114.00] s, P = 0.778). Conclusions: Children and adolescents with ADHD and learning difficulties have more severe cognitive impairment than pure ADHD patients even after controlling for the effect of ADHD symptoms. However, the differences in impairment in inhibition and shift function are no longer significant when these individuals were 12–14 years old.

Published
2016
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19. Changes in Foxtail Millet (Setaria italica L.) Yield, Quality, and Soil Microbiome after Replacing Chemical Nitrogen Fertilizers with Organic Fertilizers

Author

Ming-Jie Sun, Ying Chao, Wei He, Xi-Rui Kang, Quan-Gang Yang, Hui Wang, Hong Pan, Yan-Hong Lou, and Yu-Ping Zhuge

Subjects
Renewable Energy, Sustainability and the Environment, Geography, Planning and Development, Building and Construction, Management, Monitoring, Policy and Law, foxtail millet, appearance quality, taste quality, nutritional quality, organic fertilizer, soil microbiome
Abstract

Foxtail millet (Setaria italica L.) is one of the most economically valuable drought-resistant crops in arid and semi-arid regions as a nutrition health crop, which has garnered considerable research attention. We evaluated the effects of replacing chemical nitrogen fertilizers with organic fertilizers on two primary plant accessions of foxtail millet (Dungu and Jinfen no. 2). Nitrogen in a standard fertilizer was replaced with organic fertilizer at application levels of 0, 25, 50, 75, and 100%, with effects on crop yield, quality (appearance, taste, and nutritional value), and soil microbiome, assessed using field cultivation experiments. Our results indicate that partial replacement of conventional fertilizers with organic fertilizers improved both yield and quality. Specifically, the 75% replacement significantly improved the appearance (yellow pigment content and grain diameter) and taste (amylose content and soluble sugar content) of foxtail millet, while the 50% replacement significantly improved the taste (gel consistency) and nutritional qualities (crude protein content and seven amino acids’ content). The 50% replacement of organic fertilizer regulated amino acid content more significantly than starch content. Increased ratios of organic fertilizer significantly reduced the soil pH by 0.03–0.36 and increased the relative abundance of Chloroflexi as well as that of Basidiomycota and Cercozoa in the soil microbiome. Our findings provide a solid theoretical foundation for subsequent studies on fertilizer use for foxtail millet and contribute to developing functional nutritional foods in the foxtail millet industry.

Published
2022
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20. Leber’s hereditary optic neuropathy companied with multiple-related diseases

Author

Sun, Ming-ming, Zhou, Huan-fen, Sun, Qiao, Li, Hong-en, Liu, Hong-juan, Song, Hong-lu, Yang, Mo, Teng, Da, Wei, Shi-hui, and Xu, Quan-gang

Subjects
Behavioral Neuroscience, Psychiatry and Mental health, Neuropsychology and Physiological Psychology, Neurology, Biological Psychiatry
Abstract

ObjectiveTo elucidate the clinical, radiologic characteristics of Leber’s hereditary optic neuropathy (LHON) associated with the other diseases.Materials and methodsClinical data were retrospectively collected from hospitalized patients with LHON associated with the other diseases at the Neuro-Ophthalmology Department at the Chinese People’s Liberation Army General Hospital (PLAGH) from December 2014 to October 2018.ResultsA total of 13 patients, 24 eyes (10 men and 3 women; mean age, 30.69 ± 12.76 years) with LHON mitochondrial DNA (mtDNA) mutations, were included in the cohort. 14502(5)11778(4)11778 &11696(1)12811(1)11696(1)3460(1). One patient was positive for aquaporin-4 antibody (AQP4-Ab), and two were positive for myelin oligodendrocyte glycoprotein antibody (MOG-Ab). Three patients were associated with idiopathic optic neuritis (ON). Two patients were with compression optic neuropathy. Three patients were with the central nervous system (CNS) diseases. One patient was with proliferative diabetic retinopathy (PDR) and one with idiopathic orbital inflammatory syndrome (IOIS). At the onset, visual acuity (VA) in eighteen eyes was below 0.1, one eye was 0.5, five eyes were above 0.5, while VA in sixteen eyes was below a 0.1 outcome, three eyes experienced moderate vision loss. MRI images showed T2 lesions and enhancement in nine patients who received corticosteroids treatment; additional immune modulators treatment was performed on two patients. None of the patients had relapse during the follow-up time.ConclusionLeber’s hereditary optic neuropathy can be accompanied with multiple-related diseases, especially different subtypes of ON, which were also exhibited with IOIS and compression optic neuropathy for the first time in this cohort. This condition may be a distinct entity with an unusual clinical and therapeutic profile.

Published
2022

25. Effects of three amendments on the soil properties of and maize growth in coastal saline-alkali soils

Author

WANG De-ling, ZHUGE Yu-ping, YANG Quan-gang, LOU Yan-hong, ZHANG Hang, WANG Hui, and PAN Hong

Subjects
Environmental sciences, maize yield, amendment, Agriculture (General), coastal saline soil, soil salt, GE1-350, water-stable aggregate, S1-972
Abstract

This study explored the effects of different soil amendments-a calcium preparation(GZJ), furfural residue(KQZ), and weathered coal(FHM)on the improvement of moderately saline-alkali coastal soil and maize growth therein. The effects of the treatments on the physicochemical properties of the soil and on maize plant height, chlorophyll content(SPAD), and yield were studied via pot experiments, and the experimental dosage of each treatment was as follows:GZJ1(15 t·hm-2), GZJ2(22.5 t·hm-2), KQZ1(30 t·hm-2), KQZ2(45 t·hm-2), FHM1(30 t·hm-2), and FHM2(45 t·hm-2). The results showed that the three amendments significantly increased the cation exchange capacity(CEC) of saline-alkali soil by 17.53%~49.45%, compared to when no amendments were added. Three amendments reduced soil bulk density and salt content while two different doses of furfural slag and high levels of weathered coal reduced soil bulk density significantly by 7.80%~12.06%. Two different doses of weathered coal and a low dose of the calcium preparation reduced the soil salt content significantly by 13.19%~19.33%. In addition, the calcium preparation and furfural residue significantly increased the quantity of water-stable aggregates(0.25~0.5 mm and 0.5~1 mm, respectively), increasing these by 5.36~6.59 percentage points and 1.92~2.81 percentage points, respectively. The quantity of micro-aggregates(-2 of furfural residue). Furfural slag and weathered coal significantly increased the plant height and SPAD of maize at different stages. The height of the maize plant at maturity increased by 9.71%~13.09% and the SPAD at jointing stage increased by 10.13%~16.44%. The three amendments increased the number of grains per ear and yield per plant by 15.97%~37.43% and 25.86%~49.65%, respectively; Once again, treatment KQZ1 had the best effect. The calcium preparation, furfural slag, and weathered coal all improved the moderately saline-alkali coastal soil and the kernel number and yield of maize. However, there was no significant difference between the three kinds of amendments in different dosages. The comprehensive effect of improvement with the use of furfural slag was better than those with the use of weathered coal and the calcium preparation; and treatment KQZ1 (30 t·hm-2)had the best comprehensive improvement effect among the furfural slag treatments.

Published
2021

30. Structural-visual functional relationships detected by optical coherence tomography in varying age-cohorts' patients with optic neuritis

Author

Wei, Shi, Hong-Tao, Zhang, Hua-Xin, Zuo, Si-Yuan, Li, Pan-Pan, Zheng, Quan-Gang, Xu, Si-Yu, Cai, Shi-Hui, Wei, Li, Li, and Chun-Xia, Peng

Subjects
Clinical Research
Abstract

AIM: To assess the relationships of final best-corrected visual acuity (BCVA) and the optic nerve structural loss in varying age-cohorts of optic neuritis (ON) patients. METHODS: This is a retrospective, cross-sectional study. Totally 130 ON subjects (200 eyes) without ON onset within 6mo were included, who underwent BCVA assessment, peripapillary retinal nerve fibre layer (pRNFL) and macular segmented layers evaluation by optical coherence tomography (OCT). RESULTS: For the 0-18y cohort, the final BCVA (logMAR) was significantly better and less frequent recurrences than adult cohorts (P=0.000). The final BCVA (logMAR) in all age-cohorts of the ON patients had negative and linear correlations to the pRNFL thicknesses and macular retinal ganglion cell layer (mRGCL) volumes, when the pRNFL thicknesses were reduced to the thresholds of 57.2-67.5 µm or 0.691-0.737 mm(3) in mRGCL volumes, respectively, with the strongest interdependence in the 19-40y cohort. The ON patients from varying age cohorts would be threatened by blindness when their pRNFL thicknesses dropped 36.7-48.3 µm or the mRGCL volumes dropped to 0.495-0.613 mm(3). CONCLUSION: The paediatric ON has best prognosis and young adult ON exhibits perfectly linear correlations of final vision and structural loss. The pRNFL and the mRGCL could be potential structural markers to predict the vision prognosis for varying-age ON patients.

Published
2021

31. Celastrol Attenuates Psoriasiform Inflammation by Targeting the IRF1/GSTM3 Axis

Author

Le Kuai, Yi Ru, Quan-gang Zhu, Shuang-yi Yin, Yong-yong Li, Mi Zhou, Ying Luo, Yue Luo, Jian-kun Song, Xiao-ya Fei, Jing-si Jiang, Cong-cong Zhu, and Bin Li

Subjects
Inflammation, Humans, Psoriasis, Cell Biology, Dermatology, Pentacyclic Triterpenes, Molecular Biology, Biochemistry, Triterpenes, Glutathione Transferase, Interferon Regulatory Factor-1
Published
2021

32. Calibration equations for Diviner 2000 capacitance measurements of volumetric soil water content in salt-affected soils

Author

Tedeschi, Anna, Huang, Cui Hua, Zong, Li, You, Quan Gang, and Xue, Xian

Subjects
Soils -- Measurement, Soil moisture -- Measurement, Sensors -- Measurement, Water -- Measurement, Agricultural industry, Earth sciences, Soil Science Society of America
Abstract

The capacitance sensor Diviner 2000 was used in an open field to monitor the volumetric soil water content ([θ.sub.v]) in the Minqin Oasis of Northwest China. The objectives of the work were to evaluate the accuracy of the factory calibration equation; to obtain a soil-specific calibration as a linear and a power equation with both a saline and a tapwater reference; and to obtain a general equation for multiple soil layers. Calibration was done during an irrigation experiment by using water with different salinities. The soil was characterised by different salinities and textures across the plots and soil layers. The calibration was carried out using water of the same salinity and composition as the local irrigation water. This procedure would yield a better normalisation of the scaled frequency (SF) for each irrigation treatment. For the treatments under study, the accuracy of the factory calibration equation was not good (range of the root mean square error, RMSE: 0.048-0.171 [cm.sup.3] [cm.sup.-3]). The accuracy of the soil-specific field calibration was higher. We therefore concluded that a soil-specific calibration is necessary. The RMSE shows no difference for the calibration equation with either tap or saline water reference. The linear and power equations, determined with a tap and saline water reference for each treatment and layer, gave larger differences in [θ.sub.v], Δ[θ.sub.v], at high SF than at low SF values. The Δ[θ.sub.v] values increased with increasing salinity, i.e. from the control to the most saline water irrigation treatment. The linear equation had a significantly different slope for the 0.3-0.6 m layer, which has higher clay content. Pooling in a single equation of the data from multiple layers and/or treatments was satisfactory for the 0.3--0.6 m layer of the treatments [W.sub.2] and [W.sub.5], with RMSE of 0.026, with the higher clay content. Additional keywords: capacitance sensor, soil texture, saline water, salinity, volumetric soil water content., Introduction Knowledge of the volumetric water content in soil ([θ.sub.v]) and the energy at which it is held is fundamental in irrigation management and in the study of the response [...]

Published
2014
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34. Neural Kalman filtering for speech enhancement

Author

Xue, Wei, Quan, Gang, Zhang, Chao, Ding, Guohong, He, Xiaodong, Zhou, Bowen, Xue, Wei, Quan, Gang, Zhang, Chao, Ding, Guohong, He, Xiaodong, and Zhou, Bowen

Abstract

Conventional learning-based speech enhancement methods usually utilize existing building blocks to design the deep neural networks (DNNs), while how to effectively integrate the statistical signal processing based schemes, which are expert-knowledge driven and could ameliorate the over-fitting problem, into the network design remains an open issue. In this paper, we extend the conventional Kalman filtering (KF) and propose a supervised-learning based neural Kalman filter (NKF) for speech enhancement. Similar to KF, the proposed method first obtains a prediction from the speech evolution model and then integrates the short-term instantaneous observation by linear weighting, and the weights are calculated by comparing between the speech prediction residual error and the environmental noise level. An end-to-end network is designed to convert the speech linear prediction model in KF to non-linear, and to compact all other conventional linear filtering operations. Different with other DNN based methods, the proposed method provides a specialized network design inspired from the conventional signal processing, the backpropagation can be directly applied on the linear filtering operations integrated from KF. We conduct experiments in different noisy conditions, and the results demonstrate that the proposed method outperforms the baseline methods which are based on either signal processing or DNNs. © 2021 IEEE

Published
2021

37. Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms

Author

Quan, Gang, Greenwood, Garrison W., Liu, Donglin, and Hu, Sharon

Subjects
Algorithms, Computer science, Algorithm, Business, Business, general, Business, international
Abstract

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.12.015 Byline: Gang Quan (a), Garrison W. Greenwood (b), Donglin Liu (c), Sharon Hu (c) Keywords: Evolutionary computations; Scheduling; Utility theory; Preventive maintenance; Multi-objective optimization Abstract: Heavy industry maintenance facilities at aircraft service centers or railroad yards must contend with scheduling preventive maintenance tasks to ensure critical equipment remains available. The workforce that performs these tasks are often high-paid, which means the task scheduling should minimize worker idle time. Idle time can always be minimized by reducing the workforce. However, all preventive maintenance tasks should be completed as quickly as possible to make equipment available. This means the completion time should be also minimized. Unfortunately, a small workforce cannot complete many maintenance tasks per hour. Hence, there is a tradeoff: should the workforce be small to reduce idle time or should it be large so more maintenance can be performed each hour? A cost effective schedule should strike some balance between a minimum schedule and a minimum size workforce. This paper uses evolutionary algorithms to solve this multiobjective problem. However, rather than conducting a conventional dominance-based Pareto search, we introduce a form of utility theory to find Pareto optimal solutions. The advantage of this method is the user can target specific subsets of the Pareto front by merely ranking a small set of initial solutions. A large example problem is used to demonstrate our method. Author Affiliation: (a) Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA (b) Department of Electrical and Computer Engineering, Portland State University, Portland, OR 97207, USA (c) Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA

Published
2007

38. Minimal energy fixed-priority scheduling for variable voltage processors

Author

Quan, Gang and Hu, Xiaobo Sharon

Subjects
Microprocessor upgrade, Microprocessor, Real-time system, System on a chip, Embedded system, Microprocessors -- Research, Real-time systems -- Research, Real-time control -- Research, Voltage regulators -- Research, Electric current regulators -- Research, Embedded systems -- Research
Published
2003

39. Method of Tower-less Calibration for Phase Parameter of Tracking System

Author

Ge Tiezhi, Wei Mingshan, Su Qiang, Huang Longcheng, and Quan Gang

Subjects
tracking system, phase calibration method, the radio star, wave path difference, Engineering (General). Civil engineering (General), TA1-2040
Abstract

This paper introduced the principle of angle errors in tracking system. The demodulation was only related to signal envelop, and supported the phase calibration of radio star. And this paper which is combined with the commonly-used phase calibration methods, carried out the phase calibration of radio star and the satellite on the specific device, summarized the procedure of radio star for phase calibration and compared the accuracy of it. On the basis of analyzing the theory of phase calibration, the authors concluded the relationship between the parameter of phase calibration and the working frequency. Through utilizing the results of satellite phase calibration to verification and the results of phase calibration of radio star on full-band, and achieving the parameter of phase calibration without the calibration tower, it has a good engineering practice value.

Published
2015
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40. Chemokine <scp>CXCL</scp> 1 may serve as a potential molecular target for hepatocellular carcinoma

Author

Hua Nian, Xiaodong Guo, Jie Chen, Xue-Qun He, Lei Wang, Ma‐wei Jiang, Quan-Gang Zhu, Xiao‐feng Zhai, Xue‐ming Zhang, Ke‐qi Han, and Hui Han

Subjects
0301 basic medicine, Cancer Research, Chemokine, Carcinoma, Hepatocellular, Chemokine CXCL1, Chemokine CXCL2, Interleukin-1beta, Mice, 03 medical and health sciences, 0302 clinical medicine, Cell Line, Tumor, Gene expression, medicine, Animals, Humans, Radiology, Nuclear Medicine and imaging, Original Research, Cancer Biology, Oligonucleotide Array Sequence Analysis, Tumor microenvironment, Gene knockdown, biology, PCR array, Gene Expression Profiling, Liver Neoplasms, hepatocellular carcinoma, medicine.disease, digestive system diseases, Gene Expression Regulation, Neoplastic, CXCL1, CXCL2, 030104 developmental biology, CXCL3, Oncology, siRNA, 030220 oncology & carcinogenesis, Hepatocellular carcinoma, biology.protein, Cancer research, gene expression profile, Chemokines, Chemokines, CXC, Neoplasm Transplantation
Abstract

The purpose of this study was to screen for changes in chemokine and chemokine‐related genes that are expressed in hepatocellular carcinoma (HCC) as potential markers of HCC progression. Total RNA was extracted from tumor and peritumor tissues from mice with HCC and analyzed using a PCR microarray comprising 98 genes. Changes in gene expression of threefold or more were screened and subsequently confirmed by immunohistochemical analyses and western blotting. Furthermore, whether chemokine knockdown by RNA interference (RNAi) could significantly suppress tumor growth in vivo was also evaluated. Finally, total serum samples were collected from HCC patients with HBV/cirrhosis (n = 16) or liver cirrhosis (n = 16) and from healthy controls (n = 16). The serum mRNA and protein expression levels of CXCL1 in primary liver cancer patients were detected by qRT‐PCR and western blot analysis, respectively. Several genes were up‐regulated in tumor tissues during the progression period, including CXCL1, CXCL2, CXCL3, and IL‐1β, while CXCR1 expression was down‐regulated. CBRH‐7919 cells carrying CXCL1 siRNA resulted in decreased tumor growth in nude mice. The differences in serum CXCL1 mRNA and protein levels among the HCC, hepatic sclerosis (HS), and control groups were significant (P

Published
2016

41. Targeted silencing of CXCL1 by siRNA inhibits tumor growth and apoptosis in hepatocellular carcinoma

Author

Xue-Qun He, Jie Chen, Xiao-dong Guo, Wen-Zhao Zhao, Quan-Gang Zhu, Wei-Wei Zhang, Hui Han, Ke-qi Han, Meng-Yu Ma, and Xue-Min Zhang

Subjects
Male, Cancer Research, Chemokine, Carcinoma, Hepatocellular, Chemokine CXCL1, animal diseases, Blotting, Western, Mice, Nude, Apoptosis, Real-Time Polymerase Chain Reaction, Mice, RNA interference, Cell Line, Tumor, In Situ Nick-End Labeling, Animals, Humans, Gene silencing, RNA, Small Interfering, STAT3, Mice, Inbred BALB C, Gene knockdown, biology, Oncogene, Cell Cycle, Liver Neoplasms, respiratory system, Flow Cytometry, CXCL1, Oncology, Gene Knockdown Techniques, Cancer research, biology.protein, Heterografts
Abstract

Hepatocellular carcinoma (HCC) is an aggressive malignancy and a major cause of cancer-related mortality worldwide. Our previous study shows that chemokine (C-X-C motif) ligand 1 (CXCL1) was upregulated and CXCR1 was downregulated in tumor tissues as compared to peritumor tissues by chemotaxis assay. As the status of CXCL subgroups and their receptors affect progression of HCC, we evaluated potential mechanisms of CXCL1 associated with anticancer effects in HCC based on our previous study. The effects of targeting CXCL1 by RNA interference (RNAi) on the proliferation and apoptosis of CBRH-7919 cells were observed in vitro and in vivo. Additionally, whether CXCL1 knockdown significantly reduce the activity of STAT3, NF-κB and HIF-1 or not were also estimated. RNAi of CXCL1 in the CBRH-7919 cells decreased the growth of tumors in nude mice by inhibited cells proliferation and induced apoptosis. In conclusion, these findings suggest that CXCL1 plays critical roles in the growth and apoptosis of HCC. RNAi of CXCL1 inhibits the growth and apoptosis of tumor cells, which indicates that CXCL1 may be a potential molecular target for use in HCC therapy.

Published
2015

42. Characteristics of CADASIL in Chinese mainland patients

Author

Tan, Qing-Che, Zhang, Jia-Tang, Cui, Rong-Tai, Xu, Quan-Gang, Huang, Xu-Sheng, and Yu, Sheng-Yuan

Subjects
Leukoencephalopathy -- Distribution -- Genetic aspects -- Diagnosis, Company distribution practices, Health
Abstract

Byline: Qing-Che. Tan, Jia-Tang. Zhang, Rong-Tai. Cui, Quan-Gang. Xu, Xu-Sheng. Huang, Sheng-Yuan. Yu Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) has been reported in many geographical [...]

Published
2014

43. Improvement of Point by Point Comparison Interpolation Algorithm and FPGA Implementation

Author

He Yin, Zhi-Gang Hao, Yi-Xuan Wang, and Quan-Gang Wen

Subjects
Stability (learning theory), Trajectory, Point (geometry), Field-programmable gate array, Chord (peer-to-peer), MATLAB, Measure (mathematics), Algorithm, computer, Interpolation, Mathematics, computer.programming_language
Abstract

This paper presents an improved algorithm based on point by point comparison algorithm (PBP). Principle of the basic one is analyzed at first, and some improving ideas are described. Then these two algorithms are simulated using Matlab tool. In this paper, Chord error δ is used to measure position error of local points. Ratio of trajectory error β is defined to measure contour error of global points. The velocity of interpolation is measured by its total steps. Finally,the improved algorithm is implemented in FPGA chip. Through quantitative analysis and comparison of the performance between these two algorithms, the results shows it’s stability and real-time performance are improved remarkably.

Published
2017

44. Improved DDA Algorithm and FPGA Implementation

Author

Xin-Zheng Dong, Yi-Xuan Wang, He Yin, Quan-Gang Wen, and Zhi-Gang Hao

Subjects
Computer science, Improved algorithm, Chord (peer-to-peer), MATLAB, Field-programmable gate array, computer, Algorithm, computer.programming_language, Interpolation
Abstract

In this paper, the basic principle of DDA interpolation algorithm is discussed and an improved algorithm is designed based on errors analysis of DDA algorithm. These two algorithms are simulated on Matlab, testing result shows chord error δ of improved DDA algorithm was reduced by 20% - 50% on interpolation accuracy. Finally the algorithm is implemented on FPGA to test its real-time performance and interpolation speed.

Published
2017

47. Cognitive Function of Children and Adolescents with Attention Deficit Hyperactivity Disorder and Learning Difficulties: A Developmental Perspective

Author

Yufeng Wang, Li Yang, Zhaomin Wu, Quan-Gang Ma, Jia Cheng, Li Sun, Fang Huang, Ying Qian, Yi Su, Qingjiu Cao, Qiujin Qian, Qian Gao, Haimei Li, and Lu Liu

Subjects
Male, Attention Deficit Hyperactivity Disorder, Adolescent, Cross-sectional study, lcsh:Medicine, Developmental Trajectory, behavioral disciplines and activities, 050105 experimental psychology, 03 medical and health sciences, Executive Function, 0302 clinical medicine, Cognition, Multivariate analysis of variance, Children and Adolescents, Cognitive Function, Learning Difficulties, mental disorders, medicine, Attention deficit hyperactivity disorder, Humans, 0501 psychology and cognitive sciences, Child, Intelligence Tests, Intelligence quotient, Learning Disabilities, 05 social sciences, lcsh:R, Wechsler Adult Intelligence Scale, General Medicine, medicine.disease, Cross-Sectional Studies, Attention Deficit Disorder with Hyperactivity, Learning disability, Female, Original Article, medicine.symptom, Psychology, 030217 neurology & neurosurgery, Stroop effect, Clinical psychology
Abstract

Background: The cognitive function of children with either attention deficit hyperactivity disorder (ADHD) or learning disabilities (LDs) is known to be impaired. However, little is known about the cognitive function of children with comorbid ADHD and LD. The present study aimed to explore the cognitive function of children and adolescents with ADHD and learning difficulties in comparison with children with ADHD and healthy controls in different age groups in a large Chinese sample. Methods: Totally, 1043 participants with ADHD and learning difficulties (the ADHD + learning difficulties group), 870 with pure ADHD (the pure ADHD group), and 496 healthy controls were recruited. To investigate the difference in cognitive impairment using a developmental approach, all participants were divided into three age groups (6–8, 9–11, and 12–14 years old). Measurements were the Chinese-Wechsler Intelligence Scale for Children, the Stroop Color-Word Test, the Trail-Making Test, and the Behavior Rating Inventory of Executive Function-Parents (BRIEF). Multivariate analysis of variance was used. Results: The results showed that after controlling for the effect of ADHD symptoms, the ADHD + learning difficulties group was still significantly worse than the pure ADHD group, which was, in turn, worse than the control group on full intelligence quotient (98.66 ± 13.87 vs. 105.17 ± 14.36 vs. 112.93 ± 13.87, P < 0.001). The same relationship was also evident for shift function (shifting time of the Trail-Making Test, 122.50 [62.00, 194.25] s vs. 122.00 [73.00, 201.50] s vs. 66.00 [45.00, 108.00] s, P< 0.001) and everyday life executive function (BRIEF total score, 145.71 ± 19.35 vs. 138.96 ± 18.00 vs. 122.71 ± 20.45, P < 0.001) after controlling for the effect of the severity of ADHD symptoms, intelligence quotient, age, and gender. As for the age groups, the differences among groups became nonsignificant in the 12–14 years old group for inhibition (meaning interference of the Stroop Color-Word Test, 18.00 [13.00, 25.00] s vs. 17.00 [15.00, 26.00] s vs. 17.00 [10.50, 20.00] s , P = 0.704) and shift function (shifting time of the Trail-Making Test, 62.00 [43.00, 97.00] s vs. 53.00 [38.00, 81.00] s vs. 101.00 [88.00, 114.00] s, P = 0.778). Conclusions: Children and adolescents with ADHD and learning difficulties have more severe cognitive impairment than pure ADHD patients even after controlling for the effect of ADHD symptoms. However, the differences in impairment in inhibition and shift function are no longer significant when these individuals were 12–14 years old.

Published
2016

48. Analysis of Plant Height Heterosis Based on QTL Mapping in Wheat

Author

Bin Tian, Jin-Liang Liu, Shu-Xiao Han, Jichun Tian, Qian-Qian Yuan, Zhan-Ling Zhu, Zhuo-Kun Li, and Quan-Gang Xie

Subjects
Agronomy, Heterosis, Plant Science, Quantitative trait locus, Biology, Agronomy and Crop Science, Biotechnology
Published
2010

49. Pathological features of gastric cancer in Zhuanghe high-risk area in China during 1992–2005

Author

Yuan-jun Yin, Guo-peng Sun, he Huang, Yuehua Gong, Yuan Yuan, Liping Sun, Quan-gang Wang, and Yan-hou Liu

Subjects
Cancer Research, medicine.medical_specialty, business.industry, Gastric cancer prevention, digestive, oral, and skin physiology, Cancer, medicine.disease, Gastroenterology, Risk area, Oncology, Internal medicine, Medicine public health, Etiology, Medicine, sense organs, skin and connective tissue diseases, business, Pathological
Abstract

Objective To investigate the pathological features and chronological changes of 1003 cases with gastric cancer in Zhuanghe high-risk area during 1992–2005 and the relationship between the changes and etiology factors in order to make a clue for gastric cancer prevention.

Published
2008

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