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Article ; Online: Graph learning and denoising-based weighted sparse unmixing for hyperspectral images

Song, Fu-Xin / Deng, Shi-Wen

International Journal of Remote Sensing. 2023 Jan. 17, v. 44, no. 2 p.428-451

2023

Abstract: Sparse unmixing is a semisupervised unmixing method based on the linear mixture model, in which the spectral library is known a prior, and has received considerable attention recently. It has been confirmed that the spatial information in hyperspectral ... ...

Abstract	Sparse unmixing is a semisupervised unmixing method based on the linear mixture model, in which the spectral library is known a prior, and has received considerable attention recently. It has been confirmed that the spatial information in hyperspectral images plays a crucial role in improving the performance of sparse unmixing algorithms. However, the spatial information extracted or captured in most unmixing algorithms is inaccurate and robust enough, which leads to artificial block noise or outliers in the estimated abundance maps, especially as the noise level increases. To address these problems and more efficiently utilize the spatial information, this paper proposes a graph learning and denoising-based weighted sparse mixing (GLDWSU) algorithm, which includes three stages in the unmixing procedure: graph learning, denoising and unmixing. In the first stage, the graph Laplacian matrix is adaptively learned to capture the spatial structure of HSI with the relative total variation (RTV) regularization. In the next stage, HSI is denoised with the learned Laplacian matrix by using Laplacian smoothing. In the final stage, the denoised HSI is unmixed with the reweighted-norm regularization based on the alternating direction method of multipliers (ADMM) framework. The experimental results on both simulated and real data sets show that the proposed GLDWSU algorithm can more accurately capture and utilize the spatial structure information of HSI with a low computational cost and outperforms all the compared methods.
Keywords	algorithms ; models ; spatial data ; Sparse unmixing ; graph learning ; graph Laplacian ; denoising abundance ; estimation
Language	English
Dates of publication	2023-0117
Size	p. 428-451.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	1497529-4
ISSN	1366-5901 ; 0143-1161
ISSN (online)	1366-5901
ISSN	0143-1161
DOI	10.1080/01431161.2023.2165420
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: A lanthanide luminescent sensor for the detection of 4-nitrophenol in aqueous media.

Song, Xue-Qin / Song, Fu-Qiang / Zhang, Pei / Li, Juan

Dalton transactions (Cambridge, England : 2003)

2023 Volume 52, Issue 39, Page(s) 14054–14063

Abstract: The development of facile luminescent sensors for detecting nitrophenols in aqueous media is of great necessity for the safety of the environment and human health, as they are a class of widespread toxic organic pollutants that cause serious adverse ... ...

Abstract	The development of facile luminescent sensors for detecting nitrophenols in aqueous media is of great necessity for the safety of the environment and human health, as they are a class of widespread toxic organic pollutants that cause serious adverse effects upon consumption. Based on a new multidentate asymmetric ligand (H2L) in which salicylamide and 4-nitryl-salicylaldimine are spaced by 1,2-bis(2-ethoxy)ethyl, a new hydrostable lanthanide intercycle, [Tb
Language	English
Publishing date	2023-10-10
Publishing country	England
Document type	Journal Article
ZDB-ID	1472887-4
ISSN	1477-9234 ; 1364-5447 ; 0300-9246 ; 1477-9226
ISSN (online)	1477-9234 ; 1364-5447
ISSN	0300-9246 ; 1477-9226
DOI	10.1039/d3dt02413j
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Cloning the full-length CDNA of actin gene and analysing alliinase gene expression in tillering onion

Yang Yang / Ye Song Fu / Qiu Feng Yang / Chen Ke Li

Bioscience Journal, Vol 39, Pp e39017-e

2023 Volume 39017

Abstract: Tillering onion is a herbaceous plant belonging to the Liliaceae family. We cloned the cDNAs of the actin gene (AcACT, GenBank: MF919598) of tillering onion using rapid amplification of the cDNA ends. The full-length cDNA of AcACT was 1,357 bp long with ... ...

Abstract	Tillering onion is a herbaceous plant belonging to the Liliaceae family. We cloned the cDNAs of the actin gene (AcACT, GenBank: MF919598) of tillering onion using rapid amplification of the cDNA ends. The full-length cDNA of AcACT was 1,357 bp long with an open reading frame of 1,131 bp encoding 376 amino acids. The amino acid sequence of AcACT shared > 96% similarity with the amino acid sequences of other ACTs and was found (by means of phylogenetic tree analysis) to be closely related to those of Ananas comosus and Papaver somniferum. AcACT expressions showed no significant differences (p > 0.01) in two cultivars L-SH and L-SY over three growth periods and under suitable conditions, low temperature, and short-day conditions. In addition, AcACT was used as an internal reference gene to analyse the expression of the alliinase gene (AcALL). AcALL expression trends in the roots, stems and leaves were consistent with those of diallyl disulphide and diallyl trisulphide. Thus, AcACT is highly conserved and can be used as a suitable internal reference gene when analysing gene expression in tillering onion.
Keywords	actin ; alliinase ; race ; tillering onion ; Agriculture ; S ; Biology (General) ; QH301-705.5
Subject code	612
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	Universidade Federal de Uberlândia
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: When Neural Code Completion Models Size up the Situation

Sun, Zhensu / Du, Xiaoning / Song, Fu / Wang, Shangwen / Li, Li

Attaining Cheaper and Faster Completion through Dynamic Model Inference

2024

Abstract: Leveraging recent advancements in large language models, modern neural code completion models have demonstrated the capability to generate highly accurate code suggestions. However, their massive size poses challenges in terms of computational costs and ... ...

Abstract	Leveraging recent advancements in large language models, modern neural code completion models have demonstrated the capability to generate highly accurate code suggestions. However, their massive size poses challenges in terms of computational costs and environmental impact, hindering their widespread adoption in practical scenarios. Dynamic inference emerges as a promising solution, as it allocates minimal computation during inference while maintaining the model's performance. In this research, we explore dynamic inference within the context of code completion. Initially, we conducted an empirical investigation on GPT-2, focusing on the inference capabilities of intermediate layers for code completion. We found that 54.4% of tokens can be accurately generated using just the first layer, signifying significant computational savings potential. Moreover, despite using all layers, the model still fails to predict 14.5% of tokens correctly, and the subsequent completions continued from them are rarely considered helpful, with only a 4.2% Acceptance Rate. These findings motivate our exploration of dynamic inference in code completion and inspire us to enhance it with a decision-making mechanism that stops the generation of incorrect code. We thus propose a novel dynamic inference method specifically tailored for code completion models. This method aims not only to produce correct predictions with largely reduced computation but also to prevent incorrect predictions proactively. Our extensive evaluation shows that it can averagely skip 1.7 layers out of 16 layers in the models, leading to an 11.2% speedup with only a marginal 1.1% reduction in ROUGE-L. Comment: Accepted to ICSE24
Keywords	Computer Science - Software Engineering ; Computer Science - Artificial Intelligence
Subject code	005
Publishing date	2024-01-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Automated Verification of Correctness for Masked Arithmetic Programs

Liu, Mingyang / Song, Fu / Chen, Taolue

2023

Abstract: Masking is a widely-used effective countermeasure against power side-channel attacks for implementing cryptographic algorithms. Surprisingly, few formal verification techniques have addressed a fundamental question, i.e., whether the masked program and ... ...

Abstract	Masking is a widely-used effective countermeasure against power side-channel attacks for implementing cryptographic algorithms. Surprisingly, few formal verification techniques have addressed a fundamental question, i.e., whether the masked program and the original (unmasked) cryptographic algorithm are functional equivalent. In this paper, we study this problem for masked arithmetic programs over Galois fields of characteristic 2. We propose an automated approach based on term rewriting, aided by random testing and SMT solving. The overall approach is sound, and complete under certain conditions which do meet in practice. We implement the approach as a new tool FISCHER and carry out extensive experiments on various benchmarks. The results confirm the effectiveness, efficiency and scalability of our approach. Almost all the benchmarks can be proved for the first time by the term rewriting system solely. In particular, FISCHER detects a new flaw in a masked implementation published in EUROCRYPT 2017.
Keywords	Computer Science - Cryptography and Security ; Computer Science - Programming Languages ; Computer Science - Software Engineering
Subject code	005 ; 000
Publishing date	2023-05-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: QFA2SR

Chen, Guangke / Zhang, Yedi / Zhao, Zhe / Song, Fu

Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems

2023

Abstract: Current adversarial attacks against speaker recognition systems (SRSs) require either white-box access or heavy black-box queries to the target SRS, thus still falling behind practical attacks against proprietary commercial APIs and voice-controlled ... ...

Abstract	Current adversarial attacks against speaker recognition systems (SRSs) require either white-box access or heavy black-box queries to the target SRS, thus still falling behind practical attacks against proprietary commercial APIs and voice-controlled devices. To fill this gap, we propose QFA2SR, an effective and imperceptible query-free black-box attack, by leveraging the transferability of adversarial voices. To improve transferability, we present three novel methods, tailored loss functions, SRS ensemble, and time-freq corrosion. The first one tailors loss functions to different attack scenarios. The latter two augment surrogate SRSs in two different ways. SRS ensemble combines diverse surrogate SRSs with new strategies, amenable to the unique scoring characteristics of SRSs. Time-freq corrosion augments surrogate SRSs by incorporating well-designed time-/frequency-domain modification functions, which simulate and approximate the decision boundary of the target SRS and distortions introduced during over-the-air attacks. QFA2SR boosts the targeted transferability by 20.9%-70.7% on four popular commercial APIs (Microsoft Azure, iFlytek, Jingdong, and TalentedSoft), significantly outperforming existing attacks in query-free setting, with negligible effect on the imperceptibility. QFA2SR is also highly effective when launched over the air against three wide-spread voice assistants (Google Assistant, Apple Siri, and TMall Genie) with 60%, 46%, and 70% targeted transferability, respectively. Comment: Accepted by the 32nd USENIX Security Symposium (2023 USENIX Security); Full Version
Keywords	Computer Science - Cryptography and Security ; Computer Science - Machine Learning ; Computer Science - Multimedia ; Computer Science - Sound ; Electrical Engineering and Systems Science - Audio and Speech Processing
Subject code	303
Publishing date	2023-05-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: SLMIA-SR

Chen, Guangke / Zhang, Yedi / Song, Fu

Speaker-Level Membership Inference Attacks against Speaker Recognition Systems

2023

Abstract: Membership inference attacks allow adversaries to determine whether a particular example was contained in the model's training dataset. While previous works have confirmed the feasibility of such attacks in various applications, none has focused on ... ...

Abstract	Membership inference attacks allow adversaries to determine whether a particular example was contained in the model's training dataset. While previous works have confirmed the feasibility of such attacks in various applications, none has focused on speaker recognition (SR), a promising voice-based biometric recognition technique. In this work, we propose SLMIA-SR, the first membership inference attack tailored to SR. In contrast to conventional example-level attack, our attack features speaker-level membership inference, i.e., determining if any voices of a given speaker, either the same as or different from the given inference voices, have been involved in the training of a model. It is particularly useful and practical since the training and inference voices are usually distinct, and it is also meaningful considering the open-set nature of SR, namely, the recognition speakers were often not present in the training data. We utilize intra-similarity and inter-dissimilarity, two training objectives of SR, to characterize the differences between training and non-training speakers and quantify them with two groups of features driven by carefully-established feature engineering to mount the attack. To improve the generalizability of our attack, we propose a novel mixing ratio training strategy to train attack models. To enhance the attack performance, we introduce voice chunk splitting to cope with the limited number of inference voices and propose to train attack models dependent on the number of inference voices. Our attack is versatile and can work in both white-box and black-box scenarios. Additionally, we propose two novel techniques to reduce the number of black-box queries while maintaining the attack performance. Extensive experiments demonstrate the effectiveness of SLMIA-SR. Comment: In Proceedings of the 31st Network and Distributed System Security (NDSS) Symposium, 2024
Keywords	Computer Science - Cryptography and Security ; Computer Science - Machine Learning ; Computer Science - Multimedia ; Computer Science - Sound ; Electrical Engineering and Systems Science - Audio and Speech Processing
Subject code	006
Publishing date	2023-09-14
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: [The Prognostic Factors for AML Children with CBFβ/MYH11 Positive].

Yan, Min / Song, Fu-Xing / Lu, Jun

Zhongguo shi yan xue ye xue za zhi

2021 Volume 29, Issue 2, Page(s) 369–373

Abstract: Objective: To analyze the prognostic factors of AML children with CBFβ/MYH11 positive.: Methods: Twenty-eight children with CBFβ/MYH11 positive treated in our hospital from May 2012 to June 2018 were selected, the clinical data and curative were ... ...

Abstract	Objective: To analyze the prognostic factors of AML children with CBFβ/MYH11 positive. Methods: Twenty-eight children with CBFβ/MYH11 positive treated in our hospital from May 2012 to June 2018 were selected, the clinical data and curative were analyzed and evaluated. Results: Five-year OS and 5-year EFS rate of CBFβ/MYH11 positive AML children was 76.8% and 64.0% efficacy, respectively. Univariate analysis results showed that the OS rate of CBFβ/MYH11 positive AML children with WBC<60.0×10 Conclusion: WBC level and XRCC-Thr241Met genotype at initial diagnosis are the major affecting factors for prognosis of AML children with CBFβ/MYH11 positive.
MeSH term(s)	Child ; Chromosome Inversion ; Genotype ; Humans ; Leukemia, Myeloid, Acute/genetics ; Myosin Heavy Chains ; Oncogene Proteins, Fusion ; Prognosis
Chemical Substances	CBFbeta-MYH11 fusion protein ; MYH11 protein, human ; Oncogene Proteins, Fusion ; Myosin Heavy Chains (EC 3.6.4.1)
Language	Chinese
Publishing date	2021-03-26
Publishing country	China
Document type	Journal Article
ZDB-ID	2404306-0
ISSN	1009-2137
ISSN	1009-2137
DOI	10.19746/j.cnki.issn.1009-2137.2021.02.010
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Article: Label-free quantitative proteomics of arbuscular mycorrhizal

Chang, Wei / Zhang, Yan / Ping, Yuan / Li, Kun / Qi, Dan-Dan / Song, Fu-Qiang

Frontiers in plant science

2023 Volume 13, Page(s) 1098260

Abstract: Introduction: Soil salinization has become one of the most serious environmental issues globally. Excessive accumulation of soluble salts will adversely affect the survival, growth, and reproduction of plants. Elaeagnus angustifolia L., commonly known ... ...

Abstract	Introduction: Soil salinization has become one of the most serious environmental issues globally. Excessive accumulation of soluble salts will adversely affect the survival, growth, and reproduction of plants. Elaeagnus angustifolia L., commonly known as oleaster or Russian olive, has the characteristics of tolerance to drought and salt. Arbuscular mycorrhizal (AM) fungi are considered to be bio-ameliorator of saline soils that can enhance the salt tolerance of the host plants. However, there is little information on the root proteomics of AM plants under salt stress. Methods: In this study, a label-free quantitative proteomics method was employed to identify the differentially abundant proteins in AM E. angustifolia seedlings under salt stress. Results: The results showed that a total of 170 proteins were significantly differentially regulated in E.angustifolia seedlings after AMF inoculation under salt stress. Mycorrhizal symbiosis helps the host plant E. angustifolia to respond positively to salt stress and enhances its salt tolerance by regulating the activities of some key proteins related to amino acid metabolism, lipid metabolism, and glutathione metabolism in root tissues. Conclusion: Aspartate aminotransferase, dehydratase-enolase-phosphatase 1 (DEP1), phospholipases D, diacylglycerol kinase, glycerol-3-phosphate O-acyltransferases, and gamma-glutamyl transpeptidases may play important roles in mitigating the detrimental effect of salt stress on mycorrhizal E. angustifolia . In conclusion, these findings provide new insights into the salt-stress tolerance mechanisms of AM E. angustifolia seedlings and also clarify the role of AM fungi in the molecular regulation network of E. angustifolia under salt stress.
Language	English
Publishing date	2023-01-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2613694-6
ISSN	1664-462X
ISSN	1664-462X
DOI	10.3389/fpls.2022.1098260
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Article ; Online: Albumin and other metabolic parameters as potential indicators of purulent vaginal discharge in dairy cows during the transition period.

Thongrueang, Natcha / Yang, Song-Fu / Ke, Guan-Ming / Hsu, Huan-Yu / Lee, Hsu-Hsun

The Journal of veterinary medical science

2023 Volume 85, Issue 7, Page(s) 743–750

Abstract: The aims of this study were to evaluate metabolic profiles obtained at -14, 14, and 28 days in milk (DIM), and to identify potential predictive biomarkers of Holstein dairy cows with purulent vaginal discharge (PVD) at 28 DIM. The body condition score ( ... ...

Abstract	The aims of this study were to evaluate metabolic profiles obtained at -14, 14, and 28 days in milk (DIM), and to identify potential predictive biomarkers of Holstein dairy cows with purulent vaginal discharge (PVD) at 28 DIM. The body condition score (BCS) and hematocrit (Hct) were evaluated, and a metabolic profile test (MPT) was performed at -14, 14, and 28 DIM using serum samples. Cows at 28 DIM were classified using a vaginoscopy and divided into groups of healthy cows (n=89) and cows with PVD (n=31). Albumin (Alb), total cholesterol (TCho), calcium (Ca) and, magnesium (Mg) levels were lower in cows with PVD than in healthy cows at 14 DIM. At 28 DIM, levels of Alb, TCho, Ca, blood urea nitrogen (BUN), Mg, and Hct were lower in cows with PVD. A multivariate stepwise logistic regression analysis showed that higher non-esterified fatty acids (NEFA; odds ratios; OR=4.47; P<0.01), lower Alb (OR=0.07; P<0.01) and lower TCho (OR=0.99; P=0.08) at 14 DIM, and lower Hct (OR=0.83; P=0.05), lower Alb (OR=0.12; P<0.01), and lower BUN (OR=0.74; P=0.02) at 28 DIM were significantly associated with PVD. In conclusion, serum Alb levels was a potential indicator associated with PVD, reflecting dietary protein deficiency preceding disease. Our findings suggest that MPT should be considered to monitor health status during the postpartum period for early diagnosis of PVD.
MeSH term(s)	Female ; Cattle ; Animals ; Vaginal Discharge/veterinary ; Postpartum Period ; Milk ; Albumins ; Lactation ; Cattle Diseases/diagnosis
Chemical Substances	Albumins
Language	English
Publishing date	2023-05-23
Publishing country	Japan
Document type	Journal Article
ZDB-ID	1071753-5
ISSN	1347-7439 ; 0916-7250
ISSN (online)	1347-7439
ISSN	0916-7250
DOI	10.1292/jvms.23-0081
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