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Book ; Online: Recovering Linear Causal Models with Latent Variables via Cholesky Factorization of Covariance Matrix

Cai, Yunfeng / Li, Xu / Sun, Minging / Li, Ping

2023

Abstract: Discovering the causal relationship via recovering the directed acyclic graph (DAG) structure from the observed data is a well-known challenging combinatorial problem. When there are latent variables, the problem becomes even more difficult. In this ... ...

Abstract	Discovering the causal relationship via recovering the directed acyclic graph (DAG) structure from the observed data is a well-known challenging combinatorial problem. When there are latent variables, the problem becomes even more difficult. In this paper, we first propose a DAG structure recovering algorithm, which is based on the Cholesky factorization of the covariance matrix of the observed data. The algorithm is fast and easy to implement and has theoretical grantees for exact recovery. On synthetic and real-world datasets, the algorithm is significantly faster than previous methods and achieves the state-of-the-art performance. Furthermore, under the equal error variances assumption, we incorporate an optimization procedure into the Cholesky factorization based algorithm to handle the DAG recovering problem with latent variables. Numerical simulations show that the modified "Cholesky + optimization" algorithm is able to recover the ground truth graph in most cases and outperforms existing algorithms.
Keywords	Statistics - Machine Learning ; Computer Science - Machine Learning
Subject code	006
Publishing date	2023-11-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: SpaceE

Yu, Jinxing / Cai, Yunfeng / Sun, Mingming / Li, Ping

Knowledge Graph Embedding by Relational Linear Transformation in the Entity Space

2022

Abstract: Translation distance based knowledge graph embedding (KGE) methods, such as TransE and RotatE, model the relation in knowledge graphs as translation or rotation in the vector space. Both translation and rotation are injective; that is, the translation or ...

Abstract	Translation distance based knowledge graph embedding (KGE) methods, such as TransE and RotatE, model the relation in knowledge graphs as translation or rotation in the vector space. Both translation and rotation are injective; that is, the translation or rotation of different vectors results in different results. In knowledge graphs, different entities may have a relation with the same entity; for example, many actors starred in one movie. Such a non-injective relation pattern cannot be well modeled by the translation or rotation operations in existing translation distance based KGE methods. To tackle the challenge, we propose a translation distance-based KGE method called SpaceE to model relations as linear transformations. The proposed SpaceE embeds both entities and relations in knowledge graphs as matrices and SpaceE naturally models non-injective relations with singular linear transformations. We theoretically demonstrate that SpaceE is a fully expressive model with the ability to infer multiple desired relation patterns, including symmetry, skew-symmetry, inversion, Abelian composition, and non-Abelian composition. Experimental results on link prediction datasets illustrate that SpaceE substantially outperforms many previous translation distance based knowledge graph embedding methods, especially on datasets with many non-injective relations. The code is available based on the PaddlePaddle deep learning platform https://www.paddlepaddle.org.cn.
Keywords	Computer Science - Computation and Language
Subject code	410
Publishing date	2022-04-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Identification of Matrix Joint Block Diagonalization

Cai, Yunfeng / Li, Ping

2020

Abstract: Given a set $\mathcal{C}=\{C_i\}_{i=1}^m$ of square matrices, the matrix blind joint block diagonalization problem (BJBDP) is to find a full column rank matrix $A$ such that $C_i=A\Sigma_iA^\text{T}$ for all $i$, where $\Sigma_i$'s are all block diagonal ...

Abstract	Given a set $\mathcal{C}=\{C_i\}_{i=1}^m$ of square matrices, the matrix blind joint block diagonalization problem (BJBDP) is to find a full column rank matrix $A$ such that $C_i=A\Sigma_iA^\text{T}$ for all $i$, where $\Sigma_i$'s are all block diagonal matrices with as many diagonal blocks as possible. The BJBDP plays an important role in independent subspace analysis (ISA). This paper considers the identification problem for BJBDP, that is, under what conditions and by what means, we can identify the diagonalizer $A$ and the block diagonal structure of $\Sigma_i$, especially when there is noise in $C_i$'s. In this paper, we propose a ``bi-block diagonalization'' method to solve BJBDP, and establish sufficient conditions under which the method is able to accomplish the task. Numerical simulations validate our theoretical results. To the best of the authors' knowledge, existing numerical methods for BJBDP have no theoretical guarantees for the identification of the exact solution, whereas our method does.
Keywords	Statistics - Machine Learning ; Computer Science - Machine Learning
Subject code	518
Publishing date	2020-11-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Tensor Completion via Tensor Networks with a Tucker Wrapper

Cai, Yunfeng / Li, Ping

2020

Abstract: In recent years, low-rank tensor completion (LRTC) has received considerable attention due to its applications in image/video inpainting, hyperspectral data recovery, etc. With different notions of tensor rank (e.g., CP, Tucker, tensor train/ring, etc.), ...

Abstract	In recent years, low-rank tensor completion (LRTC) has received considerable attention due to its applications in image/video inpainting, hyperspectral data recovery, etc. With different notions of tensor rank (e.g., CP, Tucker, tensor train/ring, etc.), various optimization based numerical methods are proposed to LRTC. However, tensor network based methods have not been proposed yet. In this paper, we propose to solve LRTC via tensor networks with a Tucker wrapper. Here by "Tucker wrapper" we mean that the outermost factor matrices of the tensor network are all orthonormal. We formulate LRTC as a problem of solving a system of nonlinear equations, rather than a constrained optimization problem. A two-level alternative least square method is then employed to update the unknown factors. The computation of the method is dominated by tensor matrix multiplications and can be efficiently performed. Also, under proper assumptions, it is shown that with high probability, the method converges to the exact solution at a linear rate. Numerical simulations show that the proposed algorithm is comparable with state-of-the-art methods.
Keywords	Statistics - Machine Learning ; Computer Science - Machine Learning
Subject code	518
Publishing date	2020-10-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A study of the moving rate of positive results for use in a patient-based real-time quality control program on a procalcitonin point-of-care testing analyzer.

He, Yili / Gu, Daqing / Kong, Xiangzhi / Feng, Zhiqiang / Lin, Weishang / Cai, Yunfeng

Journal of clinical laboratory analysis

2022 Volume 36, Issue 4, Page(s) e24320

Abstract: Objective: To establish an applicable and highly sensitive patient-based real-time quality control (PBRTQC) program based on a data model constructed with patients' results of a procalcitonin point-of-care testing (POCT) analyzer.: Methods: Patients' ...

Abstract	Objective: To establish an applicable and highly sensitive patient-based real-time quality control (PBRTQC) program based on a data model constructed with patients' results of a procalcitonin point-of-care testing (POCT) analyzer. Methods: Patients' results were retrospectively collected within one year. The Excel software was used to establish quality control (QC) programs of the moving average (MA) and the moving rate of positive results (MR). A Monte Carlo simulation was used to introduce positive and negative biases between 0.01 and 1 ng/ml at random points of the testing data set. Different parameters were used to detect the biases, and the detection efficiency was expressed using the median number of patient samples affected until error detection (MNPed). After comparing the MNPeds of different programs, MA and MR programs with appropriate parameters were selected, and validation plots were generated using MNPeds and maximum number of the patient samples affected (MAX). β curves were generated using the power function of the programs, the performances were compared with that of the conventional QC program. Results: Neither the conventional QC nor MA program was sensitive to small bias, While MR program can detect the minimum positive bias of 0.06 ng/ml and negative of 0.4 ng/ml at an average daily run size of 10 specimens, with FRs < 1.0%, βs < 1%. Conclusion: The MR program, which is more sensitive to small biases than conventional QC and MA programs, with low FR and β. As such, it can be used as a PBRTQC program with high performance.
MeSH term(s)	Humans ; Point-of-Care Testing ; Procalcitonin ; Quality Control ; Retrospective Studies ; Software
Chemical Substances	Procalcitonin
Language	English
Publishing date	2022-03-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	645095-7
ISSN	1098-2825 ; 0887-8013
ISSN (online)	1098-2825
ISSN	0887-8013
DOI	10.1002/jcla.24320
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Article: Formation and migration of magnetic particles associated with iron oxide transformation at a hillslope scale

Guo, Shanglong / Cai, Yunfeng / Ren, Juan / Guan, Yanxia / Xin, Dengchun / Long, Xiaoyong

Catena. 2021 Feb., v. 197

2021

Abstract: Iron oxides are widespread on the surface of the Earth as a weathering product of iron-bearing primary minerals, which often accompany the enrichment of magnetic particles under aerobic conditions. The magnetic properties determined by the content and ... ...

Abstract	Iron oxides are widespread on the surface of the Earth as a weathering product of iron-bearing primary minerals, which often accompany the enrichment of magnetic particles under aerobic conditions. The magnetic properties determined by the content and ratio of magnetic particles have been widely employed in paleoclimate reconstructions and erosion simulations. However, water redistribution at a slope scale could cause a phase transformation of iron oxides and a corresponding change in magnetic properties. In this study, we investigated a catena with a distinct soil colour change from red to yellow, which commonly occurs in tropical and subtropical hilly and mountainous regions. From upslope to downslope, the free iron oxide content decreases while the amorphous iron oxide content increases. The hematite diminishes significantly while the goethite shows little variation. The ferrimagnetic particles decrease in phase with hematite except for the finest superparamagnetic particles. However, the concentration of finer ferrimagnetic particles relative to coarser particles and the concentration of ferrimagnetic particles relative to antiferromagnetic particles both increase downslope. This increase validates the formation path of ferrimagnetic particles as an intermediate product of hematite but reveals more significant particle growth and transformation into hematite with decreasing water activity in granitic soils with low iron content. In addition, these processes could be enhanced by the preferential migration of the finest ferrimagnetic particles or their transformation from amorphous iron oxides enriched downslope. The slope-scale redistribution of iron oxides and related magnetic particles increases their uncertainty in paleoclimate reconstruction and erosion simulation but brings promising prospects to trace geomorphic evolution and hydrologic change over the long term.
Keywords	catenas ; ferrimagnetic materials ; goethite ; hematite ; hydrology ; intermediate product ; magnetism ; mountains ; paleoclimatology ; phase transition ; soil color ; topographic slope ; uncertainty ; water activity
Language	English
Dates of publication	2021-02
Publishing place	Elsevier B.V.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	519608-5
ISSN	1872-6887 ; 0008-7769 ; 0341-8162
ISSN (online)	1872-6887 ; 0008-7769
ISSN	0341-8162
DOI	10.1016/j.catena.2020.104944
Database	NAL-Catalogue (AGRICOLA)

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Article: Combination of aqueous two-phase flotation and inverse transition cycling: Strategies for separation and purification of recombinant β-glucosidase from cell lysis solution

Han, Juan / Fang, Sihan / He, Xingchen / Wang, Lei / Li, Chunmei / Wu, Jiacong / Cai, Yunfeng / Wang, Yun

Food chemistry. 2022 Mar. 30, v. 373

2022

Abstract: This work was developed to solve the problems of the restriction of non-specific adsorption and time-dependent denaturation in the purification of recombinant proteins by multistage chromatographic procedures. A novel purification method (ATPF-ITC) which ...

Abstract	This work was developed to solve the problems of the restriction of non-specific adsorption and time-dependent denaturation in the purification of recombinant proteins by multistage chromatographic procedures. A novel purification method (ATPF-ITC) which combining aqueous two-phase flotation (ATPF) with inverse transition cycling (ITC) was established and used to efficiently purify recombinant β-glucosidase (GLEGB) from cell lysis solution. First, GLEGB would preferentially adsorb on the nitrogen bubble interface relied on the hydrophobic property of the graphene-binding (GB) tag and enter into the top phase of ATPF. Second, GLEGB was achieved further purification by one-round ITC method based on the thermosensitive of the elastin-like polypeptide (ELP) tag. Consequently, the enzymatic activity recovery of GLEGB was 124.92% ± 0.83%, and the purification factor reached 24.26 ± 0.22. The purification results remained stable after six polymer cycles, and the process of ATPF-ITC had no negative effect on the structure of recombinant protein.
Keywords	adsorption ; chromatography ; denaturation ; enzyme activity ; food chemistry ; hydrophobicity ; nitrogen ; polymers ; polypeptides ; purification methods ; recombinant proteins ; thermosensitivity
Language	English
Dates of publication	2022-0330
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	243123-3
ISSN	1873-7072 ; 0308-8146
ISSN (online)	1873-7072
ISSN	0308-8146
DOI	10.1016/j.foodchem.2021.131543
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Magnetic Noise Enabled Biocompass.

Xiao, Da-Wu / Hu, Wen-Hui / Cai, Yunfeng / Zhao, Nan

Physical review letters

2020 Volume 124, Issue 12, Page(s) 128101

Abstract: The discovery of magnetic protein provides a new understanding of a biocompass at the molecular level. However, the mechanism by which magnetic protein enables a biocompass is still under debate, mainly because of the absence of permanent magnetism in ... ...

Abstract	The discovery of magnetic protein provides a new understanding of a biocompass at the molecular level. However, the mechanism by which magnetic protein enables a biocompass is still under debate, mainly because of the absence of permanent magnetism in the magnetic protein at room temperature. Here, based on a widely accepted radical pair model of a biocompass, we propose a microscopic mechanism that allows the biocompass to operate without a finite magnetization of the magnetic protein in a biological environment. With the structure of the magnetic protein, we show that the magnetic fluctuation, rather than the permanent magnetism, of the magnetic protein can enable geomagnetic field sensing. An analysis of the quantum dynamics of our microscopic model reveals the necessary conditions for optimal sensitivity. Our work clarifies the mechanism by which magnetic protein enables a biocompass.
MeSH term(s)	Animals ; Biophysics ; Birds ; Iron-Sulfur Proteins/chemistry ; Iron-Sulfur Proteins/physiology ; Magnetic Fields ; Models, Theoretical ; Spatial Navigation
Chemical Substances	Iron-Sulfur Proteins
Language	English
Publishing date	2020-04-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.124.128101
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Article: [Determination of trace amounts of oxytetracycline in surface water samples by bubble enrichment-high performance liquid chromatography].

Xiong, Fangyong / Cai, Yunfeng / Zhang, Ying / Ding, Jianhua

Se pu = Chinese journal of chromatography

2018 Volume 36, Issue 7, Page(s) 665–669

Abstract: A method was established to determine the trace amounts of oxytetracycline (OTC) in surface water samples by bubble enrichment-high performance liquid chromatography (HPLC). A novel sample pretreatment method, bubble enrichment, was used to enrich trace ... ...

Abstract	A method was established to determine the trace amounts of oxytetracycline (OTC) in surface water samples by bubble enrichment-high performance liquid chromatography (HPLC). A novel sample pretreatment method, bubble enrichment, was used to enrich trace amounts of oxytetracycline in aqueous solutions, and the effects of bubble enrichment conditions on the enrichment efficiency was investigated. Enrichment factor of oxytetracycline had a maximum of 37.06, RSD was 4.8% (
MeSH term(s)	Chromatography, High Pressure Liquid ; Oxytetracycline/analysis ; Water/analysis ; Water Pollutants, Chemical/analysis
Chemical Substances	Water Pollutants, Chemical ; Water (059QF0KO0R) ; Oxytetracycline (X20I9EN955)
Language	Chinese
Publishing date	2018-08-22
Publishing country	China
Document type	Journal Article
ISSN	1000-8713
ISSN	1000-8713
DOI	10.3724/SP.J.1123.2018.02003
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Article: A high efficiency method combining metal chelate ionic liquid-based aqueous two-phase flotation with two-step precipitation process for bromelain purification

Han, Juan / Cai, Yunfeng / Wang, Lei / Mao, Yanli / Ni, Liang / Wang, Yun

Food chemistry. 2020 Mar. 30, v. 309

2020

Abstract: This work was to develop a cost-effective and sustainable method which included metal chelate ionic liquid-based aqueous two-phase flotation (IL-based ATPF) and a two-step precipitation process for purifying bromelain from pineapple. Firstly, the metal ... ...

Abstract	This work was to develop a cost-effective and sustainable method which included metal chelate ionic liquid-based aqueous two-phase flotation (IL-based ATPF) and a two-step precipitation process for purifying bromelain from pineapple. Firstly, the metal chelate IL-based ATPF with a copper chelate-functionalized thermosensitive block copolymer (L64-IDA-Cu(II)) as trapping agent was used as the primary purification to obtain the L64-IDA-Cu(II)-bromelain complex. Secondly, the two-step precipitation process based on the thermosensitive properties of the L64-IDA-Cu(II) was mainly carried out to achieve the further purification of bromelain. According to a series of optimal experiments, the enzymatic activity recovery of final bromelain was 95.22 ± 0.04%, and the purification factor reached 6.56 ± 0.03. The results of recycling of ILs and the trapping agent were satisfactory. Furthermore, the conclusions of comparison with other methods proved the superiority of this method. This novel recycling purification method has a goodindustrial prospect in future.
Keywords	bromelains ; composite polymers ; copper ; cost effectiveness ; enzyme activity ; ionic liquids ; pineapples ; purification methods ; recycling ; thermosensitivity
Language	English
Dates of publication	2020-0330
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	243123-3
ISSN	1873-7072 ; 0308-8146
ISSN (online)	1873-7072
ISSN	0308-8146
DOI	10.1016/j.foodchem.2019.125749
Database	NAL-Catalogue (AGRICOLA)

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