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Article: Improved stability and activity of Fe-based catalysts through strong metal support interactions due to extrinsic oxygen vacancies in Ce₀.₈Sm₀.₂O₂₋δ for the efficient synthesis of ammonia

Humphreys, John / Lan, Rong / Chen, Shigang / Tao, Shanwen

Journal of materials chemistry A. 2020 Aug. 18, v. 8, no. 32

2020

Abstract: In this article, hematite α-Fe₂O₃ was used as the precursor for the iron-based ammonia synthesis catalyst. Ce₀.₈Sm₀.₂O₂₋δ (SDC), with extrinsic oxygen vacancies was used as a promoter for forming an Fe–SDC composite catalyst. The new Fe–SDC catalyst ... ...

Abstract	In this article, hematite α-Fe₂O₃ was used as the precursor for the iron-based ammonia synthesis catalyst. Ce₀.₈Sm₀.₂O₂₋δ (SDC), with extrinsic oxygen vacancies was used as a promoter for forming an Fe–SDC composite catalyst. The new Fe–SDC catalyst achieves both high catalytic activity and excellent oxygenate tolerance, working with excellent stability at a feed-gas purity of 99.996%. At 500 °C, 10 MPa for the 80% Fe–20% SDC catalyst, and 15 MPa for the industrial Fe catalysts, and at an impurity level of 150 ppm, with known injected 107.5 ppm O₂, the activity of Fe–SDC retains 47.3% of that measured in purified gases while it is only 26.4% and 7.6% for the wüstite and magnetite – based industrial Fe catalysts respectively. It is believed that the introduction of extra extrinsic oxygen vacancies strengthen the strong metal-support interaction (SMSI), preventing the growth of formed Fe particles, leading to excellent stability and high tolerance to oxygenates. The SMSI between Fe and oxygen vacancies in SDC may also help to weaken and break the strong NN bonds in N₂, increasing the catalytic activity. The use of promoters with extrinsic oxygen and potentially other anion vacancies provides a new strategy to develop oxygenate tolerant catalysts for efficient synthesis of ammonia from less pure feed gases at reduced pressures.
Keywords	ammonia ; catalysts ; catalytic activity ; gases ; hematite ; iron ; magnetite ; nitrogen ; oxygen
Language	English
Dates of publication	2020-0818
Size	p. 16676-16689.
Publishing place	The Royal Society of Chemistry
Document type	Article
ZDB-ID	2702232-8
ISSN	2050-7496 ; 2050-7488
ISSN (online)	2050-7496
ISSN	2050-7488
DOI	10.1039/d0ta05238h
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Training Medical-Diagnosis Neural Networks on the Cloud with Privacy-Sensitive Patient Data from Multiple Clients.

Melissourgos, Dimitrios / Gao, Hanzhi / Ma, Chaoyi / Chen, Shigang / Wu, Sam S

... International Conference on Contemporary Computing. IC3 (Conference)

2022 Volume 2022, Page(s) 502–508

Abstract: Artificial neural networks (ANNs) are changing the paradigm in medical diagnosis. However, it remains an open problem how to outsource the model training operations to the cloud while protecting the privacy of distributed patient data. Homomorphic ... ...

Abstract	Artificial neural networks (ANNs) are changing the paradigm in medical diagnosis. However, it remains an open problem how to outsource the model training operations to the cloud while protecting the privacy of distributed patient data. Homomorphic encryption suffers from high overhead over data independently encrypted from numerous sources, differential privacy introduces a high level of noise which drastically increases the number of patient records needed to train a model, while federated learning requires all participants to perform synchronized local training that counters our goal of outsourcing all training operations to the cloud. This paper proposes to use matrix masking for outsourcing all model training operations to the cloud with privacy protection. After outsourcing their masked data to the cloud, the clients do not need to coordinate and perform any local training operations. The accuracy of the models trained by the cloud from the masked data is comparable to the accuracy of the optimal benchmark models that are trained directly from the original raw data. Our results are confirmed by experimental studies on privacy-preserving cloud training of medical-diagnosis neural network models based on real-world Alzheimer's disease data and Parkinson's disease data.
Language	English
Publishing date	2022-10-24
Publishing country	United States
Document type	Journal Article
ISSN	2572-6129
ISSN (online)	2572-6129
DOI	10.1145/3549206.3549291
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Effects of plant growth regulators and sucrose on proliferation and quality of embryogenic tissue in Picea pungens.

Gao, Fang / Cao, Xi / Qin, Caiyun / Chen, Shigang / Cai, Jufeng / Sun, Changbin / Kong, Lisheng / Tao, Jing

Scientific reports

2023 Volume 13, Issue 1, Page(s) 13194

Abstract: Embryogenic tissue (ET) is important for genetic modification and plant re-generation. The proliferation ability and vigor of ET are crucial for plant propagation via somatic embryogenesis. In this study, ET was induced from mature zygotic embryos in ... ...

Abstract	Embryogenic tissue (ET) is important for genetic modification and plant re-generation. The proliferation ability and vigor of ET are crucial for plant propagation via somatic embryogenesis. In this study, ET was induced from mature zygotic embryos in blue spruce (Picea pungens Engelm.). There were significant differences in ET induction between two provenances, i.e. 78.8 ± 12.5% and 62.50 ± 12.8% respectively. Effects of 2,4-Dichlorophenoxy acetic acid (2,4-D), 6-Benzyl amino-purine (6-BA) and/or sucrose on ET proliferation and somatic embryo (SE) maturation were further investigated with four cell lines. The highest ET proliferation rate reached 1473.7 ± 556.0% biweekly. Concentrations of 2,4-D or 6-BA applied at tissue proliferation stage impacted SE maturation among the cell lines, whereas sucrose showed less effects. The highest rate, 408 ± 230 mature SEs/g FW, was achieved in SE maturation cultures. This research demonstrated that the culture conditions, i.e. the specific concentrations of 2,4-D and BA, at ET proliferation stage affected not only ET growth, but also the quality of ET for SE maturation. This study revealed the necessity and benefit in developing both the general and the genotype-specific protocols for efficient production of mature SEs, or somatic plants in blue spruce.
MeSH term(s)	Plant Growth Regulators/pharmacology ; Plant Growth Regulators/metabolism ; Picea/genetics ; Sucrose/pharmacology ; Sucrose/metabolism ; Cell Proliferation ; 2,4-Dichlorophenoxyacetic Acid/pharmacology ; Seeds ; Plant Somatic Embryogenesis Techniques/methods
Chemical Substances	Plant Growth Regulators ; Sucrose (57-50-1) ; 2,4-Dichlorophenoxyacetic Acid (2577AQ9262)
Language	English
Publishing date	2023-08-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-39389-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A fast ceramic mixed OH

Zou, Peimiao / Iuga, Dinu / Ling, Sanliang / Brown, Alex J / Chen, Shigang / Zhang, Mengfei / Han, Yisong / Fortes, A Dominic / Howard, Christopher M / Tao, Shanwen

Nature communications

2024 Volume 15, Issue 1, Page(s) 909

Abstract: Low temperature ionic conducting materials such as ... ...

Abstract	Low temperature ionic conducting materials such as OH
Language	English
Publishing date	2024-01-30
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-45060-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Investigation of Perovskite Oxide SrCo

Zou, Peimiao / Chen, Shigang / Lan, Rong / Tao, Shanwen

ChemSusChem

2019 Volume 12, Issue 12, Page(s) 2788–2794

Abstract: Single-phase perovskite oxide ... ...

Abstract	Single-phase perovskite oxide SrCo
Language	English
Publishing date	2019-05-22
Publishing country	Germany
Document type	Journal Article
ISSN	1864-564X
ISSN (online)	1864-564X
DOI	10.1002/cssc.201900451
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Reducing Noise Level in Differential Privacy through Matrix Masking

Ding, A. Adam / Wu, Samuel S. / Miao, Guanhong / Chen, Shigang

2022

Abstract: Differential privacy schemes have been widely adopted in recent years to address issues of data privacy protection. We propose a new Gaussian scheme combining with another data protection technique, called random orthogonal matrix masking, to achieve $(\ ... ...

Abstract	Differential privacy schemes have been widely adopted in recent years to address issues of data privacy protection. We propose a new Gaussian scheme combining with another data protection technique, called random orthogonal matrix masking, to achieve $(\varepsilon, \delta)$-differential privacy (DP) more efficiently. We prove that the additional matrix masking significantly reduces the rate of noise variance required in the Gaussian scheme to achieve $(\varepsilon, \delta)-$DP in big data setting. Specifically, when $\varepsilon \to 0$, $\delta \to 0$, and the sample size $n$ exceeds the number $p$ of attributes by $(n-p)=O(ln(1/\delta))$, the required additive noise variance to achieve $(\varepsilon, \delta)$-DP is reduced from $O(ln(1/\delta)/\varepsilon^2)$ to $O(1/\varepsilon)$. With much less noise added, the resulting differential privacy protected pseudo data sets allow much more accurate inferences, thus can significantly improve the scope of application for differential privacy. Comment: 31 pages
Keywords	Computer Science - Cryptography and Security ; Mathematics - Statistics Theory ; 68P27 ; 62A99 ; 68P25
Subject code	303
Publishing date	2022-01-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Optimizing Somatic Embryogenesis Initiation, Maturation and Preculturing for Cryopreservation in Picea pungens

Cao, Xi / Gao, Fang / Qin, Caiyun / Chen, Shigang / Cai, Jufeng / Sun, Changbin / Weng, Yuhui / Tao, Jing

Forests. 2022 Dec. 08, v. 13, no. 12

2022

Abstract: Picea pungens (Engelm.), known for its blue-green needles, has become a likable ornamental species in northeast China since 2000. Nonetheless, a lack of propagation methods that can maintain genetic fidelity and develop seedlings at a large scale ... ...

Abstract	Picea pungens (Engelm.), known for its blue-green needles, has become a likable ornamental species in northeast China since 2000. Nonetheless, a lack of propagation methods that can maintain genetic fidelity and develop seedlings at a large scale prevents the further expansion of the species. Somatic embryogenesis (SE), paired with cryopreservation technologies, may provide a valid alternative. Picea pungens SE is not new, but its practical application has been limited due to low efficiencies in SE initiation and maturation as well as a lack of effective cryopreservation technology. In this study, experiments were carried out to overcome the limitations by modifying culture media. For initiation, the efficiency was enhanced by adjusting concentrations of 2.4-dichlorophenoxy acetic acid (2,4-D), 6-benzyl amino–purine (6-BA) or sucrose supplemented to the induction medium. The concentrations of 4.0 mg/L 2,4-D, 2 mg/L 6-BA, and 5 to 10 g/L sucrose were found optimal in maximizing initiation efficiency. For maturation, the efficiency, expressed as the number of mature somatic embryos per gram of fresh mass cultured (E/gFM), varied greatly with the choices of the basal medium and concentration of abscisic acid (ABA) of the maturation medium. Based on our results, the judicial choices were using the DCR medium as the basal medium and 10 mg/L ABA. The maturation efficiency could also be improved by adjusting the maturation medium’s osmotic pressure by manipulating the concentrations of carbohydrate and Gelrite and culture density. While the maturation medium, using sucrose as carbohydrate source or supplemented with a low (<8 g/L) Gelrite concentration, facilitated maturation, optimal selections were truly genotype-dependent. Our results also suggest that, while the optimal culture density varied with genotype, in general it is needless to culture more than 100 mg embryogenesis tissues per dish (size: 10 × 1.5 cm). Based on this study, the optimum pretreatment for embryogenesis tissue cryopreservation was culturing the tissues on the proliferation medium with 0.4 mol/L sorbitol for 24 h, followed by treatment with 5% Dimethyl sulfoxide. This study significantly improved the initiation (achieved a frequency of 0.56) and embryo maturation efficiencies (achieved 1030 E/gFM) and established an effective preculturing protocol for cryopreservation (recovered 1354 E/gFM) for the species. The protocols developed here, paired with the available ones for other SE steps in the literature, form a well-refined SE technology intended for commercial application to Picea pungens.
Keywords	2,4-D ; Picea pungens ; abscisic acid ; acetic acid ; cryopreservation ; culture media ; dimethyl sulfoxide ; genotype ; osmotic pressure ; somatic embryogenesis ; sorbitol ; sucrose ; China
Language	English
Dates of publication	2022-1208
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2527081-3
ISSN	1999-4907
ISSN	1999-4907
DOI	10.3390/f13122097
Database	NAL-Catalogue (AGRICOLA)

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Article: Collusion Resistant Multi-Matrix Masking for Privacy-Preserving Data Collection.

Wu, Samuel S / Chen, Shigang / Bhattacharjee, Abhishek / He, Ying

The Third IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2017 : The Third IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2017 ; the Second IEEE International Conferenc...

2020 Volume 2017, Page(s) 1–7

Abstract: An integral part of any social or medical research is the availability of reliable data. For the integrity of participants' responses, a secure environment for collecting sensitive data is required. This paper introduces a novel privacy-preserving data ... ...

Abstract	An integral part of any social or medical research is the availability of reliable data. For the integrity of participants' responses, a secure environment for collecting sensitive data is required. This paper introduces a novel privacy-preserving data collection method:
Language	English
Publishing date	2020-09-29
Document type	Journal Article
DOI	10.1109/bigdatasecurity.2017.10
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: On Outsourcing Artificial Neural Network Learning of Privacy-Sensitive Medical Data to the Cloud.

Melissourgos, Dimitrios / Gao, Hanzhi / Ma, Chaoyi / Chen, Shigang / Wu, Samuel S

International Conference on Tools with Artificial Intelligence : [proceedings]. International Conference on Tools for Artificial Intelligence

2021 Volume 2021, Page(s) 381–385

Abstract: Machine learning and artificial neural networks (ANNs) have been at the forefront of medical research in the last few years. It is well known that ANNs benefit from big data and the collection of the data is often decentralized, meaning that it is stored ...

Abstract	Machine learning and artificial neural networks (ANNs) have been at the forefront of medical research in the last few years. It is well known that ANNs benefit from big data and the collection of the data is often decentralized, meaning that it is stored in different computer systems. There is a practical need to bring the distributed data together with the purpose of training a more accurate ANN. However, the privacy concern prevents medical institutes from sharing patient data freely. Federated learning and multi-party computation have been proposed to address this concern. However, they require the medical data collectors to participate in the deep-learning computations of the data users, which is inconvenient or even infeasible in practice. In this paper, we propose to use matrix masking for privacy protection of patient data. It allows the data collectors to outsource privacy-sensitive medical data to the cloud in a masked form, and allows the data users to outsource deep learning to the cloud as well, where the ANN models can be trained directly from the masked data. Our experimental results on deep-learning models for diagnosis of Alzheimer's disease and Parkinson's disease show that the diagnosis accuracy of the models trained from the masked data is similar to that of the models from the original patient data.
Language	English
Publishing date	2021-12-21
Publishing country	United States
Document type	Journal Article
ISSN	2375-0197
ISSN (online)	2375-0197
DOI	10.1109/ictai52525.2021.00062
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Electricity Generation from Ammonia in Landfill Leachate by an Alkaline Membrane Fuel Cell Based on Precious-Metal-Free Electrodes

Zhang, Mengfei / Zou, Peimiao / Jeerh, Georgina / Chen, Shigang / Shields, Jane / Wang, Huanting / Tao, Shanwen

ACS sustainable chemistry & engineering. 2020 Aug. 06, v. 8, no. 34

2020

Abstract: Ammonia contaminated wastewater poses a great hazard to the safety and quality of water resources. Use of ammonia fuel cells to remove ammonia from wastewater is a promising strategy, which not only eliminates ammonia but also generates electricity as a ... ...

Abstract	Ammonia contaminated wastewater poses a great hazard to the safety and quality of water resources. Use of ammonia fuel cells to remove ammonia from wastewater is a promising strategy, which not only eliminates ammonia but also generates electricity as a bonus. For ammonia fuel cells, the key challenge is to identify stable and highly active precious-metal-free catalysts to be used as electrodes. In this study, a composite material α-MnO₂/C was prepared through a simple reaction of potassium permanganate with carbon black in a concentrated H₂SO₄ solution. An alkaline membrane fuel cell was prepared using the as-synthesized α-MnO₂/C as the cathode, previously reported NiCu/C as the anode, and an alkaline membrane as the electrolyte. The electrochemical activities of the MnO₂/C cathode and the performance of this fuel cell utilizing ammonia as the fuel were investigated. Finally, leachate from a local landfill site was tested in the fuel cell. Without the addition of alkali, the ammonia concentration in landfill leachate was reduced from 2711 to 95 ppm. Over the operational period of approximately 6 h, 96.5% of the ammonia in the leachate was removed by the fuel cell. These results demonstrate that the ammonia present within wastewater can efficiently be removed by a fuel cell employing non-precious metal electrodes at room temperature, while simultaneously generating electricity as a bonus. This provides an exciting new technology for the treatment of ammonia-rich wastewater.
Keywords	ambient temperature ; ammonia ; anodes ; catalysts ; cathodes ; composite materials ; electricity ; electricity generation ; electrochemistry ; electrolytes ; fuel cells ; fuels ; landfill leachates ; landfills ; manganese dioxide ; potassium permanganate ; soot ; sulfuric acid ; technology ; wastewater ; water resources
Language	English
Dates of publication	2020-0806
Size	p. 12817-12824.
Publishing place	American Chemical Society
Document type	Article
ISSN	2168-0485
DOI	10.1021/acssuschemeng.0c02926
Database	NAL-Catalogue (AGRICOLA)

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