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  1. Article ; Online: A Low-Code Framework for Complex Crowdsourcing Work Based on Process Modeling

    Tianhong Xiong / Maolin Pan / Yang Yu / Dingjun Lou

    Computational Intelligence and Neuroscience, Vol

    2022  Volume 2022

    Abstract: Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is ... ...

    Abstract Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is attracting more and more attention. However, complex crowdsourcing processes used for creative and open-ended work have remained out of reach for process modeling, because this type of process usually has a dynamic execution, in which the type, number, and order of tasks and subtasks are often unknown in advance but are determined dynamically at runtime. In this paper, we propose a modeling approach and supporting framework to fill this gap. Specifically, we provide a task model composition to allow task creation on demand, while collaborating on tasks in a tree structure to adapt to the dynamic execution. Moreover, we introduce a set of message communication modes to support data exchange among tasks. Finally, we construct a framework named CrowdModeller to embody this approach. Through two evaluations, we demonstrate its effectiveness.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
    Subject code 004
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: A Low-Code Framework for Complex Crowdsourcing Work Based on Process Modeling.

    Xiong, Tianhong / Pan, Maolin / Yu, Yang / Lou, Dingjun

    Computational intelligence and neuroscience

    2022  Volume 2022, Page(s) 9496741

    Abstract: Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is ... ...

    Abstract Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is attracting more and more attention. However, complex crowdsourcing processes used for creative and open-ended work have remained out of reach for process modeling, because this type of process usually has a dynamic execution, in which the type, number, and order of tasks and subtasks are often unknown in advance but are determined dynamically at runtime. In this paper, we propose a modeling approach and supporting framework to fill this gap. Specifically, we provide a task model composition to allow task creation on demand, while collaborating on tasks in a tree structure to adapt to the dynamic execution. Moreover, we introduce a set of message communication modes to support data exchange among tasks. Finally, we construct a framework named CrowdModeller to embody this approach. Through two evaluations, we demonstrate its effectiveness.
    MeSH term(s) Crowdsourcing ; Workload
    Language English
    Publishing date 2022-04-29
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2022/9496741
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: C Deletion at the re74650330 Locus of the

    Zhang, Jun / Yu, Yang / Pan, Lili / Yu, Tianhong / Luo, Guanghua

    Genetic testing and molecular biomarkers

    2021  Volume 25, Issue 10, Page(s) 660–667

    Abstract: Background: ...

    Abstract Background:
    Language English
    Publishing date 2021-10-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2486664-7
    ISSN 1945-0257 ; 1945-0265
    ISSN (online) 1945-0257
    ISSN 1945-0265
    DOI 10.1089/gtmb.2021.0083
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5195: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
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  4. Book ; Online: Smart Contract Generation for Inter-Organizational Process Collaboration

    Xiong, Tianhong / Feng, Shangqing / Pan, Maolin / Yu, Yang

    2023  

    Abstract: Currently, inter-organizational process collaboration (IOPC) has been widely used in the design and development of distributed systems that support business process execution. Blockchain-based IOPC can establish trusted data sharing among participants, ... ...

    Abstract Currently, inter-organizational process collaboration (IOPC) has been widely used in the design and development of distributed systems that support business process execution. Blockchain-based IOPC can establish trusted data sharing among participants, attracting more and more attention. The core of such study is to translate the graphical model (e.g., BPMN) into program code called smart contract that can be executed in the blockchain environment. In this context, a proper smart contract plays a vital role in the correct implementation of block-chain-based IOPC. In fact, the quality of graphical model affects the smart con-tract generation. Problematic models (e.g., deadlock) will result in incorrect contracts (causing unexpected behaviours). To avoid this undesired implementation, this paper explores to generate smart contracts by using the verified formal model as input instead of graphical model. Specifically, we introduce a prototype framework that supports the automatic generation of smart contracts, providing an end-to-end solution from modeling, verification, translation to implementation. One of the cores of this framework is to provide a CSP#-based formalization for the BPMN collaboration model from the perspective of message interaction. This formalization provides precise execution semantics and model verification for graphical models, and a verified formal model for smart contract generation. Another novelty is that it introduces a syntax tree-based translation algorithm to directly map the formal model into a smart contract. The required formalism, verification and translation techniques are transparent to users without imposing additional burdens. Finally, a set of experiments shows the effectiveness of the framework.
    Keywords Computer Science - Software Engineering
    Subject code 004
    Publishing date 2023-03-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Discriminating compounds identification based on the innovative sparse representation chemometrics to assess the quality of Maofeng tea

    Li, Haoran / Wu, Pengcheng / Dai, Jisheng / Pan, Tianhong / Holmes, Melvin / Chen, Tao / Xiaobo, Zou

    Journal of Food Composition and Analysis. 2023 Oct., v. 123 p.105590-

    2023  

    Abstract: The rich flavors and antioxidant properties within Maofeng tea are mainly attributable to numerous secondary metabolites and thus may be related to quality. Motivated by this finding, our study presents a sparse representation (SR) scheme to analyze the ... ...

    Abstract The rich flavors and antioxidant properties within Maofeng tea are mainly attributable to numerous secondary metabolites and thus may be related to quality. Motivated by this finding, our study presents a sparse representation (SR) scheme to analyze the content of various secondary metabolites and thus identify discriminating compounds (DCs) for the modelling of Maofeng tea quality. We first identified the DCs in terms of an interpretable sparse recovery strategy with LASSO regression. The optimal regularization term was estimated by a specific Karush–Kuhn–Tucker (KKT) optimal condition. Then, qualitative analysis models were trained with screened DCs and utilized to predict the quality of unseen Maofeng samples. For this purpose, 96 Maofeng samples of 6 different quality grades were collected, and standardized stoichiometry techniques determined 21 quality-related bioactive compounds and empirical quality indicators. The experimental results show that epigallocatechin (EGC), epicatechin (EC), gallocatechin gallate (GCG) and total catechins (TC) were identified as significant discriminating features, and the KNN algorithm provided the best assessment accuracy of 95.79%. Overall, the result demonstrates the superior performance of benchmarks for enhancing the reliable prediction of Maofeng tea quality, not only prediction accuracy but also providing interpretable assessment.
    Keywords algorithms ; antioxidants ; chemometrics ; epicatechin ; epigallocatechin ; food composition ; prediction ; qualitative analysis ; secondary metabolites ; stoichiometry ; tea ; Maofeng tea quality prediction ; Sparse modelling ; Discriminating compounds ; KKT-LASSO
    Language English
    Dates of publication 2023-10
    Publishing place Elsevier Inc.
    Document type Article ; Online
    ZDB-ID 743572-1
    ISSN 0889-1575 ; 1096-0481
    ISSN 0889-1575 ; 1096-0481
    DOI 10.1016/j.jfca.2023.105590
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

    Z 4776: Show issues

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  6. Article: An updated meta-analysis of Chinese herbal medicine for the prevention of COVID-19 based on Western-Eastern medicine.

    Hu, Siying / Luo, Dan / Zhu, Qikui / Pan, Jie / Chen, Bonan / Furian, Michael / Harkare, Harsh Vivek / Sun, Shoukai / Fansa, Adel / Wu, Xiaoping / Yu, Baili / Ma, Tianhong / Wang, Fei / Shi, Shihua

    Frontiers in pharmacology

    2023  Volume 14, Page(s) 1257345

    Abstract: Background and aims: ...

    Abstract Background and aims:
    Language English
    Publishing date 2023-11-13
    Publishing country Switzerland
    Document type Systematic Review
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2023.1257345
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  7. Article: Estimation of tea quality grade using statistical identification of key variables

    Li, Menghu / Pan, Tianhong / Chen, Qi

    Food control. 2021 Jan., v. 119

    2021  

    Abstract: The uncertainty in tea classification affects the market presence of tea and damages the related economic interests. The quick and accurate identification of tea quality grades has a significant impact on the profitability of the tea market as the prices ...

    Abstract The uncertainty in tea classification affects the market presence of tea and damages the related economic interests. The quick and accurate identification of tea quality grades has a significant impact on the profitability of the tea market as the prices of different grades of tea quality vary greatly. In this research, 19 chemical substances that affect the quality of Huangshan Maofeng tea were detected using stoichiometry. A model-based scheme comprising the use of the stepwise regression method (SRM) was established to estimate tea quality grades. The rationale of the filtering of sparse variables in SRM is to put the elements through the preset F-statistic test to determine the selection of variables. The results of the SRM are then compared with those of elastic net and the partial least squares discriminant analysis (PLS-DA) to demonstrate the effectiveness of the proposed scheme. Furthermore, in order to verify the stability of the model, Monte Carlo experiments were conducted on the constructed models. The predictive accuracy of the SRM, PLS-DA, and elastic net algorithms were 68.75%, 75.86%, and 71.88%, respectively. The radar diagram, which is drawn according to the sparse coefficient vector obtained using SRM, illustrates that the proposed scheme can overcome the correlation between all the detection variables. It is concluded that SRM achieves the highest prediction accuracy with the least number of features, thereby simplifying the process of chemical detection, and provides a new effective scheme for batch tea-quality-grade estimation.
    Keywords Monte Carlo method ; accuracy ; algorithms ; chemical elements ; classification ; correlation ; detection ; discriminant analysis ; estimation ; food safety ; least squares ; markets ; models ; prediction ; prices ; profitability ; radar ; research ; stoichiometry ; tea ; uncertainty
    Language English
    Dates of publication 2021-01
    Publishing place Elsevier Ltd
    Document type Article
    Note NAL-light
    ZDB-ID 1027805-9
    ISSN 0956-7135
    ISSN 0956-7135
    DOI 10.1016/j.foodcont.2020.107485
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

    Z 5255: Show issues

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  8. Article: Increasing cure rates of solid tumors by immune checkpoint inhibitors.

    Ma, Weijie / Xue, Ruobing / Zhu, Zheng / Farrukh, Hizra / Song, Wenru / Li, Tianhong / Zheng, Lei / Pan, Chong-Xian

    Experimental hematology & oncology

    2023  Volume 12, Issue 1, Page(s) 10

    Abstract: Immunotherapy has become the central pillar of cancer therapy. Immune checkpoint inhibitors (ICIs), a major category of tumor immunotherapy, reactivate preexisting anticancer immunity. Initially, ICIs were approved only for advanced and metastatic ... ...

    Abstract Immunotherapy has become the central pillar of cancer therapy. Immune checkpoint inhibitors (ICIs), a major category of tumor immunotherapy, reactivate preexisting anticancer immunity. Initially, ICIs were approved only for advanced and metastatic cancers in the salvage setting after or concurrent with chemotherapy at a response rate of around 20-30% with a few exceptions. With significant progress over the decade, advances in immunotherapy have led to numerous clinical trials investigating ICIs as neoadjuvant and/or adjuvant therapies for resectable solid tumors. The promising results of these trials have led to the United States Food and Drug Administration (FDA) approvals of ICIs as neoadjuvant or adjuvant therapies for non-small cell lung cancer, melanoma, triple-negative breast cancer, and bladder cancer, and the list continues to grow. This therapy represents a paradigm shift in cancer treatment, as many early-stage cancer patients could be cured with the introduction of immunotherapy in the early stages of cancer. Therefore, this topic became one of the main themes at the 2021 China Cancer Immunotherapy Workshop co-organized by the Chinese American Hematologist and Oncologist Network, the China National Medical Products Administration and the Tsinghua University School of Medicine. This review article summarizes the current landscape of ICI-based immunotherapy, emphasizing the new clinical developments of ICIs as curative neoadjuvant and adjuvant therapies for early-stage disease.
    Language English
    Publishing date 2023-01-16
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 2669066-4
    ISSN 2162-3619
    ISSN 2162-3619
    DOI 10.1186/s40164-023-00372-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Fast Burst-Sparsity Learning-Based Baseline Correction (FBSL-BC) Algorithm for Signals of Analytical Instruments.

    Li, Haoran / Chen, Suyi / Dai, Jisheng / Zou, Xiaobo / Chen, Tao / Pan, Tianhong / Holmes, Melvin

    Analytical chemistry

    2022  Volume 94, Issue 12, Page(s) 5113–5121

    Abstract: Baseline correction is a critical step for eliminating the interference of baseline drift in spectroscopic analysis. The recently proposed sparse Bayesian learning (SBL)-based method can significantly improve the baseline correction performance. However, ...

    Abstract Baseline correction is a critical step for eliminating the interference of baseline drift in spectroscopic analysis. The recently proposed sparse Bayesian learning (SBL)-based method can significantly improve the baseline correction performance. However, it has at least two disadvantages: (i) it works poorly for large-scale datasets and (ii) it completely ignores the burst-sparsity structure of the sparse representation of the pure spectrum. In this paper, we present a new fast burst-sparsity learning method for baseline correction to overcome these shortcomings. The first novelty of the proposed method is to jointly adopt a down-sampling strategy and construct a multiple measurements block-sparse recovery problem with the down-sampling sequences. The down-sampling strategy can significantly reduce the dimension of the spectrum; while jointly exploiting the block sparsity among the down-sampling sequences avoids losing the information contained in the original spectrum. The second novelty of the proposed method is introducing the pattern-coupled prior into the SBL framework to characterize the inherent burst-sparsity in the sparse representation of spectrum. As illustrated in the paper, burst-sparsity commonly occurs in peak zones with more denser nonzero coefficients. Properly utilizing such burst-sparsity can further enhance the baseline correction performance. Results on both simulated and real datasets (such as FT-IR, Raman spectrum, and chromatography) verify the substantial improvement, in terms of estimation accuracy and computational complexity.
    MeSH term(s) Algorithms ; Bayes Theorem ; Spectroscopy, Fourier Transform Infrared
    Language English
    Publishing date 2022-03-18
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.1c05443
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4033: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  10. Article: A 5

    Peng, Yingchun / Wu, Guoguo / Pan, Chunpeng / Lv, Cheng / Luo, Tianhong

    Micromachines

    2018  Volume 9, Issue 11

    Abstract: Our previous report based on a ... ...

    Abstract Our previous report based on a 10
    Language English
    Publishing date 2018-10-23
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2620864-7
    ISSN 2072-666X
    ISSN 2072-666X
    DOI 10.3390/mi9110539
    Database MEDical Literature Analysis and Retrieval System OnLINE

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