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  1. Buch ; Online: Problem Learning

    Zhang, Yongfeng

    Towards the Free Will of Machines

    2021  

    Abstract: A machine intelligence pipeline usually consists of six components: problem, representation, model, loss, optimizer and metric. Researchers have worked hard trying to automate many components of the pipeline. However, one key component of the pipeline-- ... ...

    Abstract A machine intelligence pipeline usually consists of six components: problem, representation, model, loss, optimizer and metric. Researchers have worked hard trying to automate many components of the pipeline. However, one key component of the pipeline--problem definition--is still left mostly unexplored in terms of automation. Usually, it requires extensive efforts from domain experts to identify, define and formulate important problems in an area. However, automatically discovering research or application problems for an area is beneficial since it helps to identify valid and potentially important problems hidden in data that are unknown to domain experts, expand the scope of tasks that we can do in an area, and even inspire completely new findings. This paper describes Problem Learning, which aims at learning to discover and define valid and ethical problems from data or from the machine's interaction with the environment. We formalize problem learning as the identification of valid and ethical problems in a problem space and introduce several possible approaches to problem learning. In a broader sense, problem learning is an approach towards the free will of intelligent machines. Currently, machines are still limited to solving the problems defined by humans, without the ability or flexibility to freely explore various possible problems that are even unknown to humans. Though many machine learning techniques have been developed and integrated into intelligent systems, they still focus on the means rather than the purpose in that machines are still solving human defined problems. However, proposing good problems is sometimes even more important than solving problems, because a good problem can help to inspire new ideas and gain deeper understandings. The paper also discusses the ethical implications of problem learning under the background of Responsible AI.

    Comment: 17 pages, 1 figure
    Schlagwörter Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Information Retrieval ; Computer Science - Machine Learning
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2021-09-01
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Effectiveness and safety of Buzzy device in needle-related procedures for children under twelve years of age: A systematic review and meta-analysis.

    Jin, Faguang / Wang, Xiaofang / Qi, Maomao / Zhang, Wenhua / Zhang, Yongfeng

    Medicine

    2024  Band 103, Heft 15, Seite(n) e37522

    Abstract: Background: Pain transcends simple physiology, encompassing biological, emotional, psychological, and social facets. Children show pronounced immediate and enduring responses to pain-related procedures. The aim of this meta-analysis is to investigate ... ...

    Abstract Background: Pain transcends simple physiology, encompassing biological, emotional, psychological, and social facets. Children show pronounced immediate and enduring responses to pain-related procedures. The aim of this meta-analysis is to investigate the efficacy and safety of the Buzzy device for needle-related procedures in children aged twelve years or younger.
    Methods: PubMed, Web of Science, and Embase were searched from inception to July 2023. Only randomized controlled trials utilizing the Buzzy device for needle-related procedures in children under twelve years old were included. Two reviewers independently conducted study selection, data extraction, and risk of bias assessment. Random-effects models were utilized, and analyses were performed using mean differences or standardized mean differences as well as risk ratios.
    Results: A total of 19 studies were included, involving 2846 participants (Buzzy = 1095, Control = 1751). Compared to no intervention, the Buzzy device significantly reduced pain response [self-report SMD = -1.90 (-2.45, -1.36), parental SMD = -3.04 (-4.09, -1.99), observer SMD = -2.88 (-3.75, -2.02)] and anxiety scores [self-report SMD = -1.97 (-3.05, -0.88), parental SMD = -2.01 (-2.93, -1.08), observer SMD = -1.92 (-2.64, -1.19)]. Compared to virtual reality (VR), the Buzzy device reduced self-reported anxiety levels SMD = -0.47 (-0.77, -0.17), and compared to distraction cards, the Buzzy device reduced parental and observer-reported pain [parental SMD = -0.85 (-1.22, -0.48), observer SMD = -0.70 (-1.00, -0.40)] and anxiety [parental SMD = -0.96 (-1.46, -0.47), observer SMD = -0.91 (-1.40, -0.42)]. Subgroup analysis results showed that procedure type, patient age, measurement scales used, and distance of operation were not the reason of heterogeneity. The summarized first puncture attempt success rate did not differ from other interventions. There were no significant adverse events in the included studies.
    Conclusion: The Buzzy device reduces pain and anxiety in children during needle procedures, ensuring success and safety. Additionally, the effectiveness of the Buzzy device in reducing pain during venipuncture is superior when compared to its effectiveness during intramuscular injections.
    Mesh-Begriff(e) Child ; Humans ; Anxiety/etiology ; Anxiety/prevention & control ; Anxiety Disorders ; Emotions ; Injections, Intramuscular ; Pain/etiology ; Pain/prevention & control
    Sprache Englisch
    Erscheinungsdatum 2024-04-12
    Erscheinungsland United States
    Dokumenttyp Meta-Analysis ; Systematic Review ; Journal Article
    ZDB-ID 80184-7
    ISSN 1536-5964 ; 0025-7974
    ISSN (online) 1536-5964
    ISSN 0025-7974
    DOI 10.1097/MD.0000000000037522
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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    Ua VI Zs.171: Hefte anzeigen Standort:
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  3. Artikel ; Online: ALDH3A1 upregulation inhibits neutrophils N2 polarization and halts oral cancer growth.

    He, Ying / Qu, Yi / Jin, Shan / Zhang, Yongfeng / Qin, Lizheng

    Oral diseases

    2024  

    Abstract: Objectives: Tumor-associated neutrophils (TANs) are among the most abundant inflammatory cells in tumor microenvironment (TME). Aldehyde dehydrogenase 3A1 (ALDH3A1) is significantly reduced in oral squamous cell carcinoma (OSCC), ALDH3A1 overexpression ... ...

    Abstract Objectives: Tumor-associated neutrophils (TANs) are among the most abundant inflammatory cells in tumor microenvironment (TME). Aldehyde dehydrogenase 3A1 (ALDH3A1) is significantly reduced in oral squamous cell carcinoma (OSCC), ALDH3A1 overexpression suppresses tumorigenesis by inhibiting inflammation. This study investigated the relationship and mechanisms underlying the crosstalk between ALDH3A1 and TANs in OSCC.
    Materials and methods: Immunohistochemistry and immunofluorescence were performed to investigate the abundance of TANs and the expression of ALDH3A1. dHL-60 were induced with tumor-conditioned media and recombinant IL-6/IL-8. The expression of key proteins in PI3K/AKT/NF-κB pathway were detected by RT-PCR and western blot. A xenograft model was utilized to examine the effect of ALDH3A1 on tumorigenicity and polarization of TANs.
    Results: In patients with OSCC, TANs significantly increased and were associated with a worse prognosis. Additionally, ALDH3A1 negatively correlated with TANs infiltration and especially the N2 phenotype which was the prominent part in OSCC. Furthermore, our study demonstrated that tumor-derived IL-8 drives ALDH3A1-mediated TANs N2 polarization in the TME through PI3K/AKT/NF-κB pathway in vitro and in vivo.
    Conclusion: Our results indicate that TANs can serve as a prognostic biomarker and ALDH3A1 could be a promising therapeutic target for regulating TANs N2 polarization in antitumor therapy.
    Sprache Englisch
    Erscheinungsdatum 2024-01-15
    Erscheinungsland Denmark
    Dokumenttyp Journal Article
    ZDB-ID 1290529-x
    ISSN 1601-0825 ; 1354-523X
    ISSN (online) 1601-0825
    ISSN 1354-523X
    DOI 10.1111/odi.14863
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 4427: Hefte anzeigen Standort:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  4. Buch ; Online: LightLM

    Mei, Kai / Zhang, Yongfeng

    A Lightweight Deep and Narrow Language Model for Generative Recommendation

    2023  

    Abstract: This paper presents LightLM, a lightweight Transformer-based language model for generative recommendation. While Transformer-based generative modeling has gained importance in various AI sub-fields such as NLP and vision, generative recommendation is ... ...

    Abstract This paper presents LightLM, a lightweight Transformer-based language model for generative recommendation. While Transformer-based generative modeling has gained importance in various AI sub-fields such as NLP and vision, generative recommendation is still in its infancy due to its unique demand on personalized generative modeling. Existing works on generative recommendation often use NLP-oriented Transformer architectures such as T5, GPT, LLaMA and M6, which are heavy-weight and are not specifically designed for recommendation tasks. LightLM tackles the issue by introducing a light-weight deep and narrow Transformer architecture, which is specifically tailored for direct generation of recommendation items. This structure is especially apt for straightforward generative recommendation and stems from the observation that language model does not have to be too wide for this task, as the input predominantly consists of short tokens that are well-suited for the model's capacity. We also show that our devised user and item ID indexing methods, i.e., Spectral Collaborative Indexing (SCI) and Graph Collaborative Indexing (GCI), enables the deep and narrow Transformer architecture to outperform large-scale language models for recommendation. Besides, to address the hallucination problem of generating items as output, we propose the constrained generation process for generative recommenders. Experiments on real-world datasets show that LightLM outperforms various competitive baselines in terms of both recommendation accuracy and efficiency. The code can be found at https://github.com/dongyuanjushi/LightLM.
    Schlagwörter Computer Science - Information Retrieval ; Computer Science - Computation and Language
    Thema/Rubrik (Code) 004 ; 600
    Erscheinungsdatum 2023-10-26
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Buch ; Online: ExplainableFold

    Tan, Juntao / Zhang, Yongfeng

    Understanding AlphaFold Prediction with Explainable AI

    2023  

    Abstract: This paper presents ExplainableFold, an explainable AI framework for protein structure prediction. Despite the success of AI-based methods such as AlphaFold in this field, the underlying reasons for their predictions remain unclear due to the black-box ... ...

    Abstract This paper presents ExplainableFold, an explainable AI framework for protein structure prediction. Despite the success of AI-based methods such as AlphaFold in this field, the underlying reasons for their predictions remain unclear due to the black-box nature of deep learning models. To address this, we propose a counterfactual learning framework inspired by biological principles to generate counterfactual explanations for protein structure prediction, enabling a dry-lab experimentation approach. Our experimental results demonstrate the ability of ExplainableFold to generate high-quality explanations for AlphaFold's predictions, providing near-experimental understanding of the effects of amino acids on 3D protein structure. This framework has the potential to facilitate a deeper understanding of protein structures.

    Comment: This work has been accepted for presentation at the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
    Schlagwörter Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-01-27
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Fairness of ChatGPT

    Li, Yunqi / Zhang, Yongfeng

    2023  

    Abstract: Understanding and addressing unfairness in LLMs are crucial for responsible AI deployment. However, there is a limited availability of quantitative analyses and in-depth studies regarding fairness evaluations in LLMs, especially when applying LLMs to ... ...

    Abstract Understanding and addressing unfairness in LLMs are crucial for responsible AI deployment. However, there is a limited availability of quantitative analyses and in-depth studies regarding fairness evaluations in LLMs, especially when applying LLMs to high-stakes fields. This work aims to fill this gap by providing a systematic evaluation of the effectiveness and fairness of LLMs using ChatGPT as a study case. We focus on assessing ChatGPT's performance in high-takes fields including education, criminology, finance and healthcare. To make thorough evaluation, we consider both group fairness and individual fairness and we also observe the disparities in ChatGPT's outputs under a set of biased or unbiased prompts. This work contributes to a deeper understanding of LLMs' fairness performance, facilitates bias mitigation and fosters the development of responsible artificial intelligence systems.
    Schlagwörter Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Computers and Society
    Thema/Rubrik (Code) 004
    Erscheinungsdatum 2023-05-22
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Buch ; Online: Sparks of Artificial General Recommender (AGR)

    Lin, Guo / Zhang, Yongfeng

    Early Experiments with ChatGPT

    2023  

    Abstract: This study investigates the feasibility of developing an Artificial General Recommender (AGR), facilitated by recent advancements in Large Language Models (LLMs). An AGR comprises both conversationality and universality to engage in natural dialogues and ...

    Abstract This study investigates the feasibility of developing an Artificial General Recommender (AGR), facilitated by recent advancements in Large Language Models (LLMs). An AGR comprises both conversationality and universality to engage in natural dialogues and generate recommendations across various domains. We propose ten fundamental principles that an AGR should adhere to, each with its corresponding testing protocols. We proceed to assess whether ChatGPT, a sophisticated LLM, can comply with the proposed principles by engaging in recommendation-oriented dialogues with the model while observing its behavior. Our findings demonstrate the potential for ChatGPT to serve as an AGR, though several limitations and areas for improvement are identified.
    Schlagwörter Computer Science - Information Retrieval ; Computer Science - Computation and Language ; Computer Science - Machine Learning
    Erscheinungsdatum 2023-05-08
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Artikel ; Online: Dispersed fringe cophasing method based on principal component analysis.

    Zhang, Yongfeng / Xian, Hao / Rao, Changhui

    Optics letters

    2023  Band 48, Heft 3, Seite(n) 696–699

    Abstract: With the success of the Webb telescope, dispersed fringe sensing (DFS), with the significant merit of a large capture range, is proving to be a promising cophasing approach for a large-aperture segmented telescope. In this Letter, a novel, to the best of ...

    Abstract With the success of the Webb telescope, dispersed fringe sensing (DFS), with the significant merit of a large capture range, is proving to be a promising cophasing approach for a large-aperture segmented telescope. In this Letter, a novel, to the best of our knowledge, piston error extraction method based on principal component analysis (PCA) technology is proposed. In this method, all the one-dimension intensity distributions along the dispersion axis for different interference positions are regarded as a set of random phase-shifted interference signals. PCA technology is utilized to obtain its corresponding continuous principal phase and the piston error could be directly estimated proportionally from the slope of the phase-wavenumber line. This method avoids nonlinear operations, similar to Shi's traditional framework; no active move is needed for fine cophasing, and the method is also free of characteristic constant calibration in sidelobe peak displacement- and slope-based methods. Preliminary simulations of the method's coarse-then-fine cophasing ability with high accuracy are presented here to show its potential.
    Sprache Englisch
    Erscheinungsdatum 2023-02-01
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1539-4794
    ISSN (online) 1539-4794
    DOI 10.1364/OL.474314
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel: Insight into the effect of chemical structure for microbial lignite methanation.

    Yang, Lin / Zhang, Yongfeng / Hao, Zhifei / Zhang, Junying

    Heliyon

    2023  Band 9, Heft 8, Seite(n) e18352

    Abstract: The chemical structure of lignite plays a fundamental role in microbial degradation, which can be altered to increase gas production. In this study, the structural changes in lignite were analyzed by conducting pretreatment and biomethane gas production ... ...

    Abstract The chemical structure of lignite plays a fundamental role in microbial degradation, which can be altered to increase gas production. In this study, the structural changes in lignite were analyzed by conducting pretreatment and biomethane gas production experiments using crushing and ball milling processes, respectively. The results revealed that different particle size ranges of lignite considerably influence gas production. The maximum methane yield under both treatments corresponded to a particle size range of 400-500 mesh. The gas production after ball milling was higher than that after crushing, irrespective of particle size. Compared with lignite subjected to crushing, that subjected to ball milling exhibited more oxygen-containing functional groups, less coalification, more disordered structures, and small aromatic ring structures, demonstrating more unstable properties, which are typically favorable to microbial flora for the utilization and degradation of lignite. Additionally, a symbiotic microbial community comprising multiple species was established during the microbial degradation of lignite into biogas. This study provides new insights and a strong scientific foundation for further research on microbial lignite methanation.
    Sprache Englisch
    Erscheinungsdatum 2023-07-16
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2023.e18352
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  10. Artikel: Chronic Mucocutaneous Candidiasis: A Case Report.

    Wang, Zhensheng / Zhang, Yongfeng / Ma, Weiyuan

    Clinical, cosmetic and investigational dermatology

    2023  Band 16, Seite(n) 231–236

    Abstract: Chronic mucocutaneous candidiasis (CMC) is a rare infectious skin disease. This study reported a case of CMC in a child with clinical manifestations of oral mucosal leukoplakia and erythema and crust-like thick scabs on the skin of the face and upper ... ...

    Abstract Chronic mucocutaneous candidiasis (CMC) is a rare infectious skin disease. This study reported a case of CMC in a child with clinical manifestations of oral mucosal leukoplakia and erythema and crust-like thick scabs on the skin of the face and upper limbs. Microscopic fungal examination revealed a large amount of pseudohyphae, and the fungal culture indicated
    Sprache Englisch
    Erscheinungsdatum 2023-01-25
    Erscheinungsland New Zealand
    Dokumenttyp Case Reports
    ZDB-ID 2494852-4
    ISSN 1178-7015
    ISSN 1178-7015
    DOI 10.2147/CCID.S396802
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