Displaying all 5 publications

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  1. Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, et al.
    Phys Rev Lett, 2024 Jan 12;132(2):021803.
    PMID: 38277607 DOI: 10.1103/PhysRevLett.132.021803
    The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140  fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.
  2. Klionsky DJ, Abdelmohsen K, Abe A, Abedin MJ, Abeliovich H, Acevedo Arozena A, et al.
    Autophagy, 2016;12(1):1-222.
    PMID: 26799652 DOI: 10.1080/15548627.2015.1100356
  3. Song W, Suandi SA
    Sensors (Basel), 2023 Jan 09;23(2).
    PMID: 36679542 DOI: 10.3390/s23020749
    Recognizing traffic signs is an essential component of intelligent driving systems' environment perception technology. In real-world applications, traffic sign recognition is easily influenced by variables such as light intensity, extreme weather, and distance, which increase the safety risks associated with intelligent vehicles. A Chinese traffic sign detection algorithm based on YOLOv4-tiny is proposed to overcome these challenges. An improved lightweight BECA attention mechanism module was added to the backbone feature extraction network, and an improved dense SPP network was added to the enhanced feature extraction network. A yolo detection layer was added to the detection layer, and k-means++ clustering was used to obtain prior boxes that were better suited for traffic sign detection. The improved algorithm, TSR-YOLO, was tested and assessed with the CCTSDB2021 dataset and showed a detection accuracy of 96.62%, a recall rate of 79.73%, an F-1 Score of 87.37%, and a mAP value of 92.77%, which outperformed the original YOLOv4-tiny network, and its FPS value remained around 81 f/s. Therefore, the proposed method can improve the accuracy of recognizing traffic signs in complex scenarios and can meet the real-time requirements of intelligent vehicles for traffic sign recognition tasks.
  4. Song W, Mansor NS, Shari NI, Azman N, Zhang R, Leong Bin Abdullah MFI
    PLoS One, 2023;18(11):e0293698.
    PMID: 37988357 DOI: 10.1371/journal.pone.0293698
    BACKGROUND: The well-being and adaptive functioning of patients with cancer depend on their perception of social support. To accurately assess and understand the impact of social support in a diverse population, validated measurement tools are essential. This study aimed to adapt and validate the Malay version of the Multidimensional Scale of Perceived Social Support (MSPSS-M) among patients with cancer in Malaysia.

    METHODS: A total of 346 cancer patients with mixed disease types were recruited and completed the socio-demographic and clinical characteristics questionnaire and the MSPSS-M. The MSPSS-M was assessed for internal consistency, construct validity, face, content, convergent, discriminant validity, and confirmatory factor analyses.

    RESULTS: The MSPSS-M and its three domains demonstrated good internal consistency with Cronbach's α ranging from 0.900 to 0.932. Confirmatory factor analysis (CFA) of the MSPSS-M supported the three-factor model of the original English version of the MSPSS. The MSPSS-M also exhibited good convergent validity and discriminant validity.

    CONCLUSION: The MSPSS-M demonstrates favorable psychometric properties among patients with cancer in Malaysia. The validation of the MSPSS-M provides a culturally adapted and linguistically valid instrument to assess perceived social support among Malay-speaking patients with cancer in Malaysia.

  5. Song W, Mansor NS, Shari NI, Zhang R, Abdullah MFILB
    BMC Public Health, 2024 Jan 13;24(1):173.
    PMID: 38218795 DOI: 10.1186/s12889-023-17060-1
    OBJECTIVE: The Illness Cognition Questionnaire (ICQ) was translated from its original English version to the Malay version for this research, adapted the Malay language version of the ICQ (ICQ-M) for use in cancer patients, and assessed the internal consistency, content, face, construct, convergent, discriminant and concurrent validity of the ICQ-M among a cohort of cancer patients with mixed cancer types in Malaysia.

    METHOD: Initially, the ICQ was translated into Malay and back-translated, and its content and face validity were evaluated. Then, 346 cancer patients with various cancer types received the ICQ-M, and its internal consistency, convergent, discriminant, construct, and concurrent validity were evaluated.

    RESULTS: The ICQ-M and its domains had acceptable internal consistency with Cronbach's α ranging from 0.742 to 0.927. Construct validity assessment demonstrated that the ICQ-M consists of 17 items designated in two domains with good convergent and discriminant validity. The ICQ-M and its domains also had moderate correlations with the Acceptance and Action Questionnaire II, which denotes that the ICQ-M had acceptable concurrent validity.

    CONCLUSION: The ICQ-M had good psychometric properties and is now available to measure the illness cognition of cancer patients in Malaysia.

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