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Background and Aim: Edible bird’s nest (EBN) is known as the “Caviar of the East” because of its high nutritional and medicinal values. Nevertheless, its effect on human immunity is yet to be explored. This study examined the effects of EBN’s aqueous extract (EBNE) on human immunity through the modular immune in vitro construct (MIMIC) model consisting of peripheral tissue equivalent (PTE) and lymphoid tissue equivalent (LTE) modules. Materials and Methods: One hundred twenty mL of full blood was obtained from four healthy human volunteers. The human immune system was simulated using an in vitro model, called MIMIC. Under EBNE treatment, monocyte transendothelial migration through reversed endothelial layers was observed. Using PTE and LTE modules, monocytes were differentiated into dendritic cells with lipopolysaccharide, then co-cultured with T- and B-cells for cytokine and immunoglobulin (Ig) production. The human cytokine array G2000 and quantitative human Ig isotyping array were used to identify the cytokine profile and Ig isotypes, respectively. Results: IgE, IgA, and IgG3 levels were significantly raised by EBNE. These cytokines, including brain-derived neurotrophic factor, ciliary neurotrophic factor, glial cell line-derivative neurotrophic factor, insulin-like growth factor 1, and insulin-like growth factor binding protein 4, were generated. Conclusion: For the first time, this work uses a MIMIC model to illustrate the impact of EBNE on human immune response. This new understanding of EBN’s immunoregulatory effect allows for further exploration of how EBN interacts with the human immune system.

Machine vision systems with programmed text detection and text recognition features are useful in manufacturing process to automatically locate and read text markings on mounted printed circuit board (PCB) components. To better handle input images with varying image quality, text quality, and text variations, the robustness of deep learning approach for end-to-end text spotting on PCB component images is worth exploring. However, limitations of public PCB component datasets for such research and imbalance of data in actual collected PCB component datasets hinder the training of deep learning text spotting model, and consequently necessitate the generation of synthetic data. In this study, a synthetic PCB component dataset is generated using our synthetic data generator that adds synthetic text with random character sequences on manually edited PCB component images to elevate the realism of the synthetic images. The synthetic dataset covers 66 character classes while providing synthetic text with diverse text variations in font, style, size, and color. We train an existing text spotting model called Text Perceptron using both real and synthetic datasets to detect and recognize arbitrary-shaped text markings on PCB components. Our synthetic PCB component dataset has improved the text spotting performance of Text Perceptron. The trained model achieves promising text detection result and encouraging end-to-end text spotting F-score on real PCB component images. It also meets an acceptable average inference time per image. Still, the text spotting performance of the trained model needs improvement to realize deployment for PCB component inspection.

The damping coefficients and ratios of piping system snubber supports were found to vary logarithmically with pipe support nodal displacement. For piping systems with fundamental frequencies in the range of 0.6 to 6.6 Hz, the support damping ratio for snubber supports was found to increase with increasing fundamental frequency. For 3-kip snubbers, damping coefficient and damping ratio decreased logarithmically with nodal displacement, indicating that the 3-kip snubbers studied behaved essentially as coulomb dampers; while for the 10-kip snubbers studied, damping coefficient and damping ratio increased logarithmically with nodal displacement.

In this study of flexible piping systems (0.6 to 6. 6 Hz), it was shown that the fundamental mode was not always the most significant mode of vibration. This study also concluded that variations in support condition do not significantly influence response in terms of nodal stress, fundamental frequency, and contribution of higher modes. In terms of support stiffness, the ratio of the magnitude of the gap (the total of all the mechanical tolerances and deadbands in the snubber support system) to the magnitude of the support nodal displacement was found to be more important than the actual magnitude of the gap. Additionally, when the magnitude of the nodal displacement exceeded the gap magnitude by a factor of about five or more, support stiffness was found to remain relatively constant.

Abstract Background Patient’s awareness and satisfaction towards ward pharmacy services may influence perception towards effectiveness and safety of drugs, affecting medication adherence and clinical outcome. Nevertheless, studies on local ward pharmacy services were lacking. This study evaluated awareness, expectation and satisfaction of ward pharmacy services among patients in medical wards and determined their association with demographic characteristics. Methods This was a cross-sectional study using self-administered questionnaire conducted in medical wards of fourteen Perak state public hospitals from September to October 2020. In-patients aged ≥18 years old were included. The validated questionnaire had four domains. The student’s t-test, one-way analysis of variance (ANOVA) and multiple linear regression were was employed to evaluate the association between patients’ demographic characteristics with their awareness, expectation and satisfaction towards ward pharmacy services. Results 467 patients agreed to participate (response rate = 83.8%) but only 441 were analysed. The mean age of the patients was 54.9 years. Majority was male (56.2%), Malay (77.3%), with secondary education (62.9%), rural resident (57.1%) and reported good medication adherence (61.6%). The mean awareness score was 49.6 out of 60. Patients were least aware about drug-drug interaction (3.85 ± 1.15) and proper storage of medications (3.98 ± 1.06). Elderly patients (β = − 2.82, P