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Fulltext Advances and Opportunities in Passive Wake-Up Radios with Wireless Energy Harvesting for the Internet of Things Applications

Bello H, Xiaoping Z, Nordin R, Xin J

Sensors (Basel), 2019 Jul 12;19(14).
PMID: 31336834 DOI: 10.3390/s19143078

Wake-up radio is a promising approach to mitigate the problem of idle listening, which incurs additional power consumption for the Internet of Things (IoT) wireless transmission. Radio frequency (RF) energy harvesting technique allows the wake-up radio to remain in a deep sleep and only become active after receiving an external RF signal to 'wake-up' the radio, thus eliminating necessary hardware and signal processing to perform idle listening, resulting in higher energy efficiency. This review paper focuses on cross-layer; physical and media access control (PHY and MAC) approaches on passive wake-up radio based on the previous works from the literature. First, an explanation of the circuit design and system architecture of the passive wake-up radios is presented. Afterward, the previous works on RF energy harvesting techniques and the existing passive wake-up radio hardware architectures available in the literature are surveyed and classified. An evaluation of the various MAC protocols utilized for the novel passive wake-up radio technologies is presented. Finally, the paper highlights the potential research opportunities and practical challenges related to the practical implementation of wake-up technology for future IoT applications.
Fulltext Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Xin J, Khishe M, Zeebaree DQ, Abualigah L, Ghazal TM

Heliyon, 2024 Apr 15;10(7):e28147.
PMID: 38689992 DOI: 10.1016/j.heliyon.2024.e28147

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeography-Based Optimizer (AHBBO) for tuning the hyperparameters of DCNNs in image classification tasks. In complicated optimization problems, the BBO suffers from premature convergence and insufficient exploration. In this regard, an adaptable habitat is presented as a solution to these problems; it would permit variable habitat sizes and regulated mutation. Better optimization performance and a greater chance of finding high-quality solutions across a wide range of problem domains are the results of this modification's increased exploration and population diversity. AHBBO is tested on 53 benchmark optimization functions and demonstrates its effectiveness in improving initial stochastic solutions and converging faster to the optimum. Furthermore, DCNN-AHBBO is compared to 23 well-known image classifiers on nine challenging image classification problems and shows superior performance in reducing the error rate by up to 5.14%. Our proposed algorithm outperforms 13 benchmark classifiers in 87 out of 95 evaluations, providing a high-performance and reliable solution for optimizing DNNs in image classification tasks. This research contributes to the field of deep learning by proposing a new optimization algorithm that can improve the efficiency of deep neural networks in image classification.
Fulltext Potential use of Pichia pastoris strain SMD1168H expressing DNA topoisomerase I in the screening of potential anti‑breast cancer agents

Xin J, Wan Mahtar WNA, Siah PC, Miswan N, Khoo BY

Mol Med Rep, 2019 Jun;19(6):5368-5376.
PMID: 31059050 DOI: 10.3892/mmr.2019.10201

Cancer chemotherapy possesses high toxicity, particularly when a higher concentration of drugs is administered to patients. Therefore, searching for more effective compounds to reduce the toxicity of treatments, while still producing similar effects as current chemotherapy regimens, is required. Currently, the search for potential anticancer agents involves a random, inaccurate process with strategic deficits and a lack of specific targets. For this reason, the initial in vitro high‑throughput steps in the screening process should be reviewed for rapid identification of the compounds that may serve as anticancer agents. The present study aimed to investigate the potential use of the Pichia pastoris strain SMD1168H expressing DNA topoisomerase I (SMD1168H‑TOPOI) in a yeast‑based assay for screening potential anticancer agents. The cell density that indicated the growth of the recombinant yeast without treatment was first measured by spectrophotometry. Subsequently, the effects of glutamate (agonist) and camptothecin (antagonist) on the recombinant yeast cell density were investigated using the same approach, and finally, the effect of camptothecin on various cell lines was determined and compared with its effect on recombinant yeast. The current study demonstrated that growth was enhanced in SMD1168H‑TOPOI as compared with that in SMD1168H. Glutamate also enhanced the growth of the SMD1168H; however, the growth effect was not enhanced in SMD1168H‑TOPOI treated with glutamate. By contrast, camptothecin caused only lower cell density and growth throughout the treatment of SMD1168H‑TOPOI. The findings of the current study indicated that SMD1168H‑TOPOI has similar characteristics to MDA‑MB‑231 cells; therefore, it can be used in a yeast‑based assay to screen for more effective compounds that may inhibit the growth of highly metastatic breast cancer cells.
Fulltext What information and the extent of information research participants need in informed consent forms: a multi-country survey

Karbwang J, Koonrungsesomboon N, Torres CE, Jimenez EB, Kaur G, Mathur R, et al.

BMC Med Ethics, 2018 09 15;19(1):79.
PMID: 30219106 DOI: 10.1186/s12910-018-0318-x

BACKGROUND: The use of lengthy, detailed, and complex informed consent forms (ICFs) is of paramount concern in biomedical research as it may not truly promote the rights and interests of research participants. The extent of information in ICFs has been the subject of debates for decades; however, no clear guidance is given. Thus, the objective of this study was to determine the perspectives of research participants about the type and extent of information they need when they are invited to participate in biomedical research.
METHODS: This multi-center, cross-sectional, descriptive survey was conducted at 54 study sites in seven Asia-Pacific countries. A modified Likert-scale questionnaire was used to determine the importance of each element in the ICF among research participants of a biomedical study, with an anchored rating scale from 1 (not important) to 5 (very important).
RESULTS: Of the 2484 questionnaires distributed, 2113 (85.1%) were returned. The majority of respondents considered most elements required in the ICF to be 'moderately important' to 'very important' for their decision making (mean score, ranging from 3.58 to 4.47). Major foreseeable risk, direct benefit, and common adverse effects of the intervention were considered to be of most concerned elements in the ICF (mean score = 4.47, 4.47, and 4.45, respectively).
CONCLUSIONS: Research participants would like to be informed of the ICF elements required by ethical guidelines and regulations; however, the importance of each element varied, e.g., risk and benefit associated with research participants were considered to be more important than the general nature or technical details of research. Using a participant-oriented approach by providing more details of the participant-interested elements while avoiding unnecessarily lengthy details of other less important elements would enhance the quality of the ICF.