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The distribution network is a crucial component of the power system, with industrialization driving increased energy demand. Traditional power-generating techniques, such as thermal and hydroelectric are not enough to meet this demand, leading to the development of Distributed Generation (DG). DG requires an extensive re-evaluation of the current power system, as it modifies energy losses and line flows. Inadequate integration of DG can cause power outages, disruption of protection coordination, and lead to islanding. AI can help overcome this issue by determining the best system architecture. Researchers have been interested in the Artificial Immune System (AIS) algorithm, which has room for development and lacks a fixed template. In order to improve AIS, X3PAIS, a hybridization strategy that combines clonal selection with a three-parent crossover has been developed within the scope of the study. X3PAIS was pre-tested using applications in a planetary gear train, a wastewater treatment facility, and mathematical calculations, showcasing its robustness and versatility. In the context of power distribution, X3PAIS is used in the multiple DG architecture of the power distribution system, reducing power losses by placing DG units in the best locations and sizing them to match load profiles. The four DGs' experiment results show that X3PAIS can minimize power losses by more than 89 %. To optimize power losses in the power distribution system, X3PAIS may be improved with a three-parent multiple-point crossover operation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Introduction: The use of computed tomography (CT) in healthcare institutions has increased rapidly in recent years. The Singapore Health Services (SingHealth) cluster of healthcare institutions has taken the first step in establishing a local cluster-wide CT Diagnostic Reference Levels (DRL) in Singapore. CT dose data from each institution were collected through two primary dosimetry metrics: volume CT dose index (CTDI vol measured in mGy) and dose-length product (DLP measured in mGy.cm)., Methods: Data from 19 CT scanners in seven institutions under one of Singapore healthcare cluster were retrospectively collected and analysed. The five common adult CT examinations analysed were CT Brain (non-contrast enhanced), CT Chest (IV contrast enhanced), CT Kidney-Ureter-Bladder (CT KUB, non-contrast enhanced), CT Pulmonary Angiogram (CT PA, IV contrast enhanced) and CT Abdomen-Pelvis (CT AP, IV contrast enhanced, single phase). Median CTDI vol and DLP values for the five CT examinations from each institution were derived, with the cluster DRLs determined as the 75th percentile of the distribution of the institution median dose values., Results: A total of 2413 dose data points were collected over a six-month period from June to November 2020. The cluster CT DRLs for the five CT examinations were determined to be 47 mGy and 820 mGy.cm for CT Brain, 5.4 mGy and 225 mGy.cm for CT Chest, 6.7 mGy and 248 mGy.cm for CT PA, 4.6 mGy and 190 mGy.cm for CT KUB and 6.9 mGy and 349 mGy.cm for CT AP., Conclusion: The establishment of the cluster CT DRLs provided individual institutions with a better understanding if their CT doses are unusually high or low, while emphasising that these DRLs are not meant as hard dose limits or constraints to follow strictly., Competing Interests: Conflict of interest statement All authors have no conflict of interest to declare., (Copyright © 2022 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.)

Background: In 2019, the World Health Organization (WHO) released global guidelines for physical activity, sedentary behaviour and sleep for the early years. The International Study of Movement Behaviours in the Early Years, SUNRISE, aimed to assess the extent to which children aged three and four years meet the WHO global guidelines and its association with health and development., Objectives: To assess movement behaviours in pre-school children from low-income settings in Zimbabwe and to establish associations between these movement behaviours and adiposity, motor skills and executive function., Methods: Pre-school children/caregivers were recruited from two urban and two rural public schools respectively in Zimbabwe. The caregivers answered questions on the children's physical activity, screen time, sedentary behaviour and sleep patterns. Children's movement behaviours were objectively measured using accelerometers. Gross and fine motor skills and executive function were assessed using the Ages and Stages Questionnaire-3 and Early Years Toolbox, respectively. Focus group discussions were carried out with caregivers and teachers on the acceptability and feasibility of the study., Results: Eighty-one children participated in the study. The proportions of children meeting the guidelines were physical activity 92%, sedentary behaviour 70%, and sleep 86%, and all guidelines combined 24%. Boys and girls were similar (p>0.05 for all variables) for all executive function variables, but rural children had significantly lower inhibition scores (p=0.026) than urban children., Conclusion: The study adds to the growing literature on movement behaviours and associated risk factors in low-resourced settings. Further investigations of movement behaviours in this age group in Zimbabwe are recommended., Competing Interests: Conflict of interest and source of funding: The authors declare no conflict of interest. Research reported in this publication was supported by the Fogarty International Center (Office of The Director, National Institutes of Health (OD), National Institute of Nursing Research (NINR), National Institute of Mental Health (NIMH), National Institute of Dental & Craniofacial Research (NIDCR), National Institute of Neurological Disorders and Stroke (NINDS), National Heart, Lung, and Blood Institute (NHLBI), Fogarty International Center (FIC)) of the National Institutes of Health under Award Number D43 TW010137. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health., (Copyright © 2021 South African Journal of Sports Medicine.)