The operations of take-off and landing at hub airports are often subject to a wide variety of delays; the effects of these delays impact not only the related stakeholders, such as aircraft operators, air-traffic control unity and ground handlers but as part of the European network, delays are propagated through the network. As a result, Airport Collaborative Decision Making (A-CDM) is being employed as a methodology for increasing the efficiency of Air Traffic Management (ATM), through the involvement of partners within the airports. Under CDM, there are some strategic common objectives regardless the airport or the partner specific interest to improve operational efficiency, predictability and punctuality to the ATM network and airport stakeholders. Monitoring and controlling some strategic areas such as, Efficiency, Capacity, Safety and Environment is needed to achieve the benefits. Therefore, the present work aims to provide a framework to monitor the accuracy of capacity in the three main flight phases. It aims to provide a comprehensible and practical approach to monitoring capacity by identifying and proposing Key Performance Indicators (KPIs) based on the A-CDM Milestone Approach to optimise the use of available capacity. To illustrate our approach, Amsterdam Airport Schiphol is used as case study as a full A-CDM airport.
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This thesis focuses on topics such as preterm birth, variation in gross motor development, factors that influence (premature) infant gross motor development, and parental beliefs and practices. By gaining insight into these topics, this thesis aims to contribute to clinical decision-making of paediatric physiotherapists together with parents, and with that shape early intervention.
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Aim The aim of this study is to gain more insight into child and environmental factors that influence gross motor development (GMD) of healthy infants from birth until reaching the milestone of independent walking, based on longitudinal research. Background A systematic search was conducted using Scopus, PsycINFO, MEDLINE and CINAHL to identify studies from inception to February 2020. Studies that investigated the association between child or environmental factors and infant GMD using longitudinal measurements of infant GMD were eligible. Two independent reviewers extracted key information and assessed risk of bias of the selected studies, using the Quality in Prognostic Studies tool (QUIPS). Strength of evidence (strong, moderate, limited, conflicting and no evidence) for the factors identified was described according to a previously established classification. Results In 36 studies, six children and 11 environmental factors were identified. Five studies were categorized as having low risk of bias. Strong evidence was found for the association between birthweight and GMD in healthy full-term and preterm infants. Moderate evidence was found for associations between gestational age and GMD, and sleeping position and GMD. There was conflicting evidence for associations between twinning and GMD, and breastfeeding and GMD. No evidence was found for an association between maternal postpartum depression and GMD. Evidence for the association of other factors with GMD was classified as ‘limited’ because each of these factors was examined in only one longitudinal study. Conclusion Infant GMD appears associated with two child factors (birthweight and gestational age) and one environmental factor (sleeping position). For the other factors identified in this review, insufficient evidence for an association with GMD was found. For those factors that were examined in only one longitudinal study, and are therefore classified as having limited evidence, more research would be needed to reach a conclusion.
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