To serve this purpose, the thesis focuses on investigating values that can be delivered by designing a resilient communication network. In this thesis, the right to communicate and remain connected is considered the core of the design process. Additionally, mobile and immobile citizens stuck in impoverished, highly populated areas, so-called ‘islands of inequity’ where often initial infrastructure is missing, need to be able to connect with disaster response teams requiring hybrid communication approaches. This requires communication networks to adapt to these changing spatial-temporal-resource contexts. Citizens are confronted with challenges such as the complicated deployment of these networks, resource-constrained mobile phones and mobility. In a dynamic or disruptive situation, such as a disaster, a fully mobile and decentralized infrastructure-less network seems to be a viable option for communication. In this chapter, applications of BN to vulnerability assessment and management of process vessels in the event of hurricanes are demonstrated and discussed. Bayesian network (BN) is a probabilistic technique for reasoning under uncertainty with a variety of applications is system safety, reliability engineering, and risk assessment. However, due to the uncertainties arising from interdependent failure modes and lack of accurate and sufficient historical data, most conventional quantitative risk assessment techniques deliver inaccurate results, which in turn lead to inaccurate risk assessment and thus ineffective or non-cost-effective risk management strategies. To assess and manage the vulnerability of process plants, failure modes and respective failure probabilities both before and after implementing safety measures should be assessed. Hurricanes are multi-hazard natural hazards that can cause severe damage to chemical and process plants via individual or combined impact of strong winds, torrential rainfall, floods, and hitting waves especially in coastal areas. These results can be used to inform and refine evidence-based interventions that improve the mental health and wellbeing of disaster-exposed youth. Findings suggest that a transdiagnostic intervention may be effective for addressing a range of emotional concerns in the aftermath of a natural disaster. In this naturalistic, community-based effectiveness study we found significant improvement on measures of anxiety, depression, symptom severity, and daily functioning. Older age was correlated with more depressive symptoms at baseline and superior functioning at baseline with fewer completed treatment sessions. Clinician ratings of functionality evidenced significant improvement over time. Anxiety and depressive symptoms and symptom severity declined significantly over the treatment period. Latent growth curve modeling was used to examine symptom change over time.Ĭhildren and adolescents began treatment with moderate levels of anxiety and depressive symptoms, symptom severity, and difficulties in daily functioning. Symptom severity and level of functioning were rated by the clinician. Youth-caregiver dyads completed measures of disaster exposure and impact at baseline as well as anxiety and depression at baseline and each therapy session. One hundred forty-nine youth aged 5 to 17 years with a history of hurricane exposure and emotional difficulties received an average of 6.4 (SD = 3.4) psychotherapy sessions using the Unified Protocols for Transdiagnostic Treatment of Emotional Disorders in Children and Adolescents. We examined the effectiveness of a transdiagnostic psychotherapeutic intervention delivered to youth with emotional disorders in a large, community health system following this hurricane. Hurricane Harvey struck southeast Texas in August 2017 resulting in widespread destruction and significant emotional distress.
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