Territorial behaviour is an important part of the lives of many animals. Once a territory has been acquired, an animal may spend its entire life on it, and may have to repeatedly defend it from conspecifics. Some species make great investments in the defence of a territory, and this defence can be costly, in terms of time, energy and risk of injury. Time costs in particular have rarely been explicitly factored into such models. In this paper we consider a model of territorial defence which includes both population dynamic and time delay elements, building upon recent advances in time constraint models. Populations may divide into two distinct types, where one type makes no effort to control territories. We shall call this type nomads, and the other type territorials. Here the territory owners must divide their time between patrolling and foraging, and this balance is their only strategic decision. We show how to find the evolutionarily stable patrolling strategy and the population composition of territorials and nomads, and consider some examples demonstrating key situations. We see that both time constraints and population density pressure are crucial to influencing behaviour. In particular we find cases with both territorial individuals and nomads where a mixed, either pure or both pure patrolling strategies are evolutionarily stable. In different conditions either nomads or territorials can be absent, and indeed for a significant range of parameter combinations the population can exhibit tristability, with three distinct ecologically stable population compositions with both nomads and territorials, only nomads or only territorials. A plausible biocontrol strategy for the eradication of invasive species involves augmenting wild populations with genetically modified supermales. Supermales contain double YY chromosomes. When they are augmented into a wild population, destabilization and eventual extinction occurs over time due to a strongly skewed gender ratio towards males. Here, we employ a mathematical model that considers an Allee effect, but we have discovered through simulation that the presence of supermales leads to an increase in the minimal number of females needed for survival at a value higher than the mathematically defined Allee effect. Using this effect, we focus our research on exploring the sensitivity of the optimized supply rate of supermale fish to the initial gender ratio and density of the wild populations. We find that the eradication strategy with optimized supply rate of supermales can be determined with knowledge of reproductive rate and survival fitness of supermale fish. We report the case of an 88-year-old man with coronavirus disease 2019 (COVID-19) who presented with ARDS and septic shock. The patient had exquisite BP sensitivity to low-dose angiotensin II (Ang-2), allowing for rapid liberation from high-dose vasopressors. We hypothesize that sensitivity to Ang-2 might be related to biological effect of severe acute respiratory syndrome coronavirus 2 infection. The case is suggestive of a potential role for synthetic Ang-2 for patients with COVID-19 and septic shock. Further studies are needed to confirm our observed clinical efficacy. BACKGROUND The risks from potential exposure to COVID-19, and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. We developed consensus statements to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. METHODS An expert panel of 24 members, including pulmonologists (17), thoracic radiologists (5), and thoracic surgeons (2) was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss then vote on statements related to 12 common clinical scenarios. A pre-defined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influeated factors that should be considered when applying these statements to individual patient care. BACKGROUND Prior to developing a successful eHealth intervention, it is important that we explore stakeholders' capacity to adapt to eHealth. OBJECTIVE To explore what factors influence the use eHealth services from the perspectives of families of children with hearing loss and professionals who support families as they transition into early intervention. METHODS A qualitative study incorporating semi-structured in-depth interviews was conducted with families (n = 17) and professionals (n = 11). Interview topic guides were developed based on the COM-B model of behaviour change to explore barriers and facilitators related to capability, opportunity, and motivation. RESULTS The COM-B model captured several factors that may influence the use eHealth interventions for families of children with hearing loss. The capability factors included computer literacy and familiarity with social media. The opportunity factors were access to online resources, reliable Internet, and affordable equipment. Professionals' and families' preferences and a culture of face-to-face services were also identified as barriers for using eHealth. The motivation factors included families' and professionals' confidence in using technology and beliefs that there were benefits (e.g., saving travel) associated with using eHealth services. https://www.selleckchem.com/peptide/box5.html In contrast, beliefs that eHealth may be difficult to set up and not able to replace in-person communication identified as barriers to families and professionals adopting eHealth interventions. CONCLUSION Findings of this study indicated that implementation of an eHealth intervention could be facilitated by addressing the barriers in stakeholders' capabilities, opportunities (e.g., equipment and social support), and motivation (e.g., negative beliefs about eHealth) before developing eHealth services.