A better understanding of the transition from child to adult community mental health services is important given the high rates of service drop-out. Conducting longitudinal research is challenging during a major service provider change. Developmentally-typical transition-to-adulthood instability can deter study engagement. This study examines the efficacy of creative technology-based strategies to recruit and engage adolescents and young adults (AYA) with serious mental health diagnoses in a qualitative study during their transition from child to adult services. Participants were recruited from one agency to complete three in-depth qualitative interviews and monthly surveys exploring mental health service experiences over 12-months. Participants received a smartphone and data plan for 6-months at initial interview, $50 at 6-month interview and $55 at 12-month interview. Four research assistants used a shared Google Voice account to text monthly online surveys and to communicate with participants. 19 participants enrolled; 74% remained enrolled across the 12-months. Smartphones and data plans were not effective in recruiting nor sustaining study engagement for most participants. Participants preferred a mix of texting and phone calls to prompt study engagement; 60% of online surveys were completed. Unanticipated participant-researcher communication outside of research scope suggests that the formation of strong relationships and additional support during this transitional time is critical for sustained study engagement. Study findings have practical implications for social work longitudinal research design and effective study implementation. Future social work research is warranted on innovative strategies to boost study and service engagement among AYA with serious co-occurring mental health and developmental instability.During the COVID-19 pandemic, exposure to particles exhaled by infected passengers in commercial aircraft cabins has been a great concern. Currently, aircraft cabins adopt mixing ventilation. However, complete mixing may not be achieved, and thus the particle concentration in the respiratory zone may vary from seat to seat in a cabin. To evaluate the particle exposure in a typical single-aisle aircraft cabin, this investigation constructed an aircraft cabin mockup for experimental tests. Particles were released from a single source or dual sources at different seats to represent particles exhaled by infected passengers. The particle concentrations in the respiratory zones at various seats were measured and compared. The particle exposure was evaluated in both a cross section and a longitudinal section. Leaving the middle seat vacant to reduce particle exposure was also addressed. In addition, the velocity fields and air temperatures were measured to provide a better understanding of particle transport. It was found that the particle exposure at the window seat is always the lowest, regardless of the particle release locations. If the passenger seated in the middle does not release particles, his/her presence enhances the particle dispersion and thereby reduces the particle exposure for adjacent passengers. In the cabin mockup, the released particles can be transported across at least four rows of seats in the longitudinal direction.This study aims to examine the issue of cryptocurrency volatility modelling and forecasting based on high-frequency data. More specifically, this study assesses whether crisis periods, particularly the coronavirus disease pandemic, influence the dynamic of cryptocurrency volatility. We investigate the four main cryptocurrency markets (Bitcoin, Ethereum Classic, Ethereum, and Ripple) from April 2018 to June 2020. The realized volatility measure is computed and decomposed to various components (continuous versus discontinuous, positive and negative semi-variances, and signed jumps). https://www.selleckchem.com/products/GDC-0879.html A variety of heterogeneous autoregressive (HAR) models are developed including these components, thereby enabling assessment of different assumptions (including persistence and asymmetric dynamic) of modelling and volatility forecasting based on in-sample and out-of-sample forecasting strategies, respectively. Our results reveal three main findings. First, the extended HAR model that includes the positive and negative jumps appears to be the best model for predicting future volatility for both crisis and non-crisis periods. Second, during the crisis period, only the negative jump component is statistically significant. Third, in terms of volatility forecasting, the results show that the extended HAR model that includes positive and negative semi-variances outperform the other models.Climate change-driven health impacts are serious, widespread, and costly. Importantly, such damages are largely absent from policy debates around the costs of delay and inaction on this crisis. While climate change is a global problem, its impacts are localized and personal, and there is growing demand for specific information on how climate change affects human health in different places. Existing research indicates that climate-fueled health problems are growing, and that investments in reducing carbon pollution and improving community resilience could help to avoid tens to hundreds of billions of dollars in climate-sensitive health impacts across the USA each year, including those stemming from extreme heat, air pollution, hurricanes, and wildfires. Science that explores the underappreciated local health impacts and health-related costs of climate change can enhance advocacy by demonstrating the need to both address the root causes of climate change and enhance climate resilience in vulnerable communities. The climate crisis has historically been predominantly conceived as a global environmental challenge; examination of climate impacts on public health enables researchers to localize this urgent problem for members of the public and policymakers. In turn, approaches to climate science that focus on health can make dangerous climate impacts and the need for cost-effective solutions more salient and tangible.Colorectal cancer (CRC) requires massive iron stores, but the complete mechanisms by which CRC modulates local iron handling are poorly understood. Here, we demonstrate that hepcidin is activated ectopically in CRC. Mice deficient in hepcidin specifically in the colon tumour epithelium, compared with wild-type littermates, exhibit significantly diminished tumour number, burden and size in a sporadic model of CRC, whereas accumulation of intracellular iron by deletion of the iron exporter ferroportin exacerbates these tumour parameters. Metabolomic analysis of three-dimensional patient-derived CRC tumour enteroids indicates a prioritization of iron in CRC for the production of nucleotides, which is recapitulated in our hepcidin/ferroportin mouse CRC models. Mechanistically, our data suggest that iron chelation decreases mitochondrial function, thereby altering nucleotide synthesis, whereas exogenous supplementation of nucleosides or aspartate partially rescues tumour growth in patient-derived enteroids and CRC cell lines in the presence of an iron chelator.