Assessing Acceptability of COVID-19 Vaccine Booster Dose Among Adult Americans: A Cross-Sectional Study

Given the emergence of breakthrough infections, new variants, and concerns of waning immunity from the primary COVID-19 vaccines, booster shots emerged as a viable option to shore-up protection against COVID-19. Following the recent authorization of vaccine boosters among vulnerable Americans, this study aims to assess COVID-19 vaccine booster hesitancy and its associated factors in a nationally representative sample. A web-based 48-item psychometric valid survey was used to measure vaccine literacy, vaccine confidence, trust, and general attitudes towards vaccines. Data were analyzed through Chi-square (with a post hoc contingency table analysis) and independent-sample t-/Welch tests. Among 2138 participants, nearly 62% intended to take booster doses and the remaining were COVID-19 vaccine booster hesitant. The vaccine-booster-hesitant group was more likely to be unvaccinated (62.6% vs. 12.9%) and did not intend to have their children vaccinated (86.1% vs. 27.5%) compared to their non-hesitant counterparts. A significantly higher proportion of booster dose hesitant individuals had very little to no trust in the COVID-19 vaccine information given by public health/government agencies (55% vs. 12%) compared to non-hesitant ones. The mean scores of vaccine confidence index and vaccine literacy were lower among the hesitant group compared to the non-hesitant group. Compared to the non-hesitant group, vaccine hesitant participants were single or never married (41.8% vs. 28.7%), less educated, and living in a southern region of the nation (40.9% vs. 33.3%). These findings underscore the need of developing effective communication strategies emphasizing vaccine science in ways that are accessible to individuals with lower levels of education and vaccine literacy to increase vaccination uptake

Neural dysfunction during temporal discounting in paediatric Attention-Deficit/Hyperactivity Disorder and Obsessive-Compulsive Disorder

Both Attention-Deficit/Hyperactivity Disorder (ADHD) and Obsessive-Compulsive Disorder (OCD) are associated with choice impulsivity, i.e. the tendency to prefer smaller immediate rewards over larger delayed rewards. However, the extent to which this impulsivity is mediated by shared or distinct underlying neural mechanisms is unclear. Twenty-six boys with ADHD, 20 boys with OCD and 20 matched controls (aged 12–18) completed an fMRI version of an individually adjusted temporal discounting (TD) task which requires choosing between a variable amount of money now or £100 in one week, one month or one year. Activations to immediate and delayed reward choices were compared between groups using a three-way ANCOVA. ADHD patients had steeper discounting rates on the task relative to controls. OCD patients did not differ from controls or patients with ADHD. Patients with ADHD and OCD showed predominantly shared activation deficits during TD in fronto-striato-insular-cerebellar regions responsible for self-control and temporal foresight, suggesting that choice impulsivity is mediated by overlapping neural dysfunctions in both disorders. OCD patients alone showed dysfunction relative to controls in right orbitofrontal and rostrolateral prefrontal cortex, extending previous findings of abnormalities in these regions in OCD to the domain of choice impulsiveness

Adaptive digital twins for energy-intensive industries and their local communities

Digital Twins (DTs) are high-fidelity virtual models that behave-like, look-like and connect-to a physical system. In this work, the physical systems are operations and processes from energy-intensive industrial plants and their local communities. The creation of DTs demands expertise not just in engineering, but also in computer science, data science, and artificial intelligence. Here, we introduce the Adaptive Digital Twins (ADT) concept, anchored in five attributes inspired by the self-adaptive systems field from software engineering. These attributes are self-learning, self-optimizing, self-evolving, self-monitoring, and self-protection. This new approach merges cutting-edge computing with pragmatic engineering needs. ADTs can enhance decision-making in both the design phase and real-time operation of industrial facilities and allow for versatile 'what-if' scenario simulations. Seven applications within the energy-intensive industries are described where ADTs could be transformative