Since 2015, Canada and Norway have advanced sustainable blue economy (SBE) agendas through distinct policy pathways. This study provides a comparative assessment of their SBE trajectories using a harmonized key performance indicator (KPI)-based framework across four operational dimensions: blue economic growth, circular economy adoption, nature-based solutions (NBS), and carbon alignment. Drawing on a 20-indicator comparative grid aligned with SDGs, OECD guidance, and the EU Restore Our Ocean and Waters agenda, the study assesses progress between 2015 and 2025 using an indicative five-point scale. The results show that Norway performs more strongly in blue economic growth and maritime decarbonization, reflecting its mature ocean industries, integrated governance, and early green-shipping transition. Canada performs more strongly in NBS and shows substantial progress in circular economy governance, driven by rapid gains in marine protection, restoration, and plastics policy. The comparison reveals complementary strengths rather than a single model of SBE implementation: Canada offers lessons in collaborative conservation and restoration, while Norway provides a reference case for maritime industrial transition and low-emission shipping. The findings highlight the importance of institutional context, policy sequencing, and implementation capacity in shaping SBE outcomes, and identify transferable lessons for marine policy design, comparative benchmarking, and sustainable ocean governance beyond the two cases.
This study enhances macroeconometric modelling by utilising an I(2) cointegration framework to analyse the dynamic link between tourism prices and inflation in Slovenia and the Eurozone. Using monthly data from 2000 to 2017, we estimate cointegrated VAR models that capture long-run equilibria, short-run adjustments, and persistent deviations inherent in I(2) processes. The results reveal strong spillover effects from Slovenian tourism and input prices to Eurozone inflation and hospitality prices in the short run, while Eurozone-wide shocks dominate the long-run dynamics. By explicitly accounting for nonstationarity, structural breaks, and seasonal patterns, the I(2) model provides a more reliable framework than traditional I(1)-based approaches, which are often prone to misspecification when higher-order integration and persistent deviations are ignored. The findings contribute to macroeconometric theory by demonstrating the value of I(2) cointegration in modelling complex price systems and offer policy insights into inflation management and competitiveness in tourism-dependent economies.
Human parenting behaviors (HPBs)—including gaze, motherese, affectionate touch, and positive affect—are essential for child development and can be precisely measured during the first weeks of life (2–8 weeks) through microcoding of videotaped interactions. This study examined whether maternal exposure to adverse childhood experiences (ACEs) affects HPBs and whether postnatal depressive symptoms mediate this relationship. The sample included 272 mother–infant dyads from São Paulo, Brazil (mean maternal age: 27.2 ± 5.2 years, 67% with monthly income < US$317; infants: 48.5% female, mean age: 33 ± 19 days). Maternal ACEs and depressive symptoms were self-reported during pregnancy and postnatally, respectively. HPBs were assessed using the Coding Interactive Behavior (CIB) manual. Results showed that maternal ACEs were significantly associated with higher postnatal depressive symptoms (β = 0.665, p < 0.001), but neither a direct nor indirect association with HPBs was observed. These findings suggest that ACE-related disruptions in parenting may not manifest during the early weeks of life but could emerge later as caregiving demands increase. This study is among the few to use microcoded interaction analysis at this early stage of life and highlights the need for continued research into the complex pathways linking ACEs, maternal mental health, and parenting behaviors over time.
BACKGROUND AND AIMS:Symptoms of anxiety and depression are common in inflammatory bowel disease (IBD); the aim of this study was to assess the proportion of anxiety and depression in patients newly diagnosed with IBD, compare the rates with the Norwegian general population (NGP), and examine associations with selected sociodemographic, psychological, and disease-related factors. METHODS:This prospective cohort study included newly diagnosed patients with IBD, and data from the HUNT4 survey of the NGP. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale. Crude statistical comparisons were performed using t-tests, Mann-Whitney U test, chi-square tests, or Fisher's exact tests. Adjusted associations were modeled using multiple robust linear regression and multiple logistic regression. RESULTS:In total, 938/1562 (62.1%) patients with IBD completed the Hospital Anxiety and Depression Scale (Crohn's disease [CD]: n = 297, ulcerative colitis [UC]: n = 641). The proportion of anxiety was 37.4% in CD and 32.1% in UC, while depression was reported by 21.9% and 16.8%, respectively. Both rates were significantly higher than those observed in the NGP (17.5% for anxiety and 9.4% for depression). Compared with the NGP, males with CD had significantly higher levels of anxiety and depression, males with UC had elevated anxiety only, while females with CD and UC showed increased anxiety and depression. Both substantial fatigue and general self-efficacy were significantly associated with anxiety and depression in IBD. CONCLUSIONS:Newly diagnosed patients with IBD experienced significant psychological challenges compared with the NGP. Early identification of anxiety and depression may enable targeted interventions.
This paper investigates ultrasonic sensor technologies for autonomous navigation systems. It explores differential amplifier configurations, wireless beacon networks, and real-time signal processing techniques to enable accurate obstacle detection and person-following capabilities. A novel differential drive approach was implemented to enhance ultrasonic transmission power, while MEMS microphone technology provided cost-effective reception compared to traditional piezoelectric solutions. Wireless beacon positioning was integrated using ESP32 microcontrollers and XBee communication protocols to enable distributed sensing networks. Experimental validation demonstrated effective range performance with direct transmission reaching 9 meters and obstacle detection at 2 meters using Time of Flight calculations. Environment mapping algorithms achieved 0.5-meter spatial resolution for navigation applications. The research contributes fundamental design principles for ultrasonic navigation systems, demonstrating feasibility while identifying critical integration constraints. Results provide valuable insights for developing practical autonomous navigation solutions in robotics, smart mobility, and assistive technology applications.
