Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)

The Internal and External Factors That Determined Private Investment in Ecuador 2007–2020

This article studies how electoral processes and internal factors of the Ecuadorian economy affect the dynamics of the country’s business expectations. The hypothesis that the free market and socialist political models in an economy generate different reactions in the expectations of the agents, according to the prevailing macroeconomic context, is tested. The empirical analysis is based on time series tools on quarterly data between 2006 and 2021. The results show that the dynamics of investment adjustment to the relationships of internal factors, electoral processes, and other variables explain 84% of this behavior. This is more accelerated in political contexts that promote the free market and maintain social, political, and economic stability, showing an overreaction of agents to negative economic news following the loss-aversion hypothesis

Engagement of the e-commerce industry in the US, according to Twitter in the period of the COVID-19 pandemic

E-commerce and the use of social media, particularly Twitter, both grew rapidly during the COVID-19 period. Companies may significantly benefit from social media management, which highlights the significance of responsible consumerism highlighted in SDG 12. This study analyzed the relationship of the level of engagement of leading US e-commerce companies according to their position in the financial market through the use of Twitter. The methodology was a quantitative and longitudinal approach, analyzing statistically (through statistical analysis to descriptive statistics, multiple and simple regressions). The 22,400 tweets during 2020, to estimate their engagement. The results showed that the level of engagement on Twitter is not directly related to the financial ranking, neither to its sales nor to the share price. The main contribution lies in the contribution to the literature, to guide academics, managers and CEOs of companies in efficient decision-making in their business strategies in the areas of marketing with the use of Twitter, where companies can boost loyalty, engagement and sales of their users

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)