Considerable work indicates that early cumulative risk exposure is aversive to human development, but very little research has examined neurological underpinnings of these robust findings. We investigated amygdala volume and reactivity to facial stimuli among adults (M = 23.7 years, n = 54) as a function of cumulative risk exposure during childhood (ages 9 and 13). In addition, we tested whether expected, cumulative risk elevations in amygdala volume would mediate functional reactivity of the amygdala during socio-emotional processing. Risks included substandard housing quality, noise, crowding, family turmoil, child separation from family, and violence. Total and left hemisphere adult amygdala volumes, respectively were positively related to cumulative risk exposure during childhood. The links between childhood cumulative risk exposure and elevated amygdala responses to emotionally neutral facial stimuli in adulthood were mediated by the respective amygdala volumes. Cumulative risk exposure in later adolescence (17 years), however, was unrelated to subsequent, adult amygdala volume or function. Physical and socioemotional risk exposures early in life appear to alter amygdala development, rendering adults more reactive to ambiguous stimuli such as neutral faces. These stress-related differences in childhood amygdala development might contribute to well-documented psychological distress as a function of early risk exposure.

In a motor vehicle collision (MVC), survivors often receive mild traumatic brain injuries (mTBI). Although there have been some reports of early white matter changes after an mTBI, much less is known about early cortical structural changes. To investigate early cortical changes within a few days after an MVC, we compared cortical thickness of mTBI survivors with nonmTBI survivors, then reexamined cortical thickness in the same survivors 3 months later. MVC survivors were categorized as mTBI or non-mTBI based on concussive symptoms documented in emergency departments (EDs). Cortical thickness was measured from MRI images using FreeSurfer within a few days and again at 3 months after MVC. Post-traumatic stress symptoms and physical conditions were also assessed. Compared with the non-mTBI group (n = 23), the mTBI group (n = 21) had thicker cortex in the left rostral middle frontal (rMFG) and right precuneus gyri, but thinner cortex in the left posterior middle temporal gyrus at 7.2 -3.1 days after MVC. After 3 months, cortical thickness had decreased in left rMFG in the mTBI group but not in the non-mTBI group. The cortical thickness of the right precuneus region in the initial scans was positively correlated with acute traumatic stress symptoms for all survivors and with the number of reduced activity days for mTBI survivors who completed the follow-up. The preliminary results suggest that alterations in cortical thickness may occur at an early stage of mTBI and that frontal cortex structure may change dynamically over the initial 3 months after mTBI.

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.

This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries. This study also finds causal association between energy growth and nexus of CO2 emissions, and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1972 to 2017. The data set has been collected from the world development indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worsen the quality environment in the south Asian region. The individual country as Bangladesh shows a positively significant impact on the CO2 emissions and destroying the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth level (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use.

I. (2021). Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup megaanalysis. Molecular Psychiatry,26,[4331][4332][4333][4334][4335][4336][4337][4338][4339][4340][4341][4342][4343]

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Background Smaller hippocampal volume is associated with more severe posttraumatic stress disorder (PTSD) symptoms years after traumatic experiences. Posttraumatic stress symptoms appear early following trauma, but the relationship between hippocampal volume and PTSD symptom severity during early post-trauma periods is not well understood. It is possible that the inverse relationship between hippocampal volume and PTSD symptom severity is already present soon after trauma. To test this possibility we prospectively examined the association between hippocampal volumes and severity of PTSD symptoms within weeks to months after trauma due to motor vehicle collision (MVC). Methods Structural MRI scans of 44 survivors were collected about 2 weeks and again at 3 months after MVC to measure hippocampal volumes. The PTSD checklist (PCL) was used to evaluate PTSD symptoms at each scan time. Full (n=5) or partial (n=6) PTSD was evaluated using CAPS at 3 months. Results Left hippocampal volumes at both time points negatively correlated with PCL scores, and with subscores for re-experiencing symptoms at 3 months. Left hippocampal volumes at 3 months also negatively correlated with hyperarousal symptoms at 3 months. Finally, neither left nor right hippocampal volumes significantly changed between 2 weeks and 3 months post trauma. Conclusions The results suggest that small hippocampal volume at early post-trauma weeks is associated with increased risk for PTSD development. Furthermore, the inverse relationship between hippocampal volume and PTSD symptoms at 3 months did not arise from post-trauma shifts in hippocampal volume between 2 weeks and 3 months after trauma.