How soft are neurological soft signs? Content overlap analysis of 71 symptoms among seven most commonly used neurological soft signs scales

Objective: Increased risk for certain psychiatric disorders has been associated with season of birth. This study was undertaken to look for hypothesized season-of-birth effects for dyslexia, schizophrenia spectrum disorders, and neurological soft signs in children and adolescents. Method: Month of birth and the diagnostic findings in question were examined based on charts from a clinic population of 585 boys. Odds ratios and etiological fractions were calculated. Results: Neurological soft signs showed a sporadic peak for June births and schizophrenia spectrum showed a peak for August and November. A smooth curve suggesting true seasonality was evident in dyslexia for births in May, June, and July. For different 5-year birth cohorts, early summer birth accounts for 24 to 71% of cases of dyslexia. Conclusions: The authors suggest that viral infection, especially influenza, during the second trimester of pregnancy is the most attractive hypothesis to explain these findings. If this hypothesis is supported, immunization in women of child-bearing age could reduce the incidence of dyslexia. Secondary prevention could also be enhanced by early identification and treatment of children who were exposed in utero.

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Understory biomass estimation based on Structure from Motion data by Multi-layered forest drone survey

10.5194/egusphere-egu21-14670 ◽

2021 ◽

Author(s):

Yupan Zhang ◽

Yuichi Onda ◽

Hiroaki Kato ◽

Xinchao Sun ◽

Takashi Gomi

Keyword(s):

Structure From Motion ◽

Forest Structure ◽

Large Scale ◽

Forest Canopy ◽

Point Clouds ◽

Understory Vegetation ◽

Biomass Estimation ◽

Canopy Openness ◽

Cubic Model ◽

Overlap Analysis

Understory vegetation is an important part of evapotranspiration from forest floor. Forest management changes the forest structure and then affects the understory vegetation biomass (UVB). Quantitative measurement and estimation of&#160; UVB is a step cannot be ignored in the study of forest ecology and forest evapotranspiration. However, large-scale biomass measurement and estimation is challenging. In this study, Structure from Motion (SfM) was adopted simultaneously at two different layers in a plantation forest made by Japanese cedar and Japanese cypress to reconstruct forest structure from understory to above canopy: i) understory drone survey in a 1.1h sub-catchment to generate canopy height model (CHM) based on dense point clouds data derived from a manual low-flying drone under the canopy; ii) Above-canopy drone survey in whole catchment (33.2 ha) to compute canopy openness data based on point clouds of canopy derived from an autonomous flying drone above the canopy. Combined with actual biomass data from field harvesting to develop regression models between the CHM and UVB, which was then used to map spatial distribution of&#160; UVB in sub-catchment. The relationship between UVB and canopy openness data was then developed by overlap analysis. This approach yielded high resolution understory over catchment scale with a point cloud density of more than 20 points/cm2. Strong coefficients of determination (R-squared = 0.75) of the cubic model supported prediction of UVB from CHM, the average UVB was 0.82kg/m2 and dominated by low ferns. The corresponding forest canopy openness in this area was 42.48% on average. Overlap analysis show no significant interactions between them in a cubic model with weak predictive power (R-squared < 0.46). Overall, we reconstructed the multi-layered structure of the forest and provided models of UVB. Understory survey has high accuracy for biomass measurement, but it&#8217;s inherently difficult to estimate UVB only based on canopy openness result.

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