Buildings and terrain unified – multidimensional dual data structure for GIS

© 2016 Wuhan University. 3D city models are widely used in many disciplines and applications, such as urban planning, disaster management, and environmental simulation. Usually, the terrain and embedded objects like buildings are taken into consideration. A consistent model integrating these elements is vital for GIS analysis, especially if the geometry is accompanied by the topological relations between neighboring objects. Such a model allows for more efficient and errorless analysis. The memory consumption is another crucial aspect when the wide area of a city is considered – light models are highly desirable. Three methods of the terrain representation using the geometrical–topological data structure – the dual half-edge – are proposed in this article. The integration of buildings and other structures like bridges with the terrain is also presented

An automated 3D modeling of topological indoor navigation network

© 2015, Springer Science+Business Media Dordrecht. Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future

White Matter Hyperintensity Volume and Location: Associations with WM Microstructure, Brain Iron, and Cerebral Perfusion

Cerebral white matter hyperintensities (WMHs) represent macrostructural brain damage associated with various etiologies. However, the relative contributions of various etiologies to WMH volume, as assessed via different neuroimaging measures, is not well-understood. Here, we explored associations between three potential early markers of white matter hyperintensity volume. Specifically, the unique variance in total and regional WMH volumes accounted for by white matter microstructure, brain iron concentration and cerebral blood flow (CBF) was assessed. Regional volumes explored were periventricular and deep regions. Eighty healthy older adults (ages 60–86) were scanned at 3 Tesla MRI using fluid-attenuated inversion recovery, diffusion tensor imaging (DTI), multi-echo gradient-recalled echo and pseudo-continuous arterial spin labeling sequences. In a stepwise regression model, DTI-based radial diffusivity accounted for significant variance in total WMH volume (adjusted R2 change = 0.136). In contrast, iron concentration (adjusted R2 change = 0.043) and CBF (adjusted R2 change = 0.027) made more modest improvements to the variance accounted for in total WMH volume. However, there was an interaction between iron concentration and location on WMH volume such that iron concentration predicted deep (p = 0.034) but not periventricular (p = 0.414) WMH volume. Our results suggest that WM microstructure may be a better predictor of WMH volume than either brain iron or CBF but also draws attention to the possibility that some early WMH markers may be location-specific

Normative Evidence Accumulation in Unpredictable Environments

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals

Molecular basis of interactions between CaMKII and α-actinin-2 that underlie dendritic spine enlargement

Ca2+/calmodulin-dependent protein kinase II (CaMKII) is essential for long-term potentiation (LTP) of excitatory synapses that is linked to learning and memory. In this study, we focused on understanding how interactions between CaMKIIα and the actin crosslinking protein α-actinin-2 underlie long-lasting changes in dendritic spine architecture. We found that association of the two proteins was unexpectedly elevated within two minutes of NMDA receptor stimulation that triggers structural LTP in primary hippocampal neurons. Furthermore, disruption of interactions between the two proteins prevented the accumulation of enlarged mushroom-type dendritic spines following NMDA receptor activation. α-actinin-2 binds to the regulatory segment of CaMKII. Calorimetry experiments, and a crystal structure of α-actinin-2 EF hands 3 and 4 in complex with the CaMKII regulatory segment, indicate that the regulatory segment of autoinhibited CaMKII is not fully accessible to α-actinin-2. Pull-down experiments show that occupation of the CaMKII substrate binding groove by GluN2B markedly increases α-actinin-2 access to the CaMKII regulatory segment. Furthermore, in situ labelling experiments are consistent with the notion that recruitment of CaMKII to NMDA receptors contributes to elevated interactions between the kinase and α-actinin-2 during structural LTP. Overall, our study provides new mechanistic insight into the molecular basis of structural LTP and reveals an added layer of sophistication to the function of CaMKII

Distinct Patterns of Default Mode and Executive Control Network Circuitry Contribute to Present and Future Executive Function in Older Adults

Executive function (EF) performance in older adults has been linked with functional and structural profiles within the executive control network (ECN) and default mode network (DMN), white matter hyperintensities (WMH) burden and levels of Alzheimer\u27s disease (AD) pathology. Here, we simultaneously explored the unique contributions of these factors to baseline and longitudinal EF performance in older adults. Thirty-two cognitively normal (CN) older adults underwent neuropsychological testing at baseline and annually for three years. Neuroimaging and AD pathology measures were collected at baseline. Separate linear regression models were used to determine which of these variables predicted composite EF scores at baseline and/or average annual change in composite ΔEF scores over the three-year follow-up period. Results demonstrated that low DMN deactivation, high ECN activation and WMH burden were the main predictors of EF scores at baseline. In contrast, poor DMN and ECN WM microstructure and higher AD pathology predicted greater annual decline in EF scores. Subsequent mediation analysis demonstrated that DMN WM microstructure uniquely mediated the relationship between AD pathology and ΔEF. These results suggest that functional activation patterns within the DMN and ECN and WMHs contribute to baseline EF while structural connectivity within these networks impact longitudinal EF performance in older adults

From aptamer-based biomarker discovery to diagnostic and clinical applications: an aptamer-based, streamlined multiplex proteomic assay

Recently, we reported an aptamer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community