ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan of a scene as input and predicting a complete 3D model along with per-voxel semantic labels. The key contribution of our method is its ability to handle large scenes with varying spatial extent, managing the cubic growth in data size as scene size increases. To this end, we devise a fully-convolutional generative 3D CNN model whose filter kernels are invariant to the overall scene size. The model can be trained on scene subvolumes but deployed on arbitrarily large scenes at test time. In addition, we propose a coarse-to-fine inference strategy in order to produce high-resolution output while also leveraging large input context sizes. In an extensive series of experiments, we carefully evaluate different model design choices, considering both deterministic and probabilistic models for completion and semantic inference. Our results show that we outperform other methods not only in the size of the environments handled and processing efficiency, but also with regard to completion quality and semantic segmentation performance by a significant margin.Comment: Video: https://youtu.be/5s5s8iH0NF

Generation and analysis of networks with a prescribed degree sequence and subgraph family: higher-order structure matters

Designing algorithms that generate networks with a given degree sequence while varying both subgraph composition and distribution of subgraphs around nodes is an important but challenging research problem. Current algorithms lack control of key network parameters, the ability to specify to what subgraphs a node belongs to, come at a considerable complexity cost or, critically and sample from a limited ensemble of networks. To enable controlled investigations of the impact and role of subgraphs, especially for epidemics, neuronal activity or complex contagion, it is essential that the generation process be versatile and the generated networks as diverse as possible. In this article, we present two new network generation algorithms that use subgraphs as building blocks to construct networks preserving a given degree sequence. Additionally, these algorithms provide control over clustering both at node and global level. In both cases, we show that, despite being constrained by a degree sequence and global clustering, generated networks have markedly different topologies as evidenced by both subgraph prevalence and distribution around nodes, and large-scale network structure metrics such as path length and betweenness measures. Simulations of standard epidemic and complex contagion models on those networks reveal that degree distribution and global clustering do not always accurately predict the outcome of dynamical processes taking place on them. We conclude by discussing the benefits and limitations of both methods

Modeling superimposed preeclampsia using Ang II (Angiotensin II) infusion in pregnant stroke-prone spontaneously hypertensive rats

Hypertensive disorders of pregnancy are the second leading cause of maternal deaths worldwide. Superimposed preeclampsia is an increasingly common problem and often associated with impaired placental perfusion. Understanding the underlying mechanisms and developing treatment options are crucial. The pregnant stroke-prone spontaneously hypertensive rat has impaired uteroplacental blood flow and abnormal uterine artery remodeling. We used Ang II (angiotensin II) infusion in pregnant stroke-prone spontaneously hypertensive rats to mimic the increased cardiovascular stress associated with superimposed preeclampsia and examine the impact on the maternal cardiovascular system and fetal development. Continuous infusion of Ang II at 500 or 1000 ng/kg per minute was administered from gestational day 10.5 until term. Radiotelemetry and echocardiography were used to monitor hemodynamic and cardiovascular changes, and urine was collected prepregnancy and throughout gestation. Uterine artery myography assessed uteroplacental vascular function and structure. Fetal measurements were made at gestational day 18.5, and placentas were collected for histological and gene expression analyses. The 1000 ng/kg per minute Ang II treatment significantly increased blood pressure (P<0.01), reduced cardiac output (P<0.05), and reduced diameter and increased stiffness of the uterine arteries (P<0.01) during pregnancy. The albumin:creatinine ratio was increased in both Ang II treatment groups (P<0.05; P<0.0001). The 1000 ng/kg per minute–treated fetuses were significantly smaller than vehicle treatment (P<0.001). Placental expression of Ang II receptors was increased in the junctional zone in 1000 ng/kg per minute Ang II–treated groups (P<0.05), with this zone showing depletion of glycogen content and structural abnormalities. Ang II infusion in pregnant stroke-prone spontaneously hypertensive rats mirrors hemodynamic, cardiac, and urinary profiles observed in preeclamptic women, with evidence of impaired fetal growth

Ordering our world: the quest for traces of temporal organization in autobiographical memory

An experiment examined the idea, derived from the Self Memory System model (Conway & Pleydell-Pearce, 2000), that autobiographical events are sometimes tagged in memory with labels reflecting the life era in which an event occurred. The presence of such labels should affect the ease of judgments of the order in which life events occurred. Accordingly, 39 participants judged the order of two autobiographical events. Latency data consistently showed that between-era judgments were faster than within-era judgments, when the eras were defined in terms of either: (a) college versus high school, (b) academic quarter within year, or (c) academic year within school. The accuracy data similarly supported the presence of a between-era judgment effect for the college versus high school dichotomy

Thickness dependence of electron-electron interactions in topological p-n junctions

Electron-electron interactions in topological p-n junctions consisting of vertically stacked topological insulators are investigated. n-type Bi2Te3 and p-type Sb2Te3 of varying relative thicknesses are deposited using molecular beam epitaxy and their electronic properties measured using low-temperature transport. The screening factor is observed to decrease with increasing sample thickness, a finding which is corroborated by semi-classical Boltzmann theory. The number of two-dimensional states determined from electron-electron interactions is larger compared to the number obtained from weak-antilocalization, in line with earlier experiments using single layers.Comment: 38 pages, 5 figures, 1 tabl

Higher-order structure in networks: construction and its impact on dynamics

Networks are often characterised in terms of their degree distribution and global clustering coefficient. It is assumed that these provide a sufficient parametrisation of networks. However, since the global clustering coefficient is only sensitive to the total number of triangles found in the network, it is evident that two networks could have the same number of triangles but significantly different higher-order structure, i.e., the topologies that result from the placement of closed subgraphs around nodes. The two main objectives of my work are: (1) developing network generating algorithms and network based epidemic models with controllable higher-order structure and (2) investigating the impact of higher-order structure on dynamics on networks. This thesis is based on three papers, corresponding to Chapters. 3, 4 and 5. Chapter 3 presents a novel higher-order structure based network generating algorithm and subgraph counting algorithm. Chapter. 4, generalises a previously proposed ODE model that accurately captures the time evolution of the susceptible-infected-recovered (SIR) dynamics on networks constructed using arbitrary subgraphs. Chapter. 5, improves, extends and generalises the network generating algorithms proposed in the previous two papers. All three chapters demonstrate that for a fixed degree distribution and global clustering, diverse higher-order structure is still possible and that this structure will impact significantly on dynamics unfolding on networks. Hence, we suggest that higher-order structure should receive more attention when analysing network-based systems and dynamics

To Disclose or Not to Disclose: The Dilemma of the School Counselor

Symposiuim on Education La