Interactive 3D Modeling with a Generative Adversarial Network

This paper proposes the idea of using a generative adversarial network (GAN) to assist a novice user in designing real-world shapes with a simple interface. The user edits a voxel grid with a painting interface (like Minecraft). Yet, at any time, he/she can execute a SNAP command, which projects the current voxel grid onto a latent shape manifold with a learned projection operator and then generates a similar, but more realistic, shape using a learned generator network. Then the user can edit the resulting shape and snap again until he/she is satisfied with the result. The main advantage of this approach is that the projection and generation operators assist novice users to create 3D models characteristic of a background distribution of object shapes, but without having to specify all the details. The core new research idea is to use a GAN to support this application. 3D GANs have previously been used for shape generation, interpolation, and completion, but never for interactive modeling. The new challenge for this application is to learn a projection operator that takes an arbitrary 3D voxel model and produces a latent vector on the shape manifold from which a similar and realistic shape can be generated. We develop algorithms for this and other steps of the SNAP processing pipeline and integrate them into a simple modeling tool. Experiments with these algorithms and tool suggest that GANs provide a promising approach to computer-assisted interactive modeling.Comment: Published at International Conference on 3D Vision 2017 (http://irc.cs.sdu.edu.cn/3dv/index.html

Biocompatible parylene neurocages developing a robust method for live neural network studies

We present a refined method and design for fabricating parylene neurocages for in vitro studies of live neural networks. Parylene neurocages are biocompatible and very robust, making them ideally suited for studying the synaptic connections netween individual neurons to gain insight into learning and memory. The neurocage fabrication process is significantly less complex than earlier versions. Previous neurocage designs achieved limited neuronal outgrowth; however, the long-term cell survival rate was 50%

Development of biocompatible parylene neurocages

We present a refined method and design for building parylene neurocages for in vitro studies of live neural networks. Parylene neurocages are biocompatible and very robust, making them ideally suited for studying the synaptic connections between individual neurons to gain insight into learning and memory. The neurocage fabrication process is significantly less complex than earlier versions. Previous neurocage designs achieved limited neuronal outgrowth; however, the long-term cell survival rate was 50%

Quantum phase transitional patterns in the SD-pair shell model

Patterns of shape-phase transition in the proton-neutron coupled systems are studied within the $SD$-pair shell model. The results show that some transitional patterns in the $SD$-pair shell model are similar to the $U(5)-SU(3)$, $U(5)-SO(6)$ transitions with signatures of the critical point symmetry of the interacting boson model.Comment: 13 pages, 7 figure

Antenatal Depressive Symptoms and Antidepressant Use in Pregnancy

Review of the current literature reveals inconsistent findings on potential associations between antidepressant use during pregnancy and adverse fetal and child health and development. This study aims to examine the effect of antenatal SSRI exposure on several neonatal (preterm birth, small- and large-for-gestational age, Apgar score, and neonatal intensive care unit admission) and child developmental outcomes (measured by Ages and Stages Questionnaire) while controlling for confounding by indication. Data were obtained from the Prenatal Health Project, a longitudinal cohort study of 2,357 women in London, Ontario. Results from univariable analysis discovered that infants exposed to in utero SSRIs were more likely to be large-for-gestational age compared to infants of women exposed to antenatal depressive symptoms but not SSRIs and to infants of women unexposed to either antenatal depression or SSRIs. The small sample size of the antidepressant-exposed population limited our study and further research is warranted to verify the significance of our findings

Multiple sensor theory in cardiovascular mechanosensory units

Multiple sensor theory (MST) has advanced our understanding of how lung mechanosensors operate. That is, single lung units contain multiple homogeneous or heterogeneous sensors. Each detects sensor-specific mechanical information and interacts with other sensors lying within the unit sending integrated information to the brain to evoke reflexes. MST explains numerous controversial issues in the respiratory system. Recent studies in baroreceptors (BRs), along with reinterpretation of recordings appearing in the literature, indicate MST also operates in the cardiovascular (CV) system. This review outlines evidence supporting MST in the CV system and provides examples to apply the theory. Longstanding controversies surrounding the CV sensors are also considered