Progressive Neural Networks

Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding catastrophic forgetting--remains a key obstacle to achieving human-level intelligence. The progressive networks approach represents a step forward in this direction: they are immune to forgetting and can leverage prior knowledge via lateral connections to previously learned features. We evaluate this architecture extensively on a wide variety of reinforcement learning tasks (Atari and 3D maze games), and show that it outperforms common baselines based on pretraining and finetuning. Using a novel sensitivity measure, we demonstrate that transfer occurs at both low-level sensory and high-level control layers of the learned policy

Towards a high-resolution 3D-analysis of sand-bank architecture on the Belgian Continental Shelf (RESOURCE-3D): Final report

Revealing the internal structure of sand banks by means of high-resolution seismic (acoustic) methods remains one of the classic methodological challenges in shallow marine geophysical prospection. This is mostly due to the strong heterogeneity of the sand-bank body in combination with complex sea-floor morphology. This study has focussed on the optimisation of a methodological-technological approach through a comparison of various state-of-the-art high-resolution seismic source/receiver configurations for the investigation of the internal architecture of sand banks. On the basis of a dense network of seismic profiles, the 3D architecture of a test site on the Belgian Continental Shelf was studied in detail. Digital acquisition of the data enabled postacquisition processing and data enhancement. Specialised software was used to identify, trace and map the structuring sediment bodies. To translate the “acoustic information” in a most unbiased way, in terms of its lithological and sedimentological nature, UGent-RCMG’s knowledge database and available background information on the Quaternary geology of the Belgian part of the North Sea has been used intensively. Finally, the interpreted seismic data were integrated with other datasets, such as multibeam bathymetry. This enabled a highresolution 3D quantitative analysis and representation of the sand-bank architecture and its economical potential. After comparison of the acquired test data sets, a set of recommendations is formulated regarding the most optimal strategy for future 4D prospecting of marine aggregates on the Belgian Continental Shelf

A new dimension in documenting new species:high-detail imaging for myriapod taxonomy and first 3D cybertype of a new millipede species (Diplopoda, Julida, Julidae)

We review the state-of-the-art approaches currently applied in myriapod taxonomy, and we describe, for the first time, a new species of millipede (Ommatoiulus avatar n. sp., family Julidae) using high-resolution X-ray microtomography (microCT) as a substantive adjunct to traditional morphological examination. We present 3D models of the holotype and paratype specimens and discuss the potential of this non-destructive technique in documenting new species of millipedes and other organisms. The microCT data have been uploaded to an open repository (Dryad) to serve as the first actual millipede cybertypes to be published

ImageNet Large Scale Visual Recognition Challenge

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The challenge has been run annually from 2010 to present, attracting participation from more than fifty institutions. This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field of large-scale image classification and object detection, and compare the state-of-the-art computer vision accuracy with human accuracy. We conclude with lessons learned in the five years of the challenge, and propose future directions and improvements.Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional reference

Effect of down—regulation of voltage—gated sodium channel Nav1.7 on activation of astrocytes and microglia in DRG in rats with cancer pain

AbstractObjectiveTo evaluate the effect of down-regulation of Nav1.7 on the activation of astrocytes and microglia in DRG of rats with cancer pain, and explore the transmission of the nociceptive information.MethodsLentiviral vector harboring RNAi sequence targeting the Nav1.7 gene was constructed, and Walker 256 breast cancer cell and morphine was injected to build the bone cancer pain model and morphine tolerance model in rats. Lentiviral vector was injected. Rats in each model were divided into 4 groups: model group, PBS group, vehicle group and LV-Nav1.7 group. The expression levels of GFAP and OX42 in dorsal root ganglia (DRG) were measured.ResultsAfter the animal model was built, the level of Nav1.7, GFAP and OX42 was improved obviously with the time prolonged, which was statistically significant (P<0.05). The expression level of GFAP and OX42 in the DRG in the LV-Nav1.7 group declined obviously compared to the model group, PBS group and vehicle group (P<0.05).ConclusionsIntrathecal injection of Navl.7 shRNA lentiviral vector can reduce the expression of Nav1.7 and inhibit the activation of astrocytes and microglia in DRG. The effort is also effective in morphine tolerance bone cancer pain model rats

Venom Yield, Regeneration, and Composition in the Centipede Scolopendra Polymorpha

In this dissertation, I investigated yield, regeneration, and composition of centipede venom. In the first of three empirical studies, I investigated how size influenced venom volume yield and protein concentration in Scolopendra polymorpha and S. subspinipes. I also examined additional potential influences on yield in S. polymorpha, including relative forcipule size, relative mass, geographic origin, sex, time in captivity, and milking history. Volume yield was positively linearly related to body length in both species; however, body length and protein concentration were uncorrelated. In S. polymorpha, yield was most influenced by body length, but was also positively associated with relative forcipule length and relative body mass. In the second study, I investigated venom volume and total protein regeneration during the 14-day period subsequent to venom extraction in S. polymorpha. I further tested the hypothesis that venom protein components, separated by RP-FPLC, undergo asynchronous synthesis. During the first 48 hours, volume and protein mass increased linearly. However, protein regeneration lagged behind volume regeneration, with only 65–86% of venom volume and 29–47% of protein mass regenerated during the first 2 days. No significant additional regeneration occurred over the subsequent 12 days. Analysis of chromatograms of individual venom samples revealed that five of 10 chromatographic regions and 12 of 28 peaks demonstrated changes in percent of total peak area among milking intervals, indicating that venom proteins are regenerated asynchronously. In the third study, I characterized the venom composition of S. polymorpha using proteomic methods. I demonstrated that the venom of S. polymorpha is complex, generating 23 bands by SDS-PAGE and 56 peaks by RP-FPLC. MALDI TOF MS revealed hundreds of components with masses ranging from 1014.5 to 82863.9 Da. The distribution of molecular masses was skewed toward smaller peptides and proteins, with 72% of components found below 12 kDa. BLASTp sequence similarity searching of MS/MSderived amino acid sequences demonstrated 20 different sequences with similarity to known venom components, including serine proteases, ion-channel activators/inhibitors, and neurotoxins. In Appendix A, I reviewed how animals strategically deploy various emissions, including venom, highlighting how the metabolic and ecological value of these emissions leads to their judicious use