Revisiting a kNN-based Image Classification System with High-capacity Storage

In existing image classification systems that use deep neural networks, the knowledge needed for image classification is implicitly stored in model parameters. If users want to update this knowledge, then they need to fine-tune the model parameters. Moreover, users cannot verify the validity of inference results or evaluate the contribution of knowledge to the results. In this paper, we investigate a system that stores knowledge for image classification, such as image feature maps, labels, and original images, not in model parameters but in external high-capacity storage. Our system refers to the storage like a database when classifying input images. To increase knowledge, our system updates the database instead of fine-tuning model parameters, which avoids catastrophic forgetting in incremental learning scenarios. We revisit a kNN (k-Nearest Neighbor) classifier and employ it in our system. By analyzing the neighborhood samples referred by the kNN algorithm, we can interpret how knowledge learned in the past is used for inference results. Our system achieves 79.8% top-1 accuracy on the ImageNet dataset without fine-tuning model parameters after pretraining, and 90.8% accuracy on the Split CIFAR-100 dataset in the task incremental learning setting.Comment: 16 pages, 7 figures, 6 table

Self-folded soft robotic structures with controllable joints

This paper describes additive self-folding, an origami-inspired rapid fabrication approach for creating actuatable compliant structures. Recent work in 3-D printing and other rapid fabrication processes have mostly focused on rigid objects or objects that can achieve small deformations. In contrast, soft robots often require elastic materials and large amounts of movement. Additive self-folding is a process that involves cutting slices of a 3-D object in a long strip and then pleat folding them into a likeness of the original model. The zigzag pattern for folding enables large bending movements that can be actuated and controlled. Gaps between slices in the folded model can be designed to provide larger deformations or higher shape accuracy. We advance existing planar fabrication and self-folding techniques to automate the fabrication process, enabling highly compliant structures with complex 3-D geometries to be designed and fabricated within a few hours. We describe this process in this paper and provide algorithms for converting 3-D meshes into additive self-folding designs. The designs can be rapidly instrumented for global control using magnetic fields or tendon-driven for local bending. We also describe how the resulting structures can be modeled and their responses to tendon-driven control predicted. We test our design and fabrication methods on three models (a bunny, a tuna fish, and a starfish) and demonstrate the method's potential for actuation by actuating the tuna fish and starfish models using tendons and magnetic control.National Science Foundation (U.S.) (Grant 1240383)National Science Foundation (U.S.) (Grant 1138967

An iterative agent bidding mechanism for responsive manufacturing

In today's market, the global competition has put manufacturing businesses in great pressures to respond rapidly to dynamic variations in demand patterns across products and changing product mixes. To achieve substantial responsiveness, the manufacturing activities associated with production planning and control must be integrated dynamically, efficiently and cost-effectively. This paper presents an iterative agent bidding mechanism, which performs dynamic integration of process planning and production scheduling to generate optimised process plans and schedules in response to dynamic changes in the market and production environment. The iterative bidding procedure is carried out based on currency-like metrics in which all operations (e.g. machining processes) to be performed are assigned with virtual currency values, and resource agents bid for the operations if the costs incurred for performing them are lower than the currency values. The currency values are adjusted iteratively and resource agents re-bid for the operations based on the new set of currency values until the total production cost is minimised. A simulated annealing optimisation technique is employed to optimise the currency values iteratively. The feasibility of the proposed methodology has been validated using a test case and results obtained have proven the method outperforming non-agent-based methods

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

A Prospective Randomized Trial of Either Famotidine or Pantoprazole for the Prevention of Bleeding after Endoscopic Submucosal Dissection

Endoscopic submucosal dissection (ESD) has been reported to have a higher bleeding rate than conventional methods. However, there are few reports on whether a proton pump inhibitor or a histamine2-receptor antagonist is the more effective treatment for preventing bleeding after ESD. In a prospective trial, patients undergoing ESD due to gastric adenoma or adenocarcinoma were randomly assigned to pantoprazole or famotidine. Both drugs were given intravenously for the first 2 days, thereafter by mouth. Eighty-five in the pantoprazole group and 79 in the famotidine group were included for analysis. Primary outcome measure was the delayed bleeding rate. Clinical characteristics were not different between the two groups. The delayed bleeding rate was significantly lower in the pantoprazole group compared with the famotidine group (3.5% vs. 12.7%, p=0.031). On multivariate analysis, the preventive use of pantoprazole (relative hazard: 0.220, 95% CI: 0.051- 0.827, p=0.026) and the specimen size (≥34 mm, relative hazard: 4.178, 95% CI: 1.229-14.197, p=0.022) were two independent factors predictive of delayed bleeding. There were no significant differences in en bloc and complete resection rate between the two groups. In conclusion, pantoprazole is more effective than famotidine for the prevention of delayed bleeding after ESD

ALS/FTD Mutation-Induced Phase Transition of FUS Liquid Droplets and Reversible Hydrogels into Irreversible Hydrogels Impairs RNP Granule Function.

The mechanisms by which mutations in FUS and other RNA binding proteins cause ALS and FTD remain controversial. We propose a model in which low-complexity (LC) domains of FUS drive its physiologically reversible assembly into membrane-free, liquid droplet and hydrogel-like structures. ALS/FTD mutations in LC or non-LC domains induce further phase transition into poorly soluble fibrillar hydrogels distinct from conventional amyloids. These assemblies are necessary and sufficient for neurotoxicity in a C. elegans model of FUS-dependent neurodegeneration. They trap other ribonucleoprotein (RNP) granule components and disrupt RNP granule function. One consequence is impairment of new protein synthesis by cytoplasmic RNP granules in axon terminals, where RNP granules regulate local RNA metabolism and translation. Nuclear FUS granules may be similarly affected. Inhibiting formation of these fibrillar hydrogel assemblies mitigates neurotoxicity and suggests a potential therapeutic strategy that may also be applicable to ALS/FTD associated with mutations in other RNA binding proteins.Supported by Canadian Institutes of Health Research (PEF, PStGH), Alzheimer Society of Ontario (PEF, PStGH), Wellcome Trust (PStGH, MEV, CFK, GSK, DR, CEH), Medical Research Council (PStGH, MEV, CFK, GSK), National Institutes of Health Research, Alzheimer Research UK (CFK, GSK), Gates Cambridge Scholarship (JQL), Engineering and Physical Sciences Research Council (CFK, GSK), European Research Council Starting Grant RIBOMYLOME_309545 (GGT), European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 322817 (CEH), and National Institute of Neurological Disorders and Stroke R01 NS07377 (NAS). The authors thank Tom Cech and Roy Parker for helpful discussions.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.neuron.2015.10.03

Substorm triggering by new plasma intrusion: THEMIS all‐sky imager observations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95677/1/jgra20480.pd

ALS/FTD mutation-induced phase transition of FUS liquid droplets and reversible hydrogels into irreversible hydrogels impairs RNP granule function

The mechanisms by which mutations in FUS and other RNA binding proteins cause ALS and FTD remain controversial. We propose a model in which low-complexity (LC) domains of FUS drive its physiologically reversible assembly into membrane-free, liquid droplet and hydrogel-like structures. ALS/FTD mutations in LC or non-LC domains induce further phase transition into poorly soluble fibrillar hydrogels distinct from conventional amyloids. These assemblies are necessary and sufficient for neurotoxicity in a C. elegans model of FUS-dependent neurodegeneration. They trap other ribonucleoprotein (RNP) granule components and disrupt RNP granule function. One consequence is impairment of new protein synthesis by cytoplasmic RNP granules in axon terminals, where RNP granules regulate local RNA metabolism and translation. Nuclear FUS granules may be similarly affected. Inhibiting formation of these fibrillar hydrogel assemblies mitigates neurotoxicity and suggests a potential therapeutic strategy that may also be applicable to ALS/FTD associated with mutations in other RNA binding proteins