A shared neural ensemble links distinct contextual memories encoded close in time.

Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. According to the memory allocation hypothesis, learning triggers a temporary increase in neuronal excitability that biases the representation of a subsequent memory to the neuronal ensemble encoding the first memory, such that recall of one memory increases the likelihood of recalling the other memory. Here we show in mice that the overlap between the hippocampal CA1 ensembles activated by two distinct contexts acquired within a day is higher than when they are separated by a week. Several findings indicate that this overlap of neuronal ensembles links two contextual memories. First, fear paired with one context is transferred to a neutral context when the two contexts are acquired within a day but not across a week. Second, the first memory strengthens the second memory within a day but not across a week. Older mice, known to have lower CA1 excitability, do not show the overlap between ensembles, the transfer of fear between contexts, or the strengthening of the second memory. Finally, in aged mice, increasing cellular excitability and activating a common ensemble of CA1 neurons during two distinct context exposures rescued the deficit in linking memories. Taken together, these findings demonstrate that contextual memories encoded close in time are linked by directing storage into overlapping ensembles. Alteration of these processes by ageing could affect the temporal structure of memories, thus impairing efficient recall of related information

The Universal Cloud and Aerosol Sounding System (UCASS): a low-cost miniature optical particle counter for use in dropsonde or balloon-borne sounding systems

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. An earlier version of this work was published in Atmospheric Measurement Techniques Discussions: https://dx.doi.org/10.5194/amt-2019-70.A low-cost miniaturized particle counter has been developed by The University of Hertfordshire (UH) for the measurement of aerosol and droplet concentrations and size distributions. The Universal Cloud and Aerosol Sounding System (UCASS) is an optical particle counter (OPC), which uses wide-angle elastic light scattering for the high-precision sizing of fluid-borne particulates. The UCASS has up to 16 configurable size bins, capable of sizing particles in the range 0.4–40 µm in diameter. Unlike traditional particle counters, the UCASS is an open-geometry system that relies on an external air flow. Therefore, the instrument is suited for use as part of a dropsonde, balloon-borne sounding system, as part of an unmanned aerial vehicle (UAV), or on any measurement platform with a known air flow. Data can be logged autonomously using an on-board SD card, or the device can be interfaced with commercially available meteorological sondes to transmit data in real time. The device has been deployed on various research platforms to take measurements of both droplets and dry aerosol particles. Comparative results with co-located instrumentation in both laboratory and field settings show good agreement for the sizing and counting ability of the UCASS.Peer reviewe

Gait recognition and understanding based on hierarchical temporal memory using 3D gait semantic folding

Gait recognition and understanding systems have shown a wide-ranging application prospect. However, their use of unstructured data from image and video has affected their performance, e.g., they are easily influenced by multi-views, occlusion, clothes, and object carrying conditions. This paper addresses these problems using a realistic 3-dimensional (3D) human structural data and sequential pattern learning framework with top-down attention modulating mechanism based on Hierarchical Temporal Memory (HTM). First, an accurate 2-dimensional (2D) to 3D human body pose and shape semantic parameters estimation method is proposed, which exploits the advantages of an instance-level body parsing model and a virtual dressing method. Second, by using gait semantic folding, the estimated body parameters are encoded using a sparse 2D matrix to construct the structural gait semantic image. In order to achieve time-based gait recognition, an HTM Network is constructed to obtain the sequence-level gait sparse distribution representations (SL-GSDRs). A top-down attention mechanism is introduced to deal with various conditions including multi-views by refining the SL-GSDRs, according to prior knowledge. The proposed gait learning model not only aids gait recognition tasks to overcome the difficulties in real application scenarios but also provides the structured gait semantic images for visual cognition. Experimental analyses on CMU MoBo, CASIA B, TUM-IITKGP, and KY4D datasets show a significant performance gain in terms of accuracy and robustness

Synthetic aperture guided wave imaging using a mobile sensor platform

This oral session at conference looks at synthetic aperture guided wave imaging using a mobile sensor platfor

I-BEAT: New ultrasonic method for single bunch measurement of ion energy distribution

The shape of a wave carries all information about the spatial and temporal structure of its source, given that the medium and its properties are known. Most modern imaging methods seek to utilize this nature of waves originating from Huygens' principle. We discuss the retrieval of the complete kinetic energy distribution from the acoustic trace that is recorded when a short ion bunch deposits its energy in water. This novel method, which we refer to as Ion-Bunch Energy Acoustic Tracing (I-BEAT), is a generalization of the ionoacoustic approach. Featuring compactness, simple operation, indestructibility and high dynamic ranges in energy and intensity, I-BEAT is a promising approach to meet the needs of petawatt-class laser-based ion accelerators. With its capability of completely monitoring a single, focused proton bunch with prompt readout it, is expected to have particular impact for experiments and applications using ultrashort ion bunches in high flux regimes. We demonstrate its functionality using it with two laser-driven ion sources for quantitative determination of the kinetic energy distribution of single, focused proton bunches.Comment: Paper: 17 Pages, 3 figures Supplementary Material 16 pages, 7 figure

Miniature illustrations retrieval and innovative interaction for digital illuminated manuscripts

In this paper we propose a multimedia solution for the interactive exploration of illuminated manuscripts. We leveraged on the joint exploitation of content-based image retrieval and relevance feedback to provide an effective mechanism to navigate through the manuscript and add custom knowledge in the form of tags. The similarity retrieval between miniature illustrations is based on covariance descriptors, integrating color, spatial and gradient information. The proposed relevance feedback technique, namely Query Remapping Feature Space Warping, accounts for the user’s opinions by accordingly warping the data points. This is obtained by means of a remapping strategy (from the Riemannian space where covariance matrices lie, referring back to Euclidean space) useful to boost the retrieval performance. Experiments are reported to show the quality of the proposal. Moreover, the complete prototype with user interaction, as already showcased at museums and exhibitions, is presented

A class of structured P2P systems supporting browsing

Browsing is a way of finding documents in a large amount of data which is complementary to querying and which is particularly suitable for multimedia documents. Locating particular documents in a very large collection of multimedia documents such as the ones available in peer to peer networks is a difficult task. However, current peer to peer systems do not allow to do this by browsing. In this report, we show how one can build a peer to peer system supporting a kind of browsing. In our proposal, one must extend an existing distributed hash table system with a few features : handling partial hash-keys and providing appropriate routing mechanisms for these hash-keys. We give such an algorithm for the particular case of the Tapestry distributed hash table. This is a work in progress as no proper validation has been done yet.Comment: 14 page