Macrophage polarization impacts tunneling nanotube formation and intercellular organelle trafficking.

Tunneling nanotubes (TNTs) are cellular extensions enabling cytosol-to-cytosol intercellular interaction between numerous cell types including macrophages. Previous studies of hematopoietic stem and progenitor cell (HSPC) transplantation for the lysosomal storage disorder cystinosis have shown that HSPC-derived macrophages form TNTs to deliver cystinosin-bearing lysosomes to cystinotic cells, leading to tissue preservation. Here, we explored if macrophage polarization to either proinflammatory M1-like M(LPS/IFNγ) or anti-inflammatory M2-like M(IL-4/IL-10) affected TNT-like protrusion formation, intercellular transport and, ultimately, the efficacy of cystinosis prevention. We designed new automated image processing algorithms used to demonstrate that LPS/IFNγ polarization decreased bone marrow-derived macrophages (BMDMs) formation of protrusions, some of which displayed characteristics of TNTs, including cytoskeletal structure, 3D morphology and size. In contrast, co-culture of macrophages with cystinotic fibroblasts yielded more frequent and larger protrusions, as well as increased lysosomal and mitochondrial intercellular trafficking to the diseased fibroblasts. Unexpectedly, we observed normal protrusion formation and therapeutic efficacy following disruption of anti-inflammatory IL-4/IL-10 polarization in vivo by transplantation of HSPCs isolated from the Rac2-/- mouse model. Altogether, we developed unbiased image quantification systems that probe mechanistic aspects of TNT formation and function in vitro, while HSPC transplantation into cystinotic mice provides a complex in vivo disease model. While the differences between polarization cell culture and mouse models exemplify the oversimplicity of in vitro cytokine treatment, they simultaneously demonstrate the utility of our co-culture model which recapitulates the in vivo phenomenon of diseased cystinotic cells stimulating thicker TNT formation and intercellular trafficking from macrophages. Ultimately, we can use both approaches to expand the utility of TNT-like protrusions as a delivery system for regenerative medicine

High-level feature detection from video in TRECVid: a 5-year retrospective of achievements

Successful and effective content-based access to digital video requires fast, accurate and scalable methods to determine the video content automatically. A variety of contemporary approaches to this rely on text taken from speech within the video, or on matching one video frame against others using low-level characteristics like colour, texture, or shapes, or on determining and matching objects appearing within the video. Possibly the most important technique, however, is one which determines the presence or absence of a high-level or semantic feature, within a video clip or shot. By utilizing dozens, hundreds or even thousands of such semantic features we can support many kinds of content-based video navigation. Critically however, this depends on being able to determine whether each feature is or is not present in a video clip. The last 5 years have seen much progress in the development of techniques to determine the presence of semantic features within video. This progress can be tracked in the annual TRECVid benchmarking activity where dozens of research groups measure the effectiveness of their techniques on common data and using an open, metrics-based approach. In this chapter we summarise the work done on the TRECVid high-level feature task, showing the progress made year-on-year. This provides a fairly comprehensive statement on where the state-of-the-art is regarding this important task, not just for one research group or for one approach, but across the spectrum. We then use this past and on-going work as a basis for highlighting the trends that are emerging in this area, and the questions which remain to be addressed before we can achieve large-scale, fast and reliable high-level feature detection on video

Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

Colossal Tunneling Electroresistance in Co-Planar Polymer Ferroelectric Tunnel Junctions

Ferroelectric tunnel junctions (FTJs) are ideal resistance-switching devices due to their deterministic behavior and operation at low voltages. However, FTJs have remained mostly as a scientific curiosity due to three critical issues: lack of rectification in their current-voltage characteristic, small tunneling electroresistance (TER) effect, and absence of a straightforward lithography-based device fabrication method that would allow for their mass production. Co-planar FTJs that are fabricated using wafer-scale adhesion lithography technique are demonstrated, and a bi-stable rectifying behavior with colossal TER approaching 106% at room temperature is exhibited. The FTJs are based on poly(vinylidenefluoride-co-trifluoroethylene) [P(VDF-TrFE)], and employ asymmetric co-planar metallic electrodes separated by &lt;20 nm. The tunneling nature of the charge transport is corroborated using Simmons direct tunneling model. The present work is the first demonstration of functional FTJs manufactured via a scalable lithography-based nano-patterning technique and could pave the way to new and exciting memory device concepts.</p

Single core configurations of saturated core fault current limiter performance of laboratory test models

Economic growth with industrialization and urbanization lead to an extensive increase in power demand. It forced the utilities to add power generating facilities to cause the necessary demand-generation balance. The bulk power generating stations, mostly interconnected, with the penetration of distributed generation result in an enormous rise in the fault level of power networks. It necessitates for electrical utilities to control the fault current so that the existing switchgear can continue its services without up-gradation or replacement for reliable supply. The deployment of fault current limiter (FCL) at the distribution and transmission networks has been under investigation as a potential solution to the problem. A saturated core fault current limiter (SCFCL) technology is a smart, scalable, efficient, reliable, and commercially viable option to manage fault levels in existing and future MV/HV supply systems. This paper presents the comparative performance analysis of two single-core SCFCL topologies impressed with different core saturations. It has demonstrated that the single AC winding configuration needs more bias power for affecting the same current limiting performance with an acceptable steady-state voltage drop contribution. The fault state impedance has a transient nature, and the optimum bias selection is a critical design parameter in realizing the SCFCL applications

Unsupervised classemes

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33885-4_41Proceedings of Information Fusion in Computer Vision for Concept Recognition at the ECCV 2012In this paper we present a new model of semantic features that, unlike previously presented methods, does not rely on the presence of a labeled training data base, as the creation of the feature extraction function is done in an unsupervised manner. We test these features on an unsupervised classification (clustering) task, and show that they outperform primitive (low-level) features, and that have performance comparable to that of supervised semantic features, which are much more expensive to determine relying on the presence of a labeled training set to train the feature extraction function

Everyday concept detection in visual lifelogs: validation, relationships and trends

The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user's day-to-day activities. It can capture up to 3,000 images per day, equating to almost 1 million images per year. It is used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer's life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the novel domain of visual lifelogs. A concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept's presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept. We conduct further analysis on the temporal consistency, co-occurance and trends within the detected concepts to more extensively investigate the robustness of the detectors within this novel domain. We additionally present future applications of concept detection within the domain of lifelogging

Impact of Annona reticulata L. Extract Fortified Mulberry Leaves on Silk Production Parameters of Bombyx mori L.

The effects of several plant extracts in different quantities on Bombyx mori L. commercial parameters have been seen in commercial silk farming in recent years. In this study, the effects of various concentrations of chloroformic extract of Annona reticulata L. on Bombyx mori L. larvae were investigated. The overall performance of Bombyx mori in response to A. reticulata treatments were observed in the present study. According to experimental study, by utilizing concentrations of Annona reticulata L. at 1: 2, 1: 4, and 1: 8 resulted in an increasing trend for key commercial characteristics, such as filament length, filament weight, single cocoon weight, pupal weight, and shell weight of B. mori L