ZENODO

    LEGAL DIMENSIONS OF PARAMETERS OF LIBERTY IN INDIAN CONTEXT: AN OVERVIEW

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    Liberty is an essentially a political and legal term which connotes protection from state interferences. In the Indian context the legal dimension can be found in Article 21 of the Constitution which secures the right to life and liberty. The Supreme Court verdict of August 2017 has not only widened the legal dimension of liberty, by making right to Privacy, its intrinsic part but it has other implications as well

    Multi-modal Deep Learning Approach for Flood Detection

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    In this paper we propose a multi-modal deep learning approach to detect floods in social media posts. Social media posts normally contain some metadata and/or visual information, therefore in order to detect the floods we use this information. The model is based on a Convolutional Neural Network which extracts the visual features and a bidirectional Long Short-Term Memory network to extract the semantic features from the textual metadata. We validate the method on images extracted from Flickr which contain both visual information and metadata and compare the results when using both, visual information only or metadata only. This work has been done in the context of the MediaEval Multimedia Satellite Task

    Intra- Datacenter Challenges; System Perspective

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    Invited presentation at ECOC Sunday workshop with title: Data Center Networks: Meeting the emerging requirements for capacity, cost, energy consumption and reac

    Efficient Cell Planning for Reliable Support of Event-Driven Machine-Type Traffic in LTE

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    The reliable support of event-driven massive machine-type communication (MTC) requires radical enhancements in the standard LTE random access channel (RACH) procedure to avoid performance degradation due to a high probability of collision in the preamble transmission. In this paper, we investigate the relation between the cell size and the number of preambles generated from a single or multiple root sequences and we study their impact on the achieved reliability. Based on an analytical expression of the RACH reliability per cell, we introduce an interference- and load-aware cell-planning mechanism that efficiently allocates the root sequences among multiple cells and regulates the traffic load to guarantee reliable support of MTC. In addition, we propose a realistic traffic model that accurately captures the event-driven nature of MTC traffic. Finally, a performance evaluation of a power distribution automation scenario with MTC-overload reveals the superior performance of our proposed mechanism in terms of RACH reliability against benchmarking network-deployment schemes

    Gold-Catalyzed Reactions via Cyclopropyl Gold Carbene-like Intermediates

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    Cycloisomerizations of 1,n-enynes catalyzed by gold(I) proceed via electrophilic species with a highly distorted cyclopropyl gold(I) carbene-like structure, which can react with different nucleophiles to form a wide variety of products by attack at the cyclopropane or the carbene carbons. Particularly important are reactions in which the gold(I) carbene reacts with alkenes to form cyclopropanes either intra- or intermolecularly. In the absence of nucleophiles, 1,n-enynes lead to a variety of cycloisomerized products including those resulting from skeletal rearrangements. Reactions proceeding through cyclopropyl gold(I) carbene-like intermediates are ideally suited for the bioinspired synthesis of terpenoid natural products by the selective activation of the alkyne in highly functionalized enynes or polyenynes

    Strategies for the Synthesis of Higher Acenes

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    The outstanding performance of pentacene-based molecules in molecular electronics, as well as the predicted en- hanced semiconducting properties of extended acenes, have stimulated the development of new synthetic methods and functionalization strategies for the preparation of stable and soluble acenes larger than tetracene with the aim of obtaining improved functional materials

    Pseudo-proxy evaluation of climate field reconstruction methods of North Atlantic climate based on an annually resolved marine proxy network

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    Two statistical methods are tested to reconstruct the interannual variations in past sea surface temperatures (SSTs) of the North Atlantic (NA) Ocean over the past millennium based on annually resolved and absolutely dated marine proxy records of the bivalve mollusk Arctica islandica. The methods are tested in a pseudo-proxy experiment (PPE) setup using state-of-the-art climate models (CMIP5 Earth system models) and reanalysis data from the COBE2 SST data set. The methods were applied in the virtual reality provided by global climate simulations and reanalysis data to reconstruct the past NA SSTs using pseudo-proxy records that mimic the statistical characteristics and network of Arctica islandica. The multivariate linear regression methods evaluated here are principal component regression and canonical correlation analysis. Differences in the skill of the climate field reconstruction (CFR) are assessed according to different calibration periods and different proxy locations within the NA basin. The choice of the climate model used as a surrogate reality in the PPE has a more profound effect on the CFR skill than the calibration period and the statistical reconstruction method. The differences between the two methods are clearer for the MPI-ESM model due to its higher spatial resolution in the NA basin. The pseudo-proxy results of the CCSM4 model are closer to the pseudo-proxy results based on the reanalysis data set COBE2. Conducting PPEs using noise-contaminated pseudo-proxies instead of noise-free pseudo-proxies is important for the evaluation of the methods, as more spatial differences in the reconstruction skill are revealed. Both methods are appropriate for the reconstruction of the temporal evolution of the NA SSTs, even though they lead to a great loss of variance away from the proxy sites. Under reasonable assumptions about the characteristics of the non-climate noise in the proxy records, our results show that the marine network of Arctica islandica can be used to skillfully reconstruct the spatial patterns of SSTs at the eastern NA basin

    Validation of Enhanced Emotion Enabled Cognitive Agent Using Virtual Overlay Multi-Agent System Approach

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    ABSTRACT Making roads safer by avoiding road collisions is one of the main reasons for inventing Autonomous vehicles (AVs). In this context, designing agent-based collision avoidance components of AVs which truly represent human cognition and emotions look is a more feasible approach as agents can replace human drivers. However, to the best of our knowledge, very few human emotion and cognition-inspired agent-based studies have previously been conducted in this domain. Furthermore, these agent-based solutions have not been validated using any key validation technique. Keeping in view this lack of validation practices, we have selected state-of-the-art Emotion Enabled Cognitive Agent (EEC_Agent), which was proposed to avoid lateral collisions between semi-AVs. The architecture of EEC_Agent has been revised using Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework and real-time fear emotion generation mechanism using the Ortony, Clore & Collins (OCC) model has also been introduced. Then the proposed fear generation mechanism has been validated using the Validated Agent Based Modeling level of CABC framework using a Virtual Overlay MultiAgent System (VOMAS). Extensive simulation and practical experiments demonstrate that the Enhanced EEC_Agent exhibits the capability to feel different levels of fear, according to different traffic situations and also needs a smaller Stopping Sight Distance (SSD) and Overtaking Sight Distance (OSD) as compared to human drivers

    Workshop Report: Container Based Analysis Environments for Research Data Access and Computing

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    Report of the first workshop on Container Based Analysis Environments for Research Data Access and Computing supported by the National Data Service and Data Exploration Lab and held at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign

    TREASURE - MANGALITSA LOCAL PIG BREED IN SERBIA

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    The main objective of this paper is to present the results of the research of the Swallow belly Mangalitsa genotype in the last six decades. According to the research, females reach the full maturity the age of 9-10 months, but they are mated at the age of 1-1.5 years. Average age at first farrowing is 556 days. Reproductive ability is poorly expressed, with a strong maternal instinct. Fertility of the Mangalitsa is relatively poor because it gives birth to 1-12 piglets, on average 4 to 5 piglets, with an average body weight of 1.25 kg with a variation of 0.8 to 1.8 kg. The suckling period is about 50 days (from 47 to 53 days). At lactation duration of 60 days, the piglet weight at the weaning ranges from 6-13 kg (average 9.61 kg) for piglets born in the spring, and from 7-15 kg (average 9.50 kg) for piglets born in fall. Depending on the rearing system, the start of fattening and final body weight, gains range 268 g to 830 g. The fat thickness (average measurements) at the ridge was 10.2 cm, the middle of the back 7.9 cm and the rump 8.1 cm, in previous studies, while in recent studies these values of fat thickness are somewhat lower, with the pre-slaughter body weight also being lower (the ridge 6.18 cm, the middle of the back 4.38 cm and at the rump 5.19 cm). The recent research of the Longissimus dorsi muscle shows an intramuscular fat content of 13.5%, protein content of 21.1% with specific qualitative properties pH45=6.11; pH24=5.50; CIE L*=40.13; a*=11.77; b*=3.73). In the musculus longissimus lumborum and thoracis, Mangalitsa (Swallow-bellied) pigs show higher levels of monounsaturated fatty acids (MUFA 55.1%) and lower levels of saturated fatty acids (SFA 35.3%) in comparison with Swedish Landrace pigs
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