Investigating the logical inference capabilities of Knowledge Graph Embedding Models

A knowledge graph represents factual information in the form of graphs, where nodes repre- sent real-world entities such as people, places and movies, and edges represent the relation- ships between these entities. Existing knowledge graphs are far from complete. Knowledge graph completion or link prediction refers to the task of predicting new relations (links) between entities by deriving information from the existing relations. A number of link pre- diction model have been proposed, several of which make probabilistic predictions about new links. These models can be rule-based methods derived from observed edges, latent represen- tation based embedding methods, or a combination of both. These methods must capture different kinds of relational patterns in the data, such as symmetry or inversion patterns to fully model the data. Rule-based methods explicitly learn these patterns, and provide an interpretable approach to predict new edges. With embedding based models, however, due to the nature of latent embeddings, it is difficult to understand what is being captured by these models. In this work, we explore the logical inference capabilities of knowledge graph embedding models. We experiment with various knowledge graph embedding models on syn- thetic datasets to identify specific properties of each model. The objective is to empirically validate the suitability of these models to learning different relational patterns that exist in real-world knowledge graphs

Abstract

Encoding a document in a vector is a very crucial step for any vector space model based IR (Information Retrieval) system. It is obvious that the better these vectors are constructed, the better the performance of any application built on top of it. In traditional document representation methods, a document is considered as a bag of words. The fact that the words may be semantically related- a crucial information for document representation- is not taken into account. The feature vector representing the document is constructed from the frequency count of document terms. In this paper we describe a new method for generating feature vectors, using the semantic relations between the words in a sentence. The semantic relations are captured by the Universal Networking Language (UNL) which is a recently proposed semantic representation for sentences. In order to show that the generated document vectors with this new method are better than the traditional methods, we use the concept of mutual information. We prove by experiments that the vectors generated by UNL method indeed provide more information about the documents. It is proved that this helps in improving precision-recall in an IR system built using them.

Broncho-vascular fistulas from self-expanding metallic stents: A retrospective case review

To highlight a potentially fatal complication of broncho-vascular fistula arising from the self expanding metallic stent (SEMS) placement. We retrospectively analyzed five patients with benign and malignant airway diseases, who developed tracheo/broncho-vascular fistulas following SEMS placement in our tertiary care setting. All patients received either Wallstent or Ultraflex® stent (Boston Scientific, Natick, MA) between 1999 and 2007. All patients had received adjunct therapy such as balloon bronchoplasty, laser therapy or electrocautery. Most patients presented with massive hemoptysis. A total of 483 SEMS were placed during this period. SEMS placement can be complicated by Broncho-vascular fistula formation. True incidence and precise time interval between the insertion of stent and onset of this complication is unknown. Additional therapeutic modalities to maintain stent patency may enhance the risk of fistula formation. SEMS should only be used in a select sub-group of patients, after exhaustive evaluation of other treatment options. These cases provide evidence that broncho-vascular fistulas can develop at any time following SEMS placement, suggesting the need for a more cautious approach, especially while using them for a long term management. In benign airway disease, the stent should be removed as soon as healing has taken place

Data-Driven Approach to Network Intrusion Detection System Using Modified Artificial Bee Colony Algorithm for Nature-Inspired Cybersecurity

With ever-evolving cyberspace, adaptive defense is crucial. In this paper, we show the Adaptive Defense Mechanism to identify Anomalous hosts in a network using the Artificial Bees Colonization Algorithm. A self-driven metric has been defined to determine the performance of a network that would detect the behavior of its nodes. This algorithmic metric is inspired by the Nature-Inspired Artificial Bees Colonization Algorithm. The end result is randomly generated using a dimension index that gives the same result on the node’s behavior which is then used to determine the probabilistic parametric fitness of the individual nodes. This helps to determine which nodes are getting affected the most or are nearer to the attack surface. The defense mechanism is based on the Nature Inspired Artificial Bees Colonization Algorithm, which is able to detect the nearest point/s of attack on nodes based on the experimental simulation of attacked nodes. It also shows the impact of the defense mechanism on the various topologies of the nodes as predefined in the testbed implementing a Distributed Denial-of-Service attack on the nodes. The proposed algorithm showcases the nodes that are affected due to the attack, providing the nearest point of the breach, which can provide a comprehensive way of examining the intrusion point. This algorithm outperformed in terms of stability and early identification of the malicious nodes

Progressive multifocal leukoencephalopathy in a lung transplant recipient: Isolation of John Cunningham (JC) virus from bronchoalveolar lavage

Progressive multifocal leukoencephalopathy (PML) is a demyelinating disease of the central nervous system caused by polyomavirus John Cunningham (JC) virus. We report the case of a 60-year-old woman who presented 16 months after right single lung transplant with worsening memory, behavioral problems, emotional lability, and progressive left upper extremity weakness. Magnetic resonance imaging revealed white matter changes suggestive of PML. JC virus infection was confirmed with polymerase chain reaction (PCR) from both the bronchoalveolar lavage (BAL) fluid and cerebrospinal fluid. To our knowledge, this is the first report of PCR isolation of JC virus from a BAL specimen. We also review the two additional cases in the literature that describe PML after lung transplantation. JC virus infection should be considered in the differential diagnosis of lung transplant recipients who develop neurological symptoms. BAL may have a role in the etiologic diagnosis of PML after lung transplantation

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS