672 research outputs found

    An unusual presentation of a patient with intrathoracic stomach: a case report

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    An intrathoracic stomach is the end stage of a hiatal hernial diaphragm and has a very low incidence. Frequently the diagnosis is made incidentally by endoscopic or radiographic investigations. There could be no clinical symptoms, however an intrathoracic stomach could be life treating. In this case we report a 61-year-old woman with an atypical presentation of an intrathoracic stomach. The patient had fever, night sweats and cough; the chest X-ray showed a retroperitoneal mass. A computed tomography scan was performed for determining the diagnosis of an intrathoracic stomach

    Transmitter and Receiver Architectures for Molecular Communications: A Survey on Physical Design with Modulation, Coding, and Detection Techniques

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    Inspired by nature, molecular communications (MC), i.e., the use of molecules to encode, transmit, and receive information, stands as the most promising communication paradigm to realize the nanonetworks. Even though there has been extensive theoretical research toward nanoscale MC, there are no examples of implemented nanoscale MC networks. The main reason for this lies in the peculiarities of nanoscale physics, challenges in nanoscale fabrication, and highly stochastic nature of the biochemical domain of envisioned nanonetwork applications. This mandates developing novel device architectures and communication methods compatible with MC constraints. To that end, various transmitter and receiver designs for MC have been proposed in the literature together with numerable modulation, coding, and detection techniques. However, these works fall into domains of a very wide spectrum of disciplines, including, but not limited to, information and communication theory, quantum physics, materials science, nanofabrication, physiology, and synthetic biology. Therefore, we believe it is imperative for the progress of the field that an organized exposition of cumulative knowledge on the subject matter can be compiled. Thus, to fill this gap, in this comprehensive survey, we review the existing literature on transmitter and receiver architectures toward realizing MC among nanomaterial-based nanomachines and/or biological entities and provide a complete overview of modulation, coding, and detection techniques employed for MC. Moreover, we identify the most significant shortcomings and challenges in all these research areas and propose potential solutions to overcome some of them.This work was supported in part by the European Research Council (ERC) Projects MINERVA under Grant ERC-2013-CoG #616922 and MINERGRACE under Grant ERC-2017-PoC #780645

    Reclaiming the political : emancipation and critique in security studies

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    The critical security studies literature has been marked by a shared commitment towards the politicization of security – that is, the analysis of its assumptions, implications and the practices through which it is (re)produced. In recent years, however, politicization has been accompanied by a tendency to conceive security as connected with a logic of exclusion, totalization and even violence. This has resulted in an imbalanced politicization that weakens critique. Seeking to tackle this situation, the present article engages with contributions that have advanced emancipatory versions of security. Starting with, but going beyond, the so-called Aberystwyth School of security studies, the argument reconsiders the meaning of security as emancipation by making the case for a systematic engagement with the notions of reality and power. This revised version of security as emancipation strengthens critique by addressing political dimensions that have been underplayed in the critical security literature

    EPIDEMIOLOGICAL CHARACTERISTICS OF VIRAL HEPATITIS IN PATIENTS WITH RHEUMATIC DISEASES - IMPLICATIONS FROM TREASURE DATABASE

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    EULAR European Congress of Rheumatology (EULAR) -- JUN 01-04, 2022 -- Copenhagen, DENMARK[Abstract Not Available]European Alliance Assoc Rheumato

    Quantification of Spatial Parameters in 3D Cellular Constructs Using Graph Theory

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    Multispectral three-dimensional (3D) imaging provides spatial information for biological structures that cannot be measured by traditional methods. This work presents a method of tracking 3D biological structures to quantify changes over time using graph theory. Cell-graphs were generated based on the pairwise distances, in 3D-Euclidean space, between nuclei during collagen I gel compaction. From these graphs quantitative features are extracted that measure both the global topography and the frequently occurring local structures of the “tissue constructs.” The feature trends can be controlled by manipulating compaction through cell density and are significant when compared to random graphs. This work presents a novel methodology to track a simple 3D biological event and quantitatively analyze the underlying structural change. Further application of this method will allow for the study of complex biological problems that require the quantification of temporal-spatial information in 3D and establish a new paradigm in understanding structure-function relationships

    Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

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    The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models

    Towards Transparent Linguistic Analysis of Dutch Newspaper Article Genres using Machine Learning

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    Systematic study of genre in newspapers sheds light on the development of journalism discourse. The genre conventions that can be discerned in a newspaper text signal the underlying discursive norms and practices of journalism as a profession. Historical newspapers are increasingly becoming available thanks to digital newspaper archives (in the Netherlands available through Delpher.nl), providing the opportunity for large-scale empirical research. However, the digital archives do not contain fine-grained genre information that is required for this purpose. Therefore, we use machine learning to automatically assign genre labels to newspaper articles.Machine learning facilitates substantial improvements to the outcomes of existing research by providing increased amounts of enriched data. However, the decision-making process of the machine learning pipeline needs to be verified. Our previous findings (Bilgin et al., 2018) show that accuracy scores alone are not enough to assess the performance of these pipelines and that making an informed choice not only empowers optimal study of the historical development of genre, but also increases the trustworthiness of the results. This work shows that employing a transparent approach driven by model interpretability facilitates fair comparison as well as validation of the underlying decision-making criteria of the machine learning pipelines. The criteria are presented in the form of important features, creating insights on interactions between genre-related linguistic features and bag-of-words features.</p

    A case study of controlling crossover in a selection hyper-heuristic framework using the multidimensional knapsack problem

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    Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on a single candidate solution, and two candidate solutions are required for crossover, a mechanism is required to control the choice of the other solution. The frameworks we propose maintain a list of potential solutions for use in crossover. We investigate the use of such lists at two conceptual levels. First, crossover is controlled at the hyper-heuristic level where no problem-specific information is required. Second, it is controlled at the problem domain level where problem-specific information is used to produce good-quality solutions to use in crossover. A number of selection hyper-heuristics are compared using these frameworks over three benchmark libraries with varying properties for an NP-hard optimisation problem: the multidimensional 0-1 knapsack problem. It is shown that allowing crossover to be managed at the domain level outperforms managing crossover at the hyper-heuristic level in this problem domain. © 2016 Massachusetts Institute of Technolog
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