89 research outputs found

    A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition

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    With the propagation of sensor devices applied in smart home, activity recognition has ignited huge interest and most existing works assume that there is only one habitant. While in reality, there are generally multiple residents at home, which brings greater challenge to recognize activities. In addition, many conventional approaches rely on manual time series data segmentation ignoring the inherent characteristics of events and their heuristic hand-crafted feature generation algorithms are difficult to exploit distinctive features to accurately classify different activities. To address these issues, we propose an end-to-end Tree-Structure Convolutional neural network based framework for Multi-Resident Activity Recognition (TSC-MRAR). First, we treat each sample as an event and obtain the current event embedding through the previous sensor readings in the sliding window without splitting the time series data. Then, in order to automatically generate the temporal features, a tree-structure network is designed to derive the temporal dependence of nearby readings. The extracted features are fed into the fully connected layer, which can jointly learn the residents labels and the activity labels simultaneously. Finally, experiments on CASAS datasets demonstrate the high performance in multi-resident activity recognition of our model compared to state-of-the-art techniques.Comment: 12 pages, 4 figure

    Human Activity Recognition Using Deep Models and Its Analysis from Domain Adaptation Perspective

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    © 2019, Springer Nature Switzerland AG. Human activity recognition (HAR) is a broad area of research which solves the problem of determining a user’s activity from a set of observations recorded on video or low-level sensors (accelerometer, gyroscope, etc.) HAR has important applications in medical care and entertainment. In this paper, we address sensor-based HAR, because it could be deployed on a smartphone and eliminates the need to use additional equipment. Using machine learning methods for HAR is common. However, such, methods are vulnerable to changes in the domain of training and test data. More specifically, a model trained on data collected by one user loses accuracy when utilised by another user, because of the domain gap (differences in devices and movement pattern results in differences in sensors’ readings.) Despite significant results achieved in HAR, it is not well-investigated from domain adaptation (DA) perspective. In this paper, we implement a CNN-LSTM based architecture along with several classical machine learning methods for HAR and conduct a series of cross-domain tests. The result of this work is a collection of statistics on the performance of our model under DA task. We believe that our findings will serve as a foundation for future research in solving DA problem for HAR

    Cardiovascular Risk Associated with Interactions among Polymorphisms in Genes from the Renin-Angiotensin, Bradykinin, and Fibrinolytic Systems

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    Vascular fibrinolytic balance is maintained primarily by interplay of tissue plasminogen activator (t-PA) and plasminogen activator inhibitor type 1 (PAI-1). Previous research has shown that polymorphisms in genes from the renin-angiotensin (RA), bradykinin, and fibrinolytic systems affect plasma concentrations of both t-PA and PAI-1 through a set of gene-gene interactions. In the present study, we extend this finding by exploring the effects of polymorphisms in genes from these systems on incident cardiovascular disease, explicitly examining two-way interactions in a large population-based study

    Negative responses of highland pines to anthropogenic activities in inland Spain: a palaeoecological perspective

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    Palaeoecological evidence indicates that highland pines were dominant in extensive areas of the mountains of Central and Northern Iberia during the first half of the Holocene. However, following several millennia of anthropogenic pressure, their natural ranges are now severely reduced. Although pines have been frequently viewed as first-stage successional species responding positively to human disturbance, some recent palaeobotanical work has proposed fire disturbance and human deforestation as the main drivers of this vegetation turnover. To assess the strength of the evidence for this hypothesis and to identify other possible explanations for this scenario, we review the available information on past vegetation change in the mountains of northern inland Iberia. We have chosen data from several sites that offer good chronological control, including palynological records with microscopic charcoal data and sites with plant macro- and megafossil occurrence. We conclude that although the available long-term data are still fragmentary and that new methods are needed for a better understanding of the ecological history of Iberia, fire events and human activities (probably modulated by climate) have triggered the pine demise at different locations and different temporal scales. In addition, all palaeoxylological, palynological and charcoal results obtained so far are fully compatible with a rapid human-induced ecological change that could have caused a range contraction of highland pines in western Iberia

    Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

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    <p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p

    A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk

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    We review the evolution, state of the art and future lines of research on the sources, transport pathways, and sinks of particulate trace elements in urban terrestrial environments to include the atmosphere, soils, and street and indoor dusts. Such studies reveal reductions in the emissions of some elements of historical concern such as Pb, with interest consequently focusing on other toxic trace elements such as As, Cd, Hg, Zn, and Cu. While establishment of levels of these elements is important in assessing the potential impacts of human society on the urban environment, it is also necessary to apply this knowledge in conjunction with information on the toxicity of those trace elements and the degree of exposure of human receptors to an assessment of whether such contamination represents a real risk to the city’s inhabitants and therefore how this risk can be addressed

    The role of open abdomen in non-trauma patient : WSES Consensus Paper

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    The open abdomen (OA) is defined as intentional decision to leave the fascial edges of the abdomen un-approximated after laparotomy (laparostomy). The abdominal contents are potentially exposed and therefore must be protected with a temporary coverage, which is referred to as temporal abdominal closure (TAC). OA use remains widely debated with many specific details deserving detailed assessment and clarification. To date, in patients with intra-abdominal emergencies, the OA has not been formally endorsed for routine utilization; although, utilization is seemingly increasing. Therefore, the World Society of Emergency Surgery (WSES), Abdominal Compartment Society (WSACS) and the Donegal Research Academy united a worldwide group of experts in an international consensus conference to review and thereafter propose the basis for evidence-directed utilization of OA management in non-trauma emergency surgery and critically ill patients. In addition to utilization recommendations, questions with insufficient evidence urgently requiring future study were identified.Peer reviewe

    Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains

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    Ruiz JC, D'Afonseca V, Silva A, et al. Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains. PLoS ONE. 2011;6(4): e18551.Background: Corynebacterium pseudotuberculosis, a Gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity. Methodology and Findings: We characterized two C. pseudotuberculosis genomes (Cp1002, isolated from goats; and CpC231, isolated from sheep). Analysis of the predicted genomes showed high similarity in genomic architecture, gene content and genetic order. When C. pseudotuberculosis was compared with other Corynebacterium species, it became evident that this pathogenic species has lost numerous genes, resulting in one of the smallest genomes in the genus. Other differences that could be part of the adaptation to pathogenicity include a lower GC content, of about 52%, and a reduced gene repertoire. The C. pseudotuberculosis genome also includes seven putative pathogenicity islands, which contain several classical virulence factors, including genes for fimbrial subunits, adhesion factors, iron uptake and secreted toxins. Additionally, all of the virulence factors in the islands have characteristics that indicate horizontal transfer. Conclusions: These particular genome characteristics of C. pseudotuberculosis, as well as its acquired virulence factors in pathogenicity islands, provide evidence of its lifestyle and of the pathogenicity pathways used by this pathogen in the infection process. All genomes cited in this study are available in the NCBI Genbank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers CP001809 and CP001829

    A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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