From sequence to trajectory and vice versa: solving the inverse QTC problem and coping with real-world trajectories

Spatial interactions between agents carry information of high value to human observers, as exemplified by the high-level interpretations that humans make when watching the Heider and Simmel movie, or other such videos which just contain motions of simple objects, such as points, lines and triangles. However, not all the information contained in a pair of continuous trajectories is important; and thus the need for qualitative descriptions of interaction trajectories arises. Towards that purpose, Qualitative Trajectory Calculus (QTC) has been proposed in (Van de Weghe, 2004). However, the original definition of QTC handles uncorrupted continuous-time trajectories, while real-world signals are noisy and sampled in discrete-time. Also, although QTC presents a method for transforming trajectories to qualitative descriptions, the inverse problem has not yet been studied. Thus, in this paper, after discussing several aspects of the transition from ideal QTC to discrete-time noisy QTC, we introduce a novel algorithm for solving the QTC inverse problem; i.e. transforming qualitative descriptions to archetypal trajectories that satisfy them. Both of these problems are particularly important for the successful application of qualitative trajectory calculus to Human-Robot Interaction

VISVE, a vorticity based model applied to 2-D hydrofoils in cavitating conditions

In this study, the VIScous Vorticity Equation (VISVE) method was applied to predict flow around 2-D hydrofoils in cavitating conditions. The DIVergence of velocity Equation (DIVE) was added to extend the method to compressible flows and coupled with VISVE to predict the partial cavitating flow. The flow was modeled as a homogeneous mixture of vapor and liquid with the vapor volume fraction parameter determining their concentrations inside the volume and an additional transport equation for the vapor volume fraction to predict the partial cavitating flow around 2-D hydrofoils. The VISVE method was designed to be both spatially compact and numerically efficient in comparison with the commonly used Reynolds Averaged Navier-Stokes (RANS) models. Cavity shapes and pressure from the VISVE model were compared with those from a commercial RANS solver to assess the accuracy of the numerical results. With the validation of the 2-D VISVE model, VISVE shows the prospective to model the 3D wetted and cavitating flow.Civil, Architectural, and Environmental Engineerin

Ανάλυση Λαθών: Συγκριτική παρουσίαση λαθών σε επίπεδο Β1 και Γ1 και διδακτικές προτάσεις για την αξιοποίησή τους.

Η παρούσα έρευνα αφορά την ανάλυση Λαθών των μαθητών της ελληνικής σαν δεύτερη γλώσσα σε μέσο και προχωρημένο επίπεδο. Η προσπάθειά μας έγκειται στην αξιοποίηση της Ανάλυσης Λαθών η οποία θεωρείται ως ένα σημαντικό μεθοδολογικό εργαλείο των εκπαιδευτικών στην προσπάθειά τους να κατανοήσουν πως οι μαθητές κατακτούν την Γ2. Σε πρώτη φάση, πραγματοποιήθηκε μια αναλυτική παρουσίαση του θεωρητικού πλαισίου της Ανάλυσης λαθών, ενώ σε δεύτερο επίπεδο έγινε μια συγκριτική παρουσίαση της Ανάλυσης των λαθών σε μέσο και προχωρημένο επίπεδο. Η επιλογή των δομών που μελετήθηκαν δεν έγινε με τυχαίο τρόπο αλλά με βάση τον βαθμό δυσκολίας που προκαλούν στην κατάκτησή τους από τους μαθητές. Τα παραδείγματα που χρησιμοποιήθηκαν σχετίζονται με τη Συμφωνία Υποκειμένου-Κατηγορουμένου, τη διάκριση Συνοπτικής- Μη συνοπτικής όψης καθώς και την εναλλαγή Ενεργητικής και Παθητικής Φωνής. Σε ένα τελευταίο επίπεδο μετά την αναφορά των αποτελεσμάτων της έρευνας θα οδηγηθούμε σε μια σειρά από διδακτικές προτάσεις αξιοποιώντας και βιβλιογραφικές αναφορές προκειμένου να βοηθηθούν οι μαθητές στην προσπάθειά τους να κατακτήσουν την ελληνική γλώσσα σαν Γ2.The present thesis concerns the analysis of the errors of foreign students learning Greek as a Second Language at an intermediate and advanced level. My effort is to make use of the Error Analysis which is considered as an important methological tool for teachers in their effort to understand how students acquire Greek Language. In the first stage an analytical reference of the theoretical framework was made, while a comparative presentation of students’ mistakes was held at the second level. The selection of the studied structures was not accidental but based on the degree of the difficulty they have in their acquisition by the students. The examples used are related to Subject-Predicate Agreement, the distinction between Imperfective-Perfective Aspect and the Active/ Passive switching. At the final stage, after reporting the results of the research a series of teaching proposals is presented in order to help students acquire the underdeveloped structures of the Greek Language

QTC3D: extending the qualitative trajectory calculus to three dimensions

Spatial interactions between agents (humans, animals, or machines) carry information of high value to human or electronic observers. However, not all the information contained in a pair of continuous trajectories is important and thus the need for qualitative descriptions of interaction trajectories arises. The Qualitative Trajectory Calculus (QTC) (Van de Weghe, 2004) is a promising development towards this goal. Numerous variants of QTC have been proposed in the past and QTC has been applied towards analyzing various interaction domains. However, an inherent limitation of those QTC variations that deal with lateral movements is that they are limited to two-dimensional motion; therefore, complex three-dimensional interactions, such as those occurring between flying planes or birds, cannot be captured. Towards that purpose, in this paper QTC3D is presented: a novel qualitative trajectory calculus that can deal with full three-dimensional interactions. QTC3D is based on transformations of the Frenet-Serret frames accompanying the trajectories of the moving objects. Apart from the theoretical exposition, including definition and properties, as well as computational aspects, we also present an application of QTC3D towards modeling bird flight. Thus, the power of QTC is now extended to the full dimensionality of physical space, enabling succinct yet rich representations of spatial interactions between agents

A learning algorithm for visual pose estimation of continuum robots

Continuum robots offer significant advantages for surgical intervention due to their down-scalability, dexterity, and structural flexibility. While structural compliance offers a passive way to guard against trauma, it necessitates robust methods for online estimation of the robot configuration in order to enable precise position and manipulation control. In this paper, we address the pose estimation problem by applying a novel mapping of the robot configuration to a feature descriptor space using stereo vision. We generate a mapping of known features through a supervised learning algorithm that relates the feature descriptor to known ground truth. Features are represented in a reduced sub-space, which we call eigen-features. The descriptor provides some robustness to occlusions, which are inherent to surgical environments, and the methodology that we describe can be applied to multi-segment continuum robots for closed-loop control. Experimental validation on a single-segment continuum robot demonstrates the robustness and efficacy of the algorithm for configuration estimation. Results show that the errors are in the range of 1°

Early bare-metal stent thrombosis presenting with cardiogenic shock: a case report

<p>Abstract</p> <p>Introduction</p> <p>Although stents have improved the safety and efficacy of percutaneous coronary interventions, coronary stent thrombosis remains a serious complication.</p> <p>Case presentation</p> <p>We present the case of a 64-year-old Caucasian man from Greece, with symptoms and electrocardiographic findings suggestive of acute inferior myocardial infarction, who complained of chest pain and rapidly developed cardiogenic shock 48 hours after primary percutaneous coronary intervention.</p> <p>Conclusion</p> <p>The most common cause of early bare-metal stent thrombosis is stent malapposition. Intravascular ultrasound is the preferred method to recognize predictors of coronary events that are not detected by angiography.</p

In Vivo Aortic Valve Thermal Heterogeneity in Patients With Nonrheumatic Aortic Valve Stenosis The First In Vivo Experience in Humans

ObjectivesWe investigated in vivo in aortic valve stenosis (AVS) whether there is: 1) thermal heterogeneity within the valve leaflets; 2) temperature difference between the leaflets and the ascending aortic wall; and 3) a possible correlation between heat production, inflammation, and neoangiogenesis.BackgroundHistological studies have demonstrated a potential role of inflammation and neoangiogenesis in AVS.MethodsWe examined 96 leaflets scheduled for aortic valve replacement. Twenty-five patients had AVS, and 7 had aortic valve insufficiency (AVI). Temperature measurements were performed right before hypothermic cardioplegia. Temperature difference (ΔT) was assigned as the mean temperature of each leaflet minus the temperature of the aortic wall. Histological, immunohistological analysis, and vascular endothelial growth factor (VEGF) immunoreactivity was performed.ResultsSignificant thermal heterogeneity was recorded within the leaflets of AVS, compared with AVI (1.52 ± 1.35°C vs. 0.13 ± 0.11°C, p < 0.01). In AVS ΔT was greater in all leaflets compared with the AVI group (p < 0.01). Leaflets of AVS had increased inflammatory cell infiltration, calcium deposit, and anti-VEGF expression compared with AVI (p < 0.01).ConclusionsThermal heterogeneity is increased in AVS and correlates with inflammatory mononuclear cell infiltration, expression of pro-inflammatory cytokines and neoangiogenic factors

Central Role of SREBP-2 in the Pathogenesis of Osteoarthritis

Background: Recent studies have implied that osteoarthritis (OA) is a metabolic disease linked to deregulation of genes involved in lipid metabolism and cholesterol efflux. Sterol Regulatory Element Binding Proteins (SREBPs) are transcription factors regulating lipid metabolism with so far no association with OA. Our aim was to test the hypothesis that SREBP-2, a gene that plays a key role in cholesterol homeostasis, is crucially involved in OA pathogenesis and to identify possible mechanisms of action. Methodology/Principal Findings: We performed a genetic association analysis using a cohort of 1,410 Greek OA patients and healthy controls and found significant association between single nucleotide polymorphism (SNP) 1784G>C in SREBP-2 gene and OA development. Moreover, the above SNP was functionally active, as normal chondrocytes’ transfection with SREBP-2-G/C plasmid resulted in interleukin-1β and metalloproteinase-13 (MMP-13) upregulation. We also evaluated SREBP-2, its target gene 3-hydroxy-3-methylglutaryl-coenzymeA reductase (HMGCR), phospho-phosphoinositide3-kinase (PI3K), phospho-Akt, integrin-alphaV (ITGAV) and transforming growth factor-$\beta$ (TGF-$\beta$) mRNA and protein expression levels in osteoarthritic and normal chondrocytes and found that they were all significantly elevated in OA chondrocytes. To test whether TGF-$\beta$ alone can induce SREBP-2, we treated normal chondrocytes with TGF-$\beta$ and found significant upregulation of SREBP-2, HMGCR, phospho-PI3K and MMP-13. We also showed that TGF-$\beta$ activated aggrecan (ACAN) in chondrocytes only through Smad3, which interacts with SREBP-2. Finally, we examined the effect of an integrin inhibitor, cyclo-RGDFV peptide, on osteoarthritic chondrocytes, and found that it resulted in significant upregulation of ACAN and downregulation of SREBP-2, HMGCR, phospho-PI3K and MMP-13 expression levels. Conclusions/Significance: We demonstrated, for the first time, the association of SREBP-2 with OA pathogenesis and provided evidence on the molecular mechanism involved. We suggest that TGF-$\beta$ induces SREBP-2 pathway activation through ITGAV and PI3K playing a key role in OA and that integrin blockage may be a potential molecular target for OA treatment

Integrative MicroRNA and Proteomic Approaches Identify Novel Osteoarthritis Genes and Their Collaborative Metabolic and Inflammatory Networks

BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103) and proteins (PPARA, BMP7, IL1B) to be highly correlated with Body Mass Index (BMI). Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic and clinical data provides a detailed picture of how a network state is correlated with disease and furthermore leads to the development of new treatments. This strategy will help to improve the understanding of the pathogenesis of multifactorial diseases such as osteoarthritis and provide possible novel therapeutic targets