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Deep vein thrombosis (DVT) is one of the most common diseases in developed countries with significant socioeconomic consequences. The severity of DVT lies in the potential for life-threatening pulmonary embolism and the development of chronic venous insufficiency, referred to as post-thrombotic syndrome. Virchow contributed to the understanding of the pathophysiological events that lead to thrombosis by describing three basic risk mechanisms. The first therapeutic attempts in the 17th century included venepuncture and the application of leeches. The first anticoagulant drug was heparin, which entered clinical practice after 1935. Subsequent commercialization of oral vitamin K antagonists (warfarin) and the advent of low molecular weight heparin along with compression therapy allowed the expansion of outpatient treatment of DVT. Recently, new oral anticoagulants have been introduced, leading to improved safety due to lower risk of bleeding complications and simplification of the treatment process. The next step in the development of therapeutic options are invasive methods of early thrombus removal, which significantly shorten the process and aim to reduce the occurrence of late complications. These methods include local catheter-directed thrombolysis using tissue plasminogen activator, mechanical thrombectomy and their combination called pharmaco-mechanical thrombectomy. The latter is currently used in patients with acute ilio-femoral DVT.

Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential.

Background and AimsAlagille syndrome (ALGS) is a pediatric genetic disorder, caused by mutations in the Notch ligandJAGGED1, presenting with cholestasis due to intrahepatic bile duct paucity. Despite chronic liver disease, few patients develop severe fibrosis or liver cancer, compared to other chronic liver diseases. In contrast, about 1/3 of ALGS patients suffer from reoccurring infections. Notch signaling regulates both liver and immune system development, but how immune system defects interact with liver pathology in ALGS to influence disease course is not known. Here, we aimed to determine whether a mouse model of ALGS mimics fibrosis and liver cancer, and whether ALGS immune system compromise could positively modulate inflammation or liver disease course.MethodsWe used single cell RNA sequencing and 25-color flow cytometry to characterize cell populations in embryonic and postnatal liver in an ALGS mouse model (Jag1Ndr/Ndrmice). We analyzed liver cancer prevalence inJag1Ndr/Ndrmice, in a cancer-prone genetic background, and thymic and spleen cell composition using flow cytometry. Finally, to test the functionality of theJag1Ndr/Ndrimmune system we performed adaptive immune cell transfer experiments intoRag1-/mice and assessed inflammatory capacity in an ulcerative colitis model and in a DDC model of hepatocellular damage.ResultsAdultJag1Ndr/Ndrmice do not develop liver tumors (0%) while 45% of control mice do. Interestingly,Jag1Ndr/Ndrmice display ALGS-like chicken-wire hepatocellular fibrosis concomitant with mild inflammation shortly after the onset of liver cholestasis. Comprehensive single cell analysis revealed that liver CD4+and CD8+T cells ofJag1Ndr/Ndrmice are dysregulated in favor of CD4+, and Regulatory T-cells (Tregs) manifest reduced activation. Transplantation experiments show no difference betweenJag1Ndr/NdrandJag1+/+lymphocytes in DDC-induced liver damage. In contrast,Jag1Ndr/Ndrlymphocytes do not mount an inflammatory response to bacterial infection.ConclusionHere we report immune dysregulation and cancer protection in the hypomorphicJag1mouse model of ALGS. Disrupted thymocyte differentiation coincides with limited activation of hepatocytes, blunting the inflammatory response to cholestasis. This may contribute to the pericellular fibrosis and prevent carcinogenesis. These results prompt the question of the relative contribution of Jag1 to liver cell pathology vs immune system in ALGS and highlight the need of future studies focused on dissecting apart how Jag1 modulates susceptibility to infection versus cancer risk.

The presented paper deals with possible approaches to parallel implementation of solution of a hyper-dimensional dynamical particle system. The proposed implementation approaches are generally applicable for similar particle systems of interest in various research and engineering fields. The original motivation for the present work was a simulation of particles that represent a space-filling design to be optimized for further use in design of experiments. Due to the underlying purpose of this particle system, the dimension of the particle system of interest is considered to be entirely arbitrary. Such a hyper-dimensional space is further folded into a periodically repeated domain. The theoretical background of the proposed particle system is provided along with the derivation of equations of motion of the dynamical system. As the complexity of the system is not limited by the number of particles nor the number of dimensions, the possibilities of utilizing the GPGPU platform are more restricted in comparison with today’s fast parallel implementations of common particle systems. Two distinct approaches to parallel implementation are presented, one aiming at a generalized usage of the fast on-chip resources, the other entirely relying on the GPU’s on-board global memory. Despite unambiguous mutual differences in their performance, both parallel implementations deliver major speedup compared to the single-thread CPU solution as well as a better scaling of execution time when increasing both the number of particles and dimensions.

The presented paper investigates the effect of the formulation of the energy potential of a dynamical particle system used for the optimization of statistical point sampling. The dynamical particle system, originally developed as a physical analogy to the Audze-Eglajs (AE) optimization criterion and its periodical modification (PAE), effectively demonstrated that the originally proposed energy potential performs well only in poorly applicable scenarios featuring low-dimensional design domains filled with a rather high number of design points. A remedy is presented which involves a refined formulation of the energy potential, as well as its derivation. The reasoning behind this approach is also dealt with in detail.

The topic of the presented paper is a promising approach to achieve optimal Design of Experiment (DoE), i.e. spreading of points within a design domain, using a simulation of a discrete dynamical system of interacting particles within an n-dimensional design space. The system of mutually repelling particles represents a physical analogy of the Audze-Eglājs (AE) optimization criterion and its periodical modification (PAE), respectively. The paper compares the performance of two approaches to implementation: a single-thread process using the JAVA language environment and a massively parallel solution employing the nVidia CUDA platform.

The presented contribution aims at development of a new efficient tool for generating of uniformly distributed points within a convex domain. One of use-cases of these point sets is the usage as optimized sets of integration points in statistical analyses of computer models using Monte Carlo type integration. It is well known that the pursuit of uniformly distributed sets of integration points is the only possible way of decreasing the upper bound on error of estimation of an integral over an unknown function. The optimization tool is derived based on a notion of a physical analogy between a set of sampling points and a dynamical system of mutually repelling particles.

Cement-based composites are traditionally used building materials. Concrete is the basic representative of this type of materials which exhibit the so called quasi-brittle response. Quantification of mechanical fracture parameters is performed using fracture tests on specimens with a stress concentrator. Load versus crack mouth opening displacement (P–CMOD) diagrams are recorded during these tests. In order to correctly evaluate these diagrams, an advanced own developed software tool was used for the data filtering and appropriate modifications. In this paper, the programmed Java utility is generally introduced and its utilization demonstrated on the set of recorded P–CMOD diagrams, which are further evaluated using Double-K fracture model.

In this paper, the family of ϕp optimization criteria for space-filling designs is critically reviewed, with a focus on its behavior in moderate to large dimensions, especially for small sample sizes (low saturations of the design domain). Problems that arise during the standard use of the ϕp criteria for the optimization of point sets in standard hypercubic design domains are identified and adequate remedies are proposed. It is shown how the distance exponent in the distance-based criteria should be dependent on the domain dimension. In cases of small sample sizes, we propose utilizing multiple repetitions of a periodic hyper-toroidal domain. We show that the naive use of the ϕp criterion for the construction of optimized designs can produce undesired orthogonal grid patterns (either complete or incomplete). We show how this behavior is related to the directional non-uniformity of hypercubical volume considered in the objective function, and we propose a simple remedy that involves limiting the interaction to a rotationally symmetrical neighborhood. Use of the recently proposed minimum image convention may provide too crude an approximation of the full periodic extension of the design space. We propose that a finite but sufficiently large interaction radius be considered for the evaluation of the pairwise potential. The upper bound on the interaction radius can be set to contain a sufficient number of points within the periodically repeated domain. These enhancements are embodied in the proposed ψp criterion for space-filling designs. We show that the new criterion favors designs with better space-filling property, better projection properties and also with lower discrepancy. Euclidean distances among points within high-dimensional objects tend to concentrate and the resolution between distances decreases. We show that despite the decreasing contrast of distances, the desired resolution ability of the refined criterion is retained even when this isotropic metric is used.

The paper presents approaches to implementation of solution of discrete dynamical system of mutually repelling particles. Two platforms: a single-thread JAVA process and parallelized CUDA C solution, are employed for the dynamical simulation. Qualities of both platforms are discussed and explained as their performance when solving two proposed interaction laws is compared.

The unprecedented growth of today's cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS) for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT) technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city. publishedVersion

Internet of Things (IoT) is expected to become a driver in an emerging era of interconnected world through the advanced connectivity of smart devices, systems, and services. IoT goes beyond a broad range of Machine-to-Machine (M2M) communication technologies and covers a wide variety of networking protocols. There exist solutions like MQTT or SIP collecting data from sensors, CoAP for constrained devices and networks or XMPP for interconnecting devices and people. Also there is a plethora of standards and frameworks (OSGi, AllJoyn) bringing closer the paradigm of IoT vision. However, the main constraint of most existing platforms is their limited mutual interoperability. To this end, we provide a comprehensive description of protocols suitable to support the IoT vision. Further, we advocate an alternative approach to already known principles and employ the SIP protocol as a container for M2M data. We provide description of data structures and practical implementation principles of the proposed structures (JSON and Protocols Buffers are discussed in detail) transmitted by SIP as a promising enabler for efficient M2M communication in the IoT world. Our reported findings are based on extensive hands-on experience collected after the development of advanced M2M smarthome gateway in cooperation with the operator Telekom Austria Group. Internet of Things (IoT) is expected to become a driver in an emerging era of interconnected world through the advanced connectivity of smart devices, systems, and services. IoT goes beyond a broad range of Machine-to-Machine (M2M) communication technologies and covers a wide variety of networking protocols. There exist solutions like MQTT or SIP collecting data from sensors, CoAP for constrained devices and networks or XMPP for interconnecting devices and people. Also there is a plethora of standards and frameworks (OSGi, AllJoyn) bringing closer the paradigm of IoT vision. However, the main constraint of most existing platforms is their limited mutual interoperability. To this end, we provide a comprehensive description of protocols suitable to support the IoT vision. Further, we advocate an alternative approach to already known principles and employ the SIP protocol as a container for M2M data. We provide description of data structures and practical implementation principles of the proposed structures (JSON and Protocols Buffers are discussed in detail) transmitted by SIP as a promising enabler for efficient M2M communication in the IoT world. Our reported findings are based on extensive hands-on experience collected after the development of advanced M2M smarthome gateway in cooperation with the operator Telekom Austria Group.