A Novel Generic Framework for Track Fitting in Complex Detector Systems

This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices through the experiment are also implemented as interchangeable modules. Different track parameterizations and extrapolation routines can be used simultaneously for fitting of the same physical track. Representations of detector hits are the third modular ingredient to the framework. The hit dimensionality and orientation of planar tracking detectors are not restricted. Tracking information from detectors which do not measure the passage of particles in a fixed physical detector plane, e.g. drift chambers or TPCs, is used without any simplifications. The concept is implemented in a light-weight C++ library called GENFIT, which is available as free software

Stabilization of high-order solutions of the cubic Nonlinear Schrodinger Equation

In this paper we consider the stabilization of non-fundamental unstable stationary solutions of the cubic nonlinear Schrodinger equation. Specifically we study the stabilization of radially symmetric solutions with nodes and asymmetric complex stationary solutions. For the first ones we find partial stabilization similar to that recently found for vortex solutions while for the later ones stabilization does not seem possible

Wiselib: A Generic Algorithm Library for Heterogeneous Sensor Networks

One unfortunate consequence of the success story of wireless sensor networks (WSNs) in separate research communities is an ever-growing gap between theory and practice. Even though there is a increasing number of algorithmic methods for WSNs, the vast majority has never been tried in practice; conversely, many practical challenges are still awaiting efficient algorithmic solutions. The main cause for this discrepancy is the fact that programming sensor nodes still happens at a very technical level. We remedy the situation by introducing Wiselib, our algorithm library that allows for simple implementations of algorithms onto a large variety of hardware and software. This is achieved by employing advanced C++ techniques such as templates and inline functions, allowing to write generic code that is resolved and bound at compile time, resulting in virtually no memory or computation overhead at run time. The Wiselib runs on different host operating systems, such as Contiki, iSense OS, and ScatterWeb. Furthermore, it runs on virtual nodes simulated by Shawn. For any algorithm, the Wiselib provides data structures that suit the specific properties of the target platform. Algorithm code does not contain any platform-specific specializations, allowing a single implementation to run natively on heterogeneous networks. In this paper, we describe the building blocks of the Wiselib, and analyze the overhead. We demonstrate the effectiveness of our approach by showing how routing algorithms can be implemented. We also report on results from experiments with real sensor-node hardware.Comment: 16 pages, 1 figure, 7 tables. Appears in European Conference on Wireless Sensor Networks (EWSN 2010

Liver transplantation in Romania

Institultul Clinic Fundeni-Clinica Chirurgie Generală și Transplant Hepatic “Dan Setlacec”, Al XI-lea Congres al Asociației Chirurgilor „Nicolae Anestiadi” din Republica Moldova și cea de-a XXXIII-a Reuniune a Chirurgilor din Moldova „Iacomi-Răzeșu” 27-30 septembrie 2011Analiza retrospectivă a 300 de transplanturi hepatice efectuate în Centrul de Chirurgie Generală și Transplant Hepatic “Dan Setlacec “.Retrospective analysis of 300 liver transplantation performed in General Surgery Center and Liver Transplantation “Dan Setlacec”

Defining Long-Term Survivors Following Resection of Intrahepatic Cholangiocarcinoma

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is an aggressive primary tumor of the liver. While surgery remains the cornerstone of therapy, long-term survival following curative-intent resection is generally poor. The aim of the current study was to define the incidence of actual long-term survivors, as well as identify clinicopathological factors associated with long-term survival. METHODS: Patients who underwent a curative-intent liver resection for ICC between 1990 and 2015 were identified using a multi-institutional database. Overall, 679 patients were alive with ≥ 5 years of follow-up or had died during follow-up. Prognostic factors among patients who were long-term survivors (LT) (overall survival (OS) ≥ 5) were compared with patients who were not non-long-term survivors (non-LT) (OS < 5). RESULTS: Among the 1154 patients who underwent liver resection for ICC, 5- and 10-year OS were 39.6 and 20.3% while the actual LT survival rate was 13.3%. After excluding 475 patients who survived  5 cm (OR 2.40, 95% CI, 1.54-3.74, p < 0.001), and direct invasion of an adjacent organ (OR 3.98, 95% CI, 1.18-13.4, p = 0.026). However, a subset of patients (< 10%) who had these pathological characteristics were LT. CONCLUSION: While ICC is generally associated with a poor prognosis, some patients will be LT. In fact, even a subset of patients with traditional adverse prognostic factors survived long term.info:eu-repo/semantics/publishedVersio

Proposed Modification of the Eighth Edition of the AJCC Staging System for Intrahepatic Cholangiocarcinoma

Background: To improve the prognostic accuracy of the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for intrahepatic cholangiocarcinoma (ICC) with establishment and validation of a modified TNM (mTNM) staging system. Methods: Data on patients who underwent curative-intent resection for ICC was collected from 15 high-volume centers worldwide (n = 643). An external validation dataset was obtained from the SEER registry (n = 797). The mTNM staging system was proposed by redefining T categories, and incorporating the recently proposed N status as N0 (no lymph node metastasis [LNM]), N1 (1-2 LNM) and N2 (≥3 LNM). Results: The 8th AJCC TNM staging system failed to stratify overall survival (OS) of stage II versus IIIA, stage IIIB versus IV, as well as overall stage III versus IV among all patients from the two databases, as well as stage I versus II, and stage III versus III among patients who had ≥6 LNs examined. There was a monotonic decrement in survival based on the proposed mTNM staging classification among patients derived from both the multi-institutional (Median OS, stage I 69.8 vs. II 37.1 vs. III 18.9 vs. IV 16.4 months, all p < 0.05), and SEER (Median OS, stage I 87.0 vs. II 29.3 vs. III 17.7 vs. IV 14.2 months, all p < 0.05) datasets, which was also verified among patients who had ≥6 lymph node harvested from both databases. Conclusion: The modified TNM staging system for ICC using the new T and N definitions provided an improved means to stratify patients relative to long-term OS versus the 8th AJCC staging.info:eu-repo/semantics/publishedVersio

The Multiscale Systems Immunology project: software for cell-based immunological simulation

<p>Abstract</p> <p>Background</p> <p>Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing.</p> <p>Results</p> <p>The Multiscale Systems Immunology (MSI) simulation framework is an object-oriented, modular simulation framework written in C++ and Python. The software implements a modular design that allows for flexible configuration of components and initialization of parameters, thus allowing simulations to be run that model processes occurring over different temporal and spatial scales.</p> <p>Conclusion</p> <p>MSI addresses the need for a flexible and high-performing agent based model of the immune system.</p

Survival after Resection of Multiple Tumor Foci of Intrahepatic Cholangiocarcinoma

Background: Multiple tumor foci of intrahepatic cholangiocarcinoma (ICC) are often considered a contra-indication for resection. We sought to define long-term outcomes after resection of ICC in patients with multiple foci. Methods: Patients who underwent resection for ICC between 1990 and 2017 were identified from 12 major HPB centers. Outcomes of patients with solitary lesions, multiple lesions (ML), and oligometastases (OM) were compared. OM were defined as extrahepatic metastases spread to a single organ. Results: One thousand thirteen patients underwent resection of ICC. On final pathology, 185 patients (18.4%) had ML and 27 (2.7%) had OM. Median survival of patients with a solitary tumor was 43.2 months, while the median survival of patients with 2 tumors was 21.2 months; the median survival of patients with 3 or more tumors was 15.3 months (p < 0.001). Five-year survival was 43.3%, 28.0%, and 8.6%, respectively. The median survival of patients without OM was 37.8 months versus 14.9 months among patients with OM (p < 0.001); estimated 5-year survival was 39.3% and 10.6%, respectively. In multivariable analysis, the presence of two lesions was not an independent poor prognostic factor for OS (HR 1.19; 95%CI 0.90-1.57; p = 0.229). However, the presence of three or more tumors was an independent poor prognostic factor for OS (HR 1.97; 95%CI 1.48-2.64; p < 0.001). Conclusion: Resection of multiple liver tumors for patients with ICC did not preclude 5-year survival: in particular, estimated 5-year OS for resection of two tumors was 28.0%.info:eu-repo/semantics/publishedVersio

Good governance as a strategic choice in brownfield regeneration: Regional dynamics from the Czech Republic

The application of principles of good governance in brownfield regeneration, for instance through improved transparency and participation of various groups of stakeholders, varies between regions and cities. In this article, we approach good governance as a strategic response of actors in the struggle for creating development opportunities on brownfield land. Good governance has been mostly seen as a normative consideration, but it is not clear why regions with lower development prospects would employ it more than better developed regions, as it recently happened in the Czech Republic. We assume that the public administration at the regional and municipal level plays an active role in divising strategies to attract investors for brownfield redevelopment. This process brings public administrations in interaction with each other and with investors, regulators and civil society groups within a society-wide brownfield redevelopment field. This field is an arena where all these different actors struggle for redeveloping their brownfield land. Regional and municipal administrations from developed regions stand to benefit from their higher economic growth potential and hence have a dominant position within the field. We identify the latter as the incumbents or “power-holders” of the national brownfield regeneration field. Less developed regions have lower attractiveness for brownfield redevelopment, which places them in a subordinate position in the field. They are so-called challengers that are likely to favor alternative strategies for their brownfields, going beyond mere economic attractiveness. By comparing differently developed regions and regional capitals in the Czech Republic, we show how some challengers use good governance, such as responsiveness, participation and transparency, as an alternative strategy to attract investors despite their economic predicament. For regional capitals, however, good governance is practiced both by highly developed and less developed cities. We draw evidence from interviews with key stakeholders and socio-economic data at the regional and municipal level in the Czech Republic. In the conclusion, we show some of the identified limitations in good governace, such as obstacles to participation, responsiveness or transparency, and how they can be recognized and overcome

Subependymal giant cell astrocytomas are characterized by mTORC1 hyperactivation, a very low somatic mutation rate, and a unique gene expression profile

Subependymal giant-cell astrocytomas (SEGAs) are slow-growing brain tumors that are a hallmark feature seen in 5–10% of patients with Tuberous Sclerosis Complex (TSC). Though histologically benign, they can cause serious neurologic symptoms, leading to death if untreated. SEGAs consistently show biallelic loss of TSC1 or TSC2. Herein, we aimed to define other somatic events beyond TSC1/TSC2 loss and identify potential transcriptional drivers that contribute to SEGA formation. Paired tumor-normal whole-exome sequencing was performed on 21 resected SEGAs from 20 TSC patients. Pathogenic variants in TSC1/TSC2 were identified in 19/21 (90%) SEGAs. Copy neutral loss of heterozygosity (size range: 2.2–46 Mb) was seen in 76% (16/21) of SEGAs (44% chr9q and 56% chr16p). An average of 1.4 other somatic variants (range 0–7) per tumor were identified, unlikely of pathogenic significance. Whole transcriptome RNA-sequencing analyses revealed 190 common differentially expressed genes in SEGA (n = 16, 13 from a prior study) in pairwise comparison to each of: low grade diffuse gliomas (n = 530) and glioblastoma (n = 171) from The Cancer Genome Atlas (TCGA) consortium, ganglioglioma (n = 10), TSC cortical tubers (n = 15), and multiple normal tissues. Among these, homeobox transcription factors (TFs) HMX3, HMX2, VAX1, SIX3; and TFs IRF6 and EOMES were all expressed >12-fold higher in SEGAs (FDR/q-value < 0.05). Immunohistochemistry supported the specificity of IRF6, VAX1, SIX3 for SEGAs in comparison to other tumor entities and normal brain. We conclude that SEGAs have an extremely low somatic mutation rate, suggesting that TSC1/TSC2 loss is sufficient to drive tumor growth. The unique and highly expressed SEGA-specific TFs likely reflect the neuroepithelial cell of origin, and may also contribute to the transcriptional and epigenetic state that enables SEGA growth following two-hit loss of TSC1 or TSC2 and mTORC1 activation