SISO Space Reference FOM - Tools and Testing

The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE

Pancreatic tumors imaging: an update

Currently, ultrasound (US), computed tomography (CT) and Magnetic Resonance imaging (MRI) represent the mainstay in the evaluation of pancreatic solid and cystic tumors affecting pancreas in 80-85% and 10-15% of the cases respectively. Integration of US, CT or MR imaging is essential for an accurate assessment of pancreatic parenchyma, ducts and adjacent soft tissues in order to detect and to stage the tumor, to differentiate solid from cystic lesions and to establish an appropriate treatment. The purpose of this review is to provide an overview of pancreatic tumors and the role of imaging in their diagnosis and management. In order to a prompt and accurate diagnosis and appropriate management of pancreatic lesions, it is crucial for radiologists to know the key findings of the most frequent tumors of the pancreas and the current role of imaging modalities. A multimodality approach is often helpful. If multidetector-row CT (MDCT) is the preferred initial imaging modality in patients with clinical suspicion for pancreatic cancer, multiparametric MRI provides essential information for the detection and characterization of a wide variety of pancreatic lesions and can be used as a problem-solving tool at diagnosis and during follow-up

Prognostic clinical factors in pretreated colorectal cancer patients receiving regorafenib: Implications for clinical management

Background: We assessed the impact on survival of angiogenesis and inflammation-related factors, particularly LDH serum levels, platelet, neutrophil and lymphocyte counts, and neutrophil-to-lymphocyte ratio (NLR), in metastatic colorectal cancer patients receiving regorafenib monotherapy. Methods: LDH serum levels, neutrophil, lymphocyte and platelet counts were collected at the start of regorafenib monotherapy. Cut-offvalues were calculated by ROC curve analysis. Survival analyses were performed by Kaplan-Meier method, and multivariate analysis by Cox method. Results: A total of 208 patients were eligible for analysis. Among factors who were related with worse overall survival and who maintained their role at the multivariate analysis, high platelet count (Exp(b):1.4963, 95% CI:1.0130-2.2103, p = 0.0439) and high neutrophil/lymphocyte ratio (Exp(b):1.6963, 95% CI:1.0757-2.6751, p = 0.0237) were those who more deeply were related to worse overall survival. High lymphocyte count (Exp(b):0.4527, 95% CI:0.2801-0.7316, p = 0.0013) was correlated with improved overall survival. Conclusions: High neutrophil, high platelet, low lymphocyte count and/or high NLR may represent negative prognostic factors in patients receiving regorafenib monotherapy. It is advisable that these factors are taken into account in the design of subsequent trials in colorectal cancer patients receiving this drug

Duration of oxaliplatin‐based adjuvant chemotherapy in patients with Stage III or high‐risk Stage II resected colon cancer

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The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses

QVRS; Nintedanib; Temps de deterioramentCVRS; Nintedanib; Tiempo para el deterioroHRQoL; Nintedanib; Time to deteriorationIntroduction We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results. Patients and Methods Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mean treatment difference averaged over time, using a mixed-effects growth curve model; mixed-effects models for repeated measurements (MMRM); time-to-deterioration (TTD); status change; and responder analysis) were used to analyze EORTC QLQ-C30 global health status (GHS)/QoL and scores from functional scales. Results Overall, GHS/QoL and physical functioning deteriorated over time. Mean treatment difference slightly favored nintedanib over placebo for physical functioning (adjusted mean, 2.66; 95% confidence interval [CI], 0.97-4.34) and social functioning (adjusted mean, 2.62; 95% CI, 0.66-4.47). GHS/QoL was numerically better with nintedanib versus placebo (adjusted mean, 1.61; 95% CI, −0.004 to 3.27). MMRM analysis had similar results, with better physical functioning in the nintedanib group at all timepoints. There was no significant delay in GHS/QoL deterioration (10%) and physical functioning (16%) with nintedanib versus placebo (TTD analysis). Status change analysis showed a higher proportion of patients with markedly improved GHS/QoL and physical functioning in the nintedanib versus placebo groups. Responder analysis showed a similar, less pronounced pattern. Conclusion Analyses of EORTC QLQ-C30 data showed that HRQoL was not impaired by treatment with nintedanib versus placebo. Analysis and interpretation of HRQoL endpoints should consider symptom type and severity and course of disease.This work was supported by Boehringer Ingelheim. Medical writing assistance, supported financially by Boehringer Ingelheim, was provided by Syneos Health Communications during the preparation of this manuscript