An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, it results in an execution-time speedup between 1.5x and 5.1x. This speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline

Reverse Micelle Strategy for the Synthesis of MnOx-TiO2Active Catalysts for NH3-Selective Catalytic Reduction of NOxat Both Low Temperature and Low Mn Content

MnOx-TiO2catalysts (0, 1, 5, and 10 wt % Mn nominal content) for NH3-SCR (selective catalytic reduction) of NOxhave been synthesized by the reverse micelle-assisted sol-gel procedure, with the aim of improving the dispersion of the active phase, usually poor when obtained by other synthesis methods (e.g., impregnation) and thereby lowering its amount. For comparison, a sample at nominal 10 wt % Mn was obtained by impregnation of the (undoped) TiO2sample. The catalysts were characterized by using an integrated multitechnique approach, encompassing X-ray diffraction followed by Rietveld refinement, micro-Raman spectroscopy, N2isotherm measurement at −196 °C, energy-dispersive X-ray analysis, diffuse reflectance UV-vis spectroscopy, temperature-programmed reduction technique, and X-ray photoelectron spectroscopy. The obtained results prove that the reverse micelle sol-gel approach allowed for enhancing the catalytic activity, in that the catalysts were active in a broad temperature range at a substantially low Mn loading, as compared to the impregnated catalyst. Particularly, the 5 wt % Mn catalyst showed the best NH3-SCR activity in terms of both NOxconversion (ca. 90%) and the amount of produced N2O (ca. 50 ppm) in the 200-250 °C temperature range

Coordination and organometallic precursors of group 10 and 11 Focused electron beam induced deposition of metals and insight gained from chemical vapour deposition, atomic layer deposition, and fundamental surface and gas phase studies

Nanostructured materials made from group 10 Ni, Pd, Pt and group 11 Cu, Ag, Au elements have outstanding technological relevance in microelectronics, nano optics, catalysis, and energy conversion. Processes that allow for the easy and reliable fabrication of such nanostructures are heavily sought after. Focused electron beam induced deposition FEBID is the only direct write technique that can fabricate nanostructures with arbitrary shape and dimensions down to the sub 10 nm regime. However, the complex chemistry of FEBID involving electron induced dissociation processes of metalorganic precursors molecules, surface kinetics, and thermal effects is poorly understood and far from being optimized. Here, we review in a comparative manner the performance and the underlying chemical reactions of surface deposition processes, namely, chemical vapour deposition CVD , atomic layer deposition ALD , and FEBID itself. The knowledge gained in CVD and ALD as related surface deposition techniques will help us to understand the spatially selective chemistry occurring in FEBID. Fundamental surface and gas phase studies provide insight to electron induced chemistry and desorption of precursor fragments. Specific emphasis is put on the type of the ligands and their different behaviour under thermal, surface related, and electron induced processes. The comprehensive overview of the current state of FEBID for group 10 and 11 metals includes reactive environments and purification approaches as these may provide valuable information on the design of novel precursors. The evaluation of the precursor and process performance is extended to include W, Co, Fe, Ru, Rh, and Ir to represent a general guide towards future developments in FEBID. These may not only rely on the design of novel compounds but also on optimized deposition strategies inspired by ALD and CV

Pegasus: Performance Engineering for Software Applications Targeting HPC Systems

Developing and optimizing software applications for high performance and energy efficiency is a very challenging task, even when considering a single target machine. For instance, optimizing for multicore-based computing systems requires in-depth knowledge about programming languages, application programming interfaces, compilers, performance tuning tools, and computer architecture and organization. Many of the tasks of performance engineering methodologies require manual efforts and the use of different tools not always part of an integrated toolchain. This paper presents Pegasus, a performance engineering approach supported by a framework that consists of a source-to-source compiler, controlled and guided by strategies programmed in a Domain-Specific Language, and an autotuner. Pegasus is a holistic and versatile approach spanning various decision layers composing the software stack, and exploiting the system capabilities and workloads effectively through the use of runtime autotuning. The Pegasus approach helps developers by automating tasks regarding the efficient implementation of software applications in multicore computing systems. These tasks focus on application analysis, profiling, code transformations, and the integration of runtime autotuning. Pegasus allows developers to program their strategies or to automatically apply existing strategies to software applications in order to ensure the compliance of non-functional requirements, such as performance and energy efficiency. We show how to apply Pegasus and demonstrate its applicability and effectiveness in a complex case study, which includes tasks from a smart navigation system

Task and spatial frequency modulations of object processing: an EEG study.

Visual object processing may follow a coarse-to-fine sequence imposed by fast processing of low spatial frequencies (LSF) and slow processing of high spatial frequencies (HSF). Objects can be categorized at varying levels of specificity: the superordinate (e.g. animal), the basic (e.g. dog), or the subordinate (e.g. Border Collie). We tested whether superordinate and more specific categorization depend on different spatial frequency ranges, and whether any such dependencies might be revealed by or influence signals recorded using EEG. We used event-related potentials (ERPs) and time-frequency (TF) analysis to examine the time course of object processing while participants performed either a grammatical gender-classification task (which generally forces basic-level categorization) or a living/non-living judgement (superordinate categorization) on everyday, real-life objects. Objects were filtered to contain only HSF or LSF. We found a greater positivity and greater negativity for HSF than for LSF pictures in the P1 and N1 respectively, but no effects of task on either component. A later, fronto-central negativity (N350) was more negative in the gender-classification task than the superordinate categorization task, which may indicate that this component relates to semantic or syntactic processing. We found no significant effects of task or spatial frequency on evoked or total gamma band responses. Our results demonstrate early differences in processing of HSF and LSF content that were not modulated by categorization task, with later responses reflecting such higher-level cognitive factors

Nintedanib for non-IPF progressive pulmonary fibrosis: 12-month outcome data from a real-world multicentre observational study

Background: Nintedanib slows lung function decline for patients with non-IPF progressive pulmonary fibrosis (PPF) in clinical trials, but the real-world safety and efficacy are not known. Methods: In this retrospective cohort study, standardised data was collected across 8 UK centres from patients in whom nintedanib was initiated for PPF between 2019 and 2020 through an early access programme. Rate of lung function change in the 12 months pre- and post-nintedanib initiation was the primary analysis. Symptoms, drug safety, tolerability, and stratification by interstitial lung disease (ILD) subtype and CT pattern were secondary analyses. Results: 126 patients were included; 67(53%) females, mean age 60(±13) years. At initiation of nintedanib, mean FVC was 1.87 L (58%) and DLco 32.7% predicted. 68% of patients were prescribed prednisolone (median dose 10 mg) and 69% prescribed a steroid sparing agent. In the 12 months after nintedanib initiation, lung function decline was significantly lower than in the preceding 12 months; FVC −88.8 ml versus −239.9 ml respectively, (p=0.004) and absolute decline in DLco −2.1% versus −6.1% respectively; (p=0.004). Response to nintedanib was consistent in sensitivity and secondary analyses. 89/126 (71%) of patients reported side effects but 86 of the surviving 108 patients (80%) were still taking nintedanib at 12 months with patients reporting a reduced perception of symptom decline. There were no serious adverse events. Conclusion: In PPF, the real-world efficacy of nintedanib replicated that of clinical trials, significantly attenuating lung function decline. Despite the severity of disease, nintedanib was safe and well tolerated in this real-world multicentre stud

Influence of Deposition Parameters and Thermal Annealing on the Structure and Properties of Nitride Coatings (TiHfZrVNb)N

Results of structure, phase composition, physical and mechanical properties and tribological properties investigations of nitride high-entropy coatings (TiZrHfVNb)N are presented in the paper. Proton microbeam (m-PIXE), X-ray diffraction method, including method of X-ray strains measurements, energy dispersive X-ray spectroscopy and scanning electron microscopy analysis, microhardness testing and nanoindentation were used. Thermal annealing (t = 600 C) influence on defect profiles, structure and element distribution in the coatings was investigated. It was found that thermal treatment of coatings leads to changing of defect profiles and to element redistribution.Also we can say that it influences less on grain size changing. Investigated (TiZrHfVNb)N coatings demonstrate high values of hardness and excellent wear resistance