An Exactly Solvable Model for Nonlinear Resonant Scattering

This work analyzes the effects of cubic nonlinearities on certain resonant scattering anomalies associated with the dissolution of an embedded eigenvalue of a linear scattering system. These sharp peak-dip anomalies in the frequency domain are often called Fano resonances. We study a simple model that incorporates the essential features of this kind of resonance. It features a linear scatterer attached to a transmission line with a point-mass defect and coupled to a nonlinear oscillator. We prove two power laws in the small coupling \to 0 and small nonlinearity \to 0 regime. The asymptotic relation ~ C^4 characterizes the emergence of a small frequency interval of triple harmonic solutions near the resonant frequency of the oscillator. As the nonlinearity grows or the coupling diminishes, this interval widens and, at the relation ~ C^2, merges with another evolving frequency interval of triple harmonic solutions that extends to infinity. Our model allows rigorous computation of stability in the small and limit. In the regime of triple harmonic solutions, those with largest and smallest response of the oscillator are linearly stable and the solution with intermediate response is unstable

Why Modern Open Source Projects Fail

Open source is experiencing a renaissance period, due to the appearance of modern platforms and workflows for developing and maintaining public code. As a result, developers are creating open source software at speeds never seen before. Consequently, these projects are also facing unprecedented mortality rates. To better understand the reasons for the failure of modern open source projects, this paper describes the results of a survey with the maintainers of 104 popular GitHub systems that have been deprecated. We provide a set of nine reasons for the failure of these open source projects. We also show that some maintenance practices -- specifically the adoption of contributing guidelines and continuous integration -- have an important association with a project failure or success. Finally, we discuss and reveal the principal strategies developers have tried to overcome the failure of the studied projects.Comment: Paper accepted at 25th International Symposium on the Foundations of Software Engineering (FSE), pages 1-11, 201

Assurance of security and privacy requirements for cloud deployment models

Despite of the several benefits of migrating enterprise critical assets to the Cloud, there are challenges specifically related to security and privacy. It is important that Cloud Users understand their security and privacy needs, based on their specific context and select cloud model best fit to support these needs. The literature provides works that focus on discussing security and privacy issues for cloud systems but such works do not provide a detailed methodological approach to elicit security and privacy requirements neither methods to select cloud deployment models based on satisfaction of these requirements by Cloud Service Providers. This work advances the current state of the art towards this direction. In particular, we consider requirements engineering concepts to elicit and analyze security and privacy requirements and their associated mechanisms using a conceptual framework and a systematic process. The work introduces assurance as evidence for satisfying the security and privacy requirements in terms of completeness and reportable of security incident through audit. This allows perspective cloud users to define their assurance requirements so that appropriate cloud models can be selected for a given context. To demonstrate our work, we present results from a real case study based on the Greek National Gazette

Transient Thermal Analysis of Mixed-elastohydrodynamic Contact of High Performance Transmission in a Dry Sump Environment

Fuel efficiency is one of the main concerns in the optimisation of modern racing transmissions. The dry sump transmissions are the preferred choice for high performance racing applications. While it provides adequate lubricant for gear contacts, it minimises the system churning losses, and therefore enhances the system efficiency. An important aspect is assessing its thermal performance in removing the generated frictional heat. The generated heat in the highly loaded high shear contacts of racing transmissions should be dissipated through use of directed impinging oil jets and in an air–oil mist environment. The paper presents an integrated tribological and three-dimensional computational fluid dynamics analysis for a spur gear pair, incorporated into an overall finite element model to evaluate the quantity of generated heat and its removal rate from the rotating gear surfaces. Furthermore, the temperature distribution in the circumferential direction is predicted and used to evaluate transient temperature distribution over representative race laps. Such an approach has not hitherto been reported in literature

Effect of tapered roller bearing supports on the dynamic behaviour of hypoid gear pair differentials

Noise and vibration refinement and energy efficiency are the key drivers in powertrain development. The final drive (the differential) is a source of vibration concern and also contributes to the powertrain inefficiency. To optimise differential characteristics for the key objectives of refinement and efficiency, detailed models of the gear interactions as well as the support bearing dynamics are required. This study reports the integrated lubricated bearing and gear contacts with an eight-degree-of-freedom dynamic analysis (a tribo-dynamic model). Non-Newtonian shear behaviour of thin lubricant-film conjunctions is taken into account in the integrated tribo-dynamic analysis, which has not hitherto been reported in the literature. The results show that the transmitted vibration spectra from the system onto the differential casing are dominated by the bearing frequencies rather than by those due to the meshing of gears. It is also shown that a sufficiently high bearing preload improves the vibration refinement but can lead to a marginally reduced transmission efficiency

On the dynamics of a nonlinear energy harvester with multiple resonant zones

The dynamics of a nonlinear vibration energy harvester for rotating systems is investigated analytically through harmonic balance, as well as by numerical analysis. The electromagnetic harvester is attached to a spinning shaft at constant speed. Magnetic levitation is used as the system nonlinear restoring force for broadening the resonant range of the oscillator. The system is modelled as a Duffing oscillator with linear frequency variation under static, as well as harmonic excitation. Behaviour charts and backbone curves are extracted for the fundamental harmonic response and validated against frequency response curves for selected cases, using direct numerical integration. It is found that variation in stiffness, together with asymmetric forcing, gives rise to a novel structure of multiple resonant zones, incorporating mono-stable and bi-stable dynamics. Contrary to previously considered bi-stable energy harvesters, cross-well oscillations are realized through a transition from single-well potential energy to double-well with forward frequency sweep. Furthermore, in-well_oscillations present a hardening behaviour, unlike the well-known softening in-well response of bi-stable Duffing oscillators. The analysis shows that the proposed system has multiple resonant responses to a frequency sweep, influenced by consecutive interacting backbone curves similar to a multi-modal system. This combined effect of the transition to bi-stable dynamics and the hardening in-well oscillations induces resonant response of the harvester over multiple distinct frequency ranges. Thus, the system exhibits a broadened frequency response, enhancing its energy harvesting potential

A cross-sectional study of explainable machine learning in Alzheimer’s disease: diagnostic classification using MR radiomic features

IntroductionAlzheimer’s disease (AD) even nowadays remains a complex neurodegenerative disease and its diagnosis relies mainly on cognitive tests which have many limitations. On the other hand, qualitative imaging will not provide an early diagnosis because the radiologist will perceive brain atrophy on a late disease stage. Therefore, the main objective of this study is to investigate the necessity of quantitative imaging in the assessment of AD by using machine learning (ML) methods. Nowadays, ML methods are used to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers in the assessment of AD.MethodsIn this study radiomic features from both entorhinal cortex and hippocampus were extracted from 194 normal controls (NC), 284 mild cognitive impairment (MCI) and 130 AD subjects. Texture analysis evaluates statistical properties of the image intensities which might represent changes in MRI image pixel intensity due to the pathophysiology of a disease. Therefore, this quantitative method could detect smaller-scale changes of neurodegeneration. Then the radiomics signatures extracted by texture analysis and baseline neuropsychological scales, were used to build an XGBoost integrated model which has been trained and integrated.ResultsThe model was explained by using the Shapley values produced by the SHAP (SHapley Additive exPlanations) method. XGBoost produced a f1-score of 0.949, 0.818, and 0.810 between NC vs. AD, MC vs. MCI, and MCI vs. AD, respectively.DiscussionThese directions have the potential to help to the earlier diagnosis and to a better manage of the disease progression and therefore, develop novel treatment strategies. This study clearly showed the importance of explainable ML approach in the assessment of AD

Was sind negative Emissionen, und warum brauchen wir sie? Akademienprojekt ‘Energiesysteme der Zukunft’ (ESYS)

Selbst mit ambitionierteren Maßnahmen zur Vermeidung von Emissionen lässt sich Klimaneutralität und damit die Stabilisierung der Temperatur nicht mehr erreichen. Darauf weist der Weltklimarat in seinem sechsten Sachstandsbericht hin. Zusätzlich zu einer schnelleren Reduktion der Emissionen muss CO2 der Atmosphäre entzogen und anschließend eingelagert werden, um nicht vermeidbare Restemissionen auszugleichen, etwa aus der Landwirtschaft. Sogenannte „negative Emissionen“ können zum Beispiel durch Aufforstung erzeugt werden. Es gibt aber eine Reihe weiterer natürlicher und technischer Verfahren, den entnommenen Kohlenstoff dauerhaft einzulagern und aus der Atmosphäre fernzuhalten. In diesem „Kurz erklärt“ skizzieren Fachleute des Akademienprojekts ESYS den aktuellen Forschungsstand, erläutern Verfahren zur CO2-Entnahme und benennen deren jeweiligen Vor- und Nachteile