A Class of Free Boundary Problems with Onset of a new Phase

A class of diffusion driven Free Boundary Problems is considered which is characterized by the initial onset of a phase and by an explicit kinematic condition for the evolution of the free boundary. By a domain fixing change of variables it naturally leads to coupled systems comprised of a singular parabolic initial boundary value problem and a Hamilton-Jacobi equation. Even though the one dimensional case has been thoroughly investigated, results as basic as well-posedness and regularity have so far not been obtained for its higher dimensional counterpart. In this paper a recently developed regularity theory for abstract singular parabolic Cauchy problems is utilized to obtain the first well-posedness results for the Free Boundary Problems under consideration. The derivation of elliptic regularity results for the underlying static singular problems will play an important role

Telling faults from cyber-attacks in a multi-modal logistic system with complex network analysis

We investigate the properties of systems of systems in a cybersecurity context by using complex network methodologies. We are interested in resilience and attribution. The first relates to the system's behavior in case of faults/attacks, namely to its capacity to recover full or partial functionality after a fault/attack. The second corresponds to the capability to tell faults from attacks, namely to trace the cause of an observed malfunction back to its originating cause(s). We present experiments to witness the effectiveness of our methodology considering a discrete event simulation of a multimodal logistic network featuring 40 nodes distributed across Italy and daily traffic roughly corresponding to the number of containers shipped through in Italian ports yearly averaged daily

Learning from, Understanding, and Supporting DevOps Artifacts for Docker

With the growing use of DevOps tools and frameworks, there is an increased need for tools and techniques that support more than code. The current state-of-the-art in static developer assistance for tools like Docker is limited to shallow syntactic validation. We identify three core challenges in the realm of learning from, understanding, and supporting developers writing DevOps artifacts: (i) nested languages in DevOps artifacts, (ii) rule mining, and (iii) the lack of semantic rule-based analysis. To address these challenges we introduce a toolset, binnacle, that enabled us to ingest 900,000 GitHub repositories. Focusing on Docker, we extracted approximately 178,000 unique Dockerfiles, and also identified a Gold Set of Dockerfiles written by Docker experts. We addressed challenge (i) by reducing the number of effectively uninterpretable nodes in our ASTs by over 80% via a technique we call phased parsing. To address challenge (ii), we introduced a novel rule-mining technique capable of recovering two-thirds of the rules in a benchmark we curated. Through this automated mining, we were able to recover 16 new rules that were not found during manual rule collection. To address challenge (iii), we manually collected a set of rules for Dockerfiles from commits to the files in the Gold Set. These rules encapsulate best practices, avoid docker build failures, and improve image size and build latency. We created an analyzer that used these rules, and found that, on average, Dockerfiles on GitHub violated the rules five times more frequently than the Dockerfiles in our Gold Set. We also found that industrial Dockerfiles fared no better than those sourced from GitHub. The learned rules and analyzer in binnacle can be used to aid developers in the IDE when creating Dockerfiles, and in a post-hoc fashion to identify issues in, and to improve, existing Dockerfiles.Comment: Published in ICSE'202

Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed.Comment: Submitted to Transactions on Vehicular Technologies, April 201

Life conditions for the elderly in the household sphere: aging and transferees in Montevideo-Uruguay

This work outlines the framework of the family configurations in which the elderly population of Montevideo lives as well as the transfers they are involved in. The main objective is to investigate how older people, who are recipients of a broad social protection system and have an economic situation relatively better than the younger groups, participate in the household intergenerational distribution dynamics. In order to achieve this goal, we elaborated a characterization of the households of the elderly, considering the life conditions, resources and service transfers in which they participate. The initial hypotheses is that socioeconomic inequality is the key to understand the transfer dynamics intra- and inter-households.187417120

A COBRA/TRAC, Best-Estimate Analysis of a Large-Break Accident in a PWR Equipped with Upper Head Injection

This report is about the Best-Estimate Analysis of a Large-Break Accident in a PWR Equipped with Upper Head Injection. It also documents about the simulation of a double ended (200 percent), cold leg break, loss-of-coolant accident in a PWR Equipped with Upper Head Injection

A COBRA/TRAC, Best-Estimate Analysis of a Large-Break Accident in a PWR Equipped with Upper Head Injection

This report is about the Best-Estimate Analysis of a Large-Break Accident in a PWR Equipped with Upper Head Injection. It also documents about the simulation of a double ended (200 percent), cold leg break, loss-of-coolant accident in a PWR Equipped with Upper Head Injection

Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability

Post-hoc model-agnostic interpretation methods such as partial dependence plots can be employed to interpret complex machine learning models. While these interpretation methods can be applied regardless of model complexity, they can produce misleading and verbose results if the model is too complex, especially w.r.t. feature interactions. To quantify the complexity of arbitrary machine learning models, we propose model-agnostic complexity measures based on functional decomposition: number of features used, interaction strength and main effect complexity. We show that post-hoc interpretation of models that minimize the three measures is more reliable and compact. Furthermore, we demonstrate the application of these measures in a multi-objective optimization approach which simultaneously minimizes loss and complexity

Effects of the blending ratio on the design of keratin/poly (Butylene succinate) nanofibers for drug delivery applications

In recent years there has been a growing interest in the use of proteins as biocompatible and environmentally friendly biomolecules for the design of wound healing and drug delivery sys-tems. Keratin is a fascinating protein, obtainable from several keratinous biomasses such as wool, hair or nails, with intrinsic bioactive properties including stimulatory effects on wound repair and excellent carrier capability. In this work keratin/poly (butylene succinate) blend solutions with functional properties tunable by manipulating the polymer blending ratios were prepared by using 1,1,1,3,3,3‐hexafluoroisopropanol as common solvent. Afterwards, these solutions doped with rho-damine B (RhB), were electrospun into blend mats and the drug release mechanism and kinetics as a function of blend composition was studied, in order to understand the potential of such mem-branes as drug delivery systems. The electrophoresis analysis carried out on keratin revealed that the solvent used does not degrade the protein. Moreover, all the blend solutions showed a non‐ Newtonian behavior, among which the Keratin/PBS 70/30 and 30/70 ones showed an amplified orientation ability of the polymer chains when subjected to a shear stress. Therefore, the resulting nan-ofibers showed thinner mean diameters and narrower diameter distributions compared to the Ker-atin/PBS 50/50 blend solution. The thermal stability and the mechanical properties of the blend elec-trospun mats improved by increasing the PBS content. Finally, the RhB release rate increased by increasing the keratin content of the mats and the drug diffused as drug‐protein complex