PHiLIP on the HiL: Automated Multi-Platform OS Testing With External Reference Devices

Developing an operating systems (OSs) for low-end embedded devices requires continuous adaptation to new hardware architectures and components, while serviceability of features needs to be assured for each individual platform under tight resource constraints. It is challenging to design a versatile and accurate heterogeneous test environment that is agile enough to cover a continuous evolution of the code base and platforms. This mission is even more challenging when organized in an agile open-source community process with many contributors such as for the RIOT OS. Hardware in the Loop (HiL) testing and Continuous Integration (CI) are automatable approaches to verify functionality, prevent regressions, and improve the overall quality at development speed in large community projects. In this paper, we present PHiLIP (Primitive Hardware in the Loop Integration Product), an open-source external reference device together with tools that validate the system software while it controls hardware and interprets physical signals. Instead of focusing on a specific test setting, PHiLIP takes the approach of a tool-assisted agile HiL test process, designed for continuous evolution and deployment cycles. We explain its design, describe how it supports HiL tests, evaluate performance metrics, and report on practical experiences of employing PHiLIP in an automated CI test infrastructure. Our initial deployment comprises 22 unique platforms, each of which executes 98 peripheral tests every night. PHiLIP allows for easy extension of low-cost, adaptive testing infrastructures but serves testing techniques and tools to a much wider range of applications.

Disulfide-compatible phage-assisted continuous evolution in the periplasmic space

The directed evolution of antibodies has yielded important research tools and human therapeutics. The dependence of many antibodies on disulfide bonds for stability has limited the application of continuous evolution technologies to antibodies and other disulfide-containing proteins. Here we describe periplasmic phage-assisted continuous evolution (pPACE), a system for continuous evolution of protein-protein interactions in the disulfide-compatible environment of the E. coli periplasm. We first apply pPACE to rapidly evolve novel noncovalent and covalent interactions between subunits of homodimeric YibK protein and to correct a binding-defective mutant of the anti-GCN4 Ω-graft antibody. We develop an intein-mediated system to select for soluble periplasmic expression in pPACE, leading to an eight-fold increase in soluble expression of the Ω-graft antibody. Finally, we evolve disulfide-containing trastuzumab antibody variants with improved binding to a Her2-like peptide and improved soluble expression. Together, these results demonstrate that pPACE can rapidly optimize proteins containing disulfide bonds, broadening the applicability of continuous evolution.

FRONTIER RESEARCH IN ASTROPHYSICS IN THE GRAVITATIONAL WAVE ERA – I

In this paper we will provide several examples that marked the continuous evolution on the knowledge of the physics of our Universe, updating our recent review (Giovannelli & Sabau-Graziati, 2019a). We want to emphasize that all the objects in our Universe are interdependent on each other, and that the classifications - that are usually made to simplify problems - are artificial, since nature evolves in all its manifestations continuously.

Detector-based component model abstraction for microservice-based systems

One of the chief problems in software architecture is avoiding architecture model drift and erosion in all kinds of complex software systems. Microservice-based systems introduce new challenges in this context, as they often use a large variety of technologies in their latest iteration, and are changed and released very frequently. Existing solutions that can be used to reconstruct architecture models fall short in addressing these new challenges, as they cannot easily cope with continuous evolution, their accuracy is too low, and highly polyglot settings are not supported well. In this work, we report on a research study aiming to design a highly accurate architecture model abstraction approach for comprehending component architecture models of highly polyglot systems that can cope with continuous evolution. After analyzing the results of related studies, we found two possible architecture model abstraction approaches that meet the requirements of our study: an opportunistic, and a reusable semi-automatic detector-based approach. We have conducted an empirical case study for validation and comparison of the two approaches. We conclude that both detector approaches are feasible. In our case study, the reusable approach breaks even in terms of time and effort needed for establishing reuse, if modest reuse of detectors is possible, and is producing slightly more high quality and evolution-stable solutions than the opportunistic approach.

Precision dynamical mapping using topological data analysis reveals a unique hub-like transition state at rest

Even in the absence of external stimuli, neural activity is both highly dynamic and organized across multiple spatiotemporal scales. The continuous evolution of brain activity patterns during rest is believed to help maintain a rich repertoire of possible functional configurations that relate to typical and atypical cognitive phenomena. Whether these transitions or "explorations" follow some underlying arrangement or instead lack a predictable ordered plan remains to be determined. Here, using a precision dynamics approach, we aimed at revealing the rules that govern transitions in brain activity at rest at the single participant level. We hypothesized that by revealing and characterizing the overall landscape of whole brain configurations (or states) we could interpret the rules (if any) that govern transitions in brain activity at rest. To generate the landscape of whole-brain configurations we used Topological Data Analysis based Mapper approach. Across all participants, we consistently observed a rich topographic landscape in which the transition of activity from one state to the next involved a central hub-like "transition state." The hub topography was characterized as a shared attractor-like basin where all canonical resting-state networks were represented equally. The surrounding periphery of the landscape had distinct network configurations. The intermediate transition state and traversal through it via a topographic gradient seemed to provide the underlying structure for the continuous evolution of brain activity patterns at rest. In addition, differences in the landscape architecture were more consistent within than between subjects, providing evidence of idiosyncratic dynamics and potential utility in precision medicine.