Stock-constrained truss design exploration through combinatorial equilibrium modeling

Reusing structural components has potential to reduce environmental impacts of building structures because it reduces new material use, energy consumption, and waste. When designing structures through reuse, available element characteristics become a design input. This paper presents a new computational workflow to design structures made of reused and new elements. The workflow combines Combinatorial Equilibrium Modeling, efficient Best-Fit heuristics, and Life Cycle Assessment to explore different design options in a user-interactive way and with almost real-time feedback. The method applicability is demonstrated by a realistic case study. Results show that structures combining reused and new elements have a significantly lower environmental impact than solutions made of new material only.

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families. Does successful inference mainly rely on correlations from structural contacts or from phylogeny, or both? Do these two types of signal combine constructively or hinder each other? To address these questions, we generate and analyze synthetic data produced using a minimal model that allows us to control the amounts of structural constraints and phylogeny. We show that correlations from these two sources combine constructively to increase the performance of partner inference by DCA or MI. Furthermore, signal from phylogeny can rescue partner inference when signal from contacts becomes less informative, including in the realistic case where inter-protein contacts are restricted to a small subset of sites. We also demonstrate that DCA-inferred couplings between non-contact pairs of sites improve partner inference in the presence of strong phylogeny, while deteriorating it otherwise. Moreover, restricting to non-contact pairs of sites preserves inference performance in the presence of strong phylogeny. In a natural dataset, as well as in realistic synthetic data based on it, we find that non-contact pairs of sites contribute positively to partner inference performance, and that restricting to them preserves performance, evidencing an important role of phylogeny.

MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

Automated deployment and run-time management of microservices-based applications in cloud computing environments is relatively well studied with several mature solutions. However, managing such applications and tasks in the cloud-to-edge continuum is far from trivial, with no robust, production-level solutions currently available. This paper presents our first attempt to extend an application-level cloud orchestration framework called MiCADO to utilise edge and fog worker nodes. The paper illustrates how MiCADO-Edge can automatically deploy complex sets of interconnected microservices in such multi-layered cloud-to-edge environments. Additionally, it shows how monitoring information can be collected from such services and how complex, user- defined run-time management policies can be enforced on application components running at any layer of the architecture. The implemented solution is demonstrated and evaluated using two realistic case studies from the areas of video processing and secure healthcare data analysis.

Intelligent Resource Management in the context of a Microgrid of Smart Buildings

This paper presents intelligent energy management with penetration of Distributed Generation (DG) and Electric Vehicles (EVs). The envisaged problem is a hard combinatorial Mixed-Integer Linear Programming (MILP) problem due to the continuous, discrete, and binary variables. The proposed problem focuses on minimizing the electricity cost. The MILP problem is modelled with a deterministic technique, namely TOMLAB, using a CPLEX solver. This paper includes a realistic case study using data collected from two real buildings facilities (consumption and generation profiles).

Epidemics on hypergraphs: spectral thresholds for extinction

Epidemic spreading is well understood when a disease propagates around a contact graph. In a stochastic susceptible–infected–susceptible setting, spectral conditions characterize whether the disease vanishes. However, modelling human interactions using a graph is a simplification which only considers pairwise relationships. This does not fully represent the more realistic case where people meet in groups. Hyperedges can be used to record higher order interactions, yielding more faithful and flexible models and allowing for the rate of infection of a node to depend on group size and also to vary as a nonlinear function of the number of infectious neighbours. We discuss different types of contagion models in this hypergraph setting and derive spectral conditions that characterize whether the disease vanishes. We study both the exact individual-level stochastic model and a deterministic mean field ODE approximation. Numerical simulations are provided to illustrate the analysis. We also interpret our results and show how the hypergraph model allows us to distinguish between contributions to infectiousness that (i) are inherent in the nature of the pathogen and (ii) arise from behavioural choices (such as social distancing, increased hygiene and use of masks). This raises the possibility of more accurately quantifying the effect of interventions that are designed to contain the spread of a virus.

Criminal Litigation

Criminal Litigation offers a guide to the areas of criminal litigation covered in the Legal Practice Course. Making use of realistic case studies backed up by online documentation, the text combines theory with practical considerations and encourages a focus on putting knowledge into a practical context. The volume covers all procedural and evidential issues that arise in criminal cases. The more complex areas of criminal litigation are examined using diagrams, flowcharts, and examples, while potential changes in the law are highlighted. This edition has been fully revised to reflect the most recent law and practice in all aspects of criminal litigation.

Formally-based Model-Driven Development of Collaborative Robotic Applications

The development of Human Robot Collaborative (HRC) systems faces many challenges. First, HRC systems should be adaptable and re-configurable to support fast production changes. However, in the development of HRC applications safety considerations are of paramount importance, as much as classical activities such as task programming and deployment. Hence, the reconfiguration and reprogramming of executing tasks might be necessary also to fulfill the desired safety requirements. Model-based software engineering is a suitable means for agile task programming and reconfiguration. We propose a model-based design-to-deployment toolchain that simplifies the routine of updating or modifying tasks. This toolchain relies on (i) UML profiles for quick model design, (ii) formal verification for exhaustive search for unsafe situations (caused by intended or unintended human behavior) within the model, and (iii) trans-coding tools for automating the development process. The toolchain has been evaluated on a few realistic case studies. In this paper, we show a couple of them to illustrate the applicability of the approach.

On the order reduction

In this work we present an extension of the technique of the order reduction to higher perturbative approximations in an iterative fashion. The intention is also to analyze more carefully the conditions for the validity of the order reduction technique. With this in mind, a few simple situations in which the iterative order reduction converges analytically to the exact solutions are presented as examples. It is discovered that the order reduction as a perturbative iterative technique does not converge in the weak coupling limit as most of the known perturbative schemes, at least when applied to these examples. Also, considering these specific examples, the convergence of the order reduction occurs in strong coupling regimes. As a more realistic case, the order reduction is applied to Starobinsky’s inflationary model is presented. It is verified that the method converges to the inflationary solution in the slow-roll regime.