Property preserving abstractions for the verification of concurrent systems

We study property preserving transformations for reactive systems. The main idea is the use of simulations parameterized by Galois connections (, ), relating the lattices of properties of two systems. We propose and study a notion of preservation of properties expressed by formulas of a logic, by a function mapping sets of states of a systemS into sets of states of a systemS'. We give results on the preservation of properties expressed in sublanguages of the branching time -calculus when two systemsS andS' are related via (, )-simulations. They can be used to verify a property for a system by verifying the same property on a simpler system which is an abstraction of it. We show also under which conditions abstraction of concurrent systems can be computed from the abstraction of their components. This allows a compositional application of the proposed verification method.This is a revised version of the papers [2] and [16]; the results are fully developed in [28].This work was partially supported by ESPRIT Basic Research Action REACT.Verimag is a joint laboratory of CNRS, Institut National Polytechnique de Grenoble, Université J. Fourier and Verilog SA associated with IMAG.     

Coherent Phonon-Induced Modulation of Charge Transfer in 2D Hybrid Perovskites

Electron–phonon interactions play an essential role in charge transport and transfer processes in semiconductors. For most structures, tailoring electron–phonon interactions for specific functionality remains elusive. Here, it is shown that, in hybrid perovskites, coherent phonon modes can be used to manipulate charge transfer. In the 2D double perovskite, (AE2T)₂AgBiI₈ (AE2T: 5,5“-diylbis(amino-ethyl)-(2,2”-(2)thiophene)), the valence band maximum derived from the [Ag_0.5Bi_0.5I₄]^2– framework lies in close proximity to the AE2T-derived HOMO level, thereby forming a type-II heterostructure. During transient absorption spectroscopy, pulsed excitation creates sustained coherent phonon modes, which periodically modulate the associated electronic levels. Thus, the energy offset at the organic–inorganic interface also oscillates periodically, providing a unique opportunity for modulation of interfacial charge transfer. Density-functional theory corroborates the mechanism and identifies specific phonon modes as likely drivers of the coherent charge transfer. These observations are a striking example of how electron–phonon interactions can be used to manipulate fundamentally important charge and energy transfer processes in hybrid perovskites.     

State of the Art of Molecular Visualization in Immersive Virtual Environments

Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head-mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.     

Enabling On-Demand Conformal Zn-Ion Batteries on Non-Developable Surfaces

Conventional power sources encounter difficulties in achieving structural unitization with complex-shaped electronic devices because of their fixed form factors. Here, it is realized that an on-demand conformal Zn-ion battery (ZIB) on non-developable surfaces uses direct ink writing (DIW)-based nonplanar 3D printing. First, ZIB component (manganese oxide-based cathode, Zn powder-based anode, and UV-curable gel composite electrolyte) inks are designed to regulate their colloidal interactions to fulfill the rheological requirements of nonplanar 3D printing, and establish bi-percolating ion/electron conduction pathways, thereby enabling geometrical synchronization with non-developable surfaces, and ensuring reliable electrochemical performance. The ZIB component inks are conformally printed on arbitrary curvilinear substrates to produce embodied ZIBs that can be seamlessly integrated with complicated 3D objects (including human ears). The conformal ZIB exhibits a high fill factor (i.e., areal coverage of cells on underlying substrates, ≈100%) that ensures high volumetric energy density (50.5 mWh cm_cell⁻³), which exceeds those of previously-reported shape-adaptable power sources.     

Simulation of Cortical and Cancellous Bone to Accelerate Tissue Regeneration

Different tissues have complex anisotropic structures to support biological functions. Mimicking these complex structures in vitro remains a challenge in biomaterials designs. Here, inspired by different types of silk nanofibers, a composite materials strategy is pursued toward this challenge. A combination of fabrication methods is utilized to achieve separate control of amorphous and beta-sheet rich silk nanofibers in the same solution. Aqueous solutions containing two types of silk nanofibers are simultaneously treated with an electric field and with ethylene glycol diglycidyl ether (EGDE). Under these conditions, the beta-sheet rich silk nanofibers in the mixture responded to the electric field while the amorphous nanofibers are active in the crosslinking process with the EGDE. As a result, cryogels with anisotropic structures are prepared, including mimics for cortical- and cancellous-like bone biomaterials as a complex osteoinductive niche. In vitro studies revealed that mechanical cues of the cryogels induced osteodifferentiation of stem cells while the anisotropy inside the cryogels influenced immune reactions of macrophages. These bioactive cryogels also stimulated improved bone regeneration in vivo through modulation of inflammation, angiogenesis and osteogenesis responses, suggesting an effective strategy to develop bioactive matrices with complex anisotropic structures beneficial to tissue regeneration.     

A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties

Optimization problems in software engineering typically deal with structures as they occur in the design and maintenance of software systems. In model-driven optimization (MDO), domain-specific models are used to represent these structures while evolutionary algorithms are often used to solve optimization problems. However, designing appropriate models and evolutionary algorithms to represent and evolve structures is not always straightforward. Domain experts often need deep knowledge of how to configure an evolutionary algorithm. This makes the use of model-driven meta-heuristic search difficult and expensive. We present a graph-based framework for MDO that identifies and clarifies core concepts and relies on mutation operators to specify evolutionary change. This framework is intended to help domain experts develop and study evolutionary algorithms based on domain-specific models and operators. In addition, it can help in clarifying the critical factors for conducting reproducible experiments in MDO. Based on the framework, we are able to take a first step toward identifying and studying important properties of evolutionary operators in the context of MDO. As a showcase, we investigate the impact of soundness and completeness at the level of mutation operator sets on the effectiveness and efficiency of evolutionary algorithms.

     

On measuring network robustness for weighted networks

Knowledge and Information Systems - Network robustness measures how well network structure is strong and healthy when it is under attack, such as vertices joining and leaving. It has been widely...     

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Journal of Intelligent Manufacturing - In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size,...     

Experience report on the application of genetic algorithms to reduce costs of the software validation process in the automotive sector during an engine control unit project

Software Quality Journal - The number of electronic control units (ECU) installed in vehicles is increasingly high. Manufacturers must improve the software quality and reduce cost by proposing...     

Ocular recognition databases and competitions: a survey

The use of the iris and periocular region as biometric traits has been extensively investigated, mainly due to the singularity of the iris features and the use of the periocular region when the image resolution is not sufficient to extract iris information. In addition to providing information about an individual’s identity, features extracted from these traits can also be explored to obtain other information such as the individual’s gender, the influence of drug use, the use of contact lenses, spoofing, among others. This work presents a survey of the databases created for ocular recognition, detailing their protocols and how their images were acquired. We also describe and discuss the most popular ocular recognition competitions (contests), highlighting the submitted algorithms that achieved the best results using only iris trait and also fusing iris and periocular region information. Finally, we describe some relevant works applying deep learning techniques to ocular recognition and point out new challenges and future directions. Considering that there are a large number of ocular databases, and each one is usually designed for a specific problem, we believe this survey can provide a broad overview of the challenges in ocular biometrics.