Shakespeare vs. fletcher: A stylometric analysis by radial basis functions

In this paper we show, for the first time, how Radial Basis Function (RBF) network techniques can be used to explore questions surrounding authorship of historic documents. The paper illustrates the technical and practical aspects of RBF's, using data extracted from works written in the early 17th century by William Shakespeare and his contemporary John Fletcher. We also present benchmark comparisons with other standard techniques for contrast and comparison.David Lowe is Professor of Neural Computing at Aston University, UK. His research interests span from the theoretical aspects of dynamical systems theory and statistical pattern processing, to a wide range of application domains, from financial market analysis (Novel Exploitation of Neural Network Methods in Financial Markets, invited paper,World Conference on Computational Intelligence, vol. VI, pp. 3623–28, 1994) to the artificial nose (Novel Topographic Nonlinear Feature Extraction using Radial Basis Functions for Concentration Coding in the Artificial Nose,3 ^rd IEE International Conference on Artificial Neural Networks, pp. 95–99, Conference Publication number 372, The Institute of Electrical Engineers, 1993).Robert Matthews is a visiting research fellow at Aston University. His research interests include probability, number theory and astronomy. His recent paper inNature (vol. 374, pp. 681–82, 1995) somehow managed to combine all three.     

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.     

A Novel Magnetic Hardening Mechanism for Nd-Fe-B Permanent Magnets Based on Solid-State Phase Transformation

Permanent magnets based on neodymium-iron-boron (Nd-Fe-B) alloys provide the highest performance and energy density, finding usage in many high-tech applications. Their magnetic performance relies on the intrinsic properties of the hard-magnetic Nd₂Fe₁₄B phase combined with control over the microstructure during production. In this study, a novel magnetic hardening mechanism is described in such materials based on a solid-state phase transformation. Using modified Nd-Fe-B alloys of the type Nd₁₆Fe_bal-x-y-zCo_xMo_yCu_zB₇ for the first time it is revealed how the microstructural transformation from the metastable Nd₂Fe₁₇B_x phase to the hard-magnetic Nd₂Fe₁₄B phase can be thermally controlled, leading to an astonishing increase in coercivity from ≈200 kAm⁻¹ to almost 700 kAm⁻¹. Furthermore, after thermally treating a quenched sample of Nd₁₆Fe₅₆Co₂₀Mo₂Cu₂B₇, the presence of Mo leads to the formation of fine FeMo₂B₂ precipitates, in the range from micrometers down to a few nanometers. These precipitates are responsible for the refinement of the Nd₂Fe₁₄B grains and so for the high coercivity. This mechanism can be incorporated into existing manufacturing processes and can prove to be applicable to novel fabrication routes for Nd-Fe-B magnets, such as additive manufacturing.     

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.     

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...