Interactive software for estimating the efficacy of non-isothermal heat preservation processes

The most commonly used methods to generate microbial inactivation curves are based on the assumptions that microbial mortality follows first order kinetics and that the temperature effect on the 'D value' or exponential rate constant is determined by the log linear model or the Arrhenius equation, respectively. However, many bacterial cells and spores follow the Weibull-Log Logistic (WeLL) model and software to simulate pasteurization and sterilization processes using this model has been available for some years as free downloadable programs written in MS Excel. According to this model, an organism's heat resistance parameters are T(c), a marker of the temperature level where the inactivation accelerates, k, the steepness of the Weibullian rate parameter in the lethal regime where T>T(c) and n, a measure of the semi logarithmic isothermal survival curve's concavity and its direction. Because the traditional first order kinetics is just a special case of the Weibullian model with n=1.0, the software is applicable to both linear and non-linear inactivation. Recently, Wolfram Research Inc., the maker of Mathematica, has made its interactive program Mathematica Player free downloadable software. A user, who need not have a copy of Mathematica, can view and download any of the numerous graphic demonstrations from the Wolfram Demonstrations Project web site, and continuously manipulate their dynamic parameters with sliders on the screen. One set of five such demonstrations allows the user to generate and adjust the temperature profile of heat processes, modify the targeted organism's Weibullian survival parameters and immediately observe the corresponding semi-logarithmic survival curve and the equivalent time at a reference temperature, which can also be manipulated by a slider. This free program enables food microbiologists, technologists and engineers to examine a large number of heat processing options and assess their potential safety implications. It can also serve as a training and educational tool in industry and academia.     

ZnO Nanoplatelets with Controlled Thickness: Atomic Insight into Facet-Specific Bimodal Ligand Binding Using DNP NMR

Colloidal nanoplatelets (NPLs) and nanosheets with controlled thickness have recently emerged as an exciting new class of quantum-sized nanomaterials with substantially distinct optical properties compared to 0D quantum dots. Zn-based NPLs are an attractive heavy-metal-free alternative to the so far most widespread cadmium chalcogenide colloidal 2D semiconductor nanostructures, but their synthesis remains challenging to achieve. The authors describe herein, to the best of their knowledge, the first synthesis of highly stable ZnO NPLs with the atomically precise thickness, which for the smallest NPLs is 3.2 nm (corresponding to 12 ZnO layers). Furthermore, by means of dynamic nuclear polarization-enhanced solid-state ¹⁵N NMR, the original role of the benzamidine ligands in stabilizing the surface of these nanomaterials is revealed, which can bind to both the polar and non-polar ZnO facets, acting either as X- or L-type ligands, respectively. This bimodal stabilization allows obtaining hexagonal NPLs for which the surface energy of the facets is modulated by the presence of the ligands. Thus, in-depth study of the interactions at the organic–inorganic interfaces provides a deeper understanding of the ligand–surface interface and should facilitate the future chemistry of stable-by-design nano-objects.     

Adaptive method of 5-axis milling of sculptured surfaces elements with a curved line contour

Journal of Mechanical Science and Technology - In this paper, an attempt to develop a new adaptive method of controlling the axis orientation of a toroidal milling cutter (leading angle α)...     

Correction to: A Comparative Study of Mechanical Properties,Thermal Conductivity,Residual Stresses,and Wear Resistance of Aluminum-Alumina Composites Obtained by Squeeze Casting and Powder Metallurgy

Metallurgical and Materials Transactions A -     

Threat intelligence platform for the energy sector

In recent years, critical infrastructures and power systems in particular have been subjected to sophisticated cyberthreats, including targeted attacks and advanced persistent threats. A promising response to this challenging situation is building up enhanced threat intelligence (TI) that interlinks information sharing and fine-grained situation awareness. In this paper, a framework that integrates all levels of TI, ie, strategic, tactical, operational, and technical, is presented. The platform implements the centralized model of information exchange with peer-to-peer interactions between partners as an option. Several supportive solutions were introduced, including anonymity mechanisms or data processing and correlation algorithms. A data model that enables communication of cyberincident information, both in natural language and machine-readable formats, was defined. Similarly, security requirements for critical components were devised. A pilot implementation of the platform was developed and deployed in the operational environment, which enabled practical evaluation of the design. Also, the security of the anonymity architecture was analyzed.     

Stone–Wales Defect in Graphene

2D graphene the most investigated structures from nanocarbon family studied in the last three decades. It is projected as an excellent material useful for quantum computing, artificial intelligence, and next generation advanced technologies. Graphene exists in several forms and its extraordinary thermal, mechanical, and electronic properties, principally depend on the kind of perfection of the hexagonal atomic lattice. Defects are always considered as undesired components but certain defects in graphene could be an asset for electrochemistry and quantum electronics due to the engineered electronclouds and quantum tunnelling. The authors carefully discuss the Stone-Wales imperfections in graphene and its derivatives comprehensively. A specific emphasis is focused on the experimental and theoretical aspects of the Stone-Wales defects in graphene with respect to structure-property relationships. The corroboration of extrinsic defects like external atomic doping, functionalization, edge distortion in the graphene consisting of Stone-Wales imperfections, which are very significant in designing graphene-based electronic devices, are summarized.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.