Finite element evaluation of free-edge singular stress fields in anisotropic materials

A finite element formulation based on the work of Yamada and Okumura¹⁴ is presented to determine the order of singularity and angular variation of the stress and displacement fields surrounding a singular point on a free edge of anisotropic materials. Emphasis is placed on the computational aspects of this method when applied to configurations including fully bonded multi-material junctions intersecting a free edge as well as materials containing cracks intersecting a free edge. The study shows that the singularity of the three-dimensional stress field may be accurately determined with a relatively small number of elements only when a proper level of numerical integration is used. The method is applied to isotropic and orthotropic materials with a crack intersecting a free edge and an anisotropic three-material junction intersecting a free edge. The efficiency and accuracy of the method indicates it could be used to develop a numerical solution for the singular field that could in turn be used to create free-edge enriched finite elements.     

Site-Specific Isotopic Labeling (SSIL): Access to High-Resolution Structural and Dynamic Information in Low-Complexity Proteins

Remarkable technical progress in the area of structural biology has paved the way to study previously inaccessible targets. For example, large protein complexes can now be easily investigated by cryo-electron microscopy, and modern high-field NMR magnets have challenged the limits of high-resolution characterization of proteins in solution. However, the structural and dynamic characteristics of certain proteins with important functions still cannot be probed by conventional methods. These proteins in question contain low-complexity regions (LCRs), compositionally biased sequences where only a limited number of amino acids is repeated multiple times, which hamper their characterization. This Concept article describes a site-specific isotopic labeling (SSIL) strategy, which combines nonsense suppression and cell-free protein synthesis to overcome these limitations. An overview on how poly-glutamine tracts were made amenable to high-resolution structural studies is used to illustrate the usefulness of SSIL. Furthermore, we discuss the potential of this methodology to give further insights into the roles of LCRs in human pathologies and liquid–liquid phase separation, as well as the challenges that must be addressed in the future for the popularization of SSIL.     

Macrocell corrosion of steel in concrete: Characterization of anodic behavior in relation to the chloride content

This study presents the determination of electrochemical properties of active steel in mortar, based on inverse numerical modeling that focuses on their dependency on chloride content. An experimental campaign, consisting of galvanic coupling tests between anode samples contaminated with different chloride concentrations and cathode samples without chlorides, was carried out. Cathode polarization tests allowed for directly determining passive steel electrochemical parameters. Anode polarization tests coupled with a numerical optimization were then performed for quantifying active steel parameters and focusing on chloride's effect on the iron anodic Tafel coefficient. Furthermore, the steel electrochemical properties were successfully used as input parameters to model the galvanic experiments.     

Collision Avoidance Using a Cerebellar Model Arithmetic Computer Neural Network

Avoiding collisions with obstacles in a clustered environment is a difficult task for autonomous vehicles. Deterministic algorithms cannot address all scenarios encountered and may fail to perform in dynamically changing environments. Neural networks, owing to their ability to map complex relationships between multiple input-output patterns, can learn the task of maneuvering around and in-between obstacles to reach a goal state. The Cerebellar Model Arithmetic Computer (CMAC) neural network in particular is based on a model of human sensory motor responses and can efficiently model responsive control actions. A CMAC neural network controller was developed and examined, in simulation, for its suitability to capture a driver's function of steering and braking. The performance of the controller was tested in a simulation of a moving platform (vehicle) encountering obstacles of various shapes, whereas the CMAC was trained only with limited shapes and scenarios. Preliminary simulation results have shown the CMAC's ability to successfully generalize its learned patterns to avoid obstacles after only a few training sessions. The CMAC output is generated in a computationally efficient manner with physically and economically realizable memory sizes. Therefore, real-time hardware implementation of the controller is feasible. This research demonstrates that the method has the ability to accommodate more complex scenarios.     

Wireless Dual Stimuli Actuation of Dye Sensitized Conducting Polymer Hybrids

Actuators controlled by external stimuli have received a lot of attention in recent years. Herein a polymer based dual stimuli actuator is reported, triggered by light and an electric field. This allows better control of actuation, enlarging the field of potential applications, like, for example, in the frame of soft robotics. The actuator is composed of polypyrrole and TiO₂ modified with methylene blue. In an aqueous solution, the resulting freestanding hybrid film shows reversible actuation due to the synergy of light and an applied electric field. Illumination with light produces electron-hole pairs in the TiO₂ layer, which are shuttled to the opposite ends of the actuator by the potential gradient present in the solution. This results in electrochemical oxidation and reduction reactions at the two extremities and consequently in site selective swelling of the polymer, which finally leads to a controlled motion of the actuator, following the principles of logic gate operations. Such synergistically induced switching allows developing original actuation schemes for performing complex mechanical tasks triggered by more than one stimulus.     

Linear-Space Data Structures for Range Mode Query in Arrays

A mode of a multiset S is an element a∈S of maximum multiplicity; that is, a occurs at least as frequently as any other element in S. Given an array A[1:n] of n elements, we consider a basic problem: constructing a static data structure that efficiently answers range mode queries on A. Each query consists of an input pair of indices (i,j) for which a mode of A[i:j] must be returned. The best previous data structure with linear space, by Krizanc, Morin, and Smid (Proceedings of the International Symposium on Algorithms and Computation (ISAAC), pp. 517–526, 2003), requires \(\varTheta (\sqrt{n}\log\log n)\) query time in the worst case. We improve their result and present an O(n)-space data structure that supports range mode queries in \(O(\sqrt{n/\log n})\) worst-case time. In the external memory model, we give a linear-space data structure that requires \(O(\sqrt{n/B})\) I/Os per query, where B denotes the block size. Furthermore, we present strong evidence that a query time significantly below \(\sqrt{n}\) cannot be achieved by purely combinatorial techniques; we show that boolean matrix multiplication of two \(\sqrt{n} \times \sqrt{n}\) matrices reduces to n range mode queries in an array of size O(n). Additionally, we give linear-space data structures for the dynamic problem (queries and updates in near O(n ^3/4) time), for orthogonal range mode in d dimensions (queries in near O(n ^1?1/2d ) time) and for half-space range mode in d dimensions (queries in \(O(n^{1-1/d^{2}})\) time). Finally, we complement our dynamic data structure with a reduction from the multiphase problem, again supporting that we cannot hope for much more efficient data structures.     

BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

The presence of antipatterns can have a negative impact on the quality of a program. Consequently, their efficient detection has drawn the attention of both researchers and practitioners. However, most aspects of antipatterns are loosely specified because quality assessment is ultimately a human-centric process that requires contextual data. Consequently, there is always a degree of uncertainty on whether a class in a program is an antipattern or not. None of the existing automatic detection approaches handle the inherent uncertainty of the detection process. First, we present BDTEX (Bayesian Detection Expert), a Goal Question Metric (GQM) based approach to build Bayesian Belief Networks (BBNs) from the definitions of antipatterns. We discuss the advantages of BBNs over rule-based models and illustrate BDTEX on the Blob antipattern. Second, we validate BDTEX with three antipatterns: Blob, Functional Decomposition, and Spaghetti code, and two open-source programs: GanttProject v1.10.2 and Xerces v2.7.0. We also compare the results of BDTEX with those of another approach, DECOR, in terms of precision, recall, and utility. Finally, we also show the applicability of our approach in an industrial context using Eclipse JDT and JHotDraw and introduce a novel classification of antipatterns depending on the effort needed to map their definitions to automatic detection approaches.     

Photodegradation of CL-20: insights into the mechanisms of initial reactions and environmental fate

Hexanitrohexaazaisowurtzitane (HNIW) or CL-20 is a caged structure polycyclic nitramine that may replace RDX and HMX as a common use energetic chemical. To provide insight into the environmental fate of CL-20 we photolyzed the chemical in a Rayonet photoreactor (254-350 nm) and with sunlight in aqueous solutions. Previously, we found that initial photodenitration of the monocyclic nitramine RDX leads to ring cleavage and decomposition. Presently, we found that photolysis of the rigid molecule CL-20 produced NO2-, NO3-, NH3, HCOOH, N2 and N2O. Using LC/MS (ES-) we detected several key intermediates carrying important information on the initial steps involved in the degradation of CL-20. The identities of the intermediates were confirmed using a uniformly ring labeled 15N-[CL-20]. When CL-20 was photolyzed in the presence of H2(18)O, D2O or 18O2 we obtained a product distribution suggesting that the energetic chemical degraded via at least two initial routes; one involved sequential homolysis of N-NO2 bond(s) and another involved photorearrangement prior to hydrolytic ring cleavage and decomposition in water.