Crack arrest in steels

This paper examines 3 theories that have been used to characterize the arrest capabilities of steels and structures: (1) The static analysis, arrest toughness ($\text{K}{}_{\mathrm{Ia}}$) theory; (2) The dynamically loaded/stationary crack toughness ($\text{K}{}_{\mathrm{Id}}$) theory, and (3) The dynamic analysis, propagating crack energy or toughness ($\text{R}{}_{\mathrm{ID}}$ or $\text{K}{}_{\mathrm{ID}}$) theory. These three concepts are examined in the light of measurements of unstable fracture and crack arrest in wedge-loaded DCB test pieces together with a fully dynamic analysis of the experiments.     

The Structure of Infinite Solutions of Marked and Binary Post Correspondence Problems

In the infinite Post Correspondence Problem an instance (h,g) consists of two morphisms h and g, and the problem is to determine whether or not there exists an infinite word ω such that h(ω) = g(ω). This problem is undecidable in general, but it is known to be decidable for binary and marked instances. A morphism is binary if the domain alphabet is of size 2, and marked if each image of a letter begins with a different letter. We prove that the solutions of a marked instance form a set E^ω ⋃ E^* (P ⋃ F), where P is a finite set of ultimately periodic words, E is a finite set of solutions of the PCP, and F is a finite set of morphic images of fixed points of D0L systems. We also establish the structure of infinite solutions of the binary PCP.     

Carbon nanotubes as electrodes for dielectrophoresis of DNA

Dielectrophoresis can potentially be used as an efficient trapping tool in the fabrication of molecular devices. For nanoscale objects, however, the Brownian motion poses a challenge. We show that the use of carbon nanotube electrodes makes it possible to apply relatively low trapping voltages and still achieve high enough field gradients for trapping nanoscale objects, e.g., single molecules. We compare the efficiency and other characteristics of dielectrophoresis between carbon nanotube electrodes and lithographically fabricated metallic electrodes, in the case of trapping nanoscale DNA molecules. The results are analyzed using finite element method simulations and reveal information about the frequency-dependent polarizability of DNA.     

Digital Predistortion for 5G Small Cell: GPU Implementation and RF Measurements

In this paper, we present a high data rate implementation of a digital predistortion (DPD) algorithm on a modern mobile multicore CPU containing an on-chip GPU. The proposed implementation is capable of running in real-time, thanks to the execution of the predistortion stage inside the GPU, and the execution of the learning stage on a separate CPU core. This configuration, combined with the low complexity DPD design, allows for more than 400 Msamples/s sample rates. This is sufficient for satisfying 5G new radio (NR) base station radio transmission specifications in the sub-6 GHz bands, where signal bandwidths up to 100 MHz are specified. The linearization performance is validated with RF measurements on two base station power amplifiers at 3.7 GHz, showing that the 5G NR downlink emission requirements are satisfied.

     

Semi-supervised context adaptation: case study of audience excitement recognition

To recognise just the same human reaction (for example, a strong excitement) in different contexts, customary behaviours in these contexts have to be taken into account; e.g. a happy sport audience may be cheering for long time, while a happy theatrical audience may produce only short bursts of laughter in order to not interrupt the performance. Tailoring recognition algorithms to contexts can be achieved by building either a context-specific or a generic system. The former is individually trained for each context to recognise sets of characteristic responses, whereas the latter??in contrast to the context-specific one??adapts to the context via significantly more lightweight modification of parameters. This paper follows the latter way and proposes a simple modification of a hidden Markov model (HMM) classifier that enables end users to adapt the generic system to a context or a personal perception of an annotator by labelling a fairly small number of data samples of each context. For better adaptability to the limited number of the user??s annotations, the proposed semi-supervised HMM classifier employs the maximum posterior marginal, rather than the more conventional maximum a posteriori decision rule. The proposed user- and context-adaptable semi-supervised HMM classifier was tested on recognising excitement of a show audience in three contexts (a concert hall, a circus, and a sport event), differing in how the excitement is expressed. In our experiments the proposed classifier recognised reactions of a non-neutral audience with 10% higher accuracy than the conventional HMM and support vector machine based classifiers.     

Electrochemical Monitoring of Nickel(II) in Mine Water

This paper presents preliminary results in the development of a method for rapid real-time monitoring of Ni(II) in mine water. A simple electrochemical approach using a differential pulse voltammetry was developed and demonstrated by analysis of real samples.     

Synthesis of Hand Clapping Sounds

We present two physics-based analysis, synthesis, and control systems for synthesizing hand clapping sounds. They both rely on the separation of the sound synthesis and event generation, and both are capable of producing individual hand-claps, or mimicking the asynchronous/synchronized applause of a group of clappers. The synthesis models consist of resonator filters, whose coefficients are derived from experimental measurements. The difference between these systems is mainly in the statistical event generation. While the first system allows an efficient parametric synthesis of large audiences, as well as flocking and synchronization by simple rules, the second one provides parametric extensions for synthesis of various clapping styles and enhanced control strategies. The synthesis and the control models of both systems are implemented as software running in real time at the audio sample rate, and they are available for download at at http://ccrma-www.stanford.edu/software/stk and http://www.acoustics.hut.fi/go/clapd     

Complexation of Ni(II) by Dimethylglyoxime for Rapid Removal and Monitoring of Ni(II) in Water

The complexation of Ni(II) with dimethylglyoxime (DMG) entrapped within a Nafion membrane and a DMG–sol–gel matrix was studied and compared for different solutions. First and pseudo-second order kinetic models, Elovich, intra-particle, and liquid film diffusion models were applied to evaluate sorption kinetics. Complexation of Ni(II) by DMG entrapped in the polymeric materials followed a pseudo-second order kinetic model; moreover, DMG in Nafion also allowed diffusion-controlled uptake. The pseudo-second order rate constant was significantly higher for the free ligand in solution than for Ni(II) accumulation in the surface-attached DMG-Nafion. The DMG–sol–gel removal ability of Ni(II) was tested using actual mine water. The presence of interferences only insignificantly decreased the removal percentage of Ni(II), thus confirming the high selectivity of DMG towards Ni(II). Also, an electrochemical sensor modified with DMG in Nafion was investigated further for direct electrochemical determination of Ni(II) in untreated mine water. Determination errors and interference effects were low. Thus, this approach represents an effective potential solution for selective Ni(II) removal from mine water as well as a rapid and cheap sensor for on-site monitoring of Ni(II) in mine and environmental waters.