Thermal stability of substituted phenol-formaldehyde resins

A variety of crosslinked phenol-, or derivatized phenol-formaldehyde polymers have been synthesized. The phenol derivatives included o- and p-cresol, p-nonylphenol, m-pentadecylphenol, and raw and distilled cashew nutshell liquid. The derivatives were copolymerized with phenol and formaldehyde using sulfuric acid as catalyst to yield novolak-type prepolymers, which were then cured with hexamethylenetetramine. Thermogravimetric analysis was used to evaluate the thermal stability of the cured resins. It was found that the thermal stability of the resins decreased with increasing amounts of cashew nutshell liquid, with distilled cashew resins being slightly more thermally stable than raw cashew resins. The thermal stability of resins containing substituted phenols with alkyl chains was observed to increase from n-pentadecylphenol to cresol to phenol. The trend in thermal stability of the resins may be explained on the basis of alkyl groups being less thermally stable than aromatic rings. The amount of hexamethylenetetramine used to cure the prepolymers also influences the thermal stability of the resins. It appears that a level of 10 to 15% hexamethylenetetramine maximizes the thermal stability of the resin.     

Barium Metaplumbate Ceramic Electrodes for Ceramic Capacitors

A novel approach to reduce electrode costs in ceramic capacitors is presented. Barium metaplumbate (BaPbO₃) was fired onto sintered commercial (Ba, Sr)TiO₃ disk capacitors as external electrodes. Samples were compared to disk capacitors of the same composition with electrodes made of sputtered gold and air-dried silver. The ceramic electrode led to substantial changes in the insulation resistance and dc breakdown strengths, but other properties remained the same. The feasibility of using BaPbO₃ electrodes strongly depends on chemical reactions between the electrode and dielectric.     

Adaptive augmented Lagrangian methods: algorithms and practical numerical experience

In this paper, we consider augmented Lagrangian (AL) algorithms for solving large-scale nonlinear optimization problems that execute adaptive strategies for updating the penalty parameter. Our work is motivated by the recently proposed adaptive AL trust region method by Curtis et al. [An adaptive augmented Lagrangian method for large-scale constrained optimization, Math. Program. 152 (2015), pp. 201–245.]. The first focal point of this paper is a new variant of the approach that employs a line search rather than a trust region strategy, where a critical algorithmic feature for the line search strategy is the use of convexified piecewise quadratic models of the AL function for computing the search directions. We prove global convergence guarantees for our line search algorithm that are on par with those for the previously proposed trust region method. A second focal point of this paper is the practical performance of the line search and trust region algorithm variants in Matlab software, as well as that of an adaptive penalty parameter updating strategy incorporated into the Lancelot software. We test these methods on problems from the CUTEst and COPS collections, as well as on challenging test problems related to optimal power flow. Our numerical experience suggests that the adaptive algorithms outperform traditional AL methods in terms of efficiency and reliability. As with traditional AL algorithms, the adaptive methods are matrix-free and thus represent a viable option for solving large-scale problems.     

A deep bidirectional LSTM approach for video-realistic talking head

This paper proposes a deep bidirectional long short-term memory approach in modeling the long contextual, nonlinear mapping between audio and visual streams for video-realistic talking head. In training stage, an audio-visual stereo database is firstly recorded as a subject talking to a camera. The audio streams are converted into acoustic feature, i.e. Mel-Frequency Cepstrum Coefficients (MFCCs), and their textual labels are also extracted. The visual streams, in particular, the lower face region, are compactly represented by active appearance model (AAM) parameters by which the shape and texture variations can be jointly modeled. Given pairs of the audio and visual parameter sequence, a DBLSTM model is trained to learn the sequence mapping from audio to visual space. For any unseen speech audio, whether it is original recorded or synthesized by text-to-speech (TTS), the trained DBLSTM model can predict a convincing AAM parameter trajectory for the lower face animation. To further improve the realism of the proposed talking head, the trajectory tiling method is adopted to use the DBLSTM predicted AAM trajectory as a guide to select a smooth real sample image sequence from the recorded database. We then stitch the selected lower face image sequence back to a background face video of the same subject, resulting in a video-realistic talking head. Experimental results show that the proposed DBLSTM approach outperforms the existing HMM-based approach in both objective and subjective evaluations.     

Computing the Ramsey number R(4,3,3) using abstraction and symmetry breaking

The number R(4, 3, 3) is often presented as the unknown Ramsey number with the best chances of being found “soon”. Yet, its precise value has remained unknown for almost 50 years. This paper presents a methodology based on abstraction and symmetry breaking that applies to solve hard graph edge-coloring problems. The utility of this methodology is demonstrated by using it to compute the value R(4, 3, 3) = 30. Along the way it is required to first compute the previously unknown set \(\mathcal {R}(3,3,3;13)\) consisting of 78,892 Ramsey colorings.     

Infiltrating the zebrafish swarm: design,implementation and experimental tests of a miniature robotic fish lure for fish–robot interaction studies

Robotic fish are nowadays developed for various types of research, such as bio-inspiredrobotics, biomimetics and animal behavior studies. In the context of our research on the social interactions of the zebrafish Danio Rerio, we developed a miniature robotic fish lure for direct underwater interaction with the living fish. This remotely controlled and waterproof device has a total length of 7.5 cm with the same size ratio as zebrafish and is able to beat its tail with different frequencies and amplitudes, while following the group of living animals using a mobile robot moving outside water that is coupled with the robotic lure using magnets. The robotic lure is also equipped with a rechargeable battery and can be used autonomously underwater for experiments of up to 1 h. We performed experiments with the robot moving inside an aquarium with living fish to analyze its impact on the zebrafish behavior. We found that the beating rate of the tail increased the attractiveness of the lure among the zebrafish shoal. We also demonstrated that the lure could influence a collective decision of the zebrafish shoal, the swimming direction, when moving with a constant linear speed inside a circular corridor. This new robotic fish design and the experimental results are promising for the field of fish–robot interaction.     

Multigrid gradient vector flow computation on the GPU

Gradient vector flow (GVF) is a feature-preserving spatial diffusion of image gradients. It was introduced to overcome the limited capture range in traditional active contour segmentation. However, the original iterative solver for GVF, using Euler’s method, converges very slowly. Thus, many iterations are needed to achieve the desired capture range. Several groups have investigated the use of graphic processing units (GPUs) to accelerate the GVF computation. Still, this does not reduce the number of iterations needed. Multigrid methods, on the other hand, have been shown to provide a much better capture range using considerable less iterations. However, non-GPU implementations of the multigrid method are not as fast as the Euler method when executed on the GPU. In this paper, a novel GPU implementation of a multigrid solver for GVF written in OpenCL is presented. The results show that this implementation converges and provides a better capture range about 2–5 times faster than the conventional iterative GVF solver on the GPU.     

Adaptive water management in Israel: structure and policy options

Difficulties in integrating technical, economic and institutional factors present a major gap in analytical capacity to guide water policy. This article presents an integrated framework to support water policy and guide water management choices, with application to Israel. That framework rests on the theory of economic policy originally developed by Tinbergen. It sees national water challenges as consisting of external factors, constraints, policy instruments and targets. The need for a modern implementation of the theory of economic policy is motivated by emerging environmental requirements, scarce water, growing demands for domestic use, and ongoing needs to implement existing and potential peace agreements.     

SOA-enabled compliance management: instrumenting, assessing, and analyzing service-based business processes

Facilitating compliance management, that is, assisting a company’s management in conforming to laws, regulations, standards, contracts, and policies, is a hot but non-trivial task. The service-oriented architecture (SOA) has evolved traditional, manual business practices into modern, service-based IT practices that ease part of the problem: the systematic definition and execution of business processes. This, in turn, facilitates the online monitoring of system behaviors and the enforcement of allowed behaviors—all ingredients that can be used to assist compliance management on the fly during process execution. In this paper, instead of focusing on monitoring and runtime enforcement of rules or constraints, we strive for an alternative approach to compliance management in SOAs that aims at assessing and improving compliance. We propose two ingredients: (i) a model and tool to design compliant service-based processes and to instrument them in order to generate evidence of how they are executed and (ii) a reporting and analysis suite to create awareness of a company’s compliance state and to enable understanding why and where compliance violations have occurred. Together, these ingredients result in an approach that is close to how the real stakeholders—compliance experts and auditors—actually assess the state of compliance in practice and that is less intrusive than enforcing compliance.