A novel electromyographic signal simulator for muscle contraction studies

Mathematical simulation has been widely used in biomedical and biological sciences. In the case of the surface electromyographic (SEMG) activity, some models have been proposed aiming to study muscle contraction strategies that are used during different tasks and conditions. Most of SEMG simulators are based on energy modulation of a Gaussian noise. This work proposes a novel simulator in which the user-defined parameters are associated with the motor units (MUs) recruitment and their firing rate. Comparison between the mean spectrum of real SEMG signals collected in isometric contraction of the muscle biceps brachii and the mean spectrum obtained from simulated SEMG signals showed a good agreement, pointing the proposed simulator seems to be capable to generate consistent electromyographic signals in time and frequency domains and that can be used in many studies, in particular in the evaluation of automatic methods aimed to detect muscular contraction.     

Low-latency atomic broadcast in the presence of contention

The Atomic Broadcast algorithm described in this paper can deliver messages in two communication steps, even if multiple processes broadcast at the same time. It tags all broadcast messages with the local real time, and delivers all messages in the order of these timestamps. Both positive and negative statements are used: “m broadcast at time 51” vs. “no messages broadcast between times 31 and 51”. To prevent crashed processes from blocking the system, the -elected leader broadcasts negative statements on behalf of the processes it suspects () to have crashed. A new cheap Generic Broadcast algorithm is used to ensure consistency between conflicting statements. It requires only a majority of correct processes (n > 2f) and, in failure-free runs, delivers all non-conflicting messages in two steps. The main algorithm satisfies several new lower bounds, which are proved in this paper.     

Towards interactive simulation in automotive design

One of the important tasks in Mechanical Engineering is to increase the safety of the vehicle and decrease its production costs. This task is typically solved by means of Multiobjective Optimization, which formulates the problem as a mapping from the space of design variables to the space of target criteria and tries to find an optimal region in these multidimensional spaces. Due to high computational costs of numerical simulations, the sampling of this mapping is usually very sparse and scattered. Combining design of experiments methods, metamodeling, new interpolation schemes and innovative graphics methods, we enable the user to interact with simulation parameters, optimization criteria, and come to a new interpolated crash result within seconds. We denote this approach as Simulated Reality, a new concept for the interplay between simulation, optimization and interactive visualization. In this paper we show the application of Simulated Reality for solution of real life car design optimization problems.

Decomposition Approaches for Constrained Spatial Auction Market Problems

We consider several equilibrium formulations for the problem of managing spatially distributed auction markets of a homogeneous commodity, which are joined by transmission lines in a network. At each market, traders and buyers are determined by their price functions and choose their offer/bid values. We present equivalent variational inequality, optimization, and saddle point formulations of this problem. The corresponding models possess a special structure of constraint and cost functions and lead to different decomposition schemes. We propose proximal and splitting type methods and discuss their properties and preliminary computational results.     

On the robust control of nonlinear systems

In this paper we consider robust stabilization of the class of nonlinear plants of the form $$\dot x = f(x) + \sum\limits_{i = 1}^m {g_i } (x)u_i (t),$$ which are equivalent, under smooth state space coordinate transformations and nonlinear state feedback, to controllable systems. This approach is very sensitive for unknown parameters' values. Parameter adaptation may be used as a technique to robustify minimum-phase systems [3]. We give an example of a locally stable adaptive tracking system in which the last assumption is weakened. The minimum-phase plant considered in the paper is a current-controlled squirrel cage induction motor.     

The ortho-to-para conversion in solid hydrogen,catalyzed by hydrogen atoms

The combined techniques of ESR and NMR were used to investigate the process of ortho-para conversion in solid molecular hydrogen, containing small amounts ( 500 ppm) of hydrogen atoms as impurity. Although the impurity atoms catalyze the effective conversion of the neighboring ortho-H₂, the total catalyzed conversion rate at temperatures from 2.2 K to 4.4 K is much less than expected from the rate of the H atoms recombination. A possible explanation is given in terms of the diffusion of H atoms, which is confined to some defects in the crystal.     

Improving robustness of industrial object detection by automatic generation of synthetic images from CAD models

Object detection (OD) is used for visual quality control in factories. Images that compose training datasets are often collected directly from the production line and labeled with bounding boxes manually. Such data represent well the inference context but might lack diversity, implying a risk of overfitting. To address this issue, we propose a dataset construction method based on an automated pipeline, which receives a CAD model of an object and returns a set of realistic synthetic labeled images (code publicly available). Our approach can be easily used by non-expert users and is relevant for industrial applications, where CAD models are widely available. We performed experiments to compare the use of datasets obtained by the two different ways—collecting and labeling real images or applying the proposed automated pipeline—in the classification of five different industrial parts. To ensure that both approaches can be used without deep learning expertise, all training parameters were kept fixed during these experiments. In our results, both methods were successful for some objects but failed for others. However, we have shown that the combined use of real and synthetic images led to better results. This finding has the potential to make industrial OD models more robust to poor data collection and labeling errors, without increasing the difficulty of the training process.     

Strategies for electrosynthesis of poly(vinylbenzyltrimethylammonium chloride) and composite films

Poly(vinylbenzyl trimethyl ammonium chloride) (PVT) exhibits functional properties, which have generated interest in the fabrication of PVT and composite films. New electrochemical strategies have been utilized for the deposition of PVT-zirconia composites. The problems, related to the electrodeposition of strong polyelectrolytes, such as PVT, were addressed by the development of charge compensation mechanisms. The deposition strategies involved electrophoretic cathodic deposition (EPD) of PVT and EPD or electrochemical synthesis of zirconia. The proof of concept investigations involved deposition yield studies under different conditions, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential thermal analysis (DTA), and electron microscopy studies. The electrochemical strategies can be used for electrodeposition of various composites, utilizing the properties of functional polymers and inorganic materials.     

Noncontact Sonic NDE and Defect Imaging Via Local Defect Resonance

A selective acoustic activation of defects based on the concept of local defect resonance enables to enhance considerably the intensity of defect vibrations and makes it possible to reduce the input acoustic powers to the levels permissible for noncontact nondestructive inspection. Since for cm-size defects in composite materials, the LDR frequencies lie in the low kHz-range, the resonant noncontact activation shifts to an audible frequency range and can be provided by conventional sonic equipment. In this paper, the feasibility of the resonant noncontact inspection is validated for the most “problematic” methodologies of nonlinear, thermosonic and shearosonic NDE that usually require an elevated acoustic power and, therefore, a reliable contact between the specimen and the transducer. In contrast, the noncontact versions developed employ commercial loudspeakers which can simultaneously insonify large areas and be applied for a contactless sonic inspection of different materials and various scale components.     

Recommendation of RILEM Technical Committee 250-CSM: Test method for Textile Reinforced Mortar to substrate bond characterization

Textile Reinforced Mortar (TRM), also known as Fabric Reinforced Mortar or Fabric Reinforced Cementitious Matrix, composites are an emerging technology for the external repair and strengthening of existing structures. For most applications, the effectiveness of the TRM reinforcement relies on its bond performance. This recommendation identifies the best practice to characterize the bond behaviour of TRM. A shear bond test method is proposed to determine the peak axial stress (associated with the maximum load that can be transferred from the structural member to the externally bonded TRM reinforcement), the stress–slip relationship and the failure mode that controls the TRM-to-substrate load transfer capacity. Guidelines on specimen manufacturing, experimental setup, test execution, and determination of test results are provided.