Miscanthus stem fragment – Reinforced polypropylene composites: Development of an optimized preparation procedure at small scale and its validation for differentiating genotypes

The production of ligno-cellulosic biomass-based composites requires the development of new methodologies to evaluate the reinforcement potential of a given biomass, such as miscanthus studied in the work. Miscanthus stems from thirteen genotypes were broken into elongated fragments and mixed with polypropylene composites in an internal mixer. The aim is to find the best protocol able to discriminate miscanthus genotypes for their reinforcement capability. The following process parameters were optimized in order to maximize the reinforcement effect of the stem fragment filler: mixing parameters (mixing time, rotor speed and chamber temperature), temperature, fragment content, size and length distributions and coupling agent. The relationship between the process parameters and the mechanical properties of composites were analyzed to evaluate the influence of genotype on reinforcement performance, showing the robustness of the protocol in effectively discriminating genotypes according to their reinforcing capacity.     

Two-phase flow simulation for distinguishing deformable particles with a LiMCA system

In the metallurgical industry, Liquid Metal Cleanliness Analyser (LiMCA) commercial equipment cannot distinguish between hard particles (e.g., oxides, borides) and deformable particles (e.g., bubbles, molten salts). Therefore, hard particle concentrations can sometimes be grossly overestimated, which reduces the measurement accuracy. However, the method could potentially discriminate between deformable particles and hard particles by evaluating the particle's ability to deform. In this work, the coupled multiphysics problem of a particle deforming within current-carrying aluminium metal passing through the electric sensing zone (ESZ) is simulated using the conservative level-set (CLS) method. An emphasis is placed on understanding the transient deformation history, and the effect of the capillary number, Reynolds number, and confinement ratio on deformation are studied. Furthermore, a computational basis is given to estimate the influence of particle deformation on electrical resistance pulses (ERP). It is found that ERP features of deformation particles, including the peak magnitude and the pulse width, are different from those of hard particles. Based on the results, the effect of a particle's deformation and the feasibility to discriminate it from non-deformable particles in the LiMCA system is evaluated.     

Band gap engineering in silicene: A theoretical study of density functional tight-binding theory

In this work, we performed first principles calculations based on self-consistent charge density functional tight-binding to investigate different mechanisms of band gap tuning of silicene. We optimized structures of silicene sheet, functionalized silicene with H, CH₃ and F groups and nanoribbons with the edge of zigzag and armchair. Then we calculated electronic properties of silicene, functionalized silicene under uniaxial elastic strain, silicene nanoribbons and silicene under external electrical fields. It is found that the bond length and buckling value for relaxed silicene is agreeable with experimental and other theoretical values. Our results show that the band gap opens by functionalization of silicene. Also, we found that the direct band gap at K point for silicene changed to the direct band gap at the gamma point. Also, the functionalized silicene band gap decrease with increasing of the strain. For all sizes of the zigzag silicene nanoribbons, the band gap is near zero, while an oscillating decay occurs for the band gap of the armchair nanoribbons with increasing the nanoribbons width. At finally, it can be seen that the external electric field can open the band gap of silicene. We found that by increasing the electric field magnitude the band gap increases.     

A combined approach of Kullback–Leibler divergence and background subtraction for moving object detection in thermal video

In this work, a robust method for moving object detection in thermal video frames has been proposed by including Kullback–Leibler divergence (KLD) based threshold and background subtraction (BGS) technique. A trimmed-mean based background model has been developed that is capable enough to reduce noise or dynamic component of the background. This work assumed that each pixel has normally distributed. The KLD has computed between background pixel and a current pixel with the help of Gaussian mixture model. The proposed threshold is useful enough to classify the state of each pixel. The post-processing step uses morphological tool for edge linking, and then the flood-fill algorithm has applied for hole-filling, and finally the silhouette of targeted object has generated. The proposed methods run faster and have validated over various real-time based problematic thermal video sequences. In the experimental results, the average value of F₁-score, area under the curve, the percentage of correct classification, Matthew’s correlation coefficient show higher values whereas total error and percentage of the wrong classification show minimum values. Moreover, the proposed-1 method achieved higher accuracy and execution speed with minimum false alarm rate that has been compared with proposed-2 as well as considered peer methods in the real-time thermal video.     

Multi-multifractality,dynamic scaling and neighbourhood statistics in weighted planar stochastic lattice

The dynamics of random sequential partitioning of a square into ever smaller mutually exclusive rectangular blocks, which we call weighted planar stochastic lattice (WPSL), is governed by infinitely many conservation laws. Recently, we have shown one of the infinitely many conservation laws can be used as multifractal measure. In this article, we show that except the conservation of total area, each of the infinitely many non-trivial conservation laws is actually a multifractal measure and hence WPSL is a multi-multifractal. We then look at the block size distribution function and find that it exhibits dynamic scaling revealing that the spatial patterns of WPSL of different sizes are statistically self-similar. Besides, we investigate how the mean area ⟨A⟩_k of blocks with k neighbours and the average number of neighbours m_k of a typical cell that neighbours a k-sided block behaves with k. These results suggest that the Lewis law, ⟨A⟩_k∝k, is obeyed for up to k ≈ 8 and the Aboav–Weaire law, km_k∝k, is violated for the entire range of k.     

Recurrent and convolutional neural networks for deep terrain classification by autonomous robots

The future challenge for field robots is to increase the level of autonomy towards long distance (>1 km) and duration (>1h) applications. One of the key technologies is the ability to accurately estimate the properties of the traversed terrain to optimize onboard control strategies and energy efficient path-planning, ensuring safety and avoiding possible immobilization conditions that would lead to mission failure. Two main hypotheses are put forward in this research. The first hypothesis is that terrain can be effectively detected by relying exclusively on the measurement of quantities that pertain to the robot-ground interaction, i.e., on proprioceptive signals. Therefore, no visual or depth information is required. Then, artificial deep neural networks can provide an accurate and robust solution to the classification problem of different terrain types. Under these hypotheses, sensory signals are classified as time series directly by a Recurrent Neural Network or by a Convolutional Neural Network in the form of higher-level features or spectrograms resulting from additional processing. In both cases, results obtained from real experiments show comparable or better performance when contrasted with standard Support Vector Machine with the additional advantage of not requiring an a priori definition of the feature space.     

Synthesis and biotesting of new carrier prodrugs of 2-methoxyestradiol

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On the use of edge cracked short bend beam specimen for PMMA fracture toughness testing under mixed-mode I/II

In this paper an inclined edge cracked short beam specimen subjected to symmetric three-point bend loading was designed and examined for conducting mixed-mode I/II fracture toughness experiments. The aspect ratio (i.e. length to width ratio) and the loading span distance are considered much lower than the other conventional cracked bend beam samples. Crack tip parameters such as stress intensity factors and T-stress were computed numerically for this specimen by several finite element analyses and it was demonstrated that the specimen is able to produce full combinations of mode I and II including pure mode II. The practical capability of the short bend beam specimen was studied experimentally by conducting a set of mixed-mode fracture tests on PolymethylMethacrylate (PMMA) as a well-known model brittle material. The critical stress intensity factors, the direction of fracture kinking and the path of fracture trajectory were investigated both experimentally and theoretically using two stress and strain-based fracture criteria. The fracture toughness of tested PMMA was decreased by moving towards mode II case due to the effect of T-stress on the fracture mechanism of the short bend beam specimen.     

Catalytic activity of Pt and Pd in gaseous reactions of H2 and CH4 oxidation at low pressures

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