Evolution of the structure and mechanical performance of Cansas-II SiC fibres after thermal treatment

Herein, an in-depth analysis of the effect of heat treatment at temperatures between 900 and 1500 °C under an Ar atmosphere on the structure as well as strength of Cansas-II SiC fibres was presented. The untreated fibres are composed of β-SiC grains, free carbon layers, as well as a small amount of an amorphous SiC_xO_y phase. As the heat-treatment temperature was increased to 1400 °C, a significant growth of the β-SiC grains and free carbon layers occurred along with the decomposition of the SiC_xO_y phase. Moreover, owing to the decomposition of the SiC_xO_y phase, some nanopores formed on the fibre surface upon heating at 1500 °C. The mean strength of the Cansas-II fibres decreased progressively from 2.78 to 1.20 GPa with an increase in the heat-treatment temperature. The degradation of the fibre strength can be attributed to the growth of critical defects, β-SiC grains, as well as the residual tensile stress.     

Synthesis and characterization of superoleophobic fumed alumina nanocomposite coated via the sol-gel process onto ceramic-based hollow fibre membrane for oil-water separation

Oily wastewater treatment is a global challenge due to the substantial amount of effluent resulted from many industrial and domestic activities. To overcome the challenge of using existing treatment approach and fouling, superoleophobic coatings were fabricated. In this study, a superoleophobic membrane surface was obtained using the sol-gel technique with perfluorooctanoate (PFO), poly (diallyl dimethylammonium chloride) (PDADMAC), and nanoparticles as complex-polymer nanocomposites. The effects of coating cycles on the surface structure, chemical properties, surface chemistry, and oleophobicity of the surface were examined using field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and oil contact angle measurement. The results showed that the coated layer successfully adhered to the substrate surface. However, the chemical stability with respect to oil contact angle (OCA) revealed a decline at pH 7 and pH 9 and maintained stability at pH 3. Besides, oil flux at 63.0 L/m². h was achieved for PDADMAC-Al₂O₃/44 wt% PFO and the highest separation efficiency of 98% was obtained. Furthermore, the oil rejection decreases as the oil concentration increases from 1 to 3 g/L. OCA of 155° was obtained after 5 coating cycles. Apart from mitigating substrate fouling, the superoleophobic and superhydrophilic coating can be applied to a ceramic-based hollow fibre membrane and efficiently used for the separation of oil from oily wastewater.     

The effect of rice bran on physicochemical,textural and glycaemic properties of ready-to-eat extruded corn snacks

In this work, corn extruded snack products were enriched with rice bran (RB) at 10% and 15%. A co-rotating twin-screw extruder was used with a feed moisture content of 16 g 100 g⁻¹, a screw speed of 240 r.p.m. and four heating sections of the barrel (100, 140, 150 and 150 °C). The impact of RB inclusion on nutritional profile, starch digestion, physicochemical and textural properties of snack products was evaluated. RB-enriched extrudates showed a lower specific volume and hardness and higher crispness than control. RB at 15% gave a water-holding capacity lower than control. Rheology of extrudate dispersions indicated an increase in elastic interactions and solid-like behaviour with RB supplementation. Differences in rheological properties resulted in attenuation of predictive glycaemic response for RB-enriched snacks.     

Physicochemical and technological properties of beef burger as influenced by the addition of pea fibre

This study aimed to evaluate the physicochemical characteristics and sensory attributes of beef burgers with the addition of pea fibre as a partial substitute of meat or fat. Three formulations were prepared: control (CON) – similar to the commercial formulation; fibre/less meat (FLM)—5% meat reduction and addition of 1% pea fibre; fibre/less fat (FLF)—7% fat reduction and addition of 1% pea fibre. Non-significant differences were obtained for pH, colour parameters (L* and b*), texture profile, cooking loss and size reduction among formulations. Moreover, sensory analysis with consumers of beef burgers did not indicate differences among the formulations for all the analysed attributes. Therefore, pea fibre is a promising partial replacer for meat and fat in beef burgers due to the preservation of technological parameters and sensory acceptance.     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Recent Biophysical Issues About the Preparation of Solute-Filled Lipid Vesicles

Here we report some recent biophysical issues on the preparation of solute-filled lipid vesicles and their relevance to the construction of “synthetic cells.” First, we introduce the “semi-synthetic minimal cells” as the liposome-based cell-like systems, which contain a minimal number of biomolecules required to display simple and complex biological functions. Next, we focus on recent aspects related to the construction of synthetic cells. Emphasis is given to the interplay between the methods of synthetic cell preparation and the physics of solute encapsulation. We briefly introduce the notion of structural and compositional “diversity” in synthetic cell populations.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L⁻¹). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.     

Toughness enhancement and equivalent initial fracture toughness of cementitious composite reinforced with aligned steel fibres

Based on theoretical analysis and numerical simulation, the impact of steel fibres on the stress intensity factor (SIF) at the crack tip for cementitious composite was studied. The enhanced toughness of steel fibre reinforced cementitious composite (SFRC) in resisting cracks was explained by the decrement of SIF caused by steel fibre inclusions at the crack tip of the composite. The equivalent initial fracture toughness was used to characterize the crack initiation of SFRC. A simplified method for determining the of SFRC was proposed based on a linear regression method. Fracture tests were conducted on three‐point bending notched beams with different steel fibre volume fractions and specimen sizes to study the crack initiation behaviour of aligned steel fibre reinforced cementitious composite (ASFRC). of ASFRC was calculated, and the size effect of was analysed. The results showed that slightly increased with the steel fibre volume fraction and gradually became stable. For the tested specimens, whose heights varied between 40 and 100 mm, the specimen size had little impact on the .