Inactivation of peroxidase and lipoxygenase in carrots, green beans, and green peas by combination of high hydrostatic pressure and mild heat treatment

The efficiency of high hydrostatic pressure (HHP) with the combination of mild heat treatment on peroxidase (POD) and lipoxygenase (LOX) inactivation in carrots, green beans, and green peas was investigated. In the first part of the study, the samples were pressurized under 250–450 MPa at 20–50 °C for 15–60 min. In the second part, two steps treatments were performed as water blanching at 40–70 °C for 15 and 30 min after pressurization at 250 MPa and 20 °C for 15–60 min. Carrot POD was decreased to 16% residual activity within the first 30 min at a treatment condition of 350 MPa and 20 °C and then it decreased to 9% at 60 min. When the carrots were water blanched at 50 °C for 30 min after HHP treatment of 250 MPa at 20 °C for 15 min, 13% residual POD activity was obtained. For green beans, the most effective results were obtained by two steps treatment and approximately 25% residual POD activity was obtained by water blanching at 50 °C for 15 min after pressurization at 250 MPa and 20 °C for 60 min. An effective inactivation of POD in green peas was not obtained. For carrots, LOX activity could not be measured due to very low LOX activity or the presence of strong antioxidants such as carotenoids. After pressurization at 250 MPa and 20 °C for 15 or 30 min, water blanching at 60 °C for 30 min provided 2–3% residual LOX activity in green beans. The treatment of 250 MPa for 30 min and then water blanching at 50 °C for 30 min provided 70% LOX inactivation in green peas.     

Fuzzy kernel feature selection with multi-objective differential evolution algorithm

In this paper, we propose a multi-objective differential evolution-based filter approach for feature selection that interconnects fuzzy- and kernel-based information theory measures to find feature subsets that are optimal responses to the targets. In contrast to the existing filter approaches using the principles of information theory and rough set theory, our approach can be applied to continuous datasets without discretisation. Moreover, our study is the first in the literature that employs fuzzy and kernel measures to form a filter criterion for feature selection, to our knowledge. We prove various favourable results using a variety of benchmark datasets and also demonstrate that our approach can better search the dimensionality space to reach maximum predictive of the response.     

Modeling and Predicting of News Popularity in Social Media Sources

The popularity of news, which conveys newsworthy events which occur during day to people, is substantially important for the spectator or audience. People interact with news website and share news links or their opinions. This study uses supervised learning based machine learning techniques in order to predict news popularity in social media sources. These techniques consist of basically two phrases: a) the training data is sent as input to the classifier algorithm, b) the performance of pre-learned algorithm is tested on the testing data. And so, a knowledge discovery from the data is performed. In this context, firstly, twelve datasets from a set of data are obtained within the frame of four categories: Economic, Microsoft, Obama and Palestine. Second, news popularity prediction in social network services is carried out by utilizing Gradient Boosted Trees, Multi-Layer Perceptron and Random Forest learning algorithms. The prediction performances of all algorithms are examined by considering Mean Absolute Error, Root Mean Squared Error and the R-squared evaluation metrics. The results show that most of the models designed by using these algorithms are proved to be applicable for this subject. Consequently, a comprehensive study for the news prediction is presented, using different techniques, drawing conclusions about the performances of algorithms in this study.     

Mechanical,hydrological and microstructural assessment of the durability of cemented paste backfill containing alkali-activated slag

The durability of full (FT) and deslimed sulphide-rich tailings (DT) cemented paste backfill (CPB) of alkali-activated slag (AAS; LSS–S: activated slag with aqueous sodium silicate and SH–S: activated slag with sodium hydroxide) was investigated based on the mechanical (strength), hydraulic and microstructural properties. DT and AAS improved the strength gain rate by decreasing the total- and macro porosity. DT and LSS–S configuration had a profound effect on strength development and produced 4.3–9.9-fold strengths than ordinary Portland cement (OPC) samples. DT also favoured the degree of cementation with dense packing matrix, decreased the permeability and thus, limited the adverse effects of acid and sulphate. DT hindered the decalcification of C–S–H leading to higher Ca/Si ratios for OPC while AAS samples exhibited approximately similar ratios over the curing period. SH–S led to drying shrinkage due to the greater amount of threshold pores. LSS–S/DT combination provided better durability performance in case of aggressive environments by improving the microstructure of CPB.     

All‐carbon hybrids for high performance supercapacitors

A hybrid nanostructure with partially reduced graphene oxide (rGO) and carbon nanofibers (CNFs) was fabricated and used as supercapacitor electrodes. A straightforward, environmentally friendly, and low‐cost microwave‐assisted reduction process was developed for the synthesis of rGO/CNF hybrid structures. The fabricated supercapacitor devices showed a specific capacitance of 95.3 F g^?1 and a superior long‐term cycling stability. A capacitance retention of more than 97% after 11 000 galvanostatic charge discharge cycles was obtained. These and other results reported in this paper indicate that high‐rate, all‐carbon, rGO/CNF hybrid nanostructures are highly promising supercapacitor electrode materials.     

Mechanical behavior of laser micro-machined bulk 6H–SiC diaphragms

Mechanical behavior of laser micro-machined monolithic hexagonal silicon carbide (6H–SiC) diaphragms was investigated to determine the effects of laser processing. Square diaphragms with a nominal size of 1.5 mm × 1.5 mm were fabricated from bulk 6H–SiC wafers using a Q-switched Nd:YAG laser operating at a wavelength of 1064 nm, an average power of 0.35W, a pulse repetition rate of 3 kHz, and a pulse width of 100 ns. These parameters were chosen, based on previous experiments, to minimize surface roughness. Analysis of laser-machined diaphragms revealed that the average thickness of a diaphragm was 151 μm which is composed of two layers. One is a soft, black layer with a thickness of about 83 μm consisting of silicon, oxygen, and carbon. The other layer was a hard, virgin SiC layer with a thickness of 68 μm. The diaphragms were subjected to micro-hardness indentation tests to obtain load versus deflection curves. The data was validated using Timoshenko’s analytical model for maximum deflection of a thin plate under concentrated loading with hinged and clamped boundary conditions. Experimental measurements of the deflection were found to be slightly higher than those predicted by the analytical model. The variations in the thickness of the diaphragms, homogeneity of the elastic properties of the laser micro-machined SiC, and possibly inappropriate boundary conditions during testing of the diaphragms chiefly account for the deviations between the experimental results and the analytical model.     

Vertically aligned carbon nanotube – Polyaniline nanocomposite supercapacitor electrodes

We develop a fast and cost effective method for the fabrication of a nanocomposite supercapacitor electrode. In this study aluminum foils were decorated with vertically aligned carbon nanotubes (VACNT) via chemical vapor deposition (CVD) method, which was followed by the electrodeposition of polyaniline (PANI) layer on top of the VACNTs. Electrochemical behavior of the fabricated nanocomposite electrodes were evaluated through cyclic voltammetry, galvanostatic charge discharge cycles and electrochemical impedance spectroscopy method. Fabricated VACNT/PANI nanocomposite electrodes through 15 electrodeposition cycles showed significant electrochemical performance. The specific capacity of these electrodes was calculated as 16.17 mF/cm² at a current density of 0.25 mA/cm².     

Biological hydrogen production from sugar beet molasses by agar immobilized R. capsulatus in a panel photobioreactor

Biohydrogen production from sugar beet molasses was investigated by using agar immobilized R. capsulatus YO3. A panel photobioreactor (1.4 L) was employed for a long-term hydrogen production in both indoor and outdoor conditions. The impact of several initial molasses concentrations on hydrogen production, yield and productivity were assessed. Indoor studies revealed that initial sucrose concentration in molasses should be kept below 20 mM to prevent inhibition of hydrogen production. The highest hydrogen productivity of 0.64 ± 0.06 mmol H₂ L^?1 h^?1 and yield of 12.2 ± 1.5 mol H₂/mol sucrose were obtained in indoors throughout 20 days of operation. For outdoors, hydrogen production continued for 40 days including consecutive 10 rounds under natural outdoor conditions. In outdoor conditions, the maximum hydrogen productivity and yield were 0.79 ± 0.04 mmol H₂ L^?1 h^?1 and 5.2 ± 0.4 mol H₂/mol sucrose respectively. These results indicate that the proposed system is promising for biohydrogen production from molasses at large-scale natural conditions.