Effect of chemical phosphorylation on solubility of buffalo milk proteins

Buffalo milk proteins (casein, co-precipitate or whey protein concentrate) were phosphorylated with phosphorus oxychloride (POCl₃) at three different pH values (5.0, 7.0 and 9.0). The solubilities of phosphorylated milk proteins were examined over the pH range 3.0–9.0 in water and ionic (0.1 m NaCl or 10–70 mm Ca²⁺) systems. The solubilities of buffalo milk proteins decreased at pH 3.0, while there was an increase in the solubilities of casein and co-precipitate near their isoelectric points upon phosphorylation. Solubilities of these phosphorylated milk proteins were pH dependent in 0.1 m NaCl but there was a decrease in their solubilities with increase in calcium ion concentration. This alteration could be due to the shifting of isoionic points of phosphorylated buffalo milk proteins towards acidic pH.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

Analysis of a Novel Flux-Weakening Structure of High-Speed Permanent-Magnet Motors Based on Soft-Magnetic Ferrite

Soft-magnetic ferrite has advantages of high initial magnetic permeability, high electric resistivity, low loss and low cost in the high-frequency alternating field. Considering the characters of soft-magnetic ferrite, this paper uses a soft-magnetic ferrite ring as stator core and presents a novel field-weakening structure of high speed PM motors. Based on this structure, a novel field-weakening method of PM motors can be presented. The equivalent reluctance of permanent magnetic field circuit can be changed by altering saturation degree of soft-magnetic ferrite core in this method. For the convenience of analysis and calculation, considering the magnetic field distribution in the motors, this paper deduces an equivalent two-dimensional finite element model of three-dimensional magnetic field, by which the field-weakening parameters of high speed PM motor can be conveniently analyzed. The simulation results of finite element model prove: the field-weakening structure of high speed PM motor based on soft-magnetic ferrite, presented in this paper, is valid and feasible, offers a valid and applicative method for field-weakening control of high speed PM motor.     

Investigation of oil palm harvesting tools design and technique on work-related musculoskeletal disorders of the upper body

The oil palm industry is one of the important sectors in Malaysia. The growth and development of this industry shows that Malaysia is the world second-largest oil palm producers. However, in the fresh fruit bunch (FFB) harvesting process, the harvesters are exposed to many types of work-related musculoskeletal disorders (WMSDs). The FFB harvesters tend to develop WMSDs especially the shoulders and trunk. Hence, it is important to identify the exposure levels, awkward postures and the reaction forces of muscle activity based on the posture and movement of the harvesters when using pole, chisel and loading spike during the harvesting process. The objective of this study was to investigate the effect of the design of oil palm FFB harvesting tools on WMSDs of the upper body. Rapid Upper Limb Analysis (RULA) was used to investigate and assess the exposure level on the harvester body during the harvesting process. The assessment showed that the shoulders and trunk have high exposure level and undergo awkward posture. Human Musculoskeletal Model Analysis (HMMA) was used to identify the reaction force exerted on the muscle during the FFB harvesting process. In this study, 4 muscles were analysed including Triceps, Biceps, Erector Spinae and Psoas Major. The highest reaction force of 16.36 N was found on the left triceps when handling a loading spike. In conclusion, it is important to address the risks by reviewing all possible aspects that contribute to the WMSDs and interventions on the tool design, task and working shifts may be required.     

Transformation of hardening to softening behaviors induced by Sb substitution in CuO-doped KNN-based piezoceramics

Pb-free piezoceramics of K_0.5Na_0.5Nb_1-xSb_xO₃ + 1 mol% CuO are synthesized via a solid-state reaction. Furthermore, the transformation of hardening to softening behaviors induced by Sb substitution is exhibited and the corresponding microscopic mechanism is proposed. The CuO-doped K_0.5Na_0.5NbO₃ ceramic without adding Sb exhibits extremely hardening characteristics (i.e., ultrahigh Q_m of ∼2426, low tanδ of 0.32%, and pinched ferroelectric hysteresis loop) due to the formation of defect combinations (${({\text{Cu}}_{\text{Nb}}^{\text{'''}}-{\text{V}}_{\text{o}}^{••})}^{\text{'}}$ and ${({\text{V}}_{\text{o}}^{••}-{\text{Cu}}_{\text{Nb}}^{\text{'''}}-{\text{V}}_{\text{o}}^{••})}^{•}$). Whereas, the addition of Sb dramatically reduces the levels of defect combinations, leading to obviously softening properties (d₃₃ > 210 pC N⁻¹, k_p > 40%, low Q_m, and normal single P-E hysteresis loop). Our results indicate that the decrease of defect combinations with Sb addition should be responsible for the hardening-softening transformation of piezoelectricity and ferroelectricity in CuO-doped K_0.5Na_0.5Nb_1-xSb_xO₃ piezoceramics.     

Ni–Nb–O mixed oxides as highly active and selective catalysts for ethene production via ethane oxidative dehydrogenation. Part I: Characterization and catalytic performance

This work demonstrates the high potential of a new class of catalytic materials based on nickel for the oxidative dehydrogenation of ethane to ethylene. The developed bulk Ni–Nb–O mixed oxides exhibit high activity in ethane ODH and very high selectivity (∼90% ethene selectivity) at low reaction temperature, resulting in an overall ethene yield of 46% at 400 °C. Varying the Nb/Ni atomic ratio led to an optimum catalytic performance for catalysts with Nb/Ni ratio in the range 0.11–0.18. Detailed characterization of the materials with several techniques (XRD, SEM, TPR, TPD-NH₃, TPD-O₂, Raman, XPS, electrical conductivity) showed that the key component for the excellent catalytic behavior is the Ni–Nb solid solution formed upon the introduction of niobium in NiO, evidenced by the contraction of the NiO lattice constant, since even small amounts of Nb effectively converted NiO from a total oxidation catalyst (80% selectivity to CO₂) to a very efficient ethane ODH material. An upper maximum dissolution of Nb⁵⁺ cations in the NiO lattice was attained for Nb/Ni ratios ⩽0.18, with higher Nb contents leading to inhomogeneity and segregation of the NiO and Nb₂O₅ phases. A correlation between the specific surface activity of the catalysts and the surface exposed nickel content led to the conclusion that nickel sites constitute the active centers for the alkane activation, with niobium affecting mainly the selectivity to the olefin. The incorporation of Nb in the NiO lattice by either substitution of nickel atoms and/or filling of the cationic vacancies in the defective nonstoichiometric NiO surface led to a reduction of the materials nonstoichiometry, as indicated by TPD-O₂ and electrical conductivity measurements, and, consequently, of the electrophilic oxygen species (O⁻), which are abundant on NiO and are responsible for the total oxidation of ethane to carbon dioxide.     

Effects of oxygen and carbon on the magnetic properties and microstructure of Sm2Co17 permanent magnets

The research on the sintered Sm2Co17 permanent magnets prepared by metal injection molding is still at the exploratory stage. Carbon and oxygen are two key factors that influence the magnetic properties. In this article, the effects of oxygen and carbon on the properties and microstructure of the magnets have been studied. The results indicate that oxygen consumes the effective Sm content of the magnets and forms Sm2O3-the non-magnetism phase, which result in the deterioration of the magnetic properties. Besides, the magnetic properties decrease in evidence with increasing carbon content. The main factor that affects the magnetic properties is the deterioration of the microstructure of the magnets. The Sm（Co, Cu）5 phase decreases, whereas the cell size increases with the increase of the carbon content. When the carbon content is above 0.43 wt.%, the Sm（Co, Cu）5 phase is not enough to form a uniform cellular microstructure. Thus the magnetic properties disappear. ZrC is detected in the magnets by XRD when the carbon content is above 0.21 wt.%. ZrC also reduces the properties of the magnets.     

Color segmentation robust to brightness variations by using B-spline curve modeling

Color segmentation takes a great attention because color is an effective and robust visual cue for characterizing an object from the others. However, color segmentation suffers from color variations incurred by irregular illumination changes. We propose a reliable color modeling approach in hue–saturation–intensity (HSI) color space while considering intensity information by adopting the B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to intensity. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in the HS (hue–saturation) plane. The statistical characteristics contain the mean and standard deviation of hue and saturation with respect to intensity. They are mathematically expressed as four bar graphs. In order to fit the bar graphs to continuous curves, we use B-spline curve fitting procedure. From several experimental results, we verify that the proposed algorithm is successfully applied to color segmentation under various illumination conditions.     

Do social media literacy skills help in combating fake news spread? Modelling the moderating role of social media literacy skills in the relationship between rational choice factors and fake news sharing behaviour

This study modelled the rational factors that predict fake news sharing behaviour. It also tested the moderating role of social media literacy skills. The focus was on social media users in Nigeria. An online survey was conducted to gather the responses from participants across Nigerian geopolitical zones. Structural equation modelling (SEM) Smart PLS 3.6 was used to analyse the data. We found that information sharing, the news finds me perception, trust in social media and status-seeking lead to fake news sharing among social media users in Nigeria. Specifically, trust in social media and status-seeking had a greater effect on fake news sharing behaviour. We also found that social media literacy skills significantly moderate the relationship between information sharing, status-seeking, the news finds me perception, trust in social media and fake news sharing in such a way that the effects/relationships are stronger among those with low social media literacy skills. This outcome contributes to theory and practice which was highlighted in the concluding aspect of this study.     

Prediction of stable high-pressure structures of tantalum nitride TaN2

Structure searches based on a combination of first-principles calculations and a particle swarm optimization technique unravel two new stable high-pressure structures (C2/m and Cmce) for TaN₂. The structural features, mechanical properties, formation enthalpies, electronic structure, and phase diagram of TaN₂ are fully investigated. Being mechanically and dynamically stable, the two phases could be made metastable experimentally at ambient conditions.