A novel aspartic protease from the viscera of Sardinelle (Sardinella aurita): Purification and characterisation

A novel aspartic protease was extracted from the defatted viscera of sardinelle (Sardinella aurita) and purified, with a 9.5-fold increase in specific activity and 23.3% recovery. The molecular weight of the purified enzyme was estimated to be 17 kDa by sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE). The purified enzyme appeared as a single band on native-PAGE. The optimum pH and temperature for protease activity were around 3.0 and 40 °C, respectively. The enzyme showed pH stability between 2.0 and 5.0 and retained more than 50% of its activity after heating for 30 min at 50 °C. The enzyme lost 90% of its activity after incubation with pepstatin A at room temperature, but was not inhibited by soybean trypsin inhibitor or phenylmethylsulfonyl fluoride. Its K_m value was determined to be 0.73 × 10⁻⁴ M using haemoglobin as a substrate. The N-terminal 12 amino acid sequence of the purified acidic protease was R V I I E D X D Q F C T. This sequence showed low homology with aspartic peptidases of several other species of fish, suggesting that the enzyme is a new aspartic protease.     

Viscosity decrease by interfacial slippage between immiscible polymers

The rheological behavior under pressure-driven shear flow was studied using binary blends with a sea-island structure. The addition of a low-viscosity dispersion having a high interfacial tension with the continuous phase greatly reduces the shear viscosity, for example, the addition of atactic polystyrene (PS) with a low viscosity to isotactic polypropylene (PP) and the addition of PP with a low viscosity to PS. The interfacial slippage occurs because of the poor adhesive strength with the enlarged interfacial area and is responsible for the viscosity decrease. When the dispersion has a similar viscosity to the continuous phase, the viscosity decrease is barely detected. This is because the deformation of dispersed droplets is restricted, which creates a small interfacial area. The interfacial tension between the continuous and dispersed phases plays a crucial role on the shear viscosity. In the case of PP, the addition of linear low-density polyethylene with a relatively low interfacial tension to PP has almost no impact on the shear viscosity. This is despite the polyethylene having a low viscosity.     

Throughput and cost‐efficient interference cancelation strategies for the downlink of spectrum‐sharing Long Term Evolution heterogeneous networks

In a heterogeneous network (HetNet), small cells such as femtocells considered in this work are deployed jointly with macrocells. This new cells' layer, when added to the network, generates interference, which could hamper neighboring macro‐user equipment (MUE) and femto‐user equipment (FUE) transmissions. In fact, this interference results in degradation of the network performance. In this paper, we propose a downlink interference cancelation (DL‐IC) strategy for spectrum‐sharing Long Term Evolution (LTE) HetNet. This DL‐IC strategy aims to reduce the interference impact on users by optimizing their received signal to interference plus noise ratio (SINR) using new utility functions for both FUEs and MUEs. These utility functions allow relaxation of the cancelation ratios in order to reduce implementation complexity while maximizing SINR, QoS, and throughput. We support by different system‐level simulations that both global network performance and user experience in terms of total throughput and received SNR or link‐level throughput, respectively, are significantly enhanced. Throughput gains achievable by the new DL‐IC strategy can reach as much as 200% against a homogeneous LTE network without IC along with an extra 48% per additional femtocell base station against a basic spectrum‐sharing LTE HetNet without IC. These performance figures are shown to surpass those achieved by interference avoidance techniques using either power or frequency resource allocation. Copyright © 2014 John Wiley & Sons, Ltd.     

A novel approach for dynamic hand gesture recognition using contour-based similarity images

A novel approach is proposed for the recognition of moving hand gestures based on the representation of hand motions as contour-based similarity images (CBSIs). The CBSI was constructed by calculating the similarity between hand contours in different frames. The input CBSI was then matched with CBSIs in the database to recognize the hand gesture. The proposed continuous hand gesture recognition algorithm can simultaneously divide the continuous gestures into disjointed gestures and recognize them. No restrictive assumptions were considered for the motion of the hand between the disjointed gestures. The proposed algorithm was tested using hand gestures from American Sign Language and the results showed a recognition rate of 91.3% for disjointed gestures and 90.4% for continuous gestures. The experimental results illustrate the efficiency of the algorithm for noisy videos.     

Power transformer fault diagnosis based on dissolved gas analysis by support vector machine

This paper presents an intelligent fault classification approach to power transformer dissolved gas analysis (DGA). Support vector machine (SVM) is powerful for the problem with small sampling (small amounts of training data), nonlinear and high dimension (large amounts of input data). The standard IEC 60599 proposes two DGA methods which are the ratios and graphical representation. According the experimental data, for the same input data, these two methods give two different faults diagnosis results, what brings us to a problem. This paper investigates a novel extension method which consists in elaborating an input vector establishes by the combination of ratios and graphical representation to resolve this problem. SVM is applied to establish the power transformers faults classification and to choose the most appropriate gas signature between the DGA traditional methods and a novel extension method. The experimental data from Tunisian Company of Electricity and Gas (STEG) is used to illustrate the performance of proposed SVM models. Then, the multi-layer SVM classifier is trained with the training samples. Finally, the normal state and the six fault types of transformers are identified by the trained classifier. In comparison to the results obtained from the SVM, the proposed DGA method has been shown to possess superior performance in identifying the transformer fault type. The SVM approach is compared with other AI techniques (fuzzy logic, MLP and RBF neural network); the proposed method gives a good performance for transformers fault diagnosis. The test results indicate that the novel extension method and the SVM approach can significantly improve the diagnosis accuracies for power transformer fault classification.     

Interaction diagrams for design of hybrid fiber-reinforced tunnel segments

Fiber reinforcement has emerged as an alternative to traditional reinforcing bars and welded wire mesh reinforcement for precast concrete tunnel segments. This is mainly due to improved postcracking behavior and crack control characteristics of fiber-reinforced concrete (FRC) segments. A hybrid solution of fibers and reinforcing bars is adopted when FRC is not adequate as the sole reinforcing system. Often times, this is the case in large-diameter tunnels with large curved length segments in order to achieve required strength for embedment loads in shallow cover, TBM thrust jack forces, and loading from imperfect construction and irregularities. P–M interaction diagrams are used as one of the main design tools since segment cross section, under most of governing load cases, is subjected to a combined axial force and bending moment. Standard FRC constitutive laws recently allows for a significant residual strength in tension zone below the neutral axis. However, design capacity of hybrid fiber-reinforced concrete (HRC) segment is significantly underestimated using conventional Whitney’s rectangular stress block method. Methods that currently incorporate contribution of fibers on P–M diagrams are based on numerical and finite-element analyses. However, closed-form solutions offer important advantages. This paper presents material models, derivations and for the first time closed-form solutions to construct P–M interaction diagram of HRC segments. Parametric studies are conducted and validity of the model is verified by simulating experimental results of HRC columns and model-predicted results of precast and cast-in-place concrete linings. Results show that using appropriate material models for fiber and reinforcing bar, engineers can use the proposed methodology to obtain P–M interaction diagrams for HRC tunnel segments.     

Chymotrypsin from the hepatopancreas of cuttlefish (Sepia officinalis) with high activity in the hydrolysis of long chain peptide substrates: Purification and biochemical characterisation

Chymotrypsin from the hepatopancreas of cuttlefish (Sepia officinalis) was purified to homogeneity, with a 120-fold increase in specific activity and 23% recovery. The molecular weight of the purified chymotrypsin was estimated to be 28 kDa by sodium dodecyl sulphate–polyacrylamide gel electrophoresis. The optimum pH and temperature for the chymotrypsin activity were pH 8.5 and 55 °C, respectively, using succinyl-l-ala-ala-pro-l-phenylalanine-p-nitroanilide (SAAPFpNA) as a substrate. The enzyme was extremely stable in the pH range of 7.0–10.0 and highly stable up to 50 °C after 1 h incubation. This proteinase was strongly inhibited by chymostatin, soybean trypsin inhibitor, diisopropylfluorophosphate and phenylmethylsulfonyl fluoride, but was not inhibited by tosyl-l-phenylalanine chloromethyl ketone, N-carbobenzoxy-phenylalanine chloromethyl ketone or N_α-tosyl-l-lysine chloromethyl ketone. The enzyme hydrolysed long chymotrypsin peptide substrates SAAPFpNA, SAAPLpNA and ZAALpNA and did not hydrolyse short chymotrypsin substrates. Kinetic parameters of the enzymatic reaction demonstrated that the best substrate was SAAPFpNA, with k_cat 18 s^?1 and K_m 22 μM. However, the enzyme had a lower K_m for SAAPLpNA, 54 μM.The N-terminal amino acid sequence of the first 20 amino acids of the purified chymotrypsin was IVGGQEATIGEYPWQAALQV.     

Optimisation of Manufacturing Parameters for an Ni–Ag Fuel Cell Electrode

The aim of this research is to optimise manufacturing parameters for a fuel cell electrode. The combination of nickel oxide, silver oxide and ammonium bicarbonate powders is used to produce the electrode. The main role of silver element is to increase the activity in the electrode. Ni–Ag electrode can be used in fuel cells as positive and negative electrodes. All powders are mixed in the benzene solution by a magnetic mixer and then compressed to form green electrode. The range of pressure in this step is between 40 and 160 MPa. The green electrode is sintered in hydrogen atmosphere through a tube furnace and then cooled to 200 °C under argon atmosphere. The range of sintering temperature and time is 500–800 °C and 10–60 min, respectively. Also, silver oxide and ammonium bicarbonate percentages are varied from 20 to 65 and 15 to 35%, respectively. All parameters including composition, pressure, sintering temperature and time are changed during electrode fabrication to achieve optimised properties in the electrode. So, it is necessary to perform several tests measuring porosity, surface area, density, weight loss, mechanical strength, shrinkage, exchange current density and metallographic photos. The optimum conditions of the electrode production resulting from this investigation include compacting pressure 60 MPa, sintering temperature 560 °C, sintering time 15 min, silver oxide percentage 50% and ammonium bicarbonate percentage 27%.