Estimation of Residual Pepsin and Chymosin Activity in Curd,

Pasteurized milk (225 g) adjusted to pH 6.2 was set with 3.5 milk clotting units of chymosin (EC 3.4.23.4). The same amount of milk at pH 5.8 was set with 3.5 milk clotting units of porcine pepsin (EC 3.4.23.1). Fifteen minutes after clotting, the curd was broken, and curd and whey were separated by centrifugation at 3500 × g for 20 min. The curd (30 g) was extracted at pH 6.8 in 450 ml water or at pH 6.2 (chymosin) or 5.8 (pepsin) in 450 ml 1 M sodium chloride.Chymosin was completely released from the curd and accounted for by both methods of extraction. Pepsin was completely released and accounted for after extraction in 1 M sodium chloride at pH 5.8 but was partly inactivated during extraction at pH 6.8.Assay of curd extracts and whey by a linear agar diffusion test accounted for 102 ± 6% of the pepsin activity added to milk when the curd was extracted in 1 M sodium chloride. Extraction at pH 6.8 allowed recovery of only 63% of the activity. Chymosin recovery was 100 ± 5% by both methods of curd extraction.     

Enzymic and in sacco methods to estimate rumen degradation of food protein in cattle

BACKGROUND: Two factorial studies compared enzymic and in sacco methods to estimate degradation of ruminant foods. Enzyme degradation (in vitro = enzyme) was determined from the release of leucine‐equivalent amino acid (LA) crude protein (CP) from sunflower meal (SF), maize gluten meal (MG), distillers' dark grain (DG) and field beans (FB) after their separate incubations with Streptomyces griseus enzyme for 0–24 h. In sacco crude protein (CP) degradation of these foods was estimated during washing (0 h) and rumen incubations in fistulated cows for 2–24 h. The LA data were expressed as g LA per either kg of CP (LACP) or acid‐hydrolysable LA (HLA) of each food and compared with in sacco data. RESULTS: These methods showed comparable degradation with time (P < 0.01). The in sacco and HLA were greater than LACP for all foods except MG where in sacco value was either lower or equal to LACP depending upon the incubation time (P > 0.05 or P < 0.05). Conversely, HLA was significantly (P < 0.01) greater than LACP from 2 h onwards. At 0 h, in sacco values were significantly greater than those of enzyme for SF, DG and FB (P < 0.05) but not for MG. The foods differed significantly for degradation constants (a, b, c) in each method (P < 0.05). CONCLUSIONS: Despite variations between in sacco and enzyme estimates for different foods, the relationships between these estimates suggest that the HLA enzyme method has the potential to estimate food degradation. Copyright © 2007 Society of Chemical Industry     

Priority-based joint EDF–RM scheduling algorithm for individual real-time task on distributed systems

The Journal of Supercomputing - Multiple tasks arrive in the distributed systems that can be executed in either parallel or sequential manner. Before the execution, tasks are scheduled prioritywise...     

Modeling and control of a finger-like mechanism using bending shape memory alloys

Microsystem Technologies - In this research a biologically inspired finger-like mechanism similar to human musculoskeletal system is developed based on Shape Memory Alloys (SMAs). SMA actuators are...     

Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization

Neural Computing and Applications - Cryptography often involves substituting (and converting) the secret information into dummy data so that it could reach the desired destination without leakage....     

A systematic review on emperor penguin optimizer

Neural Computing and Applications - Emperor Penguin Optimizer (EPO) is a recently developed metaheuristic algorithm to solve general optimization problems. The main strength of EPO is twofold....     

Effects of Solvent Exchange Period and Heat Treatment on Physical and Chemical Properties of Rice Husk Derived Silica Aerogels

In this study, hydrophobic silica aerogels were synthesized from rice husk ash-derived sodium silicate through sol-gel processing, solvent exchange, surface modification and ambient pressure drying. By volume, 10% of trimethylchlorosilane (TMCS) in 90% of n-hexane was used as a hydrophobic solution in the surface modification process. The physical and chemical properties of silica aerogels were characterized by density and porosity measurements, scanning electron microscopy (SEM), Fourier transforms infrared (FTIR) spectroscopy, Brunauer–Emmett–Teller theory (BET) and dynamic scanning calorimetry (DSC). The hydrogels prepared were in the form of 2.5 ± 0.5 mm beads and then converted into alcogels through solvent exchange with ethanol for repetition of 3, 6 and 9 days. It is found that the optimal quality of silica aerogels with the BET surface area as high as 668.82 m²/g was obtained from the alcogels of the solvent exchange period of 9 days. Depending on the size of the gel’s block, a longer solvent exchange period will ensure adequate removal of pore water. Post heat treatment on silica aerogels obtained from the 9 days of solvent exchange at 200, 300 and 400 °C for 2 h results in slight decreased of aerogel’s density from 0.048 g/cm³ to 0.039 g/cm³ and the hydrophobicity of the aerogels is decreased above 380 °C as confirmed by DSC analysis.

     

An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation

This research presents an autonomous robotic framework for academic, vocational and training purpose. The platform is centred on a 6 Degree Of Freedom (DOF) serial robotic arm. The kinematic and dynamic models of the robot have been derived to facilitate controller design. An on-board camera to scan the arm workspace permits autonomous applications development. The sensory system consists of position feedback from each joint of the robot and a force sensor mounted at the arm gripper. External devices can be interfaced with the platform through digital and analog I/O ports of the robot controller. To enhance the learning outcome for beginners, higher level commands have been provided. Advanced users can tailor the platform by exploiting the open-source custom-developed hardware and software architectures. The efficacy of the proposed platform has been demonstrated by implementing two experiments; autonomous sorting of objects and controller design. The proposed platform finds its potential to teach technical courses (like Robotics, Control, Electronics, Image-processing and Computer vision) and to implement and validate advanced algorithms for object manipulation and grasping, trajectory generation, path planning, etc. It can also be employed in an industrial environment to test various strategies prior to their execution on actual manipulators.     

Temperature-dependent diffusion coefficient of soluble substances during ethanol extraction of clove

The temperature dependence of the diffusion coefficient of ethanol-soluble substances from ground cloves (particle size 250 μm) during extraction was estimated by fitting batch extraction data at several temperatures (27.8, 40, 50, and 60°C) to a previously developed mass transfer model. The model was based on spherical geometry of particles. Nonlinear regression analysis was used to develop an equation that describes the diffusivity as a function of temperature. The temperature dependence ofD _A was of the Arrhenius type.     

Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.