Effect of different precooking methods on chemical composition and lipid damage of silver carp (Hypophthalmichthys molitrix) muscle

The influence of three precooking methods (steaming, oven‐baking and microwave‐cooking) on the chemical composition and lipid quality of silver carp fillets was evaluated. The changes in protein, fat and moisture were found to be significant for all the treatments (P ≤ 0.05). The iron content in the samples subjected to steam‐cooking increased; however, the other precooking methods did not change the mineral contents (P ≥ 0.05). The free fatty acid content of the fillets did not change by the different precooking methods, while thiobarbituric acid (TBA) values increased for oven‐ and microwave‐cooked fillets and remained constant in the steam‐cooked samples. Conjugated diene and browning colour formation levels significantly increased in the oven‐baked fillets. Oven‐baking and microwave‐cooking marginally affected the fatty acid composition of the silver carp. On comparing the raw and precooked fillets, steam‐cooking was found to be the best precooking method on retaining nutritional constituents.     

Online measurement of particle size distribution during crystallization using ultrasonic spectroscopy

Particle growth during crystallization of paracetamol was monitored on-line using a new modified method based on ultrasonic spectroscopy. The model was earlier developed and tested with inert particles systems and accounts for low angle scattering and probe geometry. A graphic user interface was developed and integrated with the model based deconvolution algorithm for real-time data acquisition, analysis and display of results. The crystal growth and changes in size distribution were measured during the crystallization of paracetamol from paracetamol–isopropanol–water solution. A simplified pre-calibration procedure using acoustic velocity to estimate solution properties was established. The model based particle size distribution showed good agreement with offline measurements using laser diffraction analysis of a sample retrieved from the crystallizer.     

Dynamic modeling of continuous evaporative cooling KCl-NaCl crystallizers

Previous work on the modeling of potash crystallizers has been mainly limited to the estimation of crystal size distribution (CSD) in the presence of only one solid component (KCl). In the present study, an attempt has been made to develop a model that incorporates NaCl as a second component that may co-precipitate along with KCl under certain operating conditions. Addition of water to prevent co-saturation or as a means of internal fines dissolution is also taken into consideration. External fines dissolution using a heat exchanger is incorporated in the model. In addition to the CSD, the model is able to predict crystal impurity resulting from co-saturation with NaCl. The predictive capability of the model is tested using limited dynamic experimental data obtained from a 1 m³ pilot plant continuous evaporative crystallizer and the steady-state experimental data from a two-stage evaporative Swenson DTB industrial potash crystallizer circuit. In both cases, a good agreement between the model predictions and the experimental data was noticed.     

High speed and silicon-saving adaptive tuning system for high frequency Gm-C filters

In this paper, a novel adaptive tuning system used in Gm-C continuous time (CT) filters has been presented. The novelty of this method is the generation of quasi-gradient functions for the adaptive algorithm. By this method we have implemented the fully adaptive tuning algorithm on chip, and received more than 95% precision for the all characteristics of Gm-C filter. All the circuit level simulations and prototype fabrication have been done using 0.6 μ CMOS technology of AMS.     

Growth and interfacial properties of epitaxial oxides on semiconductors: ab initio insights

Crystalline metal oxides display a large number of physical functionalities such as ferroelectricity, magnetism, superconductivity, and Mott transitions. High quality heterostructures involving metal oxides and workhorse semiconductors such as silicon have the potential to open new directions in electronic device design that harness these degrees of freedom for computation or information storage. This review describes how first-principles theoretical modeling has informed current understanding of the growth mechanisms and resulting interfacial structures of crystalline, coherent, and epitaxial metal oxide thin films on semiconductors. Two overarching themes in this general area are addressed. First, the initial steps of oxide growth involve careful preparation of the semiconductor surface to guard against amorphous oxide formation and to create an ordered template for epitaxy. The methods by which this is achieved are reviewed, and possibilities for improving present processes to enable the epitaxial growth of a wider set of oxides are discussed. Second, once a heterointerface is created, the precise interfacial chemical composition and atomic structure is difficult to determine unambiguously from experiment or theory alone. The current understanding of the structure and properties of complex oxide/semiconductor heterostructures is reviewed, and the main challenges to prediction—namely, (i) are these heterostructures in thermodynamic equilibrium or kinetically trapped, and (ii) how do the interfaces modify or couple to the degrees of freedom in the oxide?—are explored in detail for two metal oxide thin films on silicon. Finally, an outlook of where theoretical efforts in this field may be headed in the near future is provided.     

Solving infinite horizon nonlinear optimal control problems using an extended modal series method

This paper presents a new approach for solving a class of infinite horizon nonlinear optimal control problems (OCPs).In this approach,a nonlinear two-point boundary value problem (TPBVP),derived from P...     

Fuzzy cost support vector regression on the fuzzy samples

This paper presents a new version of support vector regression (SVR) named Fuzzy Cost SVR (FCSVR) with a unique property of operating on fuzzy data where fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown to be superior in the experimental results as a property compared with conventional SVR.