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Ferromagnetic hysteresis behavior is a lagging relation between magnetization and external magnetic field. This understanding is useful for designing highly efficient magnetic applications e.g., magnetic recording devices. A magnetic phase and hysteresis properties fluctuate clearly when encountered with thermal noise. This creates difficulties in predicting and modeling; and poses a very challenging problem. In this study, we propose to fit parameters and select the suitable kernel functions of Support Vector Machine, of which the main tasks are i) managing the relationship among hysteresis properties, temperature, magnetic field, and magnetic frequency, and ii) classifying the symmetries of hysteresis. The results present a new novel of classifying symmetric behavior of hysteresis with high accuracy. [ABSTRACT FROM AUTHOR]

A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF), which is a derivation of Empirical Mode Decomposition (EMD), is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF), Wavelet Transform (WT), Particle Filter (PF) and the averaging Intrinsic Mode Function (aIMF) algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters. [ABSTRACT FROM AUTHOR]

Abstract: Volatility is a key parameter when measuring the size of errors made in modelling returns and other financial variables such as exchanged rates. The autoregressive moving-average (ARMA) model is a linear process in time series; whilst in the nonlinear system, the generalised autoregressive conditional heteroskedasticity (GARCH) and Markov switching GARCH (MS-GARCH) have been widely applied. In statistical learning theory, support vector regression (SVR) plays an important role in predicting nonlinear and nonstationary time series variables. In this paper, we propose a new algorithm, differential Empirical Mode Decomposition (EMD) for improving prediction of exchange rates under support vector regression (SVR). The new algorithm of Differential EMD has the capability of smoothing and reducing the noise, whereas the SVR model with the filtered dataset improves predicting the exchange rates. Simulations results consisting of the Differential EMD and SVR model show that our model outperforms simulations by a state-of-the-art MS-GARCH and Markov switching regression (MSR) models. [Copyright &y& Elsevier]

Abstract: This paper presents the concept of a current mode readout circuit for the ion-sensitive field effect transistor (ISFET) to be used as a pH sensor. An ISFET in conjunction with a current mirror with global feedback to the source terminal yields linearity between a wide dynamic pH range and output. Operating the ISFET and current source in the weak inversion region reduces major problems arising from channel-length modulation. Our experiment using discrete components demonstrates very high accuracy readout with total power consumption including the ISFET of early microwatts. [Copyright &y& Elsevier]

Abstract: Novel biosensors, based on immobilized creatininase, creatinase and urease are developed, using ISFETs with weak inversion at pH 6–8 and 37.0°C. The ISFETs with circuitry, demonstrate a linear relationship of urea and creatinine at the range of 0–200 and 0–20mM, respectively. Preliminary results show that biosensors operating in weak inversion mode can eliminate many of the disadvantages of ISFETs operating in the strong inversion region, providing a wide dynamic range output in nanoAmp. Such characteristics fit the analytical requirements for improving real-time monitoring in peritoneal dialysis (PD). Further work covers stability of ISFET sensors biased with CMOS circuits in the weak inversion mode working in the room temperature of 15–40°C. [Copyright &y& Elsevier]

The reaction mechanism of creatinine-creatininase binding to form creatine as a final product has been investigated by using a combined ab initio quantum mechanical/molecular mechanical approach and classical molecular dynamics (MD) simulations. In MD simulations, an X-ray crystal structure of the creatininase/creatinine was modified for creatininase/creatinine complexes and the MD simulations were run for free creatininase and creatinine in water. MD results reveal that two X-ray water molecules can be retained in the active site as catalytic water. The binding free energy from Molecular Mechanics Poisson-Boltzmann Surface Area calculation predicted the strong binding of creatinine with Zn, Asp45 and Glu183. Two step mechanisms via Mn/Zn (as in X-ray structure) and Zn/Zn were proposed for water adding step and ring opening step with two catalytic waters. The pathway using synchronous transit methods with local density approximations with PWC functional for the fragment in the active region were obtained. Preferable pathway Zn/Zn was observed due to lower activation energy in water adding step. The calculated energy in the second step for both systems were comparable with the barrier of 26.03 and 24.44 kcal/mol for Mn/Zn and Zn/Zn, respectively. [ABSTRACT FROM AUTHOR]

Abstract: The novel low-molecular-weight chitosan polysulfate (MW 5120–26,200Da) was prepared using the depolymerization of chitosan with papain (EC. 3.4.22.2). The sulfonation of depolymerized products was performed using chlorosulfonic acid in N,N-dimethylformamide under semi-heterogeneous conditions. The structures of the products were characterized by FTIR, 13C NMR, and 1H NMR (1D, 2D NMR) spectroscopy. The present study sheds light on the mechanism of anticoagulant activity of chitosan polysulfate. Anticoagulant activity was investigated by an activated partial thromboplastin assay, a thrombin time assay, a prothrombin time assay, and thrombelastography. Surface plasmon resonance also provided valuable data for understanding the relationship between the molecular binding of sulfated chitosan to two important blood clotting regulators, antithrombin III and heparin cofactor II. These results show that the principal mechanism by which this chitosan polysulfate exhibits anticoagulant activity is mediated through heparin cofactor II and is dependent on polysaccharide molecular weight. [Copyright &y& Elsevier]

Abstract: Osteoarthritis (OA) is the most common form of arthritis and affects millions of people worldwide. Patients have traditionally been treated with non-steroidal anti-inflammatory drugs (NSAIDs), but these are associated with significant side effects. Purification of the acetone extract of Alpinia galanga afforded p-hydroxycinnamaldehyde, as identified by nuclear magnetic resonance and mass spectrometry analyses. By exploiting the cartilage explant culture, p-hydroxycinnamaldehyde suppressed loss of uronic acid, resulting in release of hyaluronan (HA), sulfated glycosaminoglycans (s-GAGs) and matrix metalloproteinases (MMPs). p-Hydroxycinnamaldehyde and interleukin-1β (IL-1β), when incubated in primary human chondrocytes, also reduced release of HA, s-GAG and MMP-2. The results demonstrated: (a) that expression levels of the catabolic genes MMP-3 and MMP-13 were suppressed and (b) mRNA expression levels of anabolic genes of collagen II, SOX9 and aggrecan were increased. This study shows that p-hydroxycinnaldehyde from A. galanga Linn. is a potential therapeutic agent for treatment of OA. [Copyright &y& Elsevier]