Could chroman-4-one derivative be a better inhibitor of PTR1? – Reason for the identified disparity in its inhibitory potency in Trypanosoma brucei and Leishmania major

Most notable Kinetoplastids are of the genus Trypanosoma and Leishmania, affecting several millions of humans in Africa and Latin America. Current therapeutic options are limited by several drawbacks, hence the need to develop more efficacious inhibitors. An investigation to decipher the mechanism behind greater inhibitory potency of a chroman-4-one derivative (compound 1) in Trypanosoma brucei pteridine reductase 1 (TbPTR1) and Leishmania major pteridine reductase 1 (LmPTR1) was performed. Estimation of ΔG_bind revealed that compound 1 had a greater binding affinity in TbPTR1 with a ΔG_bind value of −49.0507 Kcal/mol than −29.2292 Kcal/mol in LmPTR1. The ΔGbind in TbPTR1 were predominantly contributed by “strong” electrostatic energy compared to the “weak” van der Waals in LmPTR1. In addition to this, the NADPH cofactor contributed significantly to the total energy of TbPTR1. A characteristic weak aromatic π interaction common in PTR1 was more prominent in TbPTR1 than LmPTR1. The consistent occurrence of high-affinity conventional hydrogen bond interactions as well as a steady interaction of crucial active site residues like Arg14/Arg17, Ser95/Ser111, Phe97/Phe113 in TbPTR1/LmPTR1 with chroman-4-one moiety equally revealed the important role the moiety played in the activity of compound 1. Overall, the structural and conformational analysis of the active site residues in TbPTR1 revealed them to be more rigid than LmPTR1. This could be the mechanism of interaction TbPTR1 employs in exerting a greater potency than LmPTR1. These findings will further give insight that will be assistive in modifying compound 1 for better potency and the design of novel inhibitors of PTR1.     

带有白噪声的Berger方程随机吸引子

考虑带有白噪声的Berger方程解的随机渐近性行为, 用渐近先验估计技术和算子分解方法, 通过引入同构映射构造等价过程, 证明随机吸引子在(H²(U)∩H¹₀(U))×L²(U)中的存在性.     

Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.     

基于多变量希尔伯特频域模型的癫痫发作预测

癫痫发作具有突发性和反复性,对患者生命安全构成巨大威胁.为了对癫痫发作进行有效地预测,提出了多变量希尔伯特频域模型的癫痫发作预测方法.将希尔伯特边际谱、希尔伯特边际谱的变化方向和希尔伯特加权频率组成一个三维特征向量作为多变量希尔伯特频域模型,输入到支持相量机中,实现癫痫的发作预测,最后采用癫痫发作预测特征方法对预测结果进行评估.实验结果表明:采用多变量希尔伯特频域模型分析方法预测δ波和θ波的癫痫发作,癫痫预测范围在30~45 min,患者有足够的时间采取措施应对;癫痫发作周期在5~10 min,缩短患者等待时间,降低焦虑程度;与多种相关方法进行比较,该方法具有较低的错误预报率和较高的预测敏感度.     

Hybrid SVM／HMM Method for Face Recognition

A face recognition system based on Support Vector Machine(SVM) and Hidden Markov Model (HMM) has been proposed. The powerful discriminative ability of SVM is combined with the temporal modeling ability of HMM. The output of SVM is moderated to be probability output, which replaces the Mixture of Gauss (MOG) in HMM. Wavelet transformation is used to extract observation vector, which reduces the data dimension and improves the robustness.The hybrid system is compared with pure HMM face recognition method based on ORL face database and Yale face database. Experiments results show that the hybrid method has better performance.     

An M/G/1 Retrial Queueing System with Two-Phase Service and Preemptive Resume

An M/G/1 retrial queueing system with additional phase of service and possible preemptive resume service discipline is considered. For an arbitrarily distributed retrial time distribution, the necessary and sufficient condition for the system stability is obtained, assuming that only the customer at the head of the orbit has priority access to the server. The steady-state distributions of the server state and the number of customers in the orbit are obtained along with other performance measures. The effects of various parameters on the system performance are analysed numerically. A general decomposition law for this retrial queueing system is established.     

Wavelet Collocation Methods for a First Kind Boundary Integral Equation in Acoustic Scattering

In this paper we consider a wavelet algorithm for the piecewise constant collocation method applied to the boundary element solution of a first kind integral equation arising in acoustic scattering. The conventional stiffness matrix is transformed into the corresponding matrix with respect to wavelet bases, and it is approximated by a compressed matrix. Finally, the stiffness matrix is multiplied by diagonal preconditioners such that the resulting matrix of the system of linear equations is well conditioned and sparse. Using this matrix, the boundary integral equation can be solved effectively.     

Stochastic signal analysis: Numerical representation and applications to system theory

Alternative procedures for representing a stochastic signal as a denumerable series with uncorrelated terms are developed. The study includes considerations about parametric rescaling and its repercussions on the orthogonal expansion, as well as numerical techniques for approaching such an expansion. In addition, applications to the Gaussian characterization of stochastic signals, filtering and stochastic modelling are treated.     

Orthogonal double covers by super‐extendable cycles

An Orthogonal Double Cover (ODC) of the complete graph K_n by an almost‐hamiltonian cycle is a decomposition of 2K_n into cycles of length n?1 such that the intersection of any two of them is exactly one edge. We introduce a new class of such decompositions. If n is a prime, the special structure of such a decomposition allows to expand it to an ODC of K_n+1 by an almost‐hamiltonian cycle. This yields the existence of an ODC of K_p+1 by an almost‐hamiltonian cycle for primes p of order 3 mod 4 and its eventual existence for arbitrary primes p. © 2002 Wiley Periodicals, Inc. J Combin Designs 10: 283–293, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/jcd.10011