Crossing statistics of laser light scattered through a nanofluid

In this paper, we investigate the crossing statistics of speckle patterns formed in Fresnel diffraction region by a laser beam scattering through a nanofluid. We extend $zero-crossing$ statistics to assess dynamical properties of nanofluid. According to joint probability density function of laser beam fluctuation and its time derivative, theoretical framework for Gaussian and non-Gaussian regimes are revisited. We count number of crossings not only at {\it zero} level but also for all available thresholds to determine the average speed of moving particles. Using probabilistic framework in determining crossing statistics, {\it a priori} Gaussianity is not essentially considered, therefore even in presence of deviation from Gaussian fluctuation, this modified approach is capable to compute relevant quantities such as mean value of speed more precisely. Generalized total crossing which represents the weighted summation of crossings for all thresholds to quantify small deviation from Gaussian statistics is introduced. This criterion can also manipulate the contribution of noises and trends to infer reliable physical quantities. The characteristic time scale for having successive crossings at a given threshold is defined. In our experimental setup, we find that increasing sample temperature leads to more consistency between Gaussian and perturbative non-Gaussian predictions. The maximum number of crossing does not necessarily occur at mean level indicating that we should take into account other levels in addition to {\it zero} level to achieve more accurate assessments.Comment: 12 pages, 7 figures, 2 tables. Matched to accepted versio

Shelf-life determination of tiger-toothed Croaker (Otolithes ruber) during flake ice storage

Quality of tiger-toothed croaker stored in flake ice was studied for 19 days by sensory, chemical (total volatile basic nitrogen (TVB-N)), (thiobarbituric values (TBA)), pH and microbial (total viable count, TVC) methods. Sensory scheme was modified according to the panelists perception and a specific schema was created for this fish. Sensory analyses showed that: "gills color and odor", "convexity of eyes", "peritoneum" and "elasticity of flesh" are the best sensory parameters. Results of sensory and microbial analyses had high correlation. Total viable count of flesh was 2.86 log cfu g-1 at first day and reached the limiting level of TVC (106) after 15 days of storage (P<0.05). TVB-N levels were 15.31mg/100 g tissue at the first day of storage and reached 36.52mg/100 g at the end of storage day (P<0.05). Measuring amounts of TVB-N showed that total volatile basic nitrogen is a good quality index for tiger-toothed croaker during ice storage. The initial level of TBA was 0.83mg of malondialdehyde per kg flesh (mg MDA/kg) and increased to 3.75mg MDA/kg at the end of storage. TBA levels were less than limiting level (5mg MDA/kg) over the period of storage. According to the results, shelf-life of tiger-toothed croaker was determined 15 days during ice storage

ANMM4CBR: a case-based reasoning method for gene expression data classification

<p>Abstract</p> <p>Background</p> <p>Accurate classification of microarray data is critical for successful clinical diagnosis and treatment. The "curse of dimensionality" problem and noise in the data, however, undermines the performance of many algorithms.</p> <p>Method</p> <p>In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR) method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR) method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data.</p> <p>Results</p> <p>The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM) and <it>k </it>nearest neighbor (<it>k</it>NN), especially when the data contains a high level of noise.</p> <p>Availability</p> <p>The source code is attached as an additional file of this paper.</p

Computational approach to the prediction of blood-brain partitioning of basic drug candidates using mixed micellar liquid chromatography

Background and Objective: The blood–brain barrier (BBB) is considered to be the main barrier to drug transport into the central nervous system. In this study, the capability of biopartitioning micellar chromatography (BMC) using the mixed micellar system of Brij-35/sodium dodecyl sulfate (Brij-35/SDS, 85:15 mol/mol) has been studied to predict pharmacokinetic parameter (BBB penetration ability) of 14 basic drugs. Methods: In this descriptive-analytical study, the potential of BMC using mixed micellar system (Brij-35/SDS, 85:15 mol/mol) in 0.04 M at physiological pH 7.4 was evaluated to predict pharmacokinetic parameter (BBB penetration ability) of 14 basic drugs. The regression model for the prediction of blood-brain distribution coefficient is derived from the multiple linear regression analysis using the training set in mixed micellar mobile phase. Also, the predictive ability of model was evaluated for a prediction set of 5 compounds (Chlorpromazine, Mianserin, Propranolol, Cimetidine, and Thioridazine). The fair R2 indicates good stability and predictive ability of the developed model for the drugs not included in modeling. Results: The relationship between the BMC retention data of 14 basic drugs and their log BB parameter showed a good statistically model (R2=0.822, F=25.42, SE=0.225, R2CV=0.781). Conclusion: This study points out the usefulness of mixed micellar solution of Brij-35/SDS, 85:15 (mol/mol) in BMC as a high-throughput primary screening tool that can provide key information about the blood-brain distribution of basic drugs in a simple and economical way