Predicting cortical oscillations with bidirectional LSTM network: a simulation study

It has been stated that up-down-state (UDS) cortical oscillation levels between excitatory and inhibitory neurons play a fundamental role in brain network construction. Predicting the time series behaviors of neurons in periodic and chaotic regimes can help in improving diseases, higher-order human activities, and memory consolidation. Predicting the time series is usually done by machine learning methods. In paper, the deep bidirectional long short-term memory (DBLSTM) network is employed to predict the time evolution of regular, large-scale UDS oscillations produced by a previously developed neocortical network model. In noisy time-series prediction tasks, we compared the DBLSTM performance with two other variants of deep LSTM networks: standard LSTM, LSTM projected, and gated recurrent unit (GRU) cells. We also applied the classic seasonal autoregressive integrated moving average (SARIMA) time-series prediction method as an additional baseline. The results are justified through qualitative resemblance between the bifurcation diagrams of the actual and predicted outputs and quantitative error analyses of the network performance. The results of extensive simulations showed that the DBLSTM network provides accurate short and long-term predictions in both periodic and chaotic behavioral regimes and offers robust solutions in the presence of the corruption process.

     

Computer-aided molecular design of (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule targeted agents in prostate cancer

Microtubules are tube-shaped, filamentous and cytoskeletal proteins that are essential in all eukaryotic cells. Microtubule is an attractive and promising target for anticancer agents. In this study, three-dimensional quantitative structure activity relationships (3D-QSAR) including comparative molecular field analysis, CoMFA, and comparative molecular similarity indices analysis, CoMSIA, were performed on a set of 45 (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule-targeted anti-prostate cancer agents. Automated grid potential analysis, AutoGPA module in Molecular Operating Environment 2009.10 (MOE) as a new 3D-QSAR approach with the pharmacophore-based alignment was carried out on the same dataset. AutoGPA-based 3D-QSAR model yielded better prediction parameters than CoMFA and CoMSIA. Based on the contour maps generated from the models, some key features were identified in (E)-N-Aryl-2-arylethene-sulfonamide analogues that were responsible for the anti-cancer activity. Virtual screening was performed based on pharmacophore modeling and molecular docking to identify the new inhibitors from ZINC database. Seven top ranked compounds were found based on Gold score fitness function. In silico ADMET studies were performed on compounds retrieved from virtual screening in compliance with the standard ranges.     

Preparation of uniform TiO2 nanostructure film on 316L stainless steel by sol-gel dip coating

Sol was prepared by the mixing of tetra-η-butyle titanat, ethyl aceto acetate, and ethanol in an optimized condition. Polished 316L specimens were coated with the sol by dip-coating method. The influences of drying condition, withdrawal speed, calcination temperature, addition of dispersant, and pH of sol on TiO₂ nanostructure coating were investigated. Choosing of alcohol as drying atmosphere hindered the crack formation. The relation between coating thickness and withdrawal speed was evaluated. The optimum temperature to create a uniform distribution of nanoparticles of anatase was derived as 400 °C. Average roughness of coating was found about 10.61 nm by AFM analysis. Dispersant addition promoted formation of a uniform film as well as prevention of agglomeration. Acidic sol provided smaller particles than neutral sol.     

Artificial neural network for quantitative determination of total protein in yogurt by infrared spectrometry

A method has been introduced for quantitative determination of protein content in yogurt samples based on the characteristic absorbance of protein in 1800-1500 cm^− 1 spectral region by mid-FTIR spectroscopy and chemometrics. Successive Projection Algorithm (SPA) wavelength selection procedure, coupled with feed forward Back-Propagation Artificial Neural Network (BP-ANN) model was the benefited chemometric technique. Relative Error of Prediction (REP) in BP-ANN and SPA-BP-ANN methods for training set was 7.25 and 3.70 respectively. Considering the complexity of the sample, the ANN model was found to be reliable, while the proposed method is rapid and simple, without any sample preparation step.     

C-20 ketone reduction of hydrocortisone by rice field microalga <Emphasis Type="Italic">Chlorella vulgaris</Emphasis> MCCS 013

A unicellular microalga, Chlorella vulgaris, was isolated from rice field and applied in the biotransformation experiment of hydrocortisone (1). This strain has not been previously tested for hydrocortisone bioconversion. Fermentation was carried out in BG-11 medium supplemented with 0.05% substrate at 25°C for 14 days incubation. The products obtained were chromatographically purified followed by their characterization using spectroscopic methods. 11β,17α,20β,21-Tetrahydroxypregn-4-en-3-one (2), 11β,17β-dihydroxyandrost-4-en-3-one (3), and 11β-hydroxyandrost-4-ene-3,17-dione (4) were the main bioproducts in the hydrocortisone bioconversion. Bioreaction characteristics observed were 20-ketone reduction for accumulation of compound 2 and side chain degradation of the substrate to prepare compounds 3 and 4. Time course study showed the accumulation of the product 2 from the second day of the fermentation and 3 as well as 4 from the third day. All the metabolites reached their maximum concentration in seven days. Microalgal 18S rRNA gene was also amplified by PCR. PCR products were sequenced to confirm their authenticity as 18S rRNA gene of microalgae. The result of PCR blasted with other sequenced microalgae in NCBI showed 100% homology to the 18S small subunit rRNA of six strains of Chlorella vulgaris.     

Association Equilibrium of Methylene Blue by Spectral Titration and Chemometrics Analysis: A Thermodynamic Study

The monomer‐dimer equilibrium of methylene blue (MB, Scheme I) has been investigated by means of UV‐Visible spectroscopy in aqueous solutions. The self aggregation of MB in water has been investigated by recording absorption spectra in the wavelength range of 450–750 nm, and in different ionic strengths using concentrated KCl solutions in the temperature range of 20–90°C. Chemometrics analysis of the spectral data gave a dimerization constant, individual spectra of the monomer and dimer forms of the dye molecule. The quantitative analysis of the data of the undefined mixture was carried out by simultaneous resolution of the overlapping spectral bands in the whole set of absorption spectra. The dimerization constants of MB determined by mathematical deconvolution of the thermometric spectral titration data show dependency on temperature variations. The concentration range of MB was 6.00 × 10^?5‐3.00 × 10^?4 M. Utilizing the van't Hoff relation, which describes the dependence of the equilibrium constant on temperature, the thermodynamics parameters ΔH° and ΔS° of the aggregation process were determined. The compensation effect was verified by the thermodynamics results of the dimerization process of the dye.     

On element-centralizers in finite groups

For any group G, let |Cent(G)| denote the number of centralizers of its elements. A group G is called n-centralizer if |Cent(G)| = n. In this paper, we find |Cent(G)| for all minimal simple groups. Using these results we prove that there exist finite simple groups G and H with the property that |Cent(G)| = |Cent(H)| but ${G\not\cong H}$ . This result gives a negative answer to a question raised by A. Ashrafi and B. Taeri. We also characterize all finite semi-simple groups G with |Cent(G)| ≤  73.     

Low-rank perturbations of normal and conjugate-normal matrices and their condensed forms under unitary similarities and congruences

Two theorems are proved on the condensed forms with respect to unitary similarity and congruence transformations. They provide a theoretical basis for constructing economical iterative methods for systems of linear equations whose matrices are low-rank perturbations of normal and conjugate-normal matrices.