Towards designing modular recurrent neural networks in learning protein secondary structures

Precise prediction of protein secondary structures from the associated amino acids sequence is of great importance in bioinformatics and yet a challenging task for machine learning algorithms. As a major step toward predicting the ultimate three dimensional structures, the secondary structure assignment specifies the protein function. Considering a multilayer perceptron neural network, pruned for optimum size of hidden layers, as the reference network, advanced kinds of recurrent neural network (RNN) are devised in this article to enhance the secondary structure prediction. To better model the strong correlations between secondary structure elements, types of modular reciprocal recurrent neural networks (MRR-NN) are examined. Additionally, to take into account the long-range interactions between amino acids in formation of the secondary structure, bidirectional RNN are investigated. A multilayer bidirectional recurrent neural network (MBR-NN) is finally applied to capture the predominant long-term dependencies. Eventually, a modular prediction system based on the interactive combination of the MRR-NN and MBR-NN boosts the percentage accuracy (Q₃) up to 76.91% and augments the segment overlap (SOV) up to 68.13% when tested on the PSIPRED dataset. The coupling effects of the secondary structure types as well as the sequential information of amino acids along the protein chain can be well cast by the integration of the MRR-NN and the MBR-NN.     

Synthesis and characterization of novel optically active poly(amide‐imide)s

4,4′‐(Hexafluoroisopropylidene)‐bis‐(phthalic anhydride) (1) was reacted with L ‐leucine (2) in toluene solution at refluxing temperature in the presence of triethylamine and the resulting imide‐acid (4) was obtained in quantitative yield. The compound (4) was converted to the diacid chloride (5) by reaction with thionyl chloride. The polymerization reaction of the imide‐acid chloride (5) with 1,6‐hexamethylenediamine (6a) , benzidine (6b) , 4,4′‐diaminodiphenylmethane (6c) , 1,5‐diaminoanthraquinone (6d) , 4,4′‐sulfonyldianiline (6e) , 3,3′‐diaminobenzophenone (6f) , p‐phenylenediamine (6g) and 2,6‐diaminopyridine (6h) was carried out in chloroform/DMAc solution. The resulting poly(amide‐imide)s were obtained in high yield and are optically active and thermally stable. All of the above compounds were fully characterized by IR, elemental analyses and specific rotation. Some structural characterization and physical properties of those optically active poly(amide‐imide)s are reported. © 1999 Society of Chemical Industry     

Detection of Human Papillomavirus in Squamous Lesions of the Conjunctiva Using RNA and DNA In-Situ Hybridization

In-situ hybridization provides a convenient and reliable method to detect human papillomavirus (HPV) infection in formalin-fixed paraffin-embedded tissue. Cases of conjunctival papillomas, conjunctival intraepithelial neoplasia (CIN), conjunctival carcinoma in situ (cCIS), and invasive squamous cell carcinoma (SCC), in which low-risk (LR) and/or high-risk (HR) HPV types were evaluated by RNA or DNA in-situ hybridization, were retrospectively identified. LR HPV types were frequently detected in conjunctival papillomas (25/30, 83%), including 17/18 (94%) with RNA probes, compared to 8/12 (75%) with DNA probes. None of the CIN/cCIS or SCC cases were positive for LR HPV by either method. HR HPV was detected by RNA in-situ hybridization in 1/16 (6%) of CIN/cCIS cases and 2/4 (50%) of SCC cases, while DNA in-situ hybridization failed to detect HPV infection in any of the CIN/cCIS lesions. Reactive atypia and dysplasia observed in papillomas was generally associated with the detection of LR HPV types. Collectively, our findings indicate RNA in-situ hybridization may provide a high-sensitivity approach for identifying HPV infection in squamous lesions of the conjunctiva and facilitate the distinction between reactive atypia and true dysplasia. There was no clear association between HPV infection and atopy in papillomas or dysplastic lesions.     

A modified sliding-mode observer design with application to diffusion equation

In many physical systems, the system's full state cannot be measured. An observer is designed to reconstruct the state from measurements. Disturbances often contribute to the dynamics of the system, and the designed observer must account for them. In this paper, a modified sliding-mode observer (SMO), a robust observer, is proposed that combines the efficiency of a nonlinear observer with the robustness of an SMO. The estimation error is proven to converge to zero under natural assumptions. This improved observer is compared with an extended Kalman filter and an unscented Kalman filter, as well as a standard SMO for three different versions of heat equation: a linear, a quasi-linear, and a nonlinear heat equation. The comparisons are done with and without an external disturbance. The simulations show improved performance of the modified SMO over other observers.     

The effect of NaCl and HPAM solution concentration on HPAM gel structure degradation by ultrasonic waves

The present study evaluated the impact of ultrasonic waves on the degradation of partially hydrolyzed polyacrylamide (HPAM) gel structures, focusing on the effects of sonication time, NaCl concentration, and HPAM solution concentration. Results showed that both sonication time and salinity levels play a crucial role in the degradation of HPAM gel, with an increase in sonication time leading to a decrease in the remaining gel and the presence of NaCl in the solution decreasing the residual time required for degradation. The results also revealed that higher levels of salinity expedite the degradation of the gel. In addition, the study discovered that a rise in polymer solution concentration usually results in a reduction in gel degradation. The research suggests there might be an ideal combination of polymer solution and NaCl concentration for achieving the greatest decrease in the degradation rate. For 2-min sonication, as the salinity of the HPAM solution, with a concentration of up to 5000 ppm, increases, the accumulated energy remains relatively constant. However, when the polymer solution concentration is increased, the accumulated energy becomes more sensitive to changes in salinity. The results of this study provide valuable insight into the interplay between polymer solution concentration, salt concentration, and the energy required for gel degradation, which can be applied in various fields including the oil and gas industry, petroleum processing, and environmental remediation.     

Effect of particle size on the rheology of Athabasca clay suspensions

The success of the separation process conventionally used in Alberta for oil sands extraction is highly influenced by the rheology of the oil sands slurry. In the gravity separation vessel, high slurry viscosities can hinder the rise of aerated bitumen and reduce the efficiency of the recovery process. In this study, the effect of particle size on the viscosity of oil sands slurries is investigated. Solids from mature fine tails (MFT) obtained from tailings pond were fractionated into three fractions of different particle size distributions and their rheological properties were studied. The solids in each fraction were characterized by XRD analysis which showed the presence of different types of clays in each fraction. For the rheological measurements, dispersions of the three fractions were prepared in the supernatant water decanted from centrifuged MFT to maintain the solution chemistry of the solids. Suspensions of each fraction showed a non‐Newtonian shear thinning behaviour as well as yield stress that is characteristic of structure formation within the suspensions. For all solids fractions, increasing solids concentration led to higher viscosities and higher yield stress values. Viscoelastic properties of the suspensions showed stronger solid‐like behaviour at higher particle concentrations. Among the three fractions numbered from 1 to 3, solids in fraction 3 were coated with organic matters, exhibiting the highest suspension viscosities. Also for fraction 3, higher gelling potency was observed at much lower weight fractions of solids as compared to the other fractions.     

An analytical model with flexible accuracy for deep submicron DCVSL cells

Differential cascoded voltage switch logic (DCVSL) cells are among the best candidates of circuit designers for a wide range of applications due to advantages such as low input capacitance, high switching speed, small area and noise-immunity; nevertheless, a proper model has not yet been developed to analyse them. This paper analyses deep submicron DCVSL cells based on a flexible accuracy-simplicity trade-off including the following key features: (1) the model is capable of producing closed-form expressions with an acceptable accuracy; (2) model equations can be solved numerically to offer higher accuracy; (3) the short-circuit currents occurring in high-low/low-high transitions are accounted in analysis and (4) the changes in the operating modes of transistors during transitions together with an efficient submicron I-V model, which incorporates the most important non-ideal short-channel effects, are considered. The accuracy of the proposed model is validated in IBM 0.13 µm CMOS technology through comparisons with the accurate physically based BSIM3 model. The maximum error caused by analytical solutions is below 10%, while this amount is below 7% for numerical solutions.     

A case study of energy use and economical analysis of irrigated and dryland wheat production systems

Current conventional agricultural systems using intensive energy has to be re-vitalized by new integrated approaches relying on renewable energy resources, which can allow farmers to stop depending on fossil resources. The aim of the present study was to compare wheat production in dryland (low input) and irrigated (high input) systems in terms of energy ratio, energy efficiency, benefit/cost ratio and amount of renewable energy use. Data were collected from 50 irrigated and 50 dryland wheat growers by using a face-to-face questionnaire in 2009. The results showed that the total energy requirement under low input was 9354.2 MJ ha⁻¹, whereas under high input systems it was 45367.6 MJ ha⁻¹. Total energy input consumed in both dryland and irrigated systems could be classified as direct, indirect, renewable and non-renewable energies which average in two wheat production systems were 47%, 53%, 24% and 76%, respectively. Energy ratios of 3.38 in dryland and 1.44 in irrigated systems were achieved. The benefit–cost ratios were 2.56 in dryland and 1.97 in irrigated wheat production systems. Based on the results of the present study, dry-land farming can have a significant positive effect on energy-related factors especially in dry and semi-dry climates such as Iran.