Molecular typing of conjunctivitis-causing adenoviruses in Hanoi, Vietnam from 2017 to 2019 and complete genome analysis of the most prevalent type (HAdV-8).

Adenoviral conjunctivitis is a common epidemic worldwide. In Vietnam, up to 80,000 patients are infected with adenoviral conjunctivitis annually. However, there are few investigations on the pathogenic adenoviruses that cause conjunctivitis. In total, 120 eye-swab samples were collected from patients with viral conjunctivitis symptoms in Hanoi, Vietnam from 2017 to 2019. Human adenoviruse (HAdV) was detected in 67 samples (55.83%) using polymerase chain reaction amplification of at least one of three HAdV-specific marker genes (hexon, penton, and fiber). Of the 67 HAdV samples, 46 samples could be analyzed by all three marker genes. DNA sequence analysis and phylogenetic tree building based on the three marker genes from the 46 HAdV samples revealed five different HAdV types associated with conjunctivitis in Hanoi, including HAdV-3 (4.3%), HAdV-4 (2.2%), HAdV-8 (89.1%), HAdV-37 (2.2%), and a potential recombinant type between types HAdV-8 and HAdV-3 (2.2%). This showed that HAdV-8 was the most common type identified in Hanoi. Complete genome analysis of HAdV-8 isolated from a Vietnamese patient (VN2017) using Sanger sequencing revealed 34 unique nucleotide changes, indicating that the adenovirus continuously accumulates new mutations. Hence, continuous surveillance of HAdV-8 changes in Vietnam is necessary in the future.

A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns.

In this study, a novel hybrid surrogate machine learning model based on a feedforward neural network (FNN) and one step secant algorithm (OSS) was developed to predict the load-bearing capacity of concrete-filled steel tube columns (CFST), whereas the OSS was used to optimize the weights and bias of the FNN for developing a hybrid model (FNN-OSS). For achieving this goal, an experimental database containing 422 instances was firstly gathered from the literature and used to develop the FNN-OSS algorithm. The input variables in the database contained the geometrical characteristics of CFST columns, and the mechanical properties of two CFST constituent materials, i.e., steel and concrete. Thereafter, the selection of the appropriate parameters of FNN-OSS was performed and evaluated by common statistical measurements, for instance, the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). In the next step, the prediction capability of the best FNN-OSS structure was evaluated in both global and local analyses, showing an excellent agreement between actual and predicted values of the load-bearing capacity. Finally, an in-depth investigation of the performance and limitations of FNN-OSS was conducted from a structural engineering point of view. The results confirmed the effectiveness of the FNN-OSS as a robust algorithm for the prediction of the CFST load-bearing capacity.

Design, synthesis and evaluation of novel hybrids between 4-anilinoquinazolines and substituted triazoles as potent cytotoxic agents.

In this research several series of novel dioxygenated ring fused 4-anilinoquinazolines (10a-d) and 4-anilinoquinazoline-substituted triazole hybrid compounds (11-14) have been designed and synthesized. Their biological significance was highlighted by evaluating in vitro for anticancer activities, wherein several compounds displayed excellent activity specifically against three human cancer cell lines (KB, epidermoid carcinoma; HepG2, hepatoma carcinoma; SK-Lu-1, non-small lung cancer). Especially, compound 13a exhibited up to 100-fold higher cytotoxicity in comparison with erlotinib. Docking the most cytotoxic compounds (11d, 13a, 13b, and 14c) into the ATP binding site of different EGFR tyrosine kinase domains was perfomed to predict the analogous binding mode of these compounds to the EGFR targets.

Assessment of the Effectiveness of Ultrasound-Guided Needle Aspiration of Lactating Breast Abscesses.

Objective: To evaluate the effectiveness of ultrasound-guided needle aspiration in treating lactating breast abscesses. Methods: This study was conducted in Bach Mai Hospital, from 6/2020 to 7/2021. Lactating patients with breast abscesses underwent ultrasound-guided aspiration followed by antibiotics therapy. Results: There were 59 lactating patients with 82 breast abscesses. Most of the abscesses had heterogeneous echogenicity, no capsule, and a size smaller than 5cm. Bacterial culture results showed that 85.4% of cases were Methicillin-resistant Staphylococcus aureus. The number of aspirations was from 1 to 5. The cure rate was 91.5%, and 5.3% of these cases had a complication associated with galactocele after treatment. Conclusion: Ultrasound-guided needle aspiration is a minimally invasive treatment option for lactating breast abscesses with a high complete cure rate and good cosmetic results.

Pb(II) adsorption mechanism and capability from aqueous solution using red mud modified by chitosan.

Red mud modified by chitosan (RM/CS) was utilized as an adsorbent to effectively remove Pb(II) from aqueous solution. The surface area of RM/CS was found to significantly increase by more than 50% compared to that of original red mud. Different factors that affected the Pb(II) removal on this material, such as initial Pb(II) concentration, pH, and contact time, were investigated. The pseudo-first-order, pseudo-second-order, and intra-diffusion models were used to fit the experimental data to investigate the Pb(II)'s removal kinetics. The Pb(II) removal followed the intra-diffusion model. Additionally, the non-zero C value obtained from this model indicates that the removal was controlled by many different mechanisms. We also found that the interaction of Pb(II) and carbonate group on the material's surface played a primary role once the adsorption equilibrium was reached. Finally, the maximum adsorptive capacity was found to be about 209 mg/g. This obtained value is higher than those obtained for some other materials. Therefore, the present RM/CS should be a potential material for removing Pb(II) from aqueous solution.

Investigation of ANN architecture for predicting shear strength of fiber reinforcement bars concrete beams.

In this paper, an extensive simulation program is conducted to find out the optimal ANN model to predict the shear strength of fiber-reinforced polymer (FRP) concrete beams containing both flexural and shear reinforcements. For acquiring this purpose, an experimental database containing 125 samples is collected from the literature and used to find the best architecture of ANN. In this database, the input variables consist of 9 inputs, such as the ratio of the beam width, the effective depth, the shear span to the effective depth, the compressive strength of concrete, the longitudinal FRP reinforcement ratio, the modulus of elasticity of longitudinal FRP reinforcement, the FRP shear reinforcement ratio, the tensile strength of FRP shear reinforcement, the modulus of elasticity of FRP shear reinforcement. Thereafter, the selection of the appropriate architecture of ANN model is performed and evaluated by common statistical measurements. The results show that the optimal ANN model is a highly efficient predictor of the shear strength of FRP concrete beams with a maximum R2 value of 0.9634 on the training part and an R2 of 0.9577 on the testing part, using the best architecture. In addition, a sensitivity analysis using the optimal ANN model over 500 Monte Carlo simulations is performed to interpret the influence of reinforcement type on the stability and accuracy of ANN model in predicting shear strength. The results of this investigation could facilitate and enhance the use of ANN model in different real-world problems in the field of civil engineering.

Fabrication of SiO2/PEGDA Inverse Opal Photonic Crystal with Fluorescence Enhancement Effects.

The present paper reports the fabrication of inverse opal photonic crystals (IOPCs) by using SiO2 spherical particles with a diameter of 300 nm as an opal photonic crystal template and poly(ethylene glycol) diacrylate (PEGDA) as an inverse opal material. Characteristics and fluorescence properties of the fabricated IOPCs were investigated by using the Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), reflection spectroscopy, and fluorescence microscopy. The results clearly showed that the IOPCs were formed comprising of air spheres with a diameter of ∼270 nm. The decrease in size led to a decrease in the average refractive indexes from 1.40 to 1.12, and a remarkable stopband blue shift for the IOPCs was thus achieved. In addition, the obtained results also showed a fluorescence enhancement over 7.7-fold for the Fluor® 488 dye infiltrated onto the IOPCs sample in comparison with onto the control sample.

Fatty acid composition and oil content during coriander fruit development.

Coriander contains petroselinic acid, an isomer fatty acid of oleic acid. Coriander seed oil has been proposed as novel food ingredient in the European Union. Field experiments were performed at Auch (France) during two seasons (2010 and 2011). From flowering to maturity, fruits were harvested weekly and oil content and fatty acid (FA) compositions were determined. Fruits presented 2% more oil in 2010 than in 2011. Petroselinic acid (PA) contents was higher in 2011 than in 2010. Oil accumulation began earlier after flowering (2 DAF) in 2011. A first step in accumulation was identified between two and 21 DAF characterized by high SFA and PUFA, which decreased 21 DAF. Subsequently, PA increased to its highest concentration (30-55 DAF) and SFA and PUFA reached their lowest. These results suggest that higher concentrations of PA can be achieved by collecting fruits before full maturity.

Parametric Investigation of Particle Swarm Optimization to Improve the Performance of the Adaptive Neuro-Fuzzy Inference System in Determining the Buckling Capacity of Circular Opening Steel Beams.

In this paper, the main objectives are to investigate and select the most suitable parameters used in particle swarm optimization (PSO), namely the number of rules (nrule), population size (npop), initial weight (wini), personal learning coefficient (c1), global learning coefficient (c2), and velocity limits (fv), in order to improve the performance of the adaptive neuro-fuzzy inference system in determining the buckling capacity of circular opening steel beams. This is an important mechanical property in terms of the safety of structures under subjected loads. An available database of 3645 data samples was used for generation of training (70%) and testing (30%) datasets. Monte Carlo simulations, which are natural variability generators, were used in the training phase of the algorithm. Various statistical measurements, such as root mean square error (RMSE), mean absolute error (MAE), Willmott's index of agreement (IA), and Pearson's coefficient of correlation (R), were used to evaluate the performance of the models. The results of the study show that the performance of ANFIS optimized by PSO (ANFIS-PSO) is suitable for determining the buckling capacity of circular opening steel beams, but is very sensitive under different PSO investigation and selection parameters. The findings of this study show that nrule = 10, npop = 50, wini = 0.1 to 0.4, c1 = [1, 1.4], c2 = [1.8, 2], fv = 0.1, which are the most suitable selection values to ensure the best performance for ANFIS-PSO. In short, this study might help in selection of suitable PSO parameters for optimization of the ANFIS model.

Chitosan-MnO2 nanocomposite for effective removal of Cr (VI) from aqueous solution.

In this report, the adsorption of Cr(VI) onto MnO2/CS nanocomposite material from aqueous solution is investigated. All the factors, which affect the adsorption, such as pH, adsorption time, Cr(VI) initial concentration and adsorbent dosage, are also examined. The results obtained show that the Cr(VI) uptake is strongly affected by pH and ion strength. Analysis within the nonlinear isotherm models indicates that the Sips isotherm combining with the Langmuir and Freundlich models offer the best fit to the experimental data due to the obtained highest R2 and smallest RMSE and χ2 values. The calculated Langmuir monolayer adsorption capacity is 61.56 mg g-1 at pH of 2.0 and adsorption time of 120 min. Moreover, the mechanism studies by combining theoretical models with analytical spectroscopies reveal that the electrostatic attraction plays the important role to the uptake of Cr(VI) onto MnO2/CS nanocomposite. Therefore, the present nanocomposite material can be applied to remove total Cr from wastewater produced by the galvanized manufacturing factory with a relatively high efficiency.