Review: the latest advances in biomedical applications of chitosan hydrogel as a powerful natural structure with eye-catching biological properties

Journal of Materials Science - Chitosan is one of the natural cationic polymers with unique properties such as non-toxicity, biodegradability, biocompatibility, environmentally friendly that has...     

Proactive task migration with a self-adjusting migration threshold for dynamic thermal management of multi-core processors

Request for more computation power steadily forces designers to provide more powerful processors using more number of cores on a single chip. The increasing complexity of processors leads to higher integration density, power density, and temperature. For avoiding thermal emergencies, various dynamic thermal management techniques have been presented. In this paper, we present a novel online self-adjusting temperature threshold schema for dynamic thermal management to minimize both average and peak temperature with very low performance overhead. Our proposed algorithm adjusts migration threshold according to workload and hardware platforms. The experimental results indicate that our technique can significantly decrease the average and peak temperature compared to Linux standard scheduler, and two well-known thermal management techniques: PDTM and TAS.     

Predictive model for shear strength estimation in reinforced concrete beams with recycled aggregates using Gaussian process regression

Neural Computing and Applications - In order to attain sustainable development, recycled concrete aggregates (RCAs) are increasingly utilized in civil engineering projects. Therefore, it is vital...     

A new set of sufficient conditions based on coupling parameters for synchronization of Hopfield like Chaotic Neural Networks

In this paper, we consider a Hopfield like Chaotic Neural Networks which have both self-coupling and non-invertible activation functions. We show that the interactions between neurons can be used as a means of chaos generation or suppression to neuron’s outputs when more adaptability or stability is required. Furthermore, a new set of sufficient conditions based on coupling weights is proposed so that the synchronization of all neuron’s outputs with each other is guaranteed, when all neuron’s have identical activation functions. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on three illustrative examples.     

Numerical solution of fuzzy relational equations based on smooth fuzzy norms

In this paper, we study and formulate a BP learning algorithm for fuzzy relational neural networks based on smooth fuzzy norms for functions approximation. To elaborate the model behavior more, we have used different fuzzy norms led to a new pair of fuzzy norms. An important practical case in fuzzy relational equations (FREs) is the identification problem which is studied in this work. In this work we employ a neuro-based approach to numerically solve the set of FREs and focus on generalized neurons that use smooth s-norms and t-norms as fuzzy compositional operators.     

A non-reference image fusion metric based on mutual information of image features

The widespread usage of image fusion causes an increase in the importance of assessing the performance of different fusion algorithms. The problem of introducing a suitable quality measure for image fusion lies in the difficulty of defining an ideal fused image. In this paper, we propose a non-reference objective image fusion metric based on mutual information which calculates the amount of information conducted from the source images to the fused image. The considered information is represented by image features like gradients or edges, which are often in the form of two-dimensional signals. In this paper, a method of estimating the joint probability distribution from marginal distributions is also presented which is employed in calculation of mutual information. The proposed method is compared with the most popular existing algorithms. Various experiments, performed on several databases, certify the efficiency of our proposed method which is more consistent with the subjective criteria.     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Fermentation of table cream by Lactobacillus plantarum strains: effect on fungal growth,aflatoxin M1 and ochratoxin A

Aflatoxin M1 (AFM₁) and ochratoxin A (OTA) are two main mycotoxins in milk and dairy products. In the present work, the ability of four Lactobacillus strains (L. plantarum PTCC 1058, L. plantarum LP3, L. plantarum AF1 and L. plantarum LU5) to remove AFM1 and OTA in fermented cream was studied during 24 h fermentation. The antifungal activity of the mentioned lactobacilli against the defined fungi (Aspergillus flavus PTCC 5004, Aspergillus parasiticus PTCC 5018, Aspergillus nidulans PTCC 5014, Aspergillus ochraceus PTCC 5060) was also evaluated. The results showed that the cell counts of all strains were increased by 64–70% during fermentation. All Lactobacillus strains decreased the amount of AFM₁ significantly (P ≤ 0.05) in the range of 26–52%, which the highest AFM₁-reducing effect was related to L. plantarum LU5 (from 0.5 to 0.24 μg kg⁻¹). The mean OTA removal by Lactobacillus strains in fermented cream also ranged from 32 to 58%. Amongst Lactobacillus strains, the cell-free culture supernatants of L. plantarum LU5 showed the highest (inhibition zone of 26.7 ± 1.2 mm) and L. plantarum LP3 and L. plantarum PTCC 1058 the lowest antifungal activities. The fermented creams contained Lactobacillus strains exhibited the highest and lowest antifungal activities against A. ochraceus and A. parasiticus, respectively. L. plantarum LU5, with the inhibition zone of 27.6 ± 0.9 mm, was the most effective fungal inhibitor, while L. plantarum PTCC 1058 had the lowest antifungal activity.     

Effect of pulsed ultrasound treatment compared to continuous mode on microbiological and quality of Mirabelle plum during postharvest storage

The effects of pulsed and continuous ultrasound treatment on microbiological and physiological quality of Mirabelle plum fruit were investigated. Freshly harvested Mirabelle plum was treated with 30‐kHz pulsed and continuous ultrasound at 20 °C for 0, 15, 30, 45 and 60 min and subsequently stored at 4 °C for 10 days. The total count of bacteria, total fungi, decay index, titratable acidity (TA), total soluble solids (TSS), colour, texture, ascorbic acid content and total phenolics was measured. The results showed that pulsed and continuous ultrasonic treatment significantly (P < 0.05) reduced the number of microorganisms and improved the quality of Mirabelle plums during storage. Increasing pretreatment time enhanced the positive effects of pulsed and continuous ultrasound. Also, in terms of the total count of bacteria, total fungi, titratable acidity and total phenolics, the pulsed and continuous ultrasound did not show a significant difference (P < 0.05). However, pulsed ultrasound was better compared to continuous mode in preservation of TSS, colour, texture and ascorbic acid content of the fruit during storage. Our results demonstrated that pulsed ultrasound is an appropriate method for improving safety and maintaining the quality of Mirabelle plum fruit.