فهرست مطالب a. ameri

This work proposes a deep learning model for skin cancer detection from skin lesion images. In this analytic study, from HAM10000 dermoscopy image database, 3400 images were employed including melanoma and non-melanoma lesions. The images comprised 860 melanoma, 327 actinic keratoses and intraepithelial carcinoma (AKIEC), 513 basal cell carcinoma (BCC), 795 melanocytic nevi, 790 benign keratosis, and 115 dermatofibroma cases. A deep convolutional neural network was developed to classify the images into benign and malignant classes. A transfer learning method was leveraged with AlexNet as the pre-trained model. The proposed model takes the raw image as the input and automatically learns useful features from the image for classification. Therefore, it eliminates complex procedures of lesion segmentation and feature extraction. The proposed model achieved an area under the receiver operating characteristic (ROC) curve of 0.91. Using a confidence score threshold of 0.5, a classification accuracy of 84%, the sensitivity of 81%, and specificity of 88% was obtained. The user can change the confidence threshold to adjust sensitivity and specificity if desired. The results indicate the high potential of deep learning for the detection of skin cancer including melanoma and non-melanoma malignancies. The proposed approach can be deployed to assist dermatologists in skin cancer detection. Moreover, it can be applied in smartphones for self-diagnosis of malignant skin lesions. Hence, it may expedite cancer detection that is critical for effective treatment.

Pattern recognition has shown remarkable success in decoding motor information from electromyogram (EMG) signals. To decrease the computational complexity in EMG pattern recognition, it may be useful to reduce the dimensionality of the model input. This paper investigates the effect of reducing the dimensionality of EMG features in a regression-based motion intent estimation model. Ten able-bodied subjects participated in this analytic study. EMG signals from the right forearm and angle of the left wrist in three degrees of freedom (DoF) were measured, concurrently. The TD features were extracted from eight EMG channels, resulting in a total of 32 features. Three dimensionality reduction methods including principal component analysis (PCA), non-negative matrix factorization (NNMF), and canonical correlation analysis (CCA) were applied to the EMG features. Reducing the dimension of the EMG features below a certain threshold degraded the performance of the EMG pattern recognition model. Otherwise, dimensionality reduction did not change the performance. These thresholds for the PCA, NNMF, and CCA methods were 25, 26, and 13, respectively. Based on the results, CCA substantially outperformed PCA and NNMF, as it allowed a significant reduction of the EMG features size, from 32 to 13, with no adverse impact on the performance.

Arcus Senilis (AS) appears as a white, grey or blue ring or arc in front of the periphery of the iris, and is a symptom of abnormally high cholesterol in patients under 50 years old.

This work proposes a deep learning approach to automatic recognition of AS in eye images.

In this analytical study, a dataset of 191 eye images (130 normal, 61 with AS) was employed where ¾ of the data were used for training the proposed model and ¼ of the data were used for test, using a 4-fold cross-validation. Due to the limited amount of training data, transfer learning was conducted with AlexNet as the pretrained network.

The proposed model achieved an accuracy of 100% in classifying the eye images into normal and AS categories.

The excellent performance of the proposed model despite limited training set, demonstrate the efficacy of deep transfer learning in AS recognition in eye images. The proposed approach is preferred to previous methods for AS recognition, as it eliminates cumbersome segmentation and feature engineering processes.

Cancer, one of the global health problems, has been introduced as one of the main death causes worldwide. Xanthine derivatives have been identified as effective compounds for prevention and treatment of cancer. In this study, a series of novel phenoxy ethyl theobromine derivatives were designed with N1 positioning and their cytotoxic activity was evaluated. Also, molecular docking studies were performed to predict the possible action mechanism of these compounds.

In the present laboratory investigation, compounds 2, 3, and 5a-l were initially synthesized. The cytotoxicity of all new synthesized compounds was studied by MTT (methylthiazolyldiphenyl-tetrazolium bromide) -based colorimetric assay against 4 human cancer cell lines. Autodock software was used to determine the binding energies of these structures on human tetrahydrofolate reductase, human octo-5'-nucleotidase (e5NT) and human phosphodiesterase enzymes. The obtained data were analyzed using one-way analysis of variance.

The results of docking studies showed acceptable binding energy (-8.42 kcal/mol) against e5NT. The results of cytotoxicity analysis showed that the greatest effect of cytotoxicity was against A549 and MCF-7 cells (compound 5e with IC50 values of 86.65 μM and 161.09 μM, respectively).

The results of molecular docking studies showed acceptable binding energy against the octo-5'-nucleotidase enzyme. Among the synthesized derivatives, compound 5a with the lowest ΔG level (-8.42 kcal/mol) was selected as the best inhibitor of this enzyme. Appropriate effects of cytotoxicity were observed at different concentrations of the synthesized compounds on MCF7 and A549 cell lines.

Today, using magnetic adsorbents and the subsequent magnetically separation of pollutants is highly considered by researchers due to it’s ease of use, low cost and rapid results. Therefore the aim of this study was the synthesis of a magnetic composite of activated carbon/Fe3O4 nanoparticles (Fe3O4/PAC), and its application as a magnetic adsorbent for simultaneous removal of lead and aniline from industrial wastewater.

Physical, surface and morphological features of the adsorbent, as well as, the performance of adsorption process were studied in a batch system by investigating the changes in parameters such as pH, contact time, adsorbent and adsorbate concentrations, and temperature. In order to explain experimental data, Freundlich and Langmuir equilibrium isotherms, in addition to Lagergren, Ho and Elovich kinetic equations were applied.

Results of this study demonstrated that 90 % of lead and 94 % of aniline were removable by the synthesized adsorbent under the optimal conditions (pH 6, a contact time 60 min and adsorbent dose of 2 g/L). Experimental data from adsorption were better described by both Langmuir and Freundlich isotherm models, and the pseudo-second-order kinetic model.

According to these results, it can be claimed that Fe3O4/PAC had an effective adsorption capacity for simultaneous adsorption of lead and aniline, and thus, it is recommended

The studied volcanic rocks are located in south of Sarab at the northern part of the Bozghoush mountaion. The rocks are megaporphyry andesite flows and trachy andesite basalt lavas associated with tuff. In the northern part of the study area these rocks are covered with younger sediments of Quarternary age. These rocks are containing phenocrysts of analcime, olivine, pyroxene and plagioclase. The major textures of these rocks are porphyry with intersertal matrix. According to whole rock analysis of the study area, rocks they are trachy andesite and tephro-phenolite. Also these rocks are high potassic to shoshonitic nature with peralluminous character. Based on textural evidence analcime seems to be primary and formed directly from magma. The rocks of north Bozghoush shows a pronounced enrichment in LILE (Rb, Ba, Tb, U, k). Enrichment of incompatible elements of k and Rb and negative anomaly of Ti and Nb in these rocks are comparable with melts of lower crust. The spider diagrams and REE patterns show that the rocks of the study area are formed from the same source. Enrichment of incompatible elements can be related to mantle metasomatism or contamination of continental crust. In this regards negative anomaly of Ta, Nb and Tb (T N T) and also with respect of eventual Neo-Thetys subduction in this area and most probably enrichment of incompatible elements indicates effects of subduction on mantle sources. According to REE investigation most probably the main source of these rocks were phologopite-bearing garnet lherzolite, with partial melting rate of 4-6 percent, at a pressure of 30-35 Kb and the depth of 90-100 Km.