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| 1 | Stir casting process for manufacture of Al-SiC composites显示文摘Stir casting is an economical process for the fabrication of aluminum matrix composites.There are many parameters in this process,which affect the final microstructure and mechanical properties of the composites.In this study,micron-sized SiC particles were used as reinforcement to fabricate Al-3 wt% SiC composites at two casting temperatures(680 and 850 ℃) and stirring periods(2 and 6 min).Factors of reaction at matrix/ceramic interface,porosity,ceramic incorporation,and agglomeration of the particles were evaluated by scanning electron microscope(SEM) and high-resolution transition electron microscope(HRTEM) studies.From microstructural characterizations,it is concluded that the shorter stirring period is required for ceramic incorporation to achieve metal/ceramic bonding at the interface.The higher stirring temperature(850 ℃) also leads to improved ceramic incorporation.In some cases,shrinkage porosity and intensive formation of Al_4C_3 at the metal/ceramic interface are also observed.Finally,the mechanical properties of the composites were evaluated,and their relation with the corresponding microstructure and processing parameters of the composites was discussed. | Shahin Soltani Rasoul Azari Khosroshahi Reza Taherzadeh Mousavian Zheng-Yi Jiang Alireza Fadavi Boostani Dermot Brabazon | 2017 | Rare Metals2017，36，7： | 7 |
| 2 | Lung nodule segmentation and recognition using SVM classifier and active contour modeling: A complete intelligent system显示文摘 | Mohsen Keshani Zohreh Azimifar Farshad Tajeripour Reza Boostani | 2012 | Computers in Biology and Medicine2012，，： | 2 |
| 3 | Lead stabilization in a polluted calcareous soil using cost-effective biochar and zeolite amendments after spinach cultivation显示文摘Biochar has been shown to be an effective organic soil amendment for the in-situ immobilization of lead(Pb).Little research has been done on the effects of biochar and zeolite interactions on Pb immobilization in contaminated calcareous soils.Therefore,the aim of this study was to investigate the effects of different levels of zeolite(2%and 4%,weight:weight)and biochars(3%,weight:weight)prepared from green compost(GB),poultry manure(PB),and municipal waste(MB)on the content of Pb in spinach shoots and Pb stabilization in a greenhouse experiment conducted using a Pb-contaminated calcareous soil.Application of GB and PB significantly decreased the Pb mobility factor(MF)from 2.8%to 4.6%and the cumulative Pb release(diethylenetriamine pentaacetate(DTPA)extraction)from 16.8%to 20.1%in the calcareous soil,which were further enhanced by the combined addition of zeolite,with Pb MF reduction from 4.4%to 8.4%and cumulative Pb release reduction from 24.8%to 28.6%.The enhancement of soil Pb immobilization was attributed to the properties of the amendments,such as high pH,ash content,and phosphorus content(10.5^(-1)1.0,390-435 g kg^(-1),and 2.5-4.3 g kg^(-1),respectively).Results of the soil Pb sequential extraction and Pb release kinetics were highly and significantly correlated with spinach shoot Pb content.Soil chemical data showed that the application of MB with 4%zeolite was the most effective treatment for immobilizing Pb(8.4%reduction in Pb MF and 28.6%reduction in cumulative DTPA-extractable Pb),which is in agreement with the results of the spinach shoot Pb(89.0%reduction in Pb uptake). | Hamid Reza BOOSTANI Ailsa G.HARDIE Mahdi NAJAFI-GHIRI | 2023 | Pedosphere2023，33，2： | 0 |
| 4 | The potential effects of Caper (Capparis spinosa L.) in the treatment of diabetic neuropathy显示文摘Diabetic neuropathy(DN)is the most common form of neuropathy worldwide,with its prevalence rising alongside diabetes,and being characterized by sensory,motor or autonomic symptoms.DN is considered to be an incurable complication of diabetes,the management of which mainly consists of improving glycemic control,managing pain relief and ensuring continuous foot care.Although gabapentin,duloxetine and tricyclic antidepressants are commonly used to reduce patient symptoms,they do not affect the pathophysiology and progression of neuropathy.Furthermore,these drugs can have various side effects including insomnia,decreased appetite,arrhythmia,heart failure,and suicidal behavior.According to traditional Persian medicine,DN is recognized as a type of“Khadar”or“Esterkha”(a sensory or motor disorder,respectively)that occurs due to the accumulation of sugars in the peripheral nerves.Capparis spinosa L.,commonly known as the caper plant,has been recommended in authentic sources of traditional Persian medicine to treat such disorders.In this study,we reviewed the pharmacological properties of C.spinosa using the Web of Science,PubMed,Scopus and Google Scholar databases,and found that Capparis spinosa L.could affect several pathways involved in DN pathogenesis,including aldose reductase activity,the secretion of inflammatory mediators(IL-17,TNF-α,IL-1β,IL-6),oxidative stress,hyperlipidemia,hyperglycemia and advanced glycation end product formation.Based on these findings,we hypothesize that Capparis spinosa L.,may prevent the progression and reduce the symptoms of diabetic neuropathy,and so can be considered as a complementary treatment in this disorder.This hypothesis should be evaluated in well-designed in vitro and in vivo studies,and through clinical trials. | Hamid Reza Esmaeilpour Reza Boostani Ali Shoeibi Mojtaba Mousavi Bazzaz Roshanak salari Mahdi Yousefi | 2020 | Traditional Medicine Research2020，5，6： | 0 |
| 5 | CDEC:a constrained deep embedded clustering显示文摘Purpose-The aim of this study is to propose a deep neural network(DNN)method that uses side information to improve clustering results for big datasets;also,the authors show that applying this information improves the performance of clustering and also increase the speed of the network training convergence.Design/methodology/approach-In data mining,semisupervised learning is an interesting approach because good performance can be achieved with a small subset of labeled data;one reason is that the data labeling is expensive,and semisupervised learning does not need all labels.One type of semisupervised learning is constrained clustering;this type of learning does not use class labels for clustering.Instead,it uses information of some pairs of instances(side information),and these instances maybe are in the same cluster(must-link[ML])or in different clusters(cannot-link[CL]).Constrained clustering was studied extensively;however,little works have focused on constrained clustering for big datasets.In this paper,the authors have presented a constrained clustering for big datasets,and the method uses a DNN.The authors inject the constraints(ML and CL)to this DNN to promote the clustering performance and call it constrained deep embedded clustering(CDEC).In this manner,an autoencoder was implemented to elicit informative low dimensional features in the latent space and then retrain the encoder network using a proposed Kullback-Leibler divergence objective function,which captures the constraints in order to cluster the projected samples.The proposed CDEC has been compared with the adversarial autoencoder,constrained 1-spectral clustering and autoencoder t k-means was applied to the known MNIST,Reuters-10k and USPS datasets,and their performance were assessed in terms of clustering accuracy.Empirical results confirmed the statistical superiority of CDEC in terms of clustering accuracy to the counterparts.Findings-First of all,this is the first DNN-constrained clustering that uses side information to improve the performance of clustering without using labels in big datasets with high dimension.Second,the author defined a formula to inject side information to the DNN.Third,the proposed method improves clustering performance and network convergence speed.Originality/value-Little works have focused on constrained clustering for big datasets;also,the studies in DNNs for clustering,with specific loss function that simultaneously extract features and clustering the data,are rare.The method improves the performance of big data clustering without using labels,and it is important because the data labeling is expensive and time-consuming,especially for big datasets. | Elham Amirizadeh Reza Boostani | 2021 | International Journal of Intelligent Computing and Cybernetics2021，14，4： | 0 |
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