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Fabrication of Porous Mg-Zn Scaffold through Modified Replica Method for Bone Tissue Engineering

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Journal of Bionic Engineering 2018年第5期15卷 907-913页

作者： Amir Hamed Aghajanian bijan abbasi Khazaei Mohammad Khodaei Mohammad Rafienia Department of Materials Engineering Faculty of Engineering Razi University Kermanshah Iran Dental Research Center School of Dentistry Isfahan University of Medical Sciences Isfahan 81746-73461 Iran Biosensor Research Center lsfahan University of Medical Sciences Isfahan 81744176 Iran

Biodegradable scaffolds are essential parts in hard tissue engineering. A highly porous magnesium-zinc （Mg-Zn 4 wt.%） scaffold with different Mg-Zn powder to liquid media ratios （50 wt.%, 70 wt.% and 90 wt.%） and different concentrations of ethanol （0 vol.%, 10 vol.%, 20 vol.% and 40 vol.%） were prepared through modified replica method. The mechanical properties were assessed through compression test and the structures of scaffolds were examined by Scanning Electron Microscope （SEM）. Results show that, the increase in Mg-Zn powder to liquid media ratio （50 wt.% to 90 wt.%） in ethanol free slurry, increases the thickness of struts （37 lam to 74 lam） and the plateau stress （0.5 MPa to 1.4 MPa）. The results obtained from X-ray Diffractometry （XRD） and compression test indicate that consuming ethanol in liquid media of replica, results in higher plateau stress by 46% due to less Mg-water reaction and no formation of Mg（OH）2 in the scaffold. The results of porosity measurement indicate that water-ethanol mixture composition and different solid fractions have no significant effects on true and apparent porosities of the fabricated scaffolds.

关键词： porous magnesium scaffold replica method Mg-Zn powder to water ratio mechanical properties

悬浮固化液相微萃取-高效液相色谱法测定人血浆和尿样中的卡巴咪嗪（英文）

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色谱 2015年第6期33卷 634-641页

作者： Mohammad ASADI Ali Mohammad HAJI SHABANI Shayessteh DADFARNIA bijan abbasi Department of Chemistry Faculty of ScienceYazd University Khorassan Research Institute for Food Science and Technology

Solidified floating organic drop microextraction(SFODME)in combination with high performance liquid chromatography was used for separation/preconcentration and determination of carbamazepine(CBZ)in human plasma and urine *** that affect the extraction efficiency such as the type and volume of extraction solvent,ionic strength,sodium hydroxide concentration,stirring rate,sample volume and extraction time,were investigated and *** the optimum conditions(extraction solvent,40μL of 1-undecanol;sodium hydroxide concentration,1 mol/L;temperature,50℃;stirring speed,400 r/min;sample volume,8 mL;sodium chloride concentration,3%(w/v)and extraction time,60 min)the calibration curve was found to be linear in the mass concentration range of 0.4-700.0μg/*** limit of detection(LOD)was 0.1μg/L and the relative standard deviation(RSD)for six replicate extraction and determination of carbamazepine at 100μg/L level was found to be 4.1%.The method was successfully applied to the determination of CBZ in human plasma and urine samples.

关键词： solidified floating organic drop microextraction(SFODME) high performance liquid chromatogra-phy(HPLC) carbamazepine(CBZ) plasma urine preconcentration

Improving the Surface Roughness of Dental Implant Fixture by Considering the Size,Angle and Spraying Pressure of Sandblast Particles

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Journal of Bionic Engineering 2024年第1期21卷 303-324页

作者： Ehsan Anbarzadeh bijan Mohammadi School of Mechanical Engineering Iran University of Science and TechnologyTehranIran

In this study,different conditions of sandblasting on dental implant fixtures were investigated to achieve the best sandblasting conditions.18 different sandblasting conditions(Using 152 implant fixture samples)were examined,including parameters such as particle size,particle blasting pressure,and particle blasting *** surface treatment of the samples was performed using the SLA+Anodizing *** testing was performed for each of the 18 different states,and the average surface roughness of each of these was compared with each ***,a bone layer was placed on the sample with the closest average surface roughness to the standard and the least amount of aluminum oxide on its surface among the 18 different states,to confirm the accuracy and quality of the desired surface roughness by examining the bone formation process and *** results showed that state No.4(sandblast particle size:75µm,spraying pressure of sandblast particles:4 bar,sandblast particle spraying angle:30 degrees),which was prepared using the SLA+Anodizing method and had a surface roughness of 1.989µm(The percentage of Al_(2)O_(3)on the surface=6%),had the best sandblasting conditions and showed 95%cell viability and accelerated the treatment and bone formation process for about a *** simulation results,using Abaqus software,indicated that the stress distribution on the surface of the implant fixture in contact with the bone surface has increased by approximately 4.3%for state *** will help prevent loosening of the dental implant fixture over time.

关键词： Dental implants Surface treatment Sandblast Surface roughness Osseointegration

Machine learning predicts long-term mortality after acute myocardial infarction using systolic time intervals and routinely collected clinical data

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智慧医学（英文） 2024年第3期04卷 170-176页

作者： Roudini bijan Khajehpiri Boshra Moghaddam Hamid Abrishami Forouzanfar Mohamad Department of Systems Engineering School of Advanced Technology University of Quebec Montreal Canada Machine Vision and Medical Image Processing (MVMIP) Laboratory Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran Research Center of the Montreal University Institute of Geriatrics Montreal Canada

Background:Precise estimation of current and future comorbidities of patients with cardiovascular disease is an important factor in prioritizing continuous physiological monitoring and new therapies. Machine learning (ML) models have shown satisfactory performance in short-term mortality prediction in patients with heart disease, whereas their utility in long-term predictions is limited. This study aimed to investigate the performance of tree-based ML models on long-term mortality prediction and effect of two recently introduced biomarkers on long-term ***:This study used publicly available data from the Collaboration Center of Health Information Application at the Ministry of Health and Welfare, Taiwan, China. The collected data were from patients admitted to the cardiac care unit for acute myocardial infarction (AMI) between November 2003 and September 2004. We collected and analyzed mortality data up to December 2018. Medical records were used to gather demographic and clinical data, including age, gender, body mass index, percutaneous coronary intervention status, and comorbidities such as hypertension, dyslipidemia, ST-segment elevation myocardial infarction, and non-ST-segment elevation myocardial infarction. Using the data, collected from 139 patients with AMI, from medical and demographic records as well as two recently introduced biomarkers, brachial pre-ejection period (bPEP) and brachial ejection time (bET), we investigated the performance of advanced ensemble tree-based ML algorithms (random forest, AdaBoost, and XGBoost) to predict all-cause mortality within 14 years. A nested cross-validation was performed to evaluate and compare the performance of our developed models precisely with that of the conventional logistic regression (LR) as the baseline ***:The developed ML models achieved significantly better performance compared to the baseline LR (C-Statistic, 0.80 for random forest, 0.79 for AdaBoost, and 0.78 for XGBoost,

关键词： Electrocardiogram Predication Mortality prediction Machine learning

GA-based approach to phase compensation of large phased array antennas

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Journal of Systems Engineering and Electronics 2018年第4期29卷 723-730页

作者： ZAHEDI Amir abbasi ARAND bijan Department of Electrical and Computer Engineering Tarbiat Modares University

The investigation of the effect of electrical and mechanical errors on the performance of a large active phased array antenna is studied. These errors can decrease the antenna performance, for instance, the gain reduction, side lobe level enhancement, and incorrect beam direction. In order to improve the performance of the antenna in the presence of these errors, phase error correction of large phased array antennas using the genetic algorithm（GA） is implemented. By using the phase compensation method, the antenna overall radiation pattern is recovered close to the ideal radiation pattern without error. By applying the simulation data to a 32×40 array of elements with a square grid at the frequency of S-band and measurement of the radiation pattern, the effectiveness of the proposed method is verified.

关键词： antenna genetic algorithm (GA) phased array radi-ating element.

Cancer immunotherapy with envelopedself-amplifying mRNA CARG-2020 thatmodulates IL-12,IL-17 and PD-L1 pathways toprevent tumor recurrence

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Acta Pharmaceutica Sinica B 2024年第1期14卷 335-349页

作者： Ju Chen Bhaskara Reddy Madina Elham Ahmadi Timur Olegovich Yarovinsky Marie Marthe Krady Eileen Victoria Meehan Isabella China Wang Xiaoyang Ye Elise Pitmon Xian-Yong Ma bijan Almassian Valerian Nakaar Kepeng Wang Department of Immunology School of MedicineUniversity of Connecticut Health CenterFarmingtonCT 06030USA CaroGen Corporation FarmingtonCT 06030USA The Eighth Clinical Medical College of Guangzhou University of Chinese Medicine Foshan Hospital of Traditional Chinese MedicineFoshan 528000China The Loomis Chaffee School WindsorCT 06095USA

Targeting multiple immune mechanisms may overcome therapy resistance and further improve cancer immunotherapy for ***,we describe the application of virus-like vesicles(VLV)for delivery of three immunomodulators alone and in combination,as a promising approach for cancer *** vectors were designed to deliver single chain interleukin(IL)-12,shorthairpin RNA(shRNA)targeting programmed death ligand 1(PD-L1),and a dominant-negative form of IL-17 receptor A(dn-IL17RA)as a single payload or as a combination *** delivery of the VLV vector expressing IL-12 alone,as well as the trivalent vector(designated CARG-2020)eradicated large established ***,only CARG-2020 prevented tumor recurrence and provided long-term survival benefit to the tumor-bearing mice,indicating a benefit of the combined *** abscopal effects of CARG-2020 on the non-injected contralateral tumors,as well as protection from the tumor cell re-challenge,suggest immune-mediated mechanism of protection and establishment of immunological ***,CARG-2020 potently activates Th1 immune mechanisms and inhibits expression of genes related to T cell exhaustion and cancer-promoting *** ability of CARG-2020 to prevent tumor recurrence and to provide survival benefit makes it a promising candidate for its development for human cancer immunotherapy.

关键词： Virus-like vesicles Oncolytic virus IL-12 IL-17 PD-L1 T cell exhaustion Combination therapy Cancer immunotherapy

Analysis of the overall pressure balance loop for a methanol-to-olefins dual fluidized bed reactor-regenerator

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Particuology 2023年第11期82卷 13-24页

作者： bijan Hejazi Neda Shabany Chemical Engineering Department Faculty of EngineeringFerdowsi University of MashhadMashhad***Iran Petrochemical Research and Technology Co. TehranIran

Development of a comprehensive reactor model is of paramount importance for design and scale-up of methanol-to-olefins (MTO) process in a dual fluidized bed reactor (DFB). These models must integrate suitable reaction kinetic expressions with hydrodynamic models properly descriptive of gas-solid contact in fluidized bed reactors. In this modeling study, our previously developed kinetic models of MTO fluidized bed reactor and regenerator are coupled with overall mass, energy and pressure balances to ensure smooth circulation of catalyst particles between the two fluidized beds. This integrated model was then applied to determine geometric dimensions of a demo-scale MTO DFB configuration and to obtain the mass distribution of catalyst particles throughout the entire system including the pipes connecting the two reactors. Our model is capable of being integrated into simulation software such as Aspen Plus for plant-wide optimization and scale-up studies.

关键词： Pressure balance loop Methanol-to-olefins Dual fluidized bed SAPO-34 catalyst

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1421-1432页

作者： bijan Afrasiabian Mosleh Eftekhari Department of Mining Engineering Science and Research BranchIslamic Azad UniversityTehranIran Department of Mining Engineering Faculty of EngineeringTarbiat Modares UniversityTehranIran

Prediction of mode I fracture toughness(KIC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression(LMR) and gene expression programming(GEP)methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and elastic modulus(E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing ***, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of KIC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination(R2),root mean square error(RMSE), and mean absolute error(MAE) were utilized herein. In the case of testing datasets, the values of R2, RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156,respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R2value and lower errors.

关键词： Mode I fracture Toughness Critical stress intensity factor Linear multiple regression(LMR) Gene expression programming(GEP)

Drivers of Forecasting the Behavioral Intention and Acceptance Behavior of the Hail Canon Technology(HCT): Using Logistic and System Dynamics Modeling

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Chinese Geographical Science 2023年第3期33卷 549-564页

作者： ABADI bijan HAGHANINIA Mohammad Faculty of Agriculture University of MaraghehGolshahr Town 55181-83111Iran

Globally known about the drivers through which farmers are instigated to uphold and use Hail Canon Technology(HCT)is ***,this article intended to examine the drivers of forecasting the behavioral intention and acceptance behavior of the HCT,249 apple farmers from northwestern Iran were recruited,including adopters(n1=114)and non-adopters(n2=135).The conceptual foundation included demographic theory,resource-based theory,theory of planned behavior,innovation diffusion model,and institutional support *** also used the system dynamics model(SDM)in the Netlogo to assess the results of the conventional statistical approach(i.e.,the logistic model).Authenticated the fitness of conceptual model with the data,logistic model manifests that the most outstanding determinants of the acceptance of HCT entail age,experience,total land size,income,attitude,compatibility,visibility,relative advantage,and financial *** the SDM,it was also shown that the results of the logistic model are confirmed by the *** conclusion,management implications are available for the university extension to eliminate the adoption obstacles and stir up farmers to join in applying HCT,furthermore,researchers would avail themselves of remarks for future research.

关键词： Canon visibility furthermore