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On the prediction of geochemical parameters(TOC,S1 and S2)by considering well log parameters using ANFIS and LSSVM strategies

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Petroleum 2022年第2期8卷 174-184页

作者： Danial Ahangari Reza Daneshfar mohammad zakeri Siavash Ashoori Bahram Soltani Soulgani Department of Petroleum Engineering Petroleum University of TechnologyAhwazIran Department of Geology Faculty of Earth SciencesS.Chamran University of AhwazIran

Geochemical parameters are useful properties to enhance hydrocarbon exploration ***,attaining these parameters,for instance total organic carbon(TOC),volatile and residual hydrocarbon(S1&S2)is a challenge for geologists due to the high cost and time ***,addressing this issue has become an interesting subject for many *** a result,on the ground of conventional well logs,vast kinds of methods,for example,back propagation artificial neural network(BPANN),have been introduced to solve this *** these kinds of methods brings scientists tremendous amounts of information related to the richness of organic matter in a ***,the precision of the aforementioned method is inadequate and BPANN is affected negatively by local ***,current study cope with this issue and alleviate the uncertainty,Least Squares Support Vector Machine(LSSVM)and Adaptive-Neuro Fuzzy Inference System(ANFIS)algorithms cooperating with the particle swarm optimization(PSO)were suggested as a suitable method to increase the precision of estimating geochemical *** data bank for this research was attained from available sources of Shahejie formation from Bohai bay basin located in China,which consists of geochemical and well logging *** of this study illustrated that ANFIS-PSO and LSSVMPSO have a great ability to estimate geochemical *** values of R^(2) obtained for these two models in order to predict the output parameters of TOC,S_(1) and S_(2) are equal to 0.6846&0.785,0.6864&0.778,and 0.7343&0.8128,*** statistical comparison between these models shows that LSSVM-PSO shows a better performance compared to another ***,a new attempt was implemented to evaluate the impacts of input parameters on the outputs and the results of sensitivity analysis suggest that transit interval time had the greatest effect on the output parameters.

关键词： Least squares support vector machine Total organic carbon Well log parameters Adaptive-neuro fuzzy inference system Particle swarm optimization

Use of complementary and alternative medicine in general population during COVID-19 outbreak: A survey in Iran

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Journal of Integrative Medicine 2022年第1期20卷 45-51页

作者： Mahlagha Dehghan Alireza Ghanbari Fatemeh Ghaedi Heidari Parvin Mangolian Shahrbabaki mohammad Ali zakeri Nursing Research Center Kerman University of Medical SciencesKerman 76169-13555Iran Anesthesiology and Critical Care Research Center Shiraz University of Medical SciencesShiraz 14336-71348Iran Faculty of Nursing and Midwifery Isfahan University of Medical SciencesIsfahan 81746-73461Iran Non-communicable Diseases Research Center Rafsanjan University of Medical SciencesRafsanjan 77179-33777Iran Social Determinants of Health Research Center Rafsanjan University of Medical SciencesRafsanjan 77179-33777Iran Department of Critical Care Nursing Faculty of Nursing and MidwiferyKerman University of Medical SciencesKerman 76169-13555Iran

Objective: Some epidemic diseases such as coronavirus disease 2019(COVID-19) have caused many physical, psychological, and social challenges, despite the existence of treatment strategies. Many people are looking for complementary and alternative medicine(CAM) to prevent such diseases. The present study was performed to determine how some types of CAM were being used during the COVID-19 epidemic in ***: The present study had a cross-sectional descriptive correlational design. All Iranian residents above 17 years old were eligible to participate in the study. A total of 782 participants completed a demographic information questionnaire, a questionnaire about their use of CAMs and a questionnaire about their satisfaction with the CAMs they used. Web-based sampling was conducted from 20 April 2020 to 20 August ***: Of the participants, 84% used at least one type of CAM during the COVID-19 outbreak. The most used CAMs were dietary supplements(61.3%), prayer(57.9%), and herbal medicines(48.8%). The majority of the participants(50%–66%) have used CAMs to prevent the transmission of COVID-19 or to reduce anxiety caused by the COVID-19 pandemic. CAM use was associated with sex, having children, place of residence, COVID-19 status, and source of gathering information about CAM(P < 0.05). All 32 participants who had been infected with COVID-19 used at least one type of CAM for treatment or alleviation of the disease ***: During the COVID-19 outbreak, some types of CAM, particularly nutritional supplements,medicinal herbs, and prayer, were commonly used to prevent COVID-19 and reduce pandemic-related anxiety.

关键词： Alternative and complementary medicine Coronavirus disease COVID-19 Cross-sectional study

Role of herbal medicines to treat the symptoms of COVID-19 disease

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TMR Clinical Research 2021年第2期4卷 42-45页

作者： mohammad Ali zakeri Mahlagha Dehghan Non-Communicable Diseases Research Center Rafsanjan University of Medical SciencesRafsanianIran Nursing Research Center Kerman University of Medical SciencesKermanlran.

The need for effective therapeutic options for patients has received increasing attention in response to the prevalence of COVID *** there are several options for the prevent of COVID-19,including vaccines,monoclonal antibodies,oligonucleotide-based therapies,peptides,and interferon therapies,no treatment for coronaviruses has yet been approved[1].

关键词： herbal interferon monoclonal

A minimal model for two-component FIMP dark matter:A basic search

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Chinese Physics C 2018年第7期42卷 1-11页

作者： S. Peyman zakeri S. mohammad Moosavi Nejad mohammadreza zakeri S. Yaser Ayazi Faculty of Physics Yazd University Yazd Iran School of Particles and Accelerators Institute for Research in Fundamental Sciences (IPM) Tehran Iran Physics and Astronomy Department University of California California 92521 USA CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing 100190 China Physics Department Semnan University Semnan Iran

In the multi-component configurations of dark matter phenomenology, we propose a minimal two-component configuration which is an extension of the Standard Model with only three new fields; one scalar and one fermion interact with the thermal soup through Higgs portal, mediated by the other scalar in such a way that the stabilities of dark matter candidates are made simultaneously by an explicit Z2 symmetry. Against the most common freeze-out framework, we look for dark matter particle signatures in the freeze-in scenario by evaluating the relic density and detection signals. A simple distinguishing feature of the model is the lack of dark matter conversion, so the dark matter components act individually and the model can be adapted entirely to both singlet scalar and singlet fermionic models, separately. We find dark matter self-interaction as the most promising approach to probe such feeble models. Although the scalar component satisfies this constraint, the fermionic one refuses it even in the resonant region.

关键词： dark matter FIMP