Search results for: Salehe Taheri

Authors: Ashkan Zargar, Ali Taheri Mirghaed, Zein Talal Barakat, Alireza Khosravi, Hamed Paknejad

Abstract:

With the increase of bacterial resistance to the chemical antibiotics, replacing it with ecofriendly herbal materials and with no adverse effects in the host body is very important. Therefore, in this study, the effect of combined essential oil (Thymus vulgaris-Origanum magorana and Ziziphora clinopodioides) on the growth behavior of Yersinia ruckeri, Aeromonas hydrophila and Lactococcus garvieae was evaluated. The compositions of the herbal essential oils used in this study were determined by gas chromatography-mass spectrometry (GC-MS) while, the investigating of antimicrobial effects was conducted by the agar-disc diffusion method, determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), and bacterial growth curves determination relied on optical density (OD) at 630 nm. The main compounds were thymol (40.60 %) and limonene (15.98 %) for Thymus vulgaris while carvacrol (57.86 %) and thymol (13.54 %) were the major compounds in Origanum magorana. As regards Ziziphora clinopodiodes, α-pinene (22.6 %) and carvacrol (21.1 %) represented the major constituents. Concerning Yersinia ruckeri, disc-diffusion results showed that t.O.z (50 % Origanum majorana) combined essential oil was presented the best inhibition zone (30.66 mm) but it was exhibited no significant differences with other tested commercial antibiotics except oxytetracycline (P <0/05). The inhibitory activity and the bactericidal effect of the t.O.z, unveiled by the MIC= 0.2 μL /mL and MBC= 1.6 μL /mL values, were clearly the best between all combined oils. The growth behaviour of Yersinia ruckeri was affected by this combined essential oil and changes in temperature and pH conditions affected herbal oil performance. As regard Aeromonas hydrophila, its results were so similar to Yersinia ruckeri results and t.O.z (50 % Origanum majorana) was the best between all combined oils (inhibition zone= 26 mm, MIC= 0.4 μL /mL and MBC= 3.2 μL /mL, combined essential oil was affected bacterial growth behavior). Also for Lactococcus garvieae, t.O.z (50 % Origanum majorana) was the best between all combined oils having the best inhibition zone= 20.66 mm, MIC= 0.8 μL /mL and MBC= 1.6 μL /mL and best effect on inhibiting bacterial growth. Combined herbal essential oils have a good and noticeable effect on the growth behavior of pathogenic bacteria in the laboratory, and by continuing research in the host, they may be a suitable alternative to control, prevent and treat diseases caused by these bacteria.

Keywords: bacterial pathogen, herbal medicine, growth behavior, fish

Procedia PDF Downloads 42

Authors: Navid Mirzaei Varzeghani, Mahmoud Saffarzadeh, Ali Naderan, Amirhossein Taheri

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Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, a range of ages more significant than 55, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: multimodal transportation, demand modeling, travel behavior, statistical models

Procedia PDF Downloads 137

Authors: Mojtaba Taheri, Saied Reza Ameli

Abstract:

In this research, we have calculated the effect of membership in international climate change treaties for 20 developed countries based on the human development index (HDI) and compared this effect with the process of pollutant reduction in the Environmental Kuznets Curve (EKC) theory. For this purpose, the data related to The real GDP per capita with 2010 constant prices is selected from the World Development Indicators (WDI) database. Ecological Footprint (ECOFP) is the amount of biologically productive land needed to meet human needs and absorb carbon dioxide emissions. It is measured in global hectares (gha), and the data retrieved from the Global Ecological Footprint (2021) database will be used, and we will proceed by examining step by step and performing several series of targeted statistical regressions. We will examine the effects of different control variables, including Energy Consumption Structure (ECS) will be counted as the share of fossil fuel consumption in total energy consumption and will be extracted from The United States Energy Information Administration (EIA) (2021) database. Energy Production (EP) refers to the total production of primary energy by all energy-producing enterprises in one country at a specific time. It is a comprehensive indicator that shows the capacity of energy production in the country, and the data for its 2021 version, like the Energy Consumption Structure, is obtained from (EIA). Financial development (FND) is defined as the ratio of private credit to GDP, and to some extent based on the stock market value, also as a ratio to GDP, and is taken from the (WDI) 2021 version. Trade Openness (TRD) is the sum of exports and imports of goods and services measured as a share of GDP, and we use the (WDI) data (2021) version. Urbanization (URB) is defined as the share of the urban population in the total population, and for this data, we used the (WDI) data source (2021) version. The descriptive statistics of all the investigated variables are presented in the results section. Related to the theories of sustainable development, Environmental Kuznets Curve (EKC) is more significant in the period of study. In this research, we use more than fourteen targeted statistical regressions to purify the net effects of each of the approaches and examine the results.

Keywords: climate change, globalization, environmental economics, sustainable development, international climate treaty

Procedia PDF Downloads 39

Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

Procedia PDF Downloads 66