Search results for: Hossein Enayat

Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

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Authors: Amir Hossein Ghaffari Nejad, Forouhar Ferdowsi, Reza Mashhadi

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In the interest-free banking system of Iran, the savings of society are in the form of bank deposits, and banks using the Islamic contracts, allocate the resources to applicants for obtaining facilities and credit. In the meantime, the central bank, with the aim of introducing monetary policy, determines the maximum interest rate on bank deposits in terms of macroeconomic requirements. But in recent years, the country's economic constraints with the stagflation and the consequence of the institutional weaknesses of the financial market of Iran have resulted in massive disturbances in the balance sheet of the banking system, resulting in a period of mismatch maturity in the banks' assets and liabilities and the implementation of a Ponzi game. This issue caused determination of the interest rate in long-term bank deposit contracts to be associated with non-observance of the maximum rate set by the central bank. The result of this condition was in the allocation of new sources of equipment to meet past commitments towards the old depositors and, as a result, a significant part of the supply of equipment was leaked out of the facilitating cycle and credit crunch emerged. The purpose of this study is to identify the most important factors affecting the occurrence of non-confirmatory financial banking behavior using data from 19 public and private banks of Iran. For this purpose, the causes of this non-confirmatory behavior of banks have been investigated using the panel vector autoregression method (PVAR) for the period of 2007-2015. Granger's causality test results suggest that the return of parallel markets for bank deposits, non-performing loans and the high share of the ratio of facilities to banks' deposits are all a cause of the formation of non-confirmatory behavior. Also, according to the results of impulse response functions and variance decomposition, NPL and the ratio of facilities to deposits have the highest long-term effect and also have a high contribution to explaining the changes in banks' non-confirmatory behavior in determining the interest rate on deposits.

Keywords: non-conformity behavior, Ponzi Game, panel vector autoregression, nonperforming loans

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Authors: Sara Taghdisi, Mehrosadat Mirmohammadi, Mostafa Mokhtarian, Mohammad Hossein Pazandeh

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Leishmaniasis is one of the 10 most important diseases of the World Health Organization with health problems in more than 90 countries. Over one billion people are at risk of these diseases on almost every continent. The present human study was performed to evaluate the therapeutic effect of cotton plant on cutaneous leishmaniasis leision. firstly, the cotton seeds were cleaned and grinded to smaller particles. In the second step, the seeds were oiled by cold press method. In order to separate bioactive compound, after saponification of the oil, its gossypol was hydrolyzed and crystalized. finally, the therapeutic effect of Cottonseed Oil on cutaneous leishmaniasis was investigated. In the current project, Gossypol was extracted with a liquid-liquid extraction method in 120 minutes in the presence of Phosphoric acid from the cotton seed oil of Golestan beach varieties, then got crystallized in darkness using Acetic acid and isolated as Gossypol Acetic acid. The efficiency of the extracted crystal was obtained at 1.28±0.12. the cotton plant could be efficient in the treatment of Cutaneous leishmaniasis. This double-blind randomized controlled clinical trial was performed on 88 cases of leishmaniasis wounds. Patients were randomly divided into two groups of 44 cases. two groups received conventional treatment. In addition to the usual treatment (glucantime), the first group received cottonseed oil and the control group received placebo. The results of the present study showed that the surface of lesion before the intervention and in the first to fourth weeks after the intervention was not significantly different between the two groups (P-value> 0.05). But the surface of lesion in the Intervention group in the eighth and twelfth weeks was lower than the control group (P-value <0.05). This study showed that the improvement of leishmaniasis lesion using topical cotton plant mark in the eighth and twelfth weeks after the intervention was significantly more than the control group. Considering the most common chemical drugs for Cutaneous leishmaniasis treatment are sodium stibogluconate, and meglumine antimonate, which not only have relatively many side effects, but also some species of the Leishmania genus have become resistant to them. Therefore, a plant base bioactive compound such as cottonseed oil can be useful whit fewer side effects.

Keywords: cottonseed oil, crystallization, gossypol, leishmaniasis

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Authors: Mehrosadat Mirmohammadi, Sara Taghdisi, Ali Padash, Mohammad Hossein Pazandeh

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Gossypol, a yellowish anti-nutritional compound found in cotton plants, exists in various plant parts, including seeds, husks, leaves, and stems. Chemically, gossypol is a potent polyphenolic aldehyde with antioxidant and therapeutic properties. However, its free form can be toxic, posing risks to both humans and animals. Initially, we extracted gossypol from cotton seeds using n-hexane as a solvent (yield: 84.0 ± 4.0%). We also obtained cotton seed and cotton boll extracts via Soxhlet extraction (25:75 hydroalcoholic ratio). These extracts, combined with cornstarch, formed four herbal medicinal formulations. Ethical approval allowed us to investigate their effects on Leishmania-caused skin wounds, comparing them to glucantime (local ampoule). Herbal formulas outperformed the control group (ethanol only) in wound treatment (p-value 0.05). The average wound diameter after two months did not significantly differ between plant extract ointments and topical glucantime. Notably, cotton boll extract with 1% extra gossypol crystal showed the best therapeutic effect. We extracted gossypol from cotton seeds using n-hexane via Soxhlet extraction. Saponification, acidification, and recrystallization steps followed. FTIR, UV-Vis, and HPLC analyses confirmed the product’s identity. Herbal medicines from cotton seeds effectively treated chronic wounds compared to the ethanol-only control group. Wound diameter differed significantly between extract ointments and glucantime injections. It seems that due to the presence of large amounts of fat in the oil, the extraction of gossypol from it faces many obstacles. The extraction of this compound with our technique showed that extraction from oil has a higher efficiency, perhaps because of the preparation of oil by cold pressing method, the possibility of losing this compound is much less than when extraction is done with Soxhlet. On the other hand, the gossypol in the oil is mostly bound to the protein, which somehow protects the gossypol until the last stage of the extraction process. Since this compound is very sensitive to light and heat, it was extracted as a derivative with acetic acid. Also, in the treatment section, it was found that the ointment prepared with the extract is more effective and Gossypol is one of the effective ingredients in the treatment. Therefore, gossypol can be extracted from the oil and added to the extract from which gossypol has been extracted to make an effective medicine with a certain dose.

Keywords: cottonseed, glucantime, gossypol, leishmaniasis

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Authors: Ayda Maadani Mallak, Amir lakzian, Elham Khodaverdi, Gholam Hossein Haghnia

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The use of pharmaceuticals and personal care products such as antibiotics and antibacterials has been increased in recent years. Since the major part of consumed compounds remains unchanged in the wastewater treatment plant, they will easily find their way into the human food chain following the land use of sewage sludge (SS). Biological treatment of SS is one the most effective methods for expunging contaminants. White rot fungi, due to their ligninolytic enzymes, are extensively used to degrade organic compounds. Among all three different morphological forms and growth patterns of filamentous fungi (mycelia, clumps, and pellets), fungal pellet formation has been the subject of interest in industrial bioprocesses. Therefore this study was aimed to investigate the uptake of tetracycline (TC) and triclosan (TCS) by radish plant (Raphanus sativus) from soil amended with untreated and pretreated SS by P. ostreatus fungal pellets under greenhouse conditions. The experimental soil was amended with 1) Contaminated SS with TC at a concentration of 100 mgkg-1 and pretreated by fungal pellets, 2) Contaminated SS with TC at 100 mgkg-1 and untreated with fungal pellets, 3) Contaminated SS with TCS at a concentration of 50 mgkg-1 and pretreated by fungal pellets, 4) contaminated SS with TCS at 50 mgkg-1 and untreated with fungal pellets. An uncontaminated and untreated SS-amended soil also was considered as control treatment. An AB SCIEX 3200 QTRAP LC-MS/MS system was used in order to analyze the concentration of TC and TCS in plant tissues and soil medium. Results of this study revealed that the presence of TC and TCS in SS-amended soil decreased the radish biomass significantly. The reduction effect of TCS on dry biomass of shoot and root was 39 and 45% compared to controls, whereas for TC, the reduction percentage for shoot and root was 27 and 40.6%, respectively. However, fungal treatment of SS by P. ostreatus pellets reduced the negative effect of both compounds on plant biomass remarkably, as no significant difference was observed compared to control treatments. Pretreatment of SS with P. ostreatus also caused a significant reduction in translocation factor (concentration in shoot/root), especially for TC compound up to 32.3%, whereas this reduction for TCS was less (8%) compared to untreated SS. Generally, the results of this study confirmed the positive effect of using fungal pellets in SS amendment to decrease TC and TCS uptake by radish plants. In conclusion, P. ostreatus fungal pellets might provide future insights into bioaugmentation to remove antibiotics from environmental matrices.

Keywords: antibiotic, fungal pellet, sewage sludge, white-rot fungi

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Authors: Bita Rabbani, Hossein Chiti, Faranak Sharifi, Saeedeh Mazloomzadeh

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Background: Lifestyle modifications, especially improving nutritional patterns and increasing physical activity, are the most important factors in preventing obesity and metabolic syndrome in children and adolescents. For this purpose, the following interventional study was designed to investigate the effects of educational programs for students, as well as changes in diet and physical activity, on obesity and components of the metabolic syndrome. Methods: This study is part of an interventional research project (elementary school) conducted on all students of Sama schools in Zanjan and Abhar in three levels of elementary, middle, and high school, including 1000 individuals in Zanjan (intervention group) and 1000 individuals (control group) in Abhar in 2011. Interventions were based on educating students, teachers, and parents, changes in food services, and physical activity. We primarily measured anthropometric indices, fasting blood sugar, lipid profiles, and blood pressure and completed standard nutrition and physical activity questionnaires. Also, blood insulin levels were randomly measured in a number of students. Data analysis was done by SPSS software version 16.0. Results: Overall, 589 individuals (252 male, 337 female) entered the case group, and 803 individuals (344 male, 459 female) entered the control group. After two years of intervention, mean waist circumference (63.8 ± 10.9) and diastolic BP (63.8 ± 10.4) were significantly lower; however, mean systolic BP (10.1.0 ± 12.5), food score (25.0 ± 5.0) and drinking score (12.1 ± 2.3) were higher in the intervention group (p<0.001). Comparing components of metabolic syndrome between the second year and at time of recruitment within the intervention group showed that although number of overweight/obese individuals, individuals with hypertriglyceridemia and high LDL increased, abdominal obesity, high BP, hyperglycemia, and insulin resistance decreased (p<0.001). On the other hand, in the control group, number of individuals with high BP increased significantly. Conclusion: The prevalence of abdominal obesity and hypertension, which are two major components of metabolic syndrome, are much higher in our study than in other regions of country. However, interventions for modification of diet and increase in physical activity are effective in lowering their prevalence.

Keywords: metabolic syndrome, obesity, life style, nutrition, hypertension

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini

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Background: There is growing evidence that Cerebral Vascular Accident (CVA) can be a consequence of Covid-19 infection. Understanding novel treatment approaches are important in optimizing patient outcomes. Case: This case explores the use of Virtual Reality (VR) in the treatment of a 23-year-old COVID-positive female presenting with left hemiparesis in August 2020. Imaging showed right globus pallidus, thalamus, and internal capsule ischemic stroke. Conventional rehabilitation was started two weeks later, with virtual reality (VR) included. This game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and functions for stroke. Physical examination showed left hemiparesis with muscle strength 3/5 in the upper extremity and 4/5 in the lower extremity. The range of motion of the shoulder was 90-100 degrees. The speech exam showed a mild decrease in fluency. Mild lower lip dynamic asymmetry was seen. Babinski was positive on the left. Gait speed was decreased (75 steps per minute). Intervention: Our game-based VR system was developed based on upper extremity physiotherapy exercises for post-stroke patients to increase the active, voluntary movement of the upper extremity joints and improve the function. The conventional program was initiated with active exercises, shoulder sanding for joint ROMs, walking shoulder, shoulder wheel, and combination movements of the shoulder, elbow, and wrist joints, alternative flexion-extension, pronation-supination movements, Pegboard and Purdo pegboard exercises. Also, fine movements included smart gloves, biofeedback, finger ladder, and writing. The difficulty of the game increased at each stage of the practice with progress in patient performances. Outcome: After 6 weeks of treatment, gait and speech were normal and upper extremity strength was improved to near normal status. No adverse effects were noted. Conclusion: This case suggests that VR is a useful tool in the treatment of a patient with covid-19 related CVA. The safety of newly developed instruments for such cases provides new approaches to improve the therapeutic outcomes and prognosis as well as increased satisfaction rate among patients.

Keywords: covid-19, stroke, virtual reality, rehabilitation

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Authors: Homeira Asadi Kavan, Seyed Nasrollah Sajjadi, Mehrzade Hamidi, Hossein Rajabi, Mahdi Bigdely

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Positioning strategies of a sports brand can create a unique impression in the minds of the fans, sponsors, and other stakeholders. In order to influence potential customer's perception in an effective and positive way, a brands positioning strategy must be unique, credible, and relevant. Many sports clubs in Iran have been struggling to implement and achieve brand positioning accomplishments, due to different reasons such as lack of experience, scarcity of experts in the sports branding, and lack of related researches in this field. This study will provide a comprehensive theoretical framework and action plan for sport managers and marketers to design and implement effective brand positioning and to enable them to be distinguishable from competing brands and sports clubs. The study instrument is interviews with sports marketing and brand experts who have been working in this industry for a minimum of 20 years. Qualitative data analysis was performed using Atlast.ti text mining software version 7 and Open, axial and selective coding were employed to uncover and systematically analyze important and complex phenomena and elements. The findings show 199 effective elements in positioning strategies in Iran Professional Soccer League. These elements are categorized into 23 concepts and sub-categories as follows: Structural prerequisites, Strategic management prerequisites, Commercial prerequisites, Major external prerequisites, Brand personality, Club symbols, Emotional aspects, Event aspects, Fans’ strategies, Marketing information strategies, Marketing management strategies, Empowerment strategies, Executive management strategies, League context, Fans’ background, Market context, Club’s organizational context, Support context, Major contexts, Political-Legal elements, Economic factors, Social factors, and Technological factors. Eventually, the study model was developed by 6 main dimensions of Causal prerequisites, Axial Phenomenon (brand position), Strategies, Context Factors, Interfering Factors, and Consequences. Based on the findings, practical recommendations and strategies are suggested that can help club managers and marketers in developing and improving their respective sport clubs, brand positioning, and activities.

Keywords: brand positioning, soccer club, sport marketing, Iran professional soccer league, brand strategy

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Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Hossein Rezaie

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Academic institutions, esp. universities, have been known as cradles of learning and teaching great thinkers while creating the type of knowledge that is supposed to be bereft of utilitarian motives. Nonetheless, it seems that such intellectual centers have entered into a competition with each other for attracting the attention of potential clients. The traditional values of (higher) education such as nurturing criticality and fostering intellectuality in students have been replaced with strategic planning, quality assurance, performance assessment, and academic audits. Not being immune from the whims and wishes of marketization, the system of higher education in the UK has been recalibrated by policy makers to address the demand and supply of student education, academic research and other university activities on the basis of monetary factors. As an immediate example in this vein, the Russell Group in the UK, which is comprised of 24 leading UK research universities, has explicitly expressed it policy on its official website as follows: ‘Russell Group universities are global businesses competing for staff, students and funding with the best in the world’. Furthermore, certain attempts have been made to corporatize the system of HE which have been manifested in remodeling of university governing bodies on corporate lines and developing measurement scales for indicating the performance of teaching practitioners. Nevertheless, it seems that such structural changes in policies toward the system of HE have bearing on the practices of practitioners and educators as well as the identity of students who are the customers of educational services. The effects of marketization have been examined mainly in terms of students’ perceptions and motivation, institutional policies and university management. However, the teaching practitioner side seems to be an under-studied area with regard to any changes in its expectations, satisfaction and perception of professional identity in the aftermath of introducing market-wise values into HE of the UK. As a result, this research aims to investigate the possible outcomes of market-driven values on the practitioner side of HE in the UK and finally seeks to address the following research questions: 1-How is the change in the mission of HE in the UK reflected in institutional documents? 1-A- How is the change of mission represented in job adverts? 1-B- How is the change of mission represented in university prospectuses? 2-How are teaching practitioners represented regarding their roles and obligations in the prospectuses and job ads published by UK HE institutions? In order to address these questions, the researcher will analyze 30 prospectuses and job ads published by Russel Group universities by taking Critical Discourse Analysis as his point of departure and the analytical methods of genre analysis and Systemic Functional Linguistics to probe into the generic features and representation of participants, in this case teaching practitioners, in the selected corpus.

Keywords: higher education, job advertisements, marketization of higher education, prospectuses

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Indika Fernando, Jiangang Fei, Roger Stanely, Hossein Enshaei

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Ever increasing demand for quality fresh produce by the consumers, had increased the gravity on the post-harvest supply chains in multi-fold in the recent years. Mechanical injury to fresh produce was a critical factor for produce wastage, especially with the expansion of supply chains, physically extending to thousands of miles. The impact of vibration damages in transit was identified as a specific area of focus which results in wastage of significant portion of the fresh produce, at times ranging from 10% to 40% in some countries. Several studies were concentrated on quantifying the impact of vibration to fresh produce, and it was a challenge to collect vibration impact data continuously due to the limitations in battery life or the memory capacity in the devices. Therefore, the study samples were limited to a stretch of the transit passage or a limited time of the journey. This may or may not give an accurate understanding of the vibration impacts encountered throughout the transit passage, which limits the accuracy of the results. Consequently, an approach which can extend the capacity and ability of determining vibration signals in the transit passage would contribute to accurately analyze the vibration damage along the post-harvest supply chain. A mechanism was developed to address this challenge, which is capable of measuring the in transit vibration continuously through the transit passage subject to a minimum acceleration threshold (0.1g). A system, consisting six tri-axel vibration transducers installed in different locations inside the cargo (produce) pallets in the truck, transmits vibration signals through LORA (Long Range Radio) technology to a central device installed inside the container. The central device processes and records the vibration signals transmitted by the portable transducers, along with the GPS location. This method enables to utilize power consumption for the portable transducers to maximize the capability of measuring the vibration impacts in the transit passage extending to days in the distribution process. The trial tests conducted using the approach reveals that it is a reliable method to measure and quantify the in transit vibrations along the supply chain. The GPS capability enables to identify the locations in the supply chain where the significant vibration impacts were encountered. This method contributes to determining the causes, susceptibility and intensity of vibration impact damages to fresh produce in the post-harvest supply chain. Extensively, the approach could be used to determine the vibration impacts not limiting to fresh produce, but for products in supply chains, which may extend from few hours to several days in transit.

Keywords: post-harvest, supply chain, wireless transducers, LORA, fresh produce

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Authors: Mohammad Hossein Pazandeh, Monir Doudi, Sona Rostampour Yasouri

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—Results The prudent administration of antibiotics aims to avoid the side effects and the microbes' resistance to antibiotics. An approach developing methods of local administration of antibiotics is especially required for localized infections caused by bacterial colonization of medical devices or implant materials. Among the wide variety of materials used as drug delivery systems, bioactive glasses (BG) have large utilization in regenerative medicine . firstly, the production of bioactive glass/nickel oxide/tin dioxide nanocomposite using sol-gel method, and then, the controlled release of imipenem from the double metal oxide/bioactive glass nanocomposite, and finally, the investigation of the antibacterial property of the nanocomposite. against a number of implant-related infectious agents. In this study, BG/SnO2 and BG/NiO single systema with different metal oxide present and BG/NiO/SnO2 nanocomposites were synthesized by sol-gel as drug carriers for tetracycline and imepinem. These two antibiotics were widely used for osteomyelitis because of its favorable penetration and bactericidal effect on all the probable osteomyelitis pathogens. The antibacterial activity of synthesized samples were evaluated against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa as bacteria model using disk diffusion method. The BG modification using metal oxides results to antibacterial property of samples containing metal oxide with highest efficiency for nancomposite. bioactivity of all samples was assessed by determining the surface morphology, structural and composition changes using scanning electron microscopy (SEM), FTIR and X-ray diffraction (XRD) spectroscopy, respectively, after soaking in simulated body fluid (SBF) for 28 days. The hydroxyapatite formation was clearly observed as a bioactivity measurement. Then, BG nanocomposite sample was loaded using two antibiotics, separately and their release profiles were studied. The BG nancomposite sample was shown the slow and continuous drug releasing for a period of 72 hours which is desirable for a drug delivery system. The loaded antibiotic nanocomposite sample retaining antibacterial property and showing inactivation effect against bacteria under test. The modified bioactive glass forming hydroxyapatite with controlled release drug and effective against bacterial infections can be introduced as scaffolds for bone implants after clinical trials for biomedical applications . Considering the formation of biofilm by infectious bacteria after sticking on the surfaces of implants, medical devices, etc. Also, considering the complications of traditional methods, solving the problems caused by the above-mentioned microorganisms in technical and biomedical industries was one of the necessities of this research.

Keywords: antibacterial, bioglass, drug delivery system, sol- gel

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Authors: Hossein Hassani, Ali Rezaei

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Heavy metals are naturally occurring elements that have a high atomic weight and a density at least five times greater than that of water. Their multiple industrial, domestic, agricultural, medical, and technological applications have led to their wide distribution in the environment, raising concerns over their potential effects on human health and the environment. Environmental protection against various pollutants, such as heavy metals formed by industries, mines and modern technologies, is a concern for researchers and industry. In order to assess the contamination of soils the distribution and environmental behavior have been investigated. Jajarm bauxite mine, the most important deposits have been discovered in Iran, which is about 22 million tons of reserve, and is the main mineral of the Diaspora. With a view to estimate the heavy metals ratio of the Jajarm bauxite mine area and to evaluate the pollution level, 50 samples have been collected and have been analyzed for the heavy metals of As, Cd, Cu, Hg, Ni and Pb with the help of Inductively Coupled Plasma-Mass Spectrometer (ICP- MS). In this study, we have dealt with determining evaluation criteria including contamination factor (CF), average concentration (AV), enrichment factor (EF) and geoaccumulation index (GI) to assess the risk of pollution from heavy metals(As, Cd, Cu, Hg, Ni and Pb) in Jajarm bauxite mine. In the samples of the studied, the average of recorded concentration of elements for Arsenic, Cadmium, Copper, Mercury, Nickel and Lead are 18, 0.11, 12, 0.07, 58 and 51 (mg/kg) respectively. The comparison of the heavy metals concentration average and the toxic potential in the samples has shown that an average with respect to the world average of the uncontaminated soil amounts. The average of Pb and As elements shows a higher quantity with respect to the world average quantity. The pollution factor for the study elements has been calculated on the basis of the soil background concentration and has been categorized on the basis of the uncontaminated world soil average with respect to the Hakanson classification. The calculation of the corrected pollutant degree shows the degree of the bulk intermediate pollutant (1.55-2.0) for the average soil sampling of the study area which is on the basis of the background quantity and the world average quantity of the uncontaminated soils. The provided conclusion from calculation of the concentrated factor, for some of the samples show that the average of the lead and arsenic elements stations are more than the background values and the unnatural metal concentration are covered under the study area, That's because the process of mining and mineral extraction. Given conclusion from the calculation of Geoaccumulation index of the soil sampling can explain that the copper, nickel, cadmium, arsenic, lead and mercury elements are Uncontamination. In general, the results indicate that the Jajarm bauxite mine of heavy metal pollution is uncontaminated area and extract the mineral from the mine, not create environmental hazards in the region.

Keywords: enrichment factor, geoaccumulation index, heavy metals, Jajarm bauxite mine, pollution

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 71

Authors: Mostafa Feiz, Mohammad Safari, Hossein Hadizadeh

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The Chalpo copper area is located in northeastern Iran, which is part of the structural zone of central Iran and the back-arc basin of Sabzevar. This sedimentary basin accumulated in destructive-oligomiocene sediments is named the Nasr-Chalpo-Sangerd (NCS) basin. The sedimentary layers in this basin originated mainly from Upper Cretaceous ophiolitic rocks and intermediate to mafic-post ophiolitic volcanic rocks, deposited as a nonconformity. The mineralized sandstone layers in the Chalpo area include leached zones (with a thickness of 5 to 8 meters) and mineralized lenses with a thickness of 0.5 to 0.7 meters. Ore minerals include primary sulfide minerals, such as chalcocite, chalcopyrite, and pyrite, as well as secondary minerals, such as covellite, digenite, malachite, and azurite, formed in three stages that comprise primary, simultaneously, and supergene stage. The best agents that control the mineralization in this area include the permeability of host rocks, the presence of fault zones as the conduits for copper oxide solutions, and significant amounts of plant fossils, which create a reducing environment for the deposition of mineralized layers. The calculations of mass changes on copper-bearing layers and primary sandstone layers indicate that Pb, As, Cd, Te, and Mo are enriched in the mineralized zones, whereas SiO₂, TiO₂, Fe₂O₃, V, Sr, and Ba are depleted. The combination of geological, stratigraphic, and geochemical studies suggests that the origin of copper may have been the underlying red strata that contained hornblende, plagioclase, biotite, alkaline feldspar, and labile minerals. Dehydration and hydrolysis of these minerals during the diagenetic process caused the leaching of copper and associated elements by circling fluids, which formed an oxidant-hydrothermal solution. Copper and silver in this oxidant solution might have moved upwards through the basin-fault zones and deposited in the reducing environments in the sandstone layers that have had abundant organic matter. Copper in these solutions was probably carried by chloride complexes. The collision of oxidant and reduced solutions caused the deposition of Cu and Ag, whereas some s elements in oxidant environments (e.g., Fe₂O₃, TiO₂, SiO₂, REEs) become uns in the reduced condition. Therefore, the copper-bearing sandstones in the study area are depleted from these elements resulting from the leaching process. The results indicate that during the mineralization stage, LREEs and MREEs were depleted, but Cu, Ag, and S were enriched. Based on field evidence, it seems that the circulation of connate fluids in the reb-bed strata, produced by diagenetic processes, encountered to reduced facies, which formed earlier by abundant fossil-plant debris in the sandstones, is the best model for precipitating sulfide-copper minerals.

Keywords: Chalpo, Oligo-Miocene red beds, sandstone-hosted copper mineralization, mass change, LREEs and MREEs

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Authors: Akram Abi, Mohammad Hossein Sarrafzadeh

Abstract:

Because of their several advantages over chemical surfactants, biosurfactants have given rise to a growing interest in the past decades. Advantages such as lower toxicity, higher biodegradability, higher selectivity and applicable at extreme temperature and pH which enables them to be used in a variety of applications such as: enhanced oil recovery, environmental and pharmaceutical applications, etc. Bacillus subtilis produces a cyclic lipopeptide, called surfactin, which is one of the most powerful biosurfactants with ability to decrease surface tension of water from 72 mN/m to 27 mN/m. In addition to its biosurfactant character, surfactin exhibits interesting biological activities such as: inhibition of fibrin clot formation, lyses of erythrocytes and several bacterial spheroplasts, antiviral, anti-tumoral and antibacterial properties. Surfactin is an antibiotic substance and has been shown recently to possess anti-HIV activity. However, application of biosurfactants is limited by their high production cost. The cost can be reduced by optimizing biosurfactant production using cheap feed stock. Utilization of inexpensive substrates and unconventional carbon sources like urban or agro-industrial wastes is a promising strategy to decrease the production cost of biosurfactants. With suitable engineering optimization and microbiological modifications, these wastes can be used as substrates for large-scale production of biosurfactants. As an effort to fulfill this purpose, in this work we have tried to utilize olive oil as second carbon source and also yeast extract as second nitrogen source to investigate the effect on both biomass and biosurfactant production improvement in Bacillus subtilis cultures. Since the turbidity of the culture was affected by presence of the oil, optical density was compromised and no longer could be used as an index of growth and biomass concentration. Therefore, cell Dry Weight measurements with applying necessary tactics for removing oil drops to prevent interference with biomass weight were carried out to monitor biomass concentration during the growth of the bacterium. The surface tension and critical micelle dilutions (CMD-1, CMD-2) were considered as an indirect measurement of biosurfactant production. Distinctive and promising results were obtained in the cultures containing olive oil compared to cultures without it: more than two fold increase in biomass production (from 2 g/l to 5 g/l) and considerable reduction in surface tension, down to 40 mN/m at surprisingly early hours of culture time (only 5hr after inoculation). This early onset of biosurfactant production in this culture is specially interesting when compared to the conventional cultures at which this reduction in surface tension is not obtained until 30 hour of culture time. Reducing the production time is a very prominent result to be considered for large scale process development. Furthermore, these results can be used to develop strategies for utilization of agro-industrial wastes (such as olive oil mill residue, molasses, etc.) as cheap and easily accessible feed stocks to decrease the high costs of biosurfactant production.

Keywords: agro-industrial waste, bacillus subtilis, biosurfactant, fermentation, second carbon and nitrogen source, surfactin

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Authors: Mohammad Hossein Pazandeh, Monir Doudi, Sona Rostampour Yasouri

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Irregular consumption of current antibiotic makes increases of antibiotic resistance between urin pathogens on all worlds. This study selected based on this great community problem. The aim of this study was the biosynthesis of silver nanoparticles from Zataria multiflora extract and then to investigate its antibacterial effect on gram-negative bacilli common in Urinary Tract Infections (UTI) and MDR. The plant used in the present research was Zataria multiflora whose extract was prepared through Soxhlet extraction method. Green synthesis condition of silver nanoparticles was investigated in terms of three parameters including the extract amount, concentration of silver nitrate salt, and temperature. The seizes of nanoparticles were determined by Zetasizer. In order to identify synthesized silver nanoparticles Transmission Electron Microscopy (TEM) and X-ray Diffraction (XRD) methods were used. For evaluating the antibacterial effects of nanoparticles synthesized through biological method different concentrations of silver nanoparticles were studied on 140 cases of Muliple Drug Resistance (MDR) bacteria strains Escherichia coli, Klebsiella pneumoniae, Enterobacter aerogenes, Proteus vulgaris,Citrobacter freundii, Acinetobacter bumanii and Pseudomonas aeruginosa, (each genus of bacteria, 20 samples), which all were MDR and cause urinary tract infections , for identification of bacteria were used of Polymerase Chain Reaction (PCR) test and laboratory methods (Agar well diffusion and Microdilution methods) to assess their sensitivity to Nanoparticles. The data were analyzed using SPSS software by nonparametric Kruskal-Wallis and Mann-Whitney tests. Significant results were found about the effects of silver nitrate concentration, different amounts of Zataria multiflora extract, and temperature on nanoparticles; that is, by increasing the concentration of silver nitrate, extract amount, and temperature, the sizes of synthesized nanoparticles declined. However, the effect of above mentioned factors on particles diffusion index was not significant. Based on the TEM results, particles were mainly spherical shape with a diameter range of 25 to 50 nm. The results of XRD Analysis indicated the formation of Nanostructures and Nanocrystals of silver.. The obtained results of antibacterial effects of different concentrations of silver nanoparticles on according to agar well diffusion and microdilution method, biologically synthesized nanoparticles showed 1000 mg /ml highest and lowest mean inhibition zone diameter in E.coli , Acinetobacter bumanii 23 and 15mm, respectively. MIC was observed for all of bacteria 125mg/ml and for Acinetobacter bumanii 250mg/ml.Comparing the growth inhibitory effect of chemically synthesized Nanoparticles and biologically synthesized Nanoparticles showed that in the chemical method the highest growth inhibition belonged to the concentration of 62.5 mg /ml. The inhibitory effect on the growth all of bacteria causes of urine infection and MDR was observed and by increasing silver ion concentration in Nanoparticles, antibacterial activity increased. Generally, the biological synthesis can be considered an efficient way not only in making Nanoparticles but also for having anti-bacterial properties. It is more biocompatible and may be possess less toxicity than the Nanoparticles synthesized chemically.

Keywords: biosynthesis, MDR bacteria, silver nanoparticles, UTI

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

Abstract:

Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 71

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Sarah Fitzpatrick, Hossein Zare-Behtash, Konstantinos Kontis

Abstract:

Traditionally, the focus of horizontal axis wind turbine (HAWT) blade aerodynamic optimisation studies has been the outer working region of the blade. However, recent works seek to better understand, and thus improve upon, the performance of the inboard blade region to enhance power production, maximise load reduction and better control the wake behaviour. This paper presents the design considerations and characterisation of a wind turbine wind tunnel model devised to further the understanding and fundamental definition of horizontal axis wind turbine root vortex shedding and interactions. Additionally, the application of passive and active flow control mechanisms – vortex generators and plasma actuators – to allow for the manipulation and mitigation of unsteady aerodynamic behaviour at the blade inboard section is investigated. A static, modular blade wind turbine model has been developed for use in the University of Glasgow’s de Havilland closed return, low-speed wind tunnel. The model components - which comprise of a half span blade, hub, nacelle and tower - are scaled using the equivalent full span radius, R, for appropriate Mach and Strouhal numbers, and to achieve a Reynolds number in the range of 1.7x105 to 5.1x105 for operational speeds up to 55m/s. The half blade is constructed to be modular and fully dielectric, allowing for the integration of flow control mechanisms with a focus on plasma actuators. Investigations of root vortex shedding and the subsequent wake characteristics using qualitative – smoke visualisation, tufts and china clay flow – and quantitative methods – including particle image velocimetry (PIV), hot wire anemometry (HWA), and laser Doppler anemometry (LDA) – were conducted over a range of blade pitch angles 0 to 15 degrees, and Reynolds numbers. This allowed for the identification of shed vortical structures from the maximum chord position, the transitional region where the blade aerofoil blends into a cylindrical joint, and the blade nacelle connection. Analysis of the trailing vorticity interactions between the wake core and freestream shows the vortex meander and diffusion is notably affected by the Reynold’s number. It is hypothesized that the shed vorticity from the blade root region directly influences and exacerbates the nacelle wake expansion in the downstream direction. As the design of inboard blade region form is, by necessity, driven by function rather than aerodynamic optimisation, a study is undertaken for the application of flow control mechanisms to manipulate the observed vortex phenomenon. The designed model allows for the effective investigation of shed vorticity and wake interactions with a focus on the accurate geometry of a root region which is representative of small to medium power commercial HAWTs. The studies undertaken allow for an enhanced understanding of the interplay of shed vortices and their subsequent effect in the near and far wake. This highlights areas of interest within the inboard blade area for the potential use of passive and active flow control devices which contrive to produce a more desirable wake quality in this region.

Keywords: vortex shedding, wake interactions, wind tunnel model, wind turbine

Procedia PDF Downloads 235

Authors: Indika Fernando, Jiangang Fei, Roger Stanley, Hossein Enshaei

Abstract:

Delicate produce such as fresh fruits are increasingly susceptible to physiological damage during the essential post-harvest operations such as transport and handling. Vibration and shock during the distribution are identified factors for produce damage within post-harvest supply chains. Mechanical damages caused during transit may significantly diminish the quality of fresh produce which may also result in a substantial wastage. Bananas are one of the staple fruit crops and the most sold supermarket produce in Australia. It is also the largest horticultural industry in the state of Queensland where 95% of the total production of bananas are cultivated. This results in significantly lengthy interstate supply chains where fruits are exposed to prolonged vibration and shocks. This paper is focused on determining the shock and vibration levels experienced by packaged bananas during transit from the farm gate to the retail market. Tri-axis acceleration data were captured by custom made accelerometer based data loggers which were set to a predetermined sampling rate of 400 Hz. The devices recorded data continuously for 96 Hours in the interstate journey of nearly 3000 Km from the growing fields in far north Queensland to the central distribution centre in Melbourne in Victoria. After the bananas were ripened at the ripening facility in Melbourne, the data loggers were used to capture the transport and handling conditions from the central distribution centre to three retail outlets within the outskirts of Melbourne. The quality of bananas were assessed before and after transport at each location along the supply chain. Time series vibration and shock data were used to determine the frequency and the severity of the transient shocks experienced by the packages. Frequency spectrogram was generated to determine the dominant frequencies within each segment of the post-harvest supply chain. Root Mean Square (RMS) acceleration levels were calculated to characterise the vibration intensity during transport. Data were further analysed by Fast Fourier Transform (FFT) and the Power Spectral Density (PSD) profiles were generated to determine the critical frequency ranges. It revealed the frequency range in which the escalated energy levels were transferred to the packages. It was found that the vertical vibration was the highest and the acceleration levels mostly oscillated between ± 1g during transport. Several shock responses were recorded exceeding this range which were mostly attributed to package handling. These detrimental high impact shocks may eventually lead to mechanical damages in bananas such as impact bruising, compression bruising and neck injuries which affect their freshness and visual quality. It was revealed that the frequency range between 0-5 Hz and 15-20 Hz exert an escalated level of vibration energy to the packaged bananas which may result in abrasion damages such as scuffing, fruit rub and blackened rub. Further research is indicated specially in the identified critical frequency ranges to minimise exposure of fruits to the harmful effects of vibration. Improving the handling conditions and also further study on package failure mechanisms when exposed to transient shock excitation will be crucial to improve the visual quality of bananas within the post-harvest supply chain in Australia.

Keywords: bananas, handling, post-harvest, supply chain, shocks, transport, vibration

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

Abstract:

Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

Procedia PDF Downloads 149

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

Abstract:

In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

Procedia PDF Downloads 150