Search results for: plant extract

Authors: Catalina Iticescu, Lucian Georgescu, Mihaela Timofti, Dumitru Dima, Gabriel Murariu

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The amounts of sludge resulting from the treatment of domestic and industrial wastewater can create serious environmental problems if no solutions are found to eliminate them. At present, the predominant method of sewage sludge disposal is to store and use them in agricultural applications. The sewage sludge has fertilizer properties and can be used to enrich agricultural soils due to the nutrient content. In addition to plant growth (nitrogen and phosphorus), the sludge also contains heavy metals in varying amounts. An increasingly used method is the incineration of sludge. Thermal processes can be used to convert large amounts of sludge into useful energy. The sewage sludge analyzed for the present paper was extracted from the Wastewater Treatment Station (WWTP) Galati, Romania. The physico-chemical parameters determined were: pH (upH), nutrients and heavy metals. The determination methods were electrochemical, spectrophotometric and energy dispersive X–ray analyses (EDX). The results of the tests made on the content of nutrients in the sewage sludge have shown that existing nutrients can be used to increase the fertility of agricultural soils. The conclusion reached was that these sludge can be safely used on agricultural land and with good agricultural productivity results. To be able to use sewage sludge as a fuel, we need to know its calorific values. For wet sludge, the caloric power is low, while for dry sludge it is high. Higher calorific value and lower calorific value are determined only for dry solids. The apparatus used to determine the calorific power was a Parr 6755 Solution Calorimeter Calorimeter (Parr Instrument Company USA 2010 model). The calorific capacities for the studied sludge indicate that they can be used successfully in incinerators. Mixed with coal, they can also be used to produce electricity. The advantages are: it reduces the cost of obtaining electricity and considerably reduces the amount of sewage sludge.

Keywords: agriculture, incinerators, properties, sewage sludge

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

Procedia PDF Downloads 170

Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

Procedia PDF Downloads 199

Authors: R. Razavizadeh, F. Adabavazeh, M. Rezaee Chermahini

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Salinity is one of the most widespread agricultural problems in arid and semi-arid areas that limits the plant growth and crop productivity. In this study, the salt stress effects on protein, reducing sugar, proline contents and antioxidant enzymes activities of Carum copticum L. under in vitro conditions were studied. Seeds of C. copticum were cultured in Murashige and Skoog (MS) medium containing 0, 25, 50, 100 and 150 mM NaCl and calli were cultured in MS medium containing 1 μM 2, 4-dichlorophenoxyacetic acid, 4 μM benzyl amino purine and different levels of NaCl (0, 25, 50, 100 and 150 mM). After NaCl treatment for 28 days, the proline and reducing sugar contents of shoots, roots and calli increased significantly in relation to the severity of the salt stress. The highest amount of proline and carbohydrate were observed at 150 and 100 mM NaCl, respectively. The reducing sugar accumulation in shoots was the highest as compared to roots, whereas, proline contents did not show any significant difference in roots and shoots under salt stress. The results showed significant reduction of protein contents in seedlings and calli. Based on these results, proteins extracted from the shoots, roots and calli of C. copticum treated with 150 mM NaCl showed the lowest contents. The positive relationships were observed between activity of antioxidant enzymes and the increase in stress levels. Catalase, ascorbate peroxidase and superoxide dismutase activity increased significantly under salt concentrations in comparison to the control. These results suggest that the accumulation of proline and sugars, and activation of antioxidant enzymes play adaptive roles in the adaptation of seedlings and callus of C. copticum to saline conditions.

Keywords: antioxidant enzymes, Carum copticum, organic solutes, salt stress

Procedia PDF Downloads 252

Authors: R. K. Saket

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This paper presents design aspects and probabilistic approach for generation reliability evaluation of an alternative resource: municipal waste water based micro hydro power generation system. Annual and daily flow duration curves have been obtained for design, installation, development, scientific analysis and reliability evaluation of the MHPP. The hydro potential of the waste water flowing through sewage system of the BHU campus has been determined to produce annual flow duration and daily flow duration curves by ordering the recorded water flows from maximum to minimum values. Design pressure, the roughness of the pipe’s interior surface, method of joining, weight, ease of installation, accessibility to the sewage system, design life, maintenance, weather conditions, availability of material, related cost and likelihood of structural damage have been considered for design of a particular penstock for reliable operation of the MHPP. A MHPGS based on MWW and SEIG is designed, developed, and practically implemented to provide reliable electric energy to suitable load in the campus of the Banaras Hindu University, Varanasi, (UP), India. Generation reliability evaluation of the developed MHPP using Gaussian distribution approach, safety factor concept, peak load consideration and Simpson 1/3rd rule has presented in this paper.

Keywords: self excited induction generator, annual and daily flow duration curve, sewage system, municipal waste water, reliability evaluation, Gaussian distribution, Simpson 1/3rd rule

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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Authors: Mohamed Rashad, Mohamed Hafez, Mohamed Emran, Emad Aboukila, Ibrahim Nassar

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Environment-friendly organic wastes of Brewers' spent grain, a byproduct of the brewing process, have recently used as soil amendment to improve soil fertility and plant production. In this work, treatments of 1% (T1) and 2% (T2) of spent grains, 1% (C1) and 2% (C2) of compost and mix of both sources (C1T1) were used and compared to the control for growing Zea mays L. on sandy soil under arid Mediterranean climate. Soils were previously incubated at 65% saturation capacity for a month. The most relevant soil physical and chemical parameters were analysed. Water holding capacity and soil organic matter (OM) increased significantly along the treatments with the highest values in T2. Soil pH decreased along the treatments and the lowest pH was in C1T1. Bicarbonate decreased by 69% in C1T1 comparing to control. Total nitrogen (TN) and available P varied significantly among all treatments and T2, C1T1 and C2 treatments increased 25, 17 and 11 folds in TN and 1.2, 0.6 and 0.3 folds in P, respectively related to control. Available K showed the highest values in C1T1. Soil micronutrients increased significantly along all treatments with the highest values in T2. After corn germination, significant variation was observed in the velocity of germination coefficients (VGC) among all treatments in the order of C1T1>T2>T1>C2>C1>control. The highest records of final germination and germination index were in C1T1 and T2. The spent grains may compensate deficiencies of macro and micronutrients in newly reclaimed sandy soils without adverse effects to sustain crop production with a rider that excessive or continuous use need to be circumvented.

Keywords: corn and squash germination, environmentally friendly organic wastes, soil carbon sequestration, spent grains as soil amendment, water holding capacity

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Authors: Mehmet Bulent Topkaya, Mustafa Yildirim

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Wastewater treatment systems are designed and used to minimize adverse impacts of the wastewater on the environment before discharging. Various treatment options for wastewater treatment have been developed, and each of them has different performance characteristics and environmental impacts (e.g. material and land usage, energy consumption, greenhouse gas emission, water and soil emission) during construction, operation or maintenance phases. Assessing the environmental impacts during these phases are essential for the overall evaluation of the treatment systems. In this study, wastewater treatment options, such as vegetated land treatment, constructed wetland, rotating biological contactor, conventional activated sludge treatment, membrane bioreactor, extended aeration and stabilization pond are evaluated. The comparison of the environmental impacts is conducted under the assumption that the effluents will be discharged to sensitive and less sensitive areas respectively. The environmental impacts of each alternative are evaluated by life cycle assessment (LCA) approach. For this purpose, data related to energy usage, land requirement, raw material consumption, and released emissions from the life phases were collected with inventory studies based on field studies and literature. The environmental impacts were assessed by using SimaPro 7.1 LCA software. As the scale of the LCA results is global, an MS-Excel based decision support tool that includes the LCA result is developed in order to meet also the local demands. Using this tool, it is possible to assign weight factors on the LCA results according to local conditions by using Analytical Hierarchy Process and finally the most environmentally appropriate treatment option can be selected.

Keywords: analytical hierarchy process, decision support system, life cycle assessment, wastewater treatment

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Authors: Hajji Lobna, Chattaoui Mayssa, Regaieg Hajer, M'Hamdi-Boughalleb Naima, Rhouma Ali, Horrigue-Raouani Najet

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In this study, three local isolates of Trichoderma (Tr1: T. viride, Tr2: T. harzianum and Tr3: T. asperellum) were isolated and evaluated for their biocontrol effectiveness under in vitro conditions and in greenhouse. In vitro bioassay revealed a biopotential control against Fusarium oxysporum f. sp. radicis lycopersici and Meloidogyne javanica (RKN) separately. All species of Trichoderma exhibited biocontrol performance and (Tr1) Trichoderma viride was the most efficient. In fact, growth rate inhibition of Fusarium oxysporum f. sp. radicis lycopersici (FORL) was reached 75.5% with Tr1. Parasitism rate of root-knot nematode was 60% for juveniles and 75% for eggs with the same one. Pots experiment results showed that Tr1 and Tr2, compared to chemical treatment, enhanced the plant growth and exhibited better antagonism against root-knot nematode and root-rot fungi separated or combined. All Trichoderma isolates revealed a bioprotection potential against Fusarium oxysporum f. sp. radicis lycopersici. When pathogen fungi inoculated alone, Fusarium wilt index and browning vascular rate were reduced significantly with Tr1 (0.91, 2.38%) and Tr2 (1.5, 5.5%), respectively. In the case of combined infection with Fusarium and nematode, the same isolate of Trichoderma Tr1 and Tr2 decreased Fusarium wilt index at 1.1 and 0.83 and reduced the browning vascular rate at 6.5% and 6%, respectively. Similarly, the isolate Tr1 and Tr2 caused maximum inhibition of nematode multiplication. Multiplication rate was declined at 4% with both isolates either tomato infected by nematode separately or concomitantly with Fusarium. The chemical treatment was moderate in activity against Meloidogyne javanica and Fusarium oxysporum f. sp. radicis lycopersici alone and combined.

Keywords: trichoderma spp., meloidogyne javanica, Fusarium oxysporum f.sp.radicis lycopersici, biocontrol

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Authors: Meghan E. Murray, Carri R. Tolmie

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This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

Procedia PDF Downloads 94

Authors: H. M. B. N Jayasinghe

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The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

Procedia PDF Downloads 220

Authors: Adebisi Adunola Demehin, Wanlaya Thamnarak, Jaruwan Chatwichien, Chatchakorn Eurtivong, Kiattawee Choowongkomon, Somsak Ruchirawat, Nopporn Thasana

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The epidermal growth factor receptor (EGFR) is a transmembrane glycoprotein involved in cellular signalling processes and, its aberrant activity is crucial in the development of many cancers such as lung cancer. Selaginellaceae are fern allies that have long been used in Chinese traditional medicine to treat various cancer types, especially lung cancer. Biflavonoids, the major secondary metabolites in Selaginellaceae, have numerous pharmacological activities, including anti-cancer and anti-inflammatory. For instance, amentoflavone induces a cytotoxic effect in the human NSCLC cell line via the inhibition of PARP-1. However, to the best of our knowledge, there are no studies on biflavonoids as EGFR inhibitors. Thus, this study aims to investigate the EGFR inhibitory activities of biflavonoids isolated from Selaginella siamensis and Selaginella bryopteris. Amentoflavone, tetrahydroamentoflavone, sciadopitysin, robustaflavone, robustaflavone-4-methylether, delicaflavone, and chrysocauloflavone were isolated from the ethyl-acetate extract of the whole plants. The structures were determined using NMR spectroscopy and mass spectrometry. In vitro study was conducted to evaluate their cytotoxicity against A549, HEPG2, and T47D human cancer cell lines using the MTT assay. In addition, a target-based assay was performed to investigate their EGFR inhibitory activity using the kinase inhibition assay. Finally, a molecular docking study was conducted to predict the binding modes of the compounds. Robustaflavone-4-methylether and delicaflavone showed the best cytotoxic activity on all the cell lines with IC50 (µM) values of 18.9 ± 2.1 and 22.7 ± 3.3 on A549, respectively. Of these biflavonoids, delicaflavone showed the most potent EGFR inhibitory activity with an 84% relative inhibition at 0.02 nM using erlotinib as a positive control. Robustaflavone-4-methylether showed a 78% inhibition at 0.15 nM. The docking scores obtained from the molecular docking study correlated with the kinase inhibition assay. Robustaflavone-4-methylether and delicaflavone had a docking score of 72.0 and 86.5, respectively. The inhibitory activity of delicaflavone seemed to be linked with the C2”=C3” and 3-O-4”’ linkage pattern. Thus, this study suggests that the structural features of these compounds could serve as a basis for developing new EGFR-TK inhibitors.

Keywords: anticancer, biflavonoids, EGFR, molecular docking, Selaginellaceae

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Authors: Patel Himeshkumar Ashokbhai, Suchit Sharma, Arvind Kumar Garg

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The results obtained from settling test of coal fines are used as an important tool to select the dewatering equipment such as thickeners, centrifuges and filters. Coal being hydrophobic in nature does not easily settle when mixed with water. Coal slurry that takes longer time to release water is highly undesirable because it poses additional challenge during sedimentation, centrifuge and filtration. If filter cake has higher than permitted moisture content then it not only creates handling problems but inflated freight costs and reduction in input and productivity for coke oven charges. It is to be noted that coal fines drastically increase moisture percentage in filter cake hence are to be minimized. To increase settling rate of coal fines in slurry chemical substances called flocculants or coagulants are added that cause coal particles to flocculate or coalesce into larger particles. These larger particles settle at faster rate and have higher settling velocity. Other important factors affecting settling rate are flocculent dosage, slurry or pulp density and particle size. Hence in this paper we tried to study the settling characteristic of clean coal fines by varying one of the four factors namely 1. Flocculant Dosage (acryl-amide) 2. pH of the water 3. Bulk density 4. Particle size of clean coal fines in settling experiment and drew important conclusions. Result of this paper will be much useful not only for coal beneficiation plant design but also for cost reduction of coke production facilities.

Keywords: bulk density, coal fines, flocculants, flocculation, settling velocity, pH

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Authors: Niki Hayatgheib, SéGolèNe Calvez, Catherine Fournel, Lionel Pineau, Herve Pouliquen, Emmanuelle Moreau

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Furunculosis caused by infection with Aeromonas salmonicida subsp. salmonicida has been a known disease found principally in salmonid aquaculture. Vaccination has been partly successful in preventing this disease, but outbreaks still occur. The application of functional feed additive found to be a promising yield to improve fish health against diseases. In this study, we tested the efficacy of prebiotics and plant essential oils-enriched diet on immune response and disease resistance in vaccinated and non-vaccinated rainbow trout (Oncorhynchus mykiss) against furunculosis. A total of 600 fish were fed with the basal diet or supplement. On 4th week of feeding, fish were vaccinated with an autovaccine. Following 8 weeks, fish were challenged with Aeromonas salmonicida subsp. salmonicida and mortalities were recorded for 3 weeks. Lysozyme activity and antibody titer in serum were measured in different groups. The results of this study showed that lysozyme and circulatory antibody titer in plasma elevated significantly in vaccinated fish fed with additive. The best growth rate and relative percentage survival (62%) were in fish fed with a supplement, while 15% in control fish. Overall, prebiotics and essential oils association can be considered as a potential component for enhancing vaccine efficacy against furunculosis by increasing the growth performance, immune responses and disease resistance in rainbow trout.

Keywords: aeromonas salmonicida subsp. salmonicida, aquaculture, disease resistance, fish, immune response, prebiotics-essential oils feed additive, rainbow trout, vaccination

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Foad Hassaninejadafarahani, Scott Ormiston

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Reflux condensation occurs in a vertical channels and tubes when there is an upward core flow of vapor (or gas-vapor mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapor-gas mixture (or pure vapor) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapor core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on a finite volume method and a co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and pressure profiles, as well as axial variations of film thickness, Nusselt number and interface gas mass fraction.

Keywords: Reflux, Condensation, CFD-Two Phase, Nusselt number

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Authors: Nour Elhouda Abed, Bedj Mimi, Wahid Slimani, Mourad Atif, Abdelhakim Ouzzane, Hocine Irekti, Abdelkader Bekki

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The most frequent system of cereal production in Algeria is fallow-wheat. This is an extensive system that meets only the half needs some cereals and fodder demand. Resorption of fallow has become a strategic necessity to ensure food security in response to the instability of supply and the persistence of higher food prices on the world market. Despite several attempts to replace the fallow by crop cultures, choosing the best crop remains. Today, the agronomic and economic interests of legumes are demonstrated. However, their crop culture remains marginalized because of the weakness and instability of their performance. In the context of improving legumes and cereals crops as well as fallow resorption, we undertook to test, in the field, the effect of rhizobial inoculation of Phaseolus vulgaris in association with Zea Mays. We firstly studied the genetic diversity of rhizobial strains that nodulate P.vulgaris isolated from fifteen (15) different regions. ARDRA had shown 18 different genetic profiles. Symbiotic characterization highlighted a strain that highly significantly improved the fresh and dry weight of the host plant, in comparison to the negative control (un-inoculated) and the positive control (inoculated with the reference strain CIAT 899). In the field, the selected strain increased significantly the growth and yield of P.vulgaris and Zea Mays comparing to the non-inoculated control. However, the mix inoculation (selected strain+ Ciat 899) had not given the best parameters showing, thus, no synergy between the strains. These results indicate the replacing fallow by a crop legume in intercropping with cereals crops.

Keywords: fallow, intercropping, inoculation, legumes-cereals

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Authors: Philip Vercoe, Ali Hardan

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Samples of 29 Australian wild natives and exotic plants were tested in vitro batch rumen culture system for their methanogenic characteristics and potential usage as feed or antimicrobial to enhance sustainable livestock ruminant production system. The plants were tested for their in vitro rumen fermentation end products properties which include: methane production, total gas pressure, concentrations of total volatile fatty acids, ammonia, and acetate to propionate ratio. All of the plants were produced less methane than the positive control (i.e., oaten chaff) in vitro. Nearly 50 % of plants inhibiting methane by over 50% in comparison to the control. Eremophila granitica had the strongest inhibitory effect about 92 % on methane production comparing with oaten chaff. The exotic weed Arctotheca calendula (Capeweed) had the highest concentration of volatile fatty acids production as well as the highest in total gas pressure among all plants and the control. Some of the acacia species have the lowest production of total gas pressure. The majority of the plants produced more ammonia than the oaten chaff control. The plant species that produced the most ammonia was Codonocarpus cotinifolius, producing over 3 times as much methane as oaten chaff control while the lowest was Eremophila galeata. There was strong positive correlation between methane production and total gas production as well as between total gas production and the concentration of VFA produced with R² = 0.74, R² = 0.84, respectively. While there was weak positive correlation between methane production and the acetate to propionate ratio as well as between the concentration of VFA produced and methane production with R² = 0.41, R² = 0.52, respectively.

Keywords: in vitro Rumen Fermentation, methane, wild Australian native plants, forages

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Authors: Ahlem Nefzi, Rania Aydi Ben Abdallah, Hayfa Jabnoun-Khiareddine, Ammar Nawaim, Rabiaa Haouala, Mejda Daami-Remadi

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Seven endophytic fungi were isolated from the wild Solanaceous species Lycium arabicum growing in the Tunisian Centre-East and were assessed for their ability to suppress Fusarium Crown and Root Rot disease caused by Fusarium oxysporum f. sp. radicis lycopersici (FORL) and to enhance plant growth. Fungal isolates were shown able to colonize tomato cv. Rio Grande roots, crowns, and stems. A significant promotion in all studied growth parameters (root length, shoot height, and roots and shoots fresh weight) was recorded in tomato plants treated with fungal conidial suspensions or their cell-free culture filtrates compared to FORL-inoculated or pathogen-free controls. I15 and I18 isolates were shown to be the most effective leading to 85.7-87.5 and 93.6-98.4% decrease in leaf and root damage index and the vascular discoloration extent, respectively, over FORL-inoculated and untreated control. These two bioactive and growth-promoting isolates (I15 and I18) were morphologically characterized and identified using rDNA sequencing gene as being Alternaria alternata (MF693801) and Fusarium fujikuroi (MF693802). These fungi significantly suppressed FORL mycelial growth and showed chitinolytic, proteolytic and amylase activities whereas only F. fujikuroi displayed a lipolytic activity. This study clearly demonstrated the potential use of fungi naturally associated with L. arabicum as biocontrol and bio-fertilizing agents.

Keywords: biocontrol, endophytic fungi, Fusarium oxysporum f. sp. radicis-lycopersici, tomato promotion, Lycium arabicum

Procedia PDF Downloads 139

Authors: Adu Micheal Kwaku, Lamptey Shirley

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Cowpea (Vigna unguiculata (L.) Walpis) is a major food grain legume in Ghana and plays a significant role in consumer diets. Drought in rain-fed crop production is known to cause substantial crop yield reduction due to their negative impacts on plant growth, physiology, and reproduction. There are various ways of reducing the effect of drought or addressing the problem of drought stress, including irrigation, breeding, and mulching. Among these three ways of reducing the effect of drought stress, the cheapest and quickest method is mulching. The broad objective of this project is to determine the influence of mulching on the performance of cowpea. The experiment was conducted at Planting for future garden located at Nyankpala Campus of the University for Development Studies (UDS), comprising five treatments (black plastic, rice hull, groundnut hull, dry grass mulch, and control). The treatments were evaluated in a Randomized Complete Block Design (RCBD) with three replications. The result shows that black plastic mulch increased soil moisture by 1, 8, 15, and 24% compared to rice hull, groundnut hull, dry grass, and control, respectively. Increased soil moisture translated into black plastic mulch increasing grain yield by 8, 25, 39, and 46% compared to groundnut hull, rice hull, dry grass and control, respectively. However, black plastic mulch increased the cost of production, resulting in decreased net returns compared to the other treatment. This study recommends the use of rice and groundnut hull as mulching material to improve soil moisture, grain yield, and profit of smallholder cowpea farmers and also because they are almost free and available.

Keywords: mulch, plastic mulch, cowpea, growth response

Procedia PDF Downloads 51

Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

Procedia PDF Downloads 28

Authors: D. Kuvshinov, A. Siswanto, W. Zimmerman

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A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil can also be used as a food stock due to its significant nutrition content. The limitations for utilizing the oil as a food stock are mainly due to a toxicity of PE. Nowadays a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence. Ozone is considered as a strong oxidative agent. It reaction with PE it attacks the carbon double bond of PE. This modification of PE molecular structure results into nontoxic ester with high lipid content. This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is a simultaneous application of new microscale plasma unit for ozone production and patented gas oscillation technology. In combination with a reactor design the technology permits ozone injection to the water-TPA mixture in form of microbubbles. The efficacy of a heterogeneous process depends on diffusion coefficient which can be controlled by contact time and interface area. The low velocity of rising microbubbles and high surface to volume ratio allow fast mass transfer to be achieved during the process. Direct injection of ozone is the most efficient process for a highly reactive and short lived chemical. Data on the plasma unit behavior are presented and influence of the gas oscillation technology to the microbubbles production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.

Keywords: microbubble, ozonolysis, synthetic phorbol ester, chemical engineering

Procedia PDF Downloads 180

Authors: Kurt Maxwell Kusterer, Sylvain Mignot, Annick Vignes

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To our best knowledge YouTube is the largest video hosting platform in the world. A high number of creators, viewers, subscribers and commentators act in this specific eco-system which generates huge sums of money. Views, subscribers, and comments help to increase the popularity of content creators. The most popular creators are sponsored by brands and participate in marketing campaigns. For a few of them, this becomes a financially rewarding profession. This is made possible through the YouTube Partner Program, which shares revenue among creators based on their popularity. We believe that the role of comments in increasing the popularity is to be emphasized. In what follows, YouTube is considered as a bilateral network between the videos and the commentators. Analyzing a detailed data set focused on French YouTubers, we consider each comment as a link between a commentator and a video. Our research question asks what are the predominant features of a video which give it the highest probability to be commented on. Following on from this question, how can we use these features to predict the action of the agent in commenting one video instead of another, considering the characteristics of the commentators, videos, topics, channels, and recommendations. We expect to see that the videos of more popular channels generate higher viewer engagement and thus are more frequently commented. The interest lies in discovering features which have not classically been considered as markers for popularity on the platform. A quick view of our data set shows that 96% of the commentators comment only once on a certain video. Thus, we study a non-weighted bipartite network between commentators and videos built on the sub-sample of 96% of unique comments. A link exists between two nodes when a commentator makes a comment on a video. We run an Exponential Random Graph Model (ERGM) approach to evaluate which characteristics influence the probability of commenting a video. The creation of a link will be explained in terms of common video features, such as duration, quality, number of likes, number of views, etc. Our data is relevant for the period of 2020-2021 and focuses on the French YouTube environment. From this set of 391 588 videos, we extract the channels which can be monetized according to YouTube regulations (channels with at least 1000 subscribers and more than 4000 hours of viewing time during the last twelve months).In the end, we have a data set of 128 462 videos which consist of 4093 channels. Based on these videos, we have a data set of 1 032 771 unique commentators, with a mean of 2 comments per a commentator, a minimum of 1 comment each, and a maximum of 584 comments.

Keywords: YouTube, social networks, economics, consumer behaviour

Procedia PDF Downloads 42

Authors: Usama Mohamed, Sam Booth, Aliysn J. Nedoma

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As part of the transition to electric vehicles, there has been a recent increase in demand for battery manufacturing. Cathodes typically account for approximately 50% of the total lithium-ion battery cell cost and are a pivotal factor in determining the viability of new industrial infrastructure. Cathodes which offer lower costs whilst maintaining or increasing performance, such as nickel-rich layered cathodes, have a significant competitive advantage when scaling up the manufacturing process. This project evaluates the techno-economic value proposition of an integrated industrial scale cathode active material (CAM) production process, closing the mass and energy balances, and optimizing the operation conditions using a sensitivity analysis. This is done by developing a process model of a co-precipitation synthesis route using Aspen Plus software and validated based on experimental data. The mechanism chemistry and equilibrium conditions were established based on previous literature and HSC-Chemistry software. This is then followed by integrating the energy streams, adding waste recovery and treatment processes, as well as testing the effect of key parameters (temperature, pH, reaction time, etc.) on CAM production yield and emissions. Finally, an economic analysis estimating the fixed and variable costs (including capital expenditure, labor costs, raw materials, etc.) to calculate the cost of CAM ($/kg and $/kWh), total plant cost ($) and net present value (NPV). This work sets the foundational blueprint for future research into sustainable industrial scale processes for CAM manufacturing.

Keywords: cathodes, industrial production, nickel-rich layered cathodes, process modelling, techno-economic analysis

Procedia PDF Downloads 62

Authors: Daniel Martin, Roberto Rodriguez, Derek Woller, Chris Reuter, Lonnie Black, Mohamed Latheef

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The grasshoppers comprised of heterogeneous assemblages of Acrididae (Family: Orthoptera) species periodically reach outbreak levels by their gregarious behavior and voracious feeding habits, devouring stems and leaves of food crops and rangeland pasture. Cattle consume about 1.5-2.5% of their body weight in forage per day, so pound for pound, a grasshopper will eat 12-20 times as much plant material as a steer and cause serious economic damage to the cattle industry, especially during a drought when forage is already scarce. Grasshoppers annually consume more than 20% of rangeland forages in the western United States at an estimated loss of $1.25 billion per year in forage. A remotely piloted aerial application system with both a spreader and spray application system was used to apply granular insect bait and a liquid formulation of Carbaryl for control of grasshopper infestations on rangeland in New Mexico, United States. Pattern testing and calibration of both the granular and liquid application systems were conducted to determine proper application rate set up and distribution pattern. From these tests, an effective swath was calculated. Results showed that 14 days after application, granular baits were only effective on those grasshopper species that accepted the baits. The liquid formulation at 16 ounces per acre was highly successful at controlling all grasshopper species. Results of this study indicated that a remotely piloted aerial application system can be used to effectively deliver grasshopper control products in both granular and liquid form. However, the spray application treatment proved to be most effective and efficient for all grasshopper species present.

Keywords: Carbaryl, Grasshopper, Insecticidal Efficacy, Remotely Piloted Aerial Application System

Procedia PDF Downloads 181

Authors: Nneka Augustina Akwu, Yougasphree Naidoo

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Molecular advancement in technology has created a means whereby the atoms and molecules (solid forms) of certain materials such as plants, can now be reduced to a range of 1-100 nanometres. Green synthesis of silver nanoparticles (AgNPs) was carried out at room temperature (RT) 25 ± 2°C and 80°C, using the metabolites in the aqueous extracts of the leaves and stem bark of Grewia lasiocarpa as reductants and stabilizing agents. The biosynthesized AgNPs were characterized by UV-Vis spectrophotometry, attenuated total reflectance - Fourier transforms infrared (ATR-FTIR) spectroscopy, nanoparticle tracking analysis (NTA), Energy Dispersive X-ray fluorescence scanning electron microscope (SEM-EDXRF) and high-resolution transmission electron microscopy (HRTEM). The AgNPs were biologically evaluated for antioxidant, antibacterial and cytotoxicity activities. The phytochemical and FTIR analyses revealed the presence of metabolites that act as reducing and capping agents, while the UV-Vis spectroscopy of the biosynthesized NPs showed absorption between 380-460 nm, confirming AgNP synthesis. The Zeta potential values were between -9.1 and -20.6 mV with a hydrodynamics diameter ranging from 38.3 to 46.7 nm. SEM and HRTEM analyses revealed that AgNPs were predominately spherical with an average particle size of 2- 31 nm for the leaves and 5-27 nm for the stem bark. The cytotoxicity IC50 values of the AgNPs against HeLa, Caco-2 and MCF-7 were >1 mg/mL. The AgNPs were sensitive to all strains of bacteria used, with methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) being more sensitive to the AgNPs. Our findings propose that antibacterial and anticancer agents could be derived from these AgNPs of G. lasiocarpa, and warrant their further investigation.

Keywords: antioxidant, cytotoxicity, Grewia lasiocarpa, silver nanoparticles, Zeta potentials

Procedia PDF Downloads 104

Authors: Shyh-Ming Chern, Te-Hsiu Tang

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Hemicellulose is one of the major constituents of all plant cell walls, making up 15-25% of dry wood. It is a biopolymer from many different sugar monomers, including pentoses, like xylose, and hexoses, like mannose. In an effort to gasify real biomass in subcritical and supercritical water in a single process, it is necessary to understand the gasification of hemicellulose, in addition to cellulose and lignin, in subcritical and supercritical water. In the present study, xylose is chosen as the model compound for hemicellulose, since it has the largest amount in most hardwoods. Xylose is gasified in subcritical and supercritical water for the production of higher-valued gaseous products. Experiments were conducted with a 16-ml autoclave batch-type reactor. Hydrogen peroxide is adopted as the oxidant in an attempt to promote the gasification yield. The major operating parameters for the gasification include reaction temperature (400 - 600°C), reaction pressure (5 - 25 MPa), the concentration of xylose (0.05 and 0.30 M), and level of oxidant added (0 and 0.25 chemical oxygen demand). 102 experimental runs were completed out of 46 different set of experimental conditions. Product gases were analyzed with a GC-TCD and determined to be mainly composed of H₂ (10 – 74 mol. %), CO (1 – 56 mol. %), CH₄ (1 – 27 mol. %), CO₂ (10 – 50 mol. %), and C₂H₆ (0 – 8 mol. %). It has been found that the gas yield (amount of gas produced per gram of xylose gasified), higher heating value (HHV) of the dry product gas, and energy yield (energy stored in the product gas divided by the energy stored in xylose) all increase significantly with rising temperature and moderately with reducing pressure. The overall best operating condition occurred at 873 K and 10 MPa, with a gas yield of 54 mmol/g of xylose, a gas HHV of 440 kJ/mol, and an energy yield of 1.3. A seemingly unreasonably energy yield of greater than unity resulted from the external heating employed in the experiments to drive the gasification process. It is concluded that xylose can be completely gasified in subcritical and supercritical water under proper operating conditions. The addition of oxidant does not promote the gasification of xylose.

Keywords: gasification, subcritical water, supercritical water, xylose

Procedia PDF Downloads 204

Authors: Hanady Hamdallah, H. Elyse Ireland, John H. H. Williams

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Conjugated linoleic acid (CLA) is a food supplement that is reported to have multiple beneficial health effects, including being anti-carcinogenic, anti-inflammatory and anti-obesity. Animal studies have shown a significant anti-obesity effect of CLA, but results in humans were inconsistent, where some of the studies found an anti-obesity effect while other studies failed to find any decline in obesity markers after CLA supplementation. This meta-analysis aimed to determine if oral CLA supplementation has been shown to reduce obesity related markers in women. Pub Med, Cochrane Library, and Google Scholar were used to identify the eligible trials using two main searching strategies: the first one was to search eligible trials using keywords 'Conjugated linoleic acid', 'CLA', 'Women', and the second strategy was to extract the eligible trials from previously published systematic reviews and meta-analyses. The eligible trials were placebo control trials where women supplemented with CLA mixture in the form of oral capsules for 6 months or less. Also, these trials provided information about body composition expressed as body weight (BW), body mass index (BMI), total body fat (TBF), percentage body fat (BF %), and/ or lean body mass (LBM). The quality of each included study was assessed using both JADAD scale and an adapted CONSERT checklist. Meta-analysis of 8 eligible trials showed that CLA supplementation was significantly associated with reduced BW (Mean ± SD, 1.2 ± 0.26 kg, p < 0.001), BMI (0.6 ± 0.13kg/m², p < 0.001) and TBF (0.76 ± 0.26 kg, p= 0.003) in women, when supplemented over 6-16 weeks. Subgroup meta-analysis demonstrated a significant reduction in BW (1.29 ± 0.31 kg, p < 0.001), BMI (0.60 ± 0.14 kg/m², p < 0.001) and TBF (0.82 ± 0.28 kg, p= 0.003) in the trials that had recruited overweight-obese women. The second subgroup meta-analysis, that considered the menopausal status of the participants, found that CLA was significantly associated with reduced BW (1.35 ± 0.37 kg, p < 0.001; 1.05 ± 0.36 kg, p= 0.003) and BMI (0.50 ± 0.17 kg/m², p= 0.003; 0.75 ± 0.2 kg/m², p < 0.001) in both pre and post-menopausal age women, respectively. A reduction in TBF (1.09 ± 0.37 kg, p= 0.003) was only significant in post-menopausal women. Interestingly, CLA supplementation was associated with a significant reduction in BW (1.05 ± 0.35 kg, p< 0.003), BMI (0.73 ± 0.2 kg/m², p < 0.001) and TBF (1.07 ± 0.36 kg, p= 0.003) in the trials without lifestyle monitoring or interventions. No significant effect of CLA on LBM was detected in this meta-analysis. This meta-analysis suggests a moderate anti-obesity effect of CLA on BW, BMI and TBF reduction in women, when supplemented over 6-16 weeks, particularly in overweight-obese women and post-menopausal women. However, this finding requires careful interpretation due to several issues in the designs of available CLA supplementation trials. More well-designed trials are required to confirm this meta-analysis results.

Keywords: body composition, body mass index, body weight, conjugated linoleic acid

Procedia PDF Downloads 262

Authors: Hisham Mousa Mohammed Ahmed, Ahmed Wali Mohamed Salad, Yousif Hamed Dldom Gomaa

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A drip or Trickle irrigation system is designed to apply a precise amount of water near the plant with a certain degree of uniformity. This study was conducted at the Experimental Farm of the Faculty of Agricultural Sciences, University of Gezira, in March 2018. The study aimed to design and evaluate the hydraulic performance of three drip emitter types using: average discharge (Qavg), discharge variation (Qvar %), coefficient of uniformity (CU %), coefficient of manufacturer variation (CV %), distribution uniformity (DU %), statistical uniformity (Us %), clogging (%) wetted diameter (cm) and wetted depth (cm). The emitter types used are regular gauges (RG), high compensating pressure (HCP) and low compensating pressure (LCP). The treatments were laid out in a randomized complete block design (RCBD) with four replications. Results showed that there were significant differences (P≤0.05) in all tested parameters except clogging, wetted diameter and wetted depth. Discharge variation (Qvar %) values were 12.71, 15.57 and 19.17 for RG, LCP, and HCP, respectively. The variation is quite good and within the acceptable range. Results of coefficient of manufacture variation (CV %) were 10.9, 27.8 and 52.7 for RG, LCP and HCP, respectively. It is considered within the unacceptable range except for RG type, which is excellent. Statistical uniformity (Us %) values were 89.1, 72.2 and 45.7 for RG, LCP and HCP, respectively. It is considered good, acceptable and unacceptable, respectively. Results of the coefficient of uniformity (CU %) were 91.3, 77.7 and 56.7 for RG, LCP and HCP, respectively. It is considered excellent, fair and unacceptable, respectively. Distribution uniformity (DU %) was 90.2, 67.9 and 36.5 for RG, LCP and HCP, respectively. It is considered excellent, poor and poor, respectively. The study recommended regular gauges (RG) type emitters under the heavy clay soil conditions of the Gezira State, Sudan.

Keywords: drip irrigation, uniformity, clogging, coefficient, performance

Procedia PDF Downloads 67

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

Procedia PDF Downloads 365