Search results for: dorsal root ganglia
381 Investigating the performance of machine learning models on PM2.5 forecasts: A case study in the city of Thessaloniki
Authors: Alexandros Pournaras, Anastasia Papadopoulou, Serafim Kontos, Anastasios Karakostas
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The air quality of modern cities is an important concern, as poor air quality contributes to human health and environmental issues. Reliable air quality forecasting has, thus, gained scientific and governmental attention as an essential tool that enables authorities to take proactive measures for public safety. In this study, the potential of Machine Learning (ML) models to forecast PM2.5 at local scale is investigated in the city of Thessaloniki, the second largest city in Greece, which has been struggling with the persistent issue of air pollution. ML models, with proven ability to address timeseries forecasting, are employed to predict the PM2.5 concentrations and the respective Air Quality Index 5-days ahead by learning from daily historical air quality and meteorological data from 2014 to 2016 and gathered from two stations with different land use characteristics in the urban fabric of Thessaloniki. The performance of the ML models on PM2.5 concentrations is evaluated with common statistical methods, such as R squared (r²) and Root Mean Squared Error (RMSE), utilizing a portion of the stations’ measurements as test set. A multi-categorical evaluation is utilized for the assessment of their performance on respective AQIs. Several conclusions were made from the experiments conducted. Experimenting on MLs’ configuration revealed a moderate effect of various parameters and training schemas on the model’s predictions. Their performance of all these models were found to produce satisfactory results on PM2.5 concentrations. In addition, their application on untrained stations showed that these models can perform well, indicating a generalized behavior. Moreover, their performance on AQI was even better, showing that the MLs can be used as predictors for AQI, which is the direct information provided to the general public.Keywords: Air Quality, AQ Forecasting, AQI, Machine Learning, PM2.5
Procedia PDF Downloads 77380 Forecasting Nokoué Lake Water Levels Using Long Short-Term Memory Network
Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin
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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake
Procedia PDF Downloads 64379 Influence of Salicylic Acid on Submergence Stress Recovery in Selected Rice Cultivars (Oryza sativa L.)
Authors: Ja’afar U., A. M. Gumi, Salisu N., Obadiah C. D.
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Rice is susceptible to flooding due to its semi-aquatic characteristics, which enable it to thrive in wet or submerged environments. The development of aerenchyma allows for oxygen transfer, enabling faster lengthening of submerged shoot organs. Rice's germination and early seedling growth phases are highly intolerant of submersion, resulting in survival in low-oxygen environments. The research involved a study on rice plants treated with salicylic acid at different concentrations. Hypo was used for washing, while a reagent was used for submergence treatment. The plants were waterlogged for 11 days and submerged for 7 days, with control plants receiving distilled water. The study found a significant difference between Jirani Zawara's control and treated plants, with plants treated with 2 g/L of S.A. showing a 6.00 node increase per plant and Faro cultivars having more nodes. The study found significant differences between the control and treated plants, with the Jirani Zawara plant showing longer internode lengths and the Faro cultivar having longer internode lengths, while the B.G. cultivar had the longest. The research found that the Jirani Zawara cultivar treated with 3 g/L of S.A. produced tallest plants, with heights increasing from 14.43 cm to 15.50 cm in Faro cultivar S.A., and the highest height was 16.30 cm. The study reveals that salicylic acid significantly enhances the number of nodes, internode length, plant height, and root length in rice cultivars, thereby improving submerged stress recovery and promoting plant development.Keywords: rice, submergence, stress, salicylic acid
Procedia PDF Downloads 15378 Study on the Effects of Grassroots Characteristics on Reinforced Soil Performance by Direct Shear Test
Authors: Zhanbo Cheng, Xueyu Geng
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Vegetation slope protection technique is economic, aesthetic and practical. Herbs are widely used in practice because of rapid growth, strong erosion resistance, obvious slope protection and simple method, in which the root system of grass plays a very important role. In this paper, through changing the variables value of grassroots quantity, grassroots diameter, grassroots length and grassroots reinforce layers, the direct shear tests were carried out to discuss the change of shear strength indexes of grassroots reinforced soil under different reinforce situations, and analyse the effects of grassroots characteristics on reinforced soil performance. The laboratory test results show that: (1) in the certain number of grassroots diameter, grassroots length and grassroots reinforce layers, the value of shear strength, and cohesion first increase and then reduce with the increasing of grassroots quantity; (2) in the certain number of grassroots quantity, grassroots length and grassroots reinforce layers, the value of shear strength and cohesion rise with the increasing of grassroots diameter; (3) in the certain number of grassroots diameter, and grassroots reinforce layers, the value of shear strength and cohesion raise with the increasing of grassroots length in a certain range of grassroots quantity, while the value of shear strength and cohesion first rise and then decline with the increasing of grassroots length when the grassroots quantity reaches a certain value; (4) in the certain number of grassroots quantity, grassroots diameter, and grassroots length, the value of shear strength and cohesion first climb and then decline with the increasing of grassroots reinforced layers; (5) the change of internal friction angle is small in different parameters of grassroots. The research results are of importance for understanding the mechanism of vegetation protection for slopes and determining the parameters of grass planting.Keywords: direct shear test, reinforced soil, grassroots characteristics, shear strength indexes
Procedia PDF Downloads 179377 Prediction of California Bearing Ratio of a Black Cotton Soil Stabilized with Waste Glass and Eggshell Powder using Artificial Neural Network
Authors: Biruhi Tesfaye, Avinash M. Potdar
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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC
Procedia PDF Downloads 191376 Final Account Closing in Construction Project: The Use of Supply Chain Management to Reduce the Delays
Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md. Yusof
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Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). This process is not easy to implement efficiently and effectively. The issue of delays in construction is a major problem for construction projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demands that are constantly changing and influencing, either directly or indirectly, the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the problem and issues in the final account closing in construction projects, and it establishes the need to embrace Supply Chain Management (SCM) and then elucidates the need and strategies for the development of a delay reduction framework. At the same time, this paper provides effective measures to avoid or at least reduce the delay to the optimum level. Allowing problems in the closure declaration to occur without proper monitoring and control can leave negative impact on the cost and time of delivery to the end user. Besides, it can also affect the reputation or image of the agency/department that manages the implementation of a contract and consequently may reduce customer's trust towards the agencies/departments. It is anticipated that the findings reported in this paper could address root delay contributors and apply SCM tools for their mitigation for the better development of construction project.Keywords: final account closing, construction project, construction delay, supply chain management
Procedia PDF Downloads 367375 Determination of the Water Needs of Some Crops Irrigated with Treated Water from the Sidi Khouiled Wastewater Treatment Plant in Ouargla, Algeria
Authors: Dalila Oulhaci, Mehdi Benlarbi, Mohammed Zahaf
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The irrigation method is fundamental for maintaining a wet bulb around the roots of the crop. This is the case with localized irrigation, where soil moisture can be maintained permanently around the root system between the two water content extremes. Also, one of the oldest methods used since Roman times throughout North Africa and the Near East is based on the frequent dumping of water into porous pottery vases buried in the ground. In this context, these two techniques have been combined by replacing the pottery vase with plastic bottles filled with sand that discharge water through their perforated walls into the surrounding soil. The first objective of this work is the theoretical determination using CLIMWAT and CROPWAT software of the irrigation doses of some crops (palm, wheat, and onion) and experimental by measuring the humidity of the soil before and after watering. The second objective is to determine the purifying power of the sand filter in the bottle. Based on the CROPWAT software results, the date palm needs 18.5 mm in the third decade of December, 57.2 mm in January, and 73.7 mm in February, whereas the doses received by experimentally determined by means of soil moisture before and after irrigation are 19.5 mm respectively, 79.66 mm and 95.66 mm. The onion needs 14.3 mm in the third decade of December of, 59.1 mm in January, and 80 mm in February, whereas the experimental dose received is 15.07 mm, respectively, 64.54 and 86.8 mm. The total requirements for the vegetative period are estimated at 1642.6 mm for date palms, 277.4 mm for wheat, and 193.5 mm for onions. The removal rate of the majority of pollutants from the bottle is 80%. This work covers, on the one hand, the context of water conservation, sustainable development, and protection of the environment, and on the other, the agricultural field.Keywords: irrigation, sand, filter, humidity, bottle
Procedia PDF Downloads 66374 M. J. Rodríguez, F. M. Sánchez, B. Velardo, P. Calvo, M. J. Serradilla, J. Delgado, J. M. López
Authors: Q. Rzina, M. Lahrouni, S. Rida, N. Saadaoui, Y. Almossaid, K. Oufdou, K. Fares
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Many organic solid wastes are produced in the world. Poultry manure (PM), municipal organic wastes (MOW) and sugar beet lime sludge (LS) are produced in large quantities in Morocco. The co-composting of these organic wastes was investigated. The recycling and the valorization of such wastes is environmentally and economically beneficial especially for PM which is known source of bacterial pathogens. The aerobic biodegradation process was carried out by using three windrows of variable compositions: C1 prepared without LS (only MOW were composted with PM), C2 prepared from MOW plus PM and10% LS; and the last one C3 from MOW plus PM and 20% LS. The main process physico-chemical parameters (temperature, pH, humidity and C/N) and microbiological populations (mesophilic and thermophilic flora, total coliform, fecal coliform, Streptococci, Staphylococcus aureus and mesophilic fungi) were monitored over three months to ascertain the compost maturity and to ensure the compost hygienic aspect. The final products were characterized by their relatively high organic matter content, and low C/N ratio of 10.6-10.9. The organic matter degradation was reached approximately 59% for C2 and C3. In addition, the monitoring of the microbial population showed that the produced composts are mature and hygienic. The agronomic valorization of the final composts was tested on radish plant with tree level of composts and poultry manure without composting. The primary results of field trial showed a growth of radish plant biomass and root development without any phytotoxicity detected which reflects the quality of the composts produced. As for poultry manure it allowed to have a better results than other composts because of its readily available nitrogen.Keywords: compost, municipal organic wastes, poultry manure, radish crop, sugar beet lime sludge
Procedia PDF Downloads 312373 The Relationship between Renewable Energy, Real Income, Tourism and Air Pollution
Authors: Eyup Dogan
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One criticism of the energy-growth-environment literature, to the best of our knowledge, is that only a few studies analyze the influence of tourism on CO₂ emissions even though tourism sector is closely related to the environment. The other criticism is the selection of methodology. Panel estimation techniques that fail to consider both heterogeneity and cross-sectional dependence across countries can cause forecasting errors. To fulfill the mentioned gaps in the literature, this study analyzes the impacts of real GDP, renewable energy and tourism on the levels of carbon dioxide (CO₂) emissions for the top 10 most-visited countries around the world. This study focuses on the top 10 touristic (most-visited) countries because they receive about the half of the worldwide tourist arrivals in late years and are among the top ones in 'Renewables Energy Country Attractiveness Index (RECAI)'. By looking at Pesaran’s CD test and average growth rates of variables for each country, we detect the presence of cross-sectional dependence and heterogeneity. Hence, this study uses second generation econometric techniques (cross-sectionally augmented Dickey-Fuller (CADF), and cross-sectionally augmented IPS (CIPS) unit root test, the LM bootstrap cointegration test, and the DOLS and the FMOLS estimators) which are robust to the mentioned issues. Therefore, the reported results become accurate and reliable. It is found that renewable energy mitigates the pollution whereas real GDP and tourism contribute to carbon emissions. Thus, regulatory policies are necessary to increase the awareness of sustainable tourism. In addition, the use of renewable energy and the adoption of clean technologies in tourism sector as well as in producing goods and services play significant roles in reducing the levels of emissions.Keywords: air pollution, tourism, renewable energy, income, panel data
Procedia PDF Downloads 184372 Green Synthesized Iron Oxide Nanoparticles: A Nano-Nutrient for the Growth and Enhancement of Flax (Linum usitatissimum L.) Plant
Authors: G. Karunakaran, M. Jagathambal, N. Van Minh, E. Kolesnikov, A. Gusev, O. V. Zakharova, E. V. Scripnikova, E. D. Vishnyakova, D. Kuznetsov
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Iron oxide nanoparticles (Fe2O3NPs) are widely used in different applications due to its ecofriendly nature and biocompatibility. Hence, in this investigation, biosynthesized Fe2O3NPs influence on flax (Linum usitatissimum L.) plant was examined. The biosynthesized nanoparticles were found to be cubic phase which is confirmed by XRD analysis. FTIR analysis confirmed the presence of functional groups corresponding to the iron oxide nanoparticle. The elemental analysis also confirmed that the obtained nanoparticle is iron oxide nanoparticle. The scanning electron microscopy and the transmission electron microscopy confirm that the average particle size was around 56 nm. The effect of Fe2O3NPs on seed germination followed by biochemical analysis was carried out using standard methods. The results obtained after four days and 11 days of seed vigor studies showed that the seedling length (cm), average number of seedling with leaves, increase in root length (cm) was found to be enhanced on treatment with iron oxide nanoparticles when compared to control. A positive correlation was noticed with the dose of the nanoparticle and plant growth, which may be due to changes in metabolic activity. Hence, to evaluate the change in metabolic activity, peroxidase and catalase activities were estimated. It was clear from the observation that higher concentration of iron oxide nanoparticles (Fe2O3NPs 1000 mg/L) has enhanced peroxidase and catalase activities and in turn plant growth. Thus, this study clearly showed that biosynthesized iron oxide nanoparticles will be an effective nano-nutrient for agriculture applications.Keywords: catalase, fertilizer, iron oxide nanoparticles, Linum usitatissimum L., nano-nutrient, peroxidase
Procedia PDF Downloads 391371 A Cadaveric Study of Branching Pattern of Arch of Aorta and Its Clinical Significance in Nepalese Population
Authors: Gulam Anwer Khan, A. Gautam
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Background: The arch of aorta is a large artery that arches over the root of the left lung and connects the ascending aorta and descending aorta. It is situated in the superior mediastinum behind the manubrium sterni. It gives off three major branches i.e. brachiocephalic trunk, left common carotid artery and left subclavian artery arising from the superior surface of arch of aorta from right to left. Material and Methods: This was a descriptive study. It was carried out in 44 cadavers, obtained during dissections for undergraduates of Department of Anatomy, Chitwan Medical College, Bharatpur, Chitwan, between March 2015 to October 2016. Cadavers of both sexes were included in the present study. The arch of aorta was dissected and exposed according to the methods described by Romanes in Cunningham’s manual of practical anatomy. Results: Out of 44 dissected cadavers, 35 (79.54%) were male and 9 (20.46%) were female cadavers. The normal branching pattern of the arch of aorta was encountered in 28 (63.64%) cadavers and the remaining 16 (36.36%) cadavers showed variations in the branching pattern of arch of aorta. Two different types of variations on the branching pattern of arch of aorta were noted in the present study, in which 12 (27.27%) cadavers had common trunk of the Arch of Aorta. In 3 (5.00%) male cadavers, we found the origin of the Thyroid ima artery. This variation was noted in 1(1.66%) female cadaver. Conclusion: The present study carried out on adult human cadavers’ revealed wide variations in the branching pattern of the arch of ao rta. These variations are of clinical significance and also very useful for the anatomists, radiologists, anesthesiologists, surgeons for practice during angiography, instrumentation, supra-aortic thoracic, head and neck surgery.Keywords: arch of aorta, brachiocephalic trunk, left common carotid artery, left subclavian artery, Thyroidea ima artery
Procedia PDF Downloads 335370 Ecotoxicity Evaluation Methodology for Metallurgical and Steel Wastes
Authors: G. Pelozo, N. Quaranta
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The assessment of environmental hazard and ecotoxicological potential of industrial wastes has become an issue of concern in many countries. Therefore, the aim of this work is to develop a methodology, adapting an Argentinian standard, which allows analyze the ecotoxicological effect of various metallurgical and steel wastes. Foundry sand, white mud, red mud, electric arc furnace dust, converter slag, among others, are the studied wastes. The species used to analyze the ecotoxicological effects of wastes is rye grass (Lolium Perenne). The choice of this kind lies, among other things, in its easy and rapid germination making it possible to develop the test in a few days. Moreover, since the processes involved are general for most seeds, the obtained results with this kind are representative, in general, of the effects on seeds or seedlings. Since the studied residues are solids, prior to performing the assay, an eluate is obtained by stirring for 2 hours and subsequent filtration of a solution of waste in water in a relationship of 1:4. This represents 100% of eluate from which two dilutions in water (25% and 50%) are prepared. A sample with untreated solid waste and water is also performed. The test is performed by placing two filter papers in a Petri dish that are saturated with 3.5ml of the prepared dilutions. After that 20 rye grass seeds are placed, and the Petri dishes are covered and the seeds are incubated for 120 hours at 24 °C. Reference controls are carried out by distilled water. Three replicates are performed for each concentration. Once the exposure period is finished, inhibiting elongation of the root is measured (IR). The results of this test show that all the studied wastes produce an unfavorable effect on the development of the seedlings, being the electric arc furnace dust which more affects the germination.Keywords: ecotoxicity, industrial wastes, environmental hazard, seeds
Procedia PDF Downloads 403369 Factor Influencing Pharmacist Engagement and Turnover Intention in Thai Community Pharmacist: A Structural Equation Modelling Approach
Authors: T. Nakpun, T. Kanjanarach, T. Kittisopee
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Turnover of community pharmacist can affect continuity of patient care and most importantly the quality of care and also the costs of a pharmacy. It was hypothesized that organizational resources, job characteristics, and social supports had direct effect on pharmacist turnover intention, and indirect effect on pharmacist turnover intention via pharmacist engagement. This research aimed to study influencing factors on pharmacist engagement and pharmacist turnover intention by testing the proposed structural hypothesized model to explain the relationship among organizational resources, job characteristics, and social supports that effect on pharmacist turnover intention and pharmacist engagement in Thai community pharmacists. A cross sectional study design with self-administered questionnaire was conducted in 209 Thai community pharmacists. Data were analyzed using Structural Equation Modeling technique with analysis of a moment structures AMOS program. The final model showed that only organizational resources had significant negative direct effect on pharmacist turnover intention (β =-0.45). Job characteristics and social supports had significant positive relationship with pharmacist engagement (β = 0.44, and 0.55 respectively). Pharmacist engagement had significant negative relationship with pharmacist turnover intention (β = - 0.24). Thus, job characteristics and social supports had significant negative indirect effect on turnover intention via pharmacist engagement (β =-0.11 and -0.13, respectively). The model fit the data well (χ2/ degree of freedom (DF) = 2.12, the goodness of fit index (GFI)=0.89, comparative fit index (CFI) = 0.94 and root mean square error of approximation (RMSEA) = 0.07). This study can be concluded that organizational resources were the most important factor because it had direct effect on pharmacist turnover intention. Job characteristics and social supports were also help decrease pharmacist turnover intention via pharmacist engagement.Keywords: community pharmacist, influencing factor, turnover intention, work engagement
Procedia PDF Downloads 204368 Synergistic Effects of Hydrogen Sulfide and Melatonin in Alleviating Vanadium Toxicity in Solanum lycopersicum L. Plants
Authors: Abazar Ghorbani, W. M. Wishwajith W. Kandegama, Seyed Mehdi Razavi, Moxian Chen
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The roles of hydrogen sulfide (H₂S) and melatonin (MT) as gasotransmitters in plants are widely recognised. Nevertheless, the precise nature of their involvement in defensive reactions remains uncertain. This study investigates the impact of the ML-H2S interaction on tomato plants exposed to vanadium (V) toxicity, focusing on synthesising secondary metabolites and V metal sequestration. The treatments applied in this study included a control (T1), V stress (T2), MT+V (T3), MT+H2S+V (T4), MT+hypotaurine (HT)+V (T5), and MT+H2S+HT+V (T6). These treatments were administered: MT (150 µM) as a foliar spray pre-treatment (3X), HT treatment (0.1 mM, an H2S scavenger) as root immersion for 12 hours as pre-treatments, and H2S (NaHS, 0.2 mM) and V (40 mg/L) treatments added to the Hoagland solution for 2 weeks. Results demonstrate that ML and H2S+ML treatments alleviate V toxicity by promoting the transcription of key genes (ANS, F3H, CHS, DFR, PAL, and CHI) involved in phenolic and anthocyanin biosynthesis. Moreover, they decreased V uptake and accumulation and enhanced the transcription of genes involved in glutathione and phytochelatin synthesis (GSH1, PCS, and ABC1), leading to V sequestration in roots and protection against V-induced damage. Additionally, ML and H2S+ML treatments optimize chlorophyll metabolism, and increase internal H2S levels, thereby promoting tomato growth under V stress. The combined treatment of ML+H2S shows superior effects compared to ML alone, suggesting synergistic/interactive effects between these two substances. Furthermore, inhibition of the beneficial impact of ML+H2S and ML treatments by HT, an H2S scavenger, underscores the significant involvement of H₂S in the signaling pathway activated by ML during V toxicity. Overall, these findings suggest that ML requires the presence of endogenous H₂S to mitigate V-induced adverse effects on tomato seedlings.Keywords: vanadium toxicity, secondary metabolites, vanadium sequestration, h2s-melatonin crosstalk
Procedia PDF Downloads 45367 Crop Leaf Area Index (LAI) Inversion and Scale Effect Analysis from Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Data
Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao
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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing
Procedia PDF Downloads 440366 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction
Authors: Luis C. Parra
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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms
Procedia PDF Downloads 107365 Potential Growth of Tomato Plants in Induced Saline Soil with Rhizobacteria (PGPR)
Authors: Arfan Ali, Idrees Ahmad Nasir
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The critical evaluation of tolerance in tomato plants against the induced saline soil were assessed by transcript analysis of genes coding for products potentially involved in stress tolerance. A reverse transcriptase PCR experiment was performed with Hsp90-1, MT2, and GR1like protein genes using RNA isolated from different tissues of tomato plants. Four strains of Bacillus magisterium were inoculated with 100 Mm & 200 Mm concentrations of salt. Eleven treatments each ten replica pots were installed in green house experiment and the parameters taken into account were morphological (length, weight, number of leaves, leaf surface area), chemical (anthocyanin, chlorophyll-a, chlorophyll-b, carotenoids) and biological (gene expression). Results bare a response i.e. highest response of MT2 like gene was at 24 hpi and the highest levels of GR1 like protein transcript accumulation were detected at 36 hpi. The chemical and morphological parameters at diverse salt concentrations bequeath superlative response amongst strains which candidly flank on Zm7 and Zm4. Therefore, Bacillus magisterium Zm7 strains and somehow Zm4 strain can be used in saline condition to make plants tolerant. The overall performance of strains Zm7, Zm6, and Zm4 was found better for all studied traits under salt stress conditions. Significant correlations among traits root length, shoot length, number of leaves, leaf surface area, carotenoids, anthocyanin, chlorophyll-a and chlorophyll-b were found and suggested that the salt tolerance in tomato may be improved through the use of PGPR strains.Keywords: Bacillus magisterium, gene expression glutathione reductase, metallothionein, PGPR, Rhizobacteria, saline
Procedia PDF Downloads 434364 In Vitro Antioxidant and Free Radical Scavenging Activity of Phyllanthus Emblica L. Extract
Authors: Benyapa Suksuwan
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Introduction: Oxidative stress is identified as the root cause of the development and progression of several diseases as the disproportion of free radicals in the body leads to tissue or cell damage. Polyphenols are the most common antioxidant found in plants and are efficient in capturing oxidative free radicals. Aim of the Study: This study focused on the antioxidant activity of polyphenols extracted from Phyllanthus Emblica L. as oxidative stress plays a vital role in developing and progressing many diseases, including cardiovascular diseases and cancer. Materials and Methods: The plant was extracted using a mixture solvent (ethyl alcohol: water in ratio 8:2). The total phenolic content of P. Emblica extract was determined using the Folin-Cioucalteu method and calculated as gallic acid equivalents (GAE) and various antioxidant assays DPPH and ABTS radical scavenging capacity assays. Results and Discussion: The findings exhibited a strong correlation between antioxidant activity and the total phenol contents. In addition, the IC₅₀ of P. Emblica extract via DPPH and ABTS assays were 68.10 μg/mL ± 0.455, and 49.24 μg/mL ± 0.716, respectively. Furthermore, P. Emblica extract showed antioxidant activities in a concentration-dependent manner. Vitamin C was used as a positive control in the DPPH assay, while Trolox was used as a positive control in the ABTS assay. Conclusions: In conclusion, P. Emblica extract consisted of a high amount of total phenolic content, which possesses potent antioxidant activity. However, further antioxidant activity assays using human cell lines such as SOD, ROS, and RNS scavenging assays and in vitro antioxidant experiments should be performed in order.Keywords: antioxidant, ABTS scavenging, DPPH scavenging assay, total phenol contents assay, Phyllanthus Emblica L
Procedia PDF Downloads 195363 Utilization of Logging Residue to Reduce Soil Disturbance of Timber Harvesting
Authors: Juang R. Matangaran, Qi Adlan
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Industrial plantation forest in Indonesia was developed in 1983, and since then, several companies have been successfully planted a total area of concessionaire approximately 10 million hectares. Currently, these plantation forests have their annual harvesting period. In the timber harvesting process, amount part of the trees generally become logging residue. Tree parts such as branches, twigs, defected stem and leaves are unused section of tree on the ground after timber harvesting. The use of heavy machines in timber harvesting area has caused damage to the forest soil. The negative impact of such machines includes loss of topsoil, soil erosion, and soil compaction. Forest soil compaction caused reduction of forest water infiltration, increase runoff and causes difficulty for root penetration. In this study, we used logging residue as soil covers on the passages passed by skidding machines in order to observe the reduction soil compaction. Bulk density of soil was measured and analyzed after several times of skidding machines passage on skid trail. The objective of the research was to analyze the effect of logging residue on reducing soil compaction. The research was taken place at one of the industrial plantation forest area of South Sumatra Indonesia. The result of the study showed that percentage increase of soil compaction bare soil was larger than soil surface covered by logging residue. The maximum soil compaction occurred after 4 to 5 passes on soil without logging residue or bare soil and after 7 to 8 passes on soil cover by logging residue. The use of logging residue coverings could reduce soil compaction from 45% to 60%. The logging residue was effective in decreasing soil disturbance of timber harvesting at the plantation forest area.Keywords: bulk density, logging residue, plantation forest, soil compaction, timber harvesting
Procedia PDF Downloads 405362 Dealing with Buckling Effect in Snorkel by Finite Element Analysis: A Life Enhancement Approach in CAS-OB Operation
Authors: Subodh Nath Patel, Raja Raman, Mananshi Adhikary, Jitendra Mathur, Sandip Bhattacharyya
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The composition adjustment by sealed argon bubbling–oxygen blowing (CAS-OB) process is a process designed for adjusting steel composition and temperature during secondary metallurgy. One of the equipment in the said process is a snorkel or bell, fixed to a movable bracket. Snorkel serves the purpose of feeding ferroalloys into the liquid metal simultaneously removing gases to the gas cleaning system through its port at its top. The bell-shaped snorkel consists of two parts. The upper part has an inside liner, and the lower part is lined on both side with high-alumina castable reinforced with 2% stainless steel needles. Both the parts are coupled with a flange bolt system. These flanges were found to get buckled during operation, and the gap was generating between them. This problem was chronic since its. It was expected to give a life of 80 heats, but it was failing within 45-50 heats. After every 25-30 heats, it had to be repaired by changing and/or tightening its nuts and bolts. Visual observation, microstructural analysis through optical microscopes and SEM, hardness measurement and thermal strain calculation were carried out to find out the root cause of this problem. The calculated thermal strain was compared with actual thermal strain; comparison of the two revealed that thermal strain was responsible for buckling. Finite element analysis (FEA) was carried out to reaffirm the effect temperature on the flanges. FEA was also used in the modification in the design of snorkel flange to accommodate thermal strain. Thermal insulation was also recommended which increased its life from 45 heats to 65 heats, impacting business process positively.Keywords: CAS OB process, finite element analysis, snorkel, thermal strain
Procedia PDF Downloads 137361 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model
Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li
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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model
Procedia PDF Downloads 147360 Phenotypic and Symbiotic Characterization of Rhizobia Isolated from Faba Bean (Vicia faba L.) in Moroccan Soils
Authors: Y. Hajjam, I. T. Alami, S. M. Udupa, S. Cherkaoui
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Faba bean (Vicia faba L.) is an important food legume crop in Morocco. It is mainly used as human food and feed for animals. Faba bean also plays an important role in cereal-based cropping systems, when rotated with cereals it improves soil fertility by fixing N2 in root nodules mediated by Rhizobium. Both faba bean and its biological nitrogen fixation symbiotic bacterium Rhizobium are affected by different stresses such as: salinity, drought, pH, heavy metal, and the uptake of inorganic phosphate compounds. Therefore, the aim of the present study was to evaluate the phenotypic diversity among the faba bean rhizobial isolates and to select the tolerant strains that can fix N2 under environmental constraints for inoculation particularly for affected soils, in order to enhance the productivity of faba bean and to improve soil fertility. Result have shown that 62% of isolates were fast growing with the ability of producing acids compounds , while 38% of isolates are slow growing with production of alkalins. Moreover, 42.5% of these isolates were able to solubilize inorganic phosphate Ca3(PO4)2 and the index of solubilization was ranged from 2.1 to 3.0. The resistance to extreme pH, temperature, water stress heavy metals and antibiotics lead us to classify rhizobial isolates into different clusters. Finally, the authentication test under greenhouse conditions showed that 55% of the rhizobial isolates could induce nodule formation on faba bean (Vicia faba L.) under greenhouse experiment. This phenotypic characterization may contribute to improve legumes and non legumes crops especially in affected soils and also to increase agronomic yield in the dry areas.Keywords: rhizobia, vicia faba, phenotypic characterization, nodule formation, environmental constraints
Procedia PDF Downloads 252359 Assessment of Heavy Metal Bioaccumulation by Tissues of Ipomoea Batatas and Manihot Esculenta Irrigated with Water from Muhammad Ayuba Dam, Kazaure, Jigawa State, Nigeria
Authors: Sa’idu A. Abdullah, Jafar Lawan, A. U. Adamu, Fowotade, S. A., Hamisu Abdu
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Scarcity of quality water in many communities compels inhabitants to use any available water resources for domestic, recreational, industrial and agricultural purposes. Global concern on the potential health hazards of anthropogenic inputs into our ecosystems imposes the need for constant monitoring of levels of pollutants in order to ensure compliance with internationally acceptable criteria. In this research, assessment of bioaccumulation of Cd, Co, Cu, Pb and Zn was carried out using tissues of Ipomoea batatas (sweet potato) and Manihot esculenta (cassava) irrigated with water from Muhammad Ayuba Dam in Kazaure, Jigawa State. The metal concentrations were determined using Flame Atomic Absorption Spectrophotometer (FAAS). The result of the analysis revealed the presence of the metals in varying concentrations. Cd and Co showed higher concentrations in the tubers of Manihot esculenta but all the other investigated metals were more concentrated in the leaves of the plant. Cd and Cu on the other hand showed higher concentration in the root of Ipomoea batatas while the remaining investigated metals were concentrated more in the leaves of the plant. The result of analysis of water samples from five sampling stations in the Dam showed the presence of the metals as follows: Cd, (0.063±0.02 mg/L), Co (0.086±0.03 mg/L), Cu (0.167±0.08 mg/L), Pb (0.22±0.01 mg/L) and Zn (0.047±0.01 mg/L) respectively. The results of bioaccumulation studies using the Bioaccumulation Factors (BAF) index indicated Ipomoea batatas to have higher bioaccumulation potential for Cd, Co and Cu while Pb and Zn were more accumulated in Manihot esculenta. The levels of the metals in both the water samples and plant tissues were all below the WHO permissible limit. This is indicative that the inhabitants of the community under investigation are not at any health risk.Keywords: agriculture, bioaccumulation, heavy metal, plant tissues
Procedia PDF Downloads 385358 Parametric Optimization of High-Performance Electric Vehicle E-Gear Drive for Radiated Noise Using 1-D System Simulation
Authors: Sanjai Sureshkumar, Sathish G. Kumar, P. V. V. Sathyanarayana
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For e-gear drivetrain, the transmission error and the resulting variation in mesh stiffness is one of the main source of excitation in High performance Electric Vehicle. These vibrations are transferred through the shaft to the bearings and then to the e-Gear drive housing eventually radiating noise. A parametrical model developed in 1-D system simulation by optimizing the micro and macro geometry along with bearing properties and oil filtration to achieve least transmission error and high contact ratio. Histogram analysis is performed to condense the actual road load data into condensed duty cycle to find the bearing forces. The structural vibration generated by these forces will be simulated in a nonlinear solver obtaining the normal surface velocity of the housing and the results will be carried forward to Acoustic software wherein a virtual environment of the surrounding (actual testing scenario) with accurate microphone position will be maintained to predict the sound pressure level of radiated noise and directivity plot of the e-Gear Drive. Order analysis will be carried out to find the root cause of the vibration and whine noise. Broadband spectrum will be checked to find the rattle noise source. Further, with the available results, the design will be optimized, and the next loop of simulation will be performed to build a best e-Gear Drive on NVH aspect. Structural analysis will be also carried out to check the robustness of the e-Gear Drive.Keywords: 1-D system simulation, contact ratio, e-Gear, mesh stiffness, micro and macro geometry, transmission error, radiated noise, NVH
Procedia PDF Downloads 149357 Verification of Satellite and Observation Measurements to Build Solar Energy Projects in North Africa
Authors: Samy A. Khalil, U. Ali Rahoma
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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa
Procedia PDF Downloads 98356 Sensor Registration in Multi-Static Sonar Fusion Detection
Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin
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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem
Procedia PDF Downloads 169355 Application of Arbuscular Mycorrhizal Fungi as Biologically Based Strategy for Mitigation of Adverse Impact of Salt Stress on Wheat
Authors: Abeer Hashem, Khalid F. Almutairi, Ulkar Ibrahimova, Elsayed Fathi Abdallah
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Salinity poses a significant challenge to wheat production, necessitating the exploration of strategies to mitigate its adverse effects. The present investigation aims to study the impact of arbuscular mycorrhizal fungi (AMF) application to improve plant tolerance in terms of growth, carbohydrate, photosynthetic characteristics, and antioxidant enzyme activities under salt stress conditions. So, a randomized complete block design with five replications was employed comprising various treatments of AMF application under salinity stress (200mM), and control samples were used for each treatment. The obtained results demonstrated significantly that AMF used in this study showed beneficial impacts in all parameters used as sensitive monitor for relation of plant-salt microbe interaction. The root colonization by AMF showed the highest plant growth criteria, relative water content, soluble sugar, starch, and total non-structural carbohydrates under both control and salinity stress conditions. Moreover, the application of AMF-treated plants showed the highest soluble protein concentration and activity in leaves and antioxidant enzymes (catalase, superoxide dismutase, guaiacol peroxidase). These findings highlight the potential impact of AMF application as a biologically based strategy to manage the mitigation of salt stress on wheat, which increases the availability of many salt marsh habitats for sustainable agriculture of such strategy crops.Keywords: arbuscular mycorrhizal fungi, salt stress, plant growth criteria, soluble protein, antioxidant enzymes, wheat plant
Procedia PDF Downloads 48354 Ordinal Regression with Fenton-Wilkinson Order Statistics: A Case Study of an Orienteering Race
Authors: Joonas Pääkkönen
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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling
Procedia PDF Downloads 125353 Microalgae as Promising Biostimulants of Plant Tolerance Against Heavy Metals
Authors: Soufiane Fal, Abderahim Aasfar, Ali Ouhssain, Hasnae Choukri, Abelaziz Smouni, Hicham El Arroussi
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Heavy metals contamination is a major environmental concern around the world. It has a harmful impact on plant productivity and poses a serious risk to humans and animals health. In the present study, the effect of Microalgae Crude Extract (MCE) on tomato growth and nutrients uptake exposed to 2 mM Pb2+ and Cd2+ was investigated. In results, 2 mM Pb2+ and Cd2+ showed a significant reduction of tomatobiomass and perturbation in nutrients absorption. Moreover, MCE application in tomato plant exposed to Pb2+ and Cd2+ showed a significant enhancement of biomass compared to tomato plants under Pb2+ and Cd2+. On the other hand, MCE application favoured heavy metals accumulation in root and inhibited their translocation to shoot as phytostabilisation mechanism. Tomato plants showed biochemical responses to Pb2+ and Cd2+ stress with elevation of scavenging enzymes and molecules such as POD, CAT, SOD, Proline, and polyphenols, etc. In addition, the treatment by MCE showed a significant reduction level of the majority of these parameters. Furthermore, the metabolomic analysis revealed a significant change in important metabolites. Pb2+ and Cd2+ showed decrease in SFA and increase of UFA, VLFA, alkanes, alkenes, sterols, which known accumulated as tolerance and resistance mechanism to heavy metal (H.M) stress. However, MCE treatment showed the inverse of these response to return tomato plants to normal state and enhanced tolerance and resistance to heavy metal stress. In the present study, we emphasized that MCE can alleviate H.M stress, enhance tomato plant growth nutrients absorption and improve biochemical responses.Keywords: microalgae crude extract, heavy metal stress, nutrient uptake, metabolomic analysis, solanum lycopersicum (Tomato), phytostabilisation
Procedia PDF Downloads 114352 The Application of Participatory Social Media in Collaborative Planning: A Systematic Review
Authors: Yujie Chen , Zhen Li
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In the context of planning transformation, how to promote public participation in the formulation and implementation of collaborative planning has been the focused issue of discussion. However, existing studies have often been case-specific or focused on a specific design field, leaving the role of participatory social media (PSM) in urban collaborative planning generally questioned. A systematic database search was conducted in December 2019. Articles and projects were eligible if they reported a quantitative empirical study applying participatory social media in the collaborative planning process (a prospective, retrospective, experimental, longitudinal research, or collective actions in planning practices). Twenty studies and seven projects were included in the review. Findings showed that social media are generally applied in public spatial behavior, transportation behavior, and community planning fields, with new technologies and new datasets. PSM has provided a new platform for participatory design, decision analysis, and collaborative negotiation most widely used in participatory design. Findings extracted several existing forms of PSM. PSM mainly act as three roles: the language of decision-making for communication, study mode for spatial evaluation, and decision agenda for interactive decision support. Three optimization content of PSM were recognized, including improving participatory scale, improvement of the grass-root organization, and promotion of politics. However, basically, participants only could provide information and comment through PSM in the future collaborative planning process, therefore the issues of low data response rate, poor spatial data quality, and participation sustainability issues worth more attention and solutions.Keywords: participatory social media, collaborative planning, planning workshop, application mode
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