Search results for: annual average concentration
5926 Sol-Gel Synthesis and Optical Characterisation of TiO2 Thin Films for Photovoltaic Application
Authors: Arabi Nour El Houda, Iratni Aicha, Talaighil Razika, Bruno Capoen, Mohamed Bouazaoui
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TiO2 thin films have been prepared by the sol-gel dip-coating technique in order to elaborate antireflective thin films for monocrystalline silicon (mono-Si). The titanium isopropoxyde was chosen as a precursor with hydrochloric acid as a catalyser for preparing a stable solution. The optical properties have been tailored with varying the solution concentration, the withdrawn speed, and the heat-treatment. We showed that using a TiO2 single layer with 64.5 nm in thickness, heat-treated at 450°C or 300°C reduces the mono-Si reflection at a level lower than 3% over the broadband spectral do mains [669-834] nm and [786-1006] nm respectively. Those latter performances are similar to the ones obtained with double layers of low and high refractive index glasses respectively.Keywords: thin film, dip-coating, mono-crystalline silicon, titanium oxide
Procedia PDF Downloads 4365925 Thiosemicarbazone Derived from 4-Aminoantipyrine as Corrosion Inhibitor
Authors: Ahmed A. Al-Amiery, Yasmin K. Al-Majedy, Abdul Amir H. Kadhum, Abu Bakar Mohamad
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The efficiency of synthesized thiosemicarbazone namely 2-(1,5-dimethyl-4-(2-methylbenzylidene)amino)-2-phenyl-1H-pyrazol-3(2H)-ylidene) hydrazinecarbothioamide investigated as corrosion inhibitor of mild steel in 1N H2SO4 using electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PD) in addition of scanning electron microscopy (SEM). The results showed that this inhibitor behaved as a good corrosion inhibitor even at low concentration with a mean efficiency of 93%. Polarization technique and EIS were tested in different concentrations reveal that this compound is adsorbed on the mild steel, therefore blocking the active sites and the adsorption follows the Langmuir adsorption isotherm model. SEM shows that mild steel surface is nearly perfect for mild steel which was immersed in a solution of H2SO4 with corrosion inhibitor.Keywords: corrosion inhibitor, thiosemicarbazide, electrochemical impedance, electrochemical impedance spectroscopy
Procedia PDF Downloads 5195924 Assessment of the Spatio-Temporal Distribution of Pteridium aquilinum (Bracken Fern) Invasion on the Grassland Plateau in Nyika National Park
Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo
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Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution
Procedia PDF Downloads 1785923 Preparation and Performance Evaluation of Green Chlorine-Free Coagulants
Authors: Huihui Zhang, Zhongzhi Zhang
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Coagulation/flocculation is regarded a simple and effective wastewater treatment technology. Chlorine-containing coagulants may release chloride ions into the wastewater, causing corrosion. A green chlorine-free coagulant of polyaluminum ferric silicate (PSAF) was prepared by the copolymerization method to treat oily refractory wastewaters. Results showed that the highest removal efficiency of turbidity and chemical oxygen demand (COD) achieved 97.4% and 93.0% at a dosage of 700 mg/L, respectively. After PSAF coagulation, the chloride ion concentration was also almost the same as that in the raw wastewater. Thus, the chlorine-free coagulant is highly efficient and does not introduce additional chloride ions into the wastewater, avoiding corrosion.Keywords: coagulation, chloride-free coagulant, oily refractory wastewater, coagulation performance
Procedia PDF Downloads 2165922 Data Refinement Enhances The Accuracy of Short-Term Traffic Latency Prediction
Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong
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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.Keywords: data refinement, machine learning, mutual information, short-term latency prediction
Procedia PDF Downloads 1675921 A Nonlocal Means Algorithm for Poisson Denoising Based on Information Geometry
Authors: Dongxu Chen, Yipeng Li
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This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.Keywords: image denoising, Poisson noise, information geometry, nonlocal-means
Procedia PDF Downloads 2845920 Analysis of Access to Credit among Rural Farmers in Giwa Local Government Area of Kaduna State, Nigeria
Authors: S. Ibrahim, Bashir Umar
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Agricultural credit is very important for sustainable agricultural development to be achieved in any country of the world. Rural credit has proven to be a powerful instrument against poverty reduction and development in rural area. Agricultural credit enhances productivity and promotes standard of living by breaking vicious cycle of poverty of small scale farmers. This study examined access to credit among rural farmers in Giwa local government area of Kaduna state. Two stages sampling procedure was employed to select forty-two (42) respondents for the study. Primary data were collected using structured questionnaire with the help of well-trained enumerators. Data were analyzed using simple descriptive statistics. The results revealed that farmers were predominantly male (57.1%) and most (54.7%), were married with one level of education or another (66.5.%). Majority of the households’ head were between the ages of 31 to 50. majority of the farmers (68.2%) had more than 2ha of farmlands with at least 5 years of farming experience and an annual farm income of N 61,000 to 100,000 (61.9%). The Various sources of credit by the farmers in the study area were commercial banks (38.1%), Co-operative banks (47.6%), Development banks (14.2%) (formal) and Relatives (26.1%), Personal Savings (Adashi scheme) (52.3%), Moneylenders (21.4%) (informal). As regard to the amount of credit obtained by the farmers 38.1% received N 50,000-100,000, 50 % obtained N 100,001-500,000 while 11.9% obtained N 500,001-1,000,000. High interest Inadequate collateral, Complicated Procedures, lack of guarantor were the major constrains encountered by the farmers in accessing loans. The study therefore recommends that Rural farmers should be encouraged to form credit and thrift cooperative societies from which they can access much cheaper credits, Moreover, to ensure that any credit obtained may be manageable for the farmers, financial institutions should provide loans with low interest rates and government and non-governmental organizations should simplify procedures associated with accessing loans.Keywords: analysis, access, credit, farmers
Procedia PDF Downloads 615919 Design and Development of an Algorithm to Predict Fluctuations of Currency Rates
Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera
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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR
Procedia PDF Downloads 2115918 GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts
Authors: Lin Cheng, Zijiang Yang
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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.Keywords: program synthesis, flow chart, specification, graph recognition, CNN
Procedia PDF Downloads 1185917 Toxicological Analysis of Some Plant Combinations Used for the Treatment of Hypertension by Lay People in Northern Kwazulu-Natal, South Africa
Authors: Mmbulaheni Ramulondi, Sandy Van Vuuren, Helene De Wet
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The use of plant combinations to treat various medical conditions is not a new concept, and it is known that traditional people do not only rely on a single plant extract for efficacy but often combine various plant species for treatment. The knowledge of plant combinations is transferred from one generation to the other in the belief that combination therapy may enhance efficacy, reduce toxicity, decreases adverse effects, increase bioavailability and result in lower dosages. However, combination therapy may also be harmful when the interaction is antagonistic, since it may result in increasing toxicity. Although a fair amount of research has been done on the toxicity of medicinal plants, there is very little done on the toxicity of medicinal plants in combination. The aim of the study was to assess the toxicity potential of 19 plant combinations which have been documented as treatments of hypertension in northern KwaZulu-Natal by lay people. The aqueous extracts were assessed using two assays; the Brine shrimp assay (Artemia franciscana) and the Ames test (Mutagenicity). Only one plant combination (Aloe marlothii with Hypoxis hemerocallidea) in the current study has been previously assessed for toxicity. With the Brine shrimp assay, the plant combinations were tested in two concentrations (2 and 4 mg/ml), while for mutagenicity tests, they were tested at 5 mg/ml. The results showed that in the Brine shrimp assay, six combinations were toxic at 4 mg/ml. The combinations were Albertisia delagoensis with Senecio serratuloides (57%), Aloe marlothii with Catharanthus roseus (98%), Catharanthus roseus with Hypoxis hemerocallidea (66%), Catharanthus roseus with Musa acuminata (89%), Catharanthus roseus with Momordica balsamina (99%) and Aloe marlothii with Trichilia emetica and Hyphaene coriacea (50%). However when the concentration was reduced to 2 mg/ml, only three combinations were toxic which were Aloe marlothii with Catharanthus roseus (76%), Catharanthus roseus with Musa acuminata (66%) and Catharanthus roseus with Momordica balsamina (73%). For the mutagenicity assay, only the combinations between Catharanthus roseus with Hypoxis hemerocallidea and Catharanthus roseus with Momordica balsamina were mutagenic towards the Salmonella typhimurium strains TA98 and TA100. Most of the combinations which were toxic involve C. roseus which was also toxic when tested singularly. It is worth noting that C. roseus was one of the most frequently used plant species both to treat hypertension singularly and in combination and some of the individuals have been using this for the last 20 years. The mortality percentage of the Brine shrimp showed a significant correlation between dosage and toxicity thus toxicity was dosage dependant. A combination which is worth noting is the combination between A. delagoensis and S. serratuloides. Singularly these plants were non-toxic towards Brine shrimp, however their combination resulted in antagonism with the mortality rate of 57% at the total concentration of 4 mg/ml. Low toxicity was mostly observed, giving some validity to combined use, however the few combinations showing increased toxicity demonstrate the importance of analysing plant combinations.Keywords: dosage, hypertension, plant combinations, toxicity
Procedia PDF Downloads 3525916 Employing GIS to Analyze Areas Prone to Flooding: Case Study of Thailand
Authors: Sanpachai Huvanandana, Settapong Malisuwan, Soparwan Tongyuak, Prust Pannachet, Anong Phoepueak, Navneet Madan
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Many regions of Thailand are prone to flooding due to tropical climate. A commonly increasing precipitation in this continent results in risk of flooding. Many efforts have been implemented such as drainage control system, multiple dams, and irrigation canals. In order to decide where the drainages, dams, and canal should be appropriately located, the flooding risk area should be determined. This paper is aimed to identify the appropriate features that can be used to classify the flooding risk area in Thailand. Several features have been analyzed and used to classify the area. Non-supervised clustering techniques have been used and the results have been compared with ten years average actual flooding area.Keywords: flood area clustering, geographical information system, flood features
Procedia PDF Downloads 2945915 Characteristics and Durability Evaluation of Air Spring
Authors: Chang Su Woo, Hyun Sung Park
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Air spring system is widely accepted for railway vehicle secondary suspension to reduce and absorb the vibration and noise. The low natural frequency ensures a comfortable ride and an invariably good stiffness. In this paper, the characteristic and durability test was conducted in laboratory by using servo-hydraulic fatigue testing system to reliability evaluation of air spring for electric railway vehicle. The experimental results show that the characteristics and durability of domestically developed products are excellent. Moreover, to guarantee the adaption of air spring, the ride comfort and air pressure variation were measured in train test on subway line. Air spring developed by this study for railway vehicles can guarantee the reliability of average usage of 1 million times at 90% confidence level.Keywords: air spring, reliability, railway, service lifetime
Procedia PDF Downloads 4715914 Domestic Wastewater Treatment by Microalgae – Removal of Nitrogen
Authors: A. Siham Dehmani, B. Djamal Zerrouki
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Domestic wastewater contains high concentrations of nitrogen, which can affect public health and cause harmful ecological impacts. The potential of microalgae as a source of renewable energy based on wastewater has received increasing interest worldwide in recent decades. The microalgae cultivation in wastewater has two advantages: wastewater treatment and algal biomass production. Our work aimed to remove nitrogen from municipal wastewater. Wastewater samples were taken from the wastewater treatment station located in Ouargla and used as a medium for the cultivation of chlorella microalgae strains inside a photobioreactor. Analysis of different parameters was done every 2 days along the period of the cultivation (10 days). The average removal efficiencies of nitrogen were maintained at 95%. Our results show the potential of integrating nutrient removal from wastewater by microalgae as a secondary wastewater treatment processes.Keywords: biomass, microalgae, treatment, wastewater
Procedia PDF Downloads 4215913 SO2 Sensing Performance of Nanostructured CdSnO3 Thin Films Prepared by Spray Pyrolysis Technique
Authors: R. H. Bari
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The nanostructured thin films of CdSnO3 are sensitive to change in their environment. CdSnO3 is successfully used as gas sensor due to the dependence of the electrical conductivity on the ambient gas composition. Nanostructured CdSnO3 thin films of different substrate temperature (300 0C, 350 0C, 400 0C and 450 0C) were deposited onto heated glass substrate by simple spray pyrolysis (SP) technique. Sensing elements of nanostructured CdSnO3 were annealed at 500 0C for 1 hrs. Characterization includes a different analytical technique such as, X-ray diffractogram (XRD), energy dispersive X-ray analysis (EDAX), and Field emission scanning electron microscope (FE-SEM). The average grain size observed from XRD and FF-SEM was found to be less than 18.36 and 23 nm respectively. The films sprayed at substrate temperature for 400 0C was observed to be most sensitive (S = 530) to SO2 for 500 ppm at 300 0C. The response and recovery time is 4 sec, 8 sec respectively.Keywords: nanostructured CdSnO3, spray pyrolysis, SO2 gas sensing, quick response
Procedia PDF Downloads 2855912 Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models
Authors: Anastasiia Yu. Timofeeva
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Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression
Procedia PDF Downloads 4135911 Forced Heat Transfer Convection in a Porous Channel with an Oriented Confined Jet
Authors: Azzedine Abdedou, Khedidja Bouhadef
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The present study is an analysis of the forced convection heat transfer in porous channel with an oriented jet at the inlet with uniform velocity and temperature distributions. The upper wall is insulated when the bottom one is kept at constant temperature higher than that of the fluid at the entrance. The dynamic field is analysed by the Brinkman-Forchheimer extended Darcy model and the thermal field is traduced by the energy one equation model. The numerical solution of the governing equations is obtained by using the finite volume method. The results mainly concern the effect of Reynolds number, jet angle and thermal conductivity ratio on the flow structure and local and average Nusselt numbers evolutions.Keywords: forced convection, porous media, oriented confined jet, fluid mechanics
Procedia PDF Downloads 3815910 Indicator-Immobilized, Cellulose Based Optical Sensing Membrane for the Detection of Heavy Metal Ions
Authors: Nisha Dhariwal, Anupama Sharma
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The synthesis of cellulose nanofibrils quaternized with 3‐chloro‐2‐hydroxypropyltrimethylammonium chloride (CHPTAC) in NaOH/urea aqueous solution has been reported. Xylenol Orange (XO) has been used as an indicator for selective detection of Sn (II) ions, by its immobilization on quaternized cellulose membrane. The effects of pH, reagent concentration and reaction time on the immobilization of XO have also been studied. The linear response, limit of detection, and interference of other metal ions have also been studied and no significant interference has been observed. The optical chemical sensor displayed good durability and short response time with negligible leaching of the reagent.Keywords: cellulose, chemical sensor, heavy metal ions, indicator immobilization
Procedia PDF Downloads 2985909 Citation Analysis on the Articles published in Bayero Journal of Pure and Applied Sciences (BAJOPAS), from 2008-2020: An International Journal in Bayero University, Kano, Nigeria
Authors: G. A. Babalola, Yusuf Muhammad
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An analysis was carried out on 19,759 citations appended to the References Section of 881 research articles published in Bayero Journal of Pure and Applied Sciences. It was found that journals publications were the most cited source of information among pure and applied sciences scientists with 12,090 (61.2%). The study also revealed that researchers in the field of pure and applied sciences used very current and up to date information sources in writing theirs articles with 10,091 (51.1%) citations and an average mean 11.1 per article in the journal.Keywords: citation analysis, BAJOPAS, journal article, Bayero University Kano, Nigeria
Procedia PDF Downloads 1635908 Orange Leaves and Rice Straw on Methane Emission and Milk Production in Murciano-Granadina Dairy Goat Diet
Authors: Tamara Romero, Manuel Romero-Huelva, Jose V. Segarra, Jose Castro, Carlos Fernandez
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Many foods resulting from processing and manufacturing end up as waste, most of which is burned, dumped into landfills or used as compost, which leads to wasted resources, and environmental problems due to unsuitable disposal. Using residues of the crop and food processing industries to feed livestock has the advantage to obviating the need for costly waste management programs. The main residue generated in citrus cultivations and rice crop are pruning waste and rice straw, respectively. Within Spain, the Valencian Community is one of the world's oldest citrus and rice production areas. The objective of this experiment found out the effects of including orange leaves and rice straw as ingredients in the concentrate diets of goats, on milk production and methane (CH₄) emissions. Ten Murciano-Granadina dairy goats (45 kg of body weight, on average) in mid-lactation were selected in a crossover design experiment, where each goat received two treatments in 2 periods. Both groups were fed with 1.7 kg pelleted mixed ration; one group (n= 5) was a control (C) and the other group (n= 5) used orange leaves and rice straw (OR). The forage was alfalfa hay, and it was the same for the two groups (1 kg of alfalfa was offered by goat and day). The diets employed to achieve the requirements during lactation period for caprine livestock. The goats were allocated to individual metabolism cages. After 14 days of adaptation, feed intake and milk yield were recorded daily over a 5 days period. Physico-chemical parameters and somatic cell count in milk samples were determined. Then, gas exchange measurements were recorded individually by an open-circuit indirect calorimetry system using a head box. The data were analyzed by mixed model with diet and digestibility as fixed effect and goat as random effect. No differences were found for dry matter intake (2.23 kg/d, on average). Higher milk yield was found for C diet than OR (2.3 vs. 2.1 kg/goat and day, respectively) and, greater milk fat content was observed for OR than C (6.5 vs. 5.5%, respectively). The cheese extract was also greater in OR than C (10.7 vs. 9.6%). Goats fed OR diet produced significantly fewer CH₄ emissions than C diet (27 vs. 30 g/d, respectively). These preliminary results (LIFE Project LOWCARBON FEED LIFE/CCM/ES/000088) suggested that the use of these waste by-products was effective in reducing CH₄ emission without detrimental effect on milk yield.Keywords: agricultural waste, goat, milk production, methane emission
Procedia PDF Downloads 1475907 Biochar and Food Security in Central Uganda
Authors: Nataliya Apanovich, Mark Wright
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Uganda is among the poorest but fastest growing populations in the world. Its annual population growth of 3% puts additional stress through land fragmentation, agricultural intensification, and deforestation on already highly weathered tropical (Ferralsol) soils. All of these factors lead to decreased agricultural yields and consequently diminished food security. The central region of Uganda, Buganda Kingdom, is especially vulnerable in terms of food security as its high population density coupled with mismanagement of natural resources led to gradual loss of its soil and even changes in microclimate. These changes are negatively affecting livelihoods of smallholder farmers who comprise 80% of all population in Uganda. This research focuses on biochar for soil remediation in Masaka District, Uganda. If produced on a small scale from locally sourced materials, biochar can increase the quality of soil in a cost and time effective manner. To assess biochar potential, 151 smallholder farmers were interviewed on the types of crops grown, agricultural residues produced and their use, as well as on attitudes towards biochar use and its production on a small scale. The interviews were conducted in 7 sub-counties, 32 parishes, and 92 villages. The total farmland covered by the study was 606.2 kilometers. Additional information on the state of agricultural development and environmental degradation in the district was solicited from four local government officials via informal interviews. This project has been conducted in collaboration with the international agricultural research institution, Makerere University in Kampala, Uganda. The results of this research can have implications on the way farmers perceive the value of their agricultural residues and what they decide to do with them. The underlying objective is to help smallholders in degraded soils increase their agricultural yields through the use of biochar without diverting the already established uses of agricultural residues to a new soil management practice.Keywords: agricultural residues, biochar, central Uganda, food security, soil erosion, soil remediation
Procedia PDF Downloads 2825906 Magnetic Nanoparticles for Protein C Purification
Authors: Duygu Çimen, Nilay Bereli, Adil Denizli
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In this study is to synthesis magnetic nanoparticles for purify protein C. For this aim, N-Methacryloyl-(L)-histidine methyl ester (MAH) containing 2-hydroxyethyl methacrylate (HEMA) based magnetic nanoparticles were synthesized by using micro-emulsion polymerization technique for templating protein C via metal chelation. The obtained nanoparticles were characterized with Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), zeta-size analysis and electron spin resonance (ESR) spectroscopy. After that, they were used for protein C purification from aqueous solution to evaluate/optimize the adsorption condition. Hereby, the effecting factors such as concentration, pH, ionic strength, temperature, and reusability were evaluated. As the last step, protein C was determined with sodium dodecyl sulfate-polyacrylamide gel electrophoresis.Keywords: immobilized metal affinity chromatography (IMAC), magnetic nanoparticle, protein C, hydroxyethyl methacrylate (HEMA)
Procedia PDF Downloads 4225905 Spectral Mixture Model Applied to Cannabis Parcel Determination
Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara
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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.Keywords: Gaussian mixture discriminant analysis, spectral mixture model, Worldview-2, land parcels
Procedia PDF Downloads 1945904 Genetic Algorithms for Parameter Identification of DC Motor ARMAX Model and Optimal Control
Authors: A. Mansouri, F. Krim
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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation
Procedia PDF Downloads 3775903 Conjugate Free Convection in a Square Cavity Filled with Nanofluid and Heated from Below by Spatial Wall Temperature
Authors: Ishak Hashim, Ammar Alsabery
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The problem of conjugate free convection in a square cavity filled with nanofluid and heated from below by spatial wall temperature is studied numerically using the finite difference method. Water-based nanofluid with copper nanoparticles are chosen for the investigation. Governing equations are solved over a wide range of nanoparticle volume fraction (0 ≤ φ ≤ 0.2), wave number ((0 ≤ λ ≤ 4) and thermal conductivity ratio (0.44 ≤ Kr ≤ 6). The results presented for values of the governing parameters in terms of streamlines, isotherms and average Nusselt number. It is found that the flow behavior and the heat distribution are clearly enhanced with the increment of the non-uniform heating.Keywords: conjugate free convection, square cavity, nanofluid, spatial temperature
Procedia PDF Downloads 3575902 The Creation of a Yeast Model for 5-oxoproline Accumulation
Authors: Pratiksha Dubey, Praveen Singh, Shantanu Sen Gupta, Anand K. Bachhawat
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5-oxoproline (pyroglutamic acid) is a cyclic lactam of glutamic acid. In the cell, it can be produced by several different pathways and is metabolized into glutamate with the help of the 5-oxoprolinase enzyme (OPLAH or OXP1). The inhibition of 5-oxoprolinase enzyme in mammals was found to result in heart failure and is thought to be a consequence of oxidative stress [1]. To analyze the consequences of 5-oxoproline accumulation more clearly, we are generating models for 5-oxoproline accumulation in yeast. The 5-oxoproline accumulation model in yeast is being developed by two different strategies. The first one is by overexpression of the mouse -glutamylcyclotransferase enzyme. It degrades -glu-met dipeptide into 5-oxoproline and methionine taken by the cell from the medium. The second strategy is by providing high concentration of 5-oxoproline externally to the yeast cells. The intracellular 5-oxoproline levels in both models are being evaluated. In addition, the metabolic and cellular consequences are being investigated.Keywords: 5-oxoproline, pyroglutamic acid, yeast, genetics
Procedia PDF Downloads 825901 The Predictive Utility of Subjective Cognitive Decline Using Item Level Data from the Everyday Cognition (ECog) Scales
Authors: J. Fox, J. Randhawa, M. Chan, L. Campbell, A. Weakely, D. J. Harvey, S. Tomaszewski Farias
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Early identification of individuals at risk for conversion to dementia provides an opportunity for preventative treatment. Many older adults (30-60%) report specific subjective cognitive decline (SCD); however, previous research is inconsistent in terms of what types of complaints predict future cognitive decline. The purpose of this study is to identify which specific complaints from the Everyday Cognition Scales (ECog) scales, a measure of self-reported concerns for everyday abilities across six cognitive domains, are associated with: 1) conversion from a clinical diagnosis of normal to either MCI or dementia (categorical variable) and 2) progressive cognitive decline in memory and executive function (continuous variables). 415 cognitively normal older adults were monitored annually for an average of 5 years. Cox proportional hazards models were used to assess associations between self-reported ECog items and progression to impairment (MCI or dementia). A total of 114 individuals progressed to impairment; the mean time to progression was 4.9 years (SD=3.4 years, range=0.8-13.8). Follow-up models were run controlling for depression. A subset of individuals (n=352) underwent repeat cognitive assessments for an average of 5.3 years. For those individuals, mixed effects models with random intercepts and slopes were used to assess associations between ECog items and change in neuropsychological measures of episodic memory or executive function. Prior to controlling for depression, subjective concerns on five of the eight Everyday Memory items, three of the nine Everyday Language items, one of the seven Everyday Visuospatial items, two of the five Everyday Planning items, and one of the six Everyday Organization items were associated with subsequent diagnostic conversion (HR=1.25 to 1.59, p=0.003 to 0.03). However, after controlling for depression, only two specific complaints of remembering appointments, meetings, and engagements and understanding spoken directions and instructions were associated with subsequent diagnostic conversion. Episodic memory in individuals reporting no concern on ECog items did not significantly change over time (p>0.4). More complaints on seven of the eight Everyday Memory items, three of the nine Everyday Language items, and three of the seven Everyday Visuospatial items were associated with a decline in episodic memory (Interaction estimate=-0.055 to 0.001, p=0.003 to 0.04). Executive function in those reporting no concern on ECog items declined slightly (p <0.001 to 0.06). More complaints on three of the eight Everyday Memory items and three of the nine Everyday Language items were associated with a decline in executive function (Interaction estimate=-0.021 to -0.012, p=0.002 to 0.04). These findings suggest that specific complaints across several cognitive domains are associated with diagnostic conversion. Specific complaints in the domains of Everyday Memory and Language are associated with a decline in both episodic memory and executive function. Increased monitoring and treatment of individuals with these specific SCD may be warranted.Keywords: alzheimer’s disease, dementia, memory complaints, mild cognitive impairment, risk factors, subjective cognitive decline
Procedia PDF Downloads 795900 Non-Linear Causality Inference Using BAMLSS and Bi-CAM in Finance
Authors: Flora Babongo, Valerie Chavez
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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.Keywords: causal inference, DAGs, BAMLSS, financial index
Procedia PDF Downloads 1495899 Dinitrotoluene and Trinitrotoluene Measuring in Double-Base Solid Propellants
Authors: Z. H. Safari, M. Anbia, G. H. Kouzegari, R. Amirkhani
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Toluene and Nitro derivatives are widely used in industry particularly in various defense applications. Tri-nitro-toluene derivative is a powerful basic explosive material that is a basis upon which to compare equivalent explosive power of similar materials. The aim of this paper is to measure the explosive power of these hazardous substances in fuels having different shelf-life and therefore optimizing their storage and maintenance. The methodology involves measuring the amounts of di- nitro- toluene and tri-nitro-toluene in the aged samples at 90 ° C by gas chromatography. Results show no significant difference in the concentration of the TNT compound over a given time while there was a significant difference in DNT compound over the same period. The underlying reason is attributed to the simultaneous production of the material with destruction of stabilizer.Keywords: dinitrotoluene, trinitrotoluene, double-base solid propellants, artificial aging
Procedia PDF Downloads 4015898 Amorphous Aluminophosphates: An Insight to the Changes in Structural Properties and Catalytic Activity by the Incorporation of Transition Metals
Authors: A. Hamza, H. Kathyayini, N. Nagaraju
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Aluminophosphates, both amorphous and crystalline materials find applications as adsorbents, ceramics, and pigments and as catalysts/catalyst supports in organic fine chemical synthesis. Most of the applications are varied depending on the type of metal incorporated, particle size, surface area, porosity and morphology of aluminophosphate. The porous and surface properties of these materials are normally fine-tuned by adopting various preparation methodologies. Numerous crystalline microporous and mesoporous aluminophosphates and metal-aluminophosphates have been reported in literature, in which the synthesis has been carried out by using structure directing organic molecules/surfactants. In present work, amorphous aluminophosphate (AlP) and metal-aluminophosphates MAlP (M = Cu, Zn, Cr, Fe, Ce and Zr) and their mixed forms M-1M2AlP are prepared under a typical precipitation condition, i.e. at low temperature in order to keep the Von-Weirmann relative super saturation of the precipitating medium and obtain small size precipitate particles. These materials are prepared without using any surfactants. All materials are thoroughly characterised for surface and bulk properties by N2 adsorption-desorption technique, XRD, FT-IR, TG and SEM. The materials are also analysed for the amount and the strength of their surface acid sites, by NH3-TPD and CO2-TPD techniques respectively. All the materials prepared in the work are investigated for their catalytic activity in following applications in the synthesis of industrially important Jasminaldehyde via, aldol condensation of n-heptanal and benzaldehyde, in the synthesis of biologically important chalcones by Claisen-shmidth condensation of benzaldehyde and substituted chalcones. The effect of the amount of the catalysts, duration of the reaction, temperature of the reaction, molar ratio of the reactants has been studied. The porosity of pure aluminophosphate is found to be changed significantly by the incorporation of transition metals during preparation of aluminophosphate. The pore size increased from microporous to mesoporous and finally to macroporous by following order of metals Cu = Zn < Cr < Ce < Fe = Zr. The change in surface area and porosity of double metal-aluminophosphates depended on the concentration of both the metals. The acidity of aluminophosphate is either increased or decreased which depended on the type and valence of metals loaded. A good number of basic sites are created in metal-aluminophosphates irrespective of the metals used. A maximum catalytic activity for synthesis of both jasminaldehyde and chalcone is obtained by FeAlP as catalysts; these materials are characterized by decreased strength and concentration of acidic sites with optimum level basic sites.Keywords: amorphous metal-aluminophosphates, surface properties, acidic-basic properties, Aldol, Claisen-Shmidth condensation, jasminaldehyde, chalcone
Procedia PDF Downloads 3035897 Characterization of the Airtightness Level in School Classrooms in Mediterranean Climate
Authors: Miguel A. Campano, Jesica Fernández-Agüera, Samuel Domínguez-Amarillo, Juan J. Sendra
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An analysis of the air tightness level is performed on a representative sample of school classrooms in Southern Spain, which allows knowing the infiltration level of these classrooms, mainly through its envelope, which can affect both energy demand and occupant's thermal comfort. By using a pressurization/depressurization equipment (Blower-Door test), a characterization of 45 multipurpose classrooms have been performed in nine non-university educational institutions of the main climate zones of Southern Spain. In spite of having two doors and a high ratio between glass surface and outer surface, it is possible to see in these classrooms that there is an adequate level of airtightness, since all the n50 values obtained are lower than 9.0 ACH, with an average value around 7.0 ACH.Keywords: air infiltration, energy efficiency, school buildings, thermal comfort, indoor air quality, ventilation
Procedia PDF Downloads 475